PROJECT MANAGEMENT, STRATEGIC COMMUNICATION MANAGEMENT, WEB AND INFORMATION TECHNOLOGIES Peer-Reviewed Proceedings Book Editors: Mladen Radujković, Božidar Veljković, Matej Mertik, Daniel Siter MARIBOR, 2026 International Scientific Conference IT'S ABOUT PEOPLE 2024–2025 PEER-REVIEWED PROCEEDINGS BOOK: PROJECT MANAGEMENT, STRATEGIC COMMUNICATION MANAGEMENT, WEB AND INFORMATION TECHNOLOGIES Honorary Committee 2024: Dubravka Šuica, European Commission Vice-President for Democracy and Demography; Klaus Mainzer, Presi-dent of the European Academy of Sciences and Arts; Felix Unger, Honorary President of the European Academy of Sciences and Arts; Ludvik Toplak, Rector of Alma Mater Europaea University; Jurij Toplak, University Profes-sor, Alma Mater Europaea – Faculty ECM, Fordham University, President of the Organisational Committee of the It’s About People Conference; Ioannis Liritzis, Dean of Natural Sciences, European Academy of Sciences and Arts; Peter Štih, President of the Slovenian Academy of Sciences and Arts; Željko Knez, University Professor, University of Maribor; Verica Trstenjak, Former Advocate General of the Court of Justice of the EU, Professor of European Law; Tatjana Christelbauer, Founder and Director, Agency for Cultural Diplomacy Vienna; Alice Siu, Senior Research Scholar at Stanford University, Associate Director, Stanford’s Deliberative Democracy Lab; Borut Pahor, President of the Republic of Slovenia 2012–22; Richard James Overy, Professor, University of Ex-eter, Fellow of the Royal Historical Academy and British Academy; Andy Sumner, Fellow of the Academy of Social Sciences, Fellow of the Royal Society of Arts, Professor at King’s College London, Senior Fellow, United Nations University; Michael Beckmann, University Professor, Dean, Technical University Dresden. Scientific and Programme Committee 2024: Klaus Mainzer (President), Ludvik Toplak, Jurij Toplak, Felix Unger, Dubravka Šuica, Ioannis Liritzis, Michael Beckmann, Peter Štih, Željko Knez, Lenart Škof, Verica Trstenjak, Barbara Toplak Perovič, Mark Franklin, Cees van der Eijk, Christopher Wlezien, Wouter van der Brug, Elias Dinas, Richard James Overy, Andy Sumner, Dany Bahar, Laurence Hewick, Jana Goriup, Luka Martin Tomažič, Daniel Siter, Anja Hellmuth Kramberger, Suzan-na Mežnarec Novosel, Matej Mertik, Sebastjan Kristovič, Jasmina Kristovič, Edvard Jakšič, David Bogataj, Peter Pavel Klasinc, Suzana Bračič Tomažič, Uroš Marušič, Svebor Sečak, Rosana Hribar, Polonca Pangrčič, Nataša Vid-nar, Marko Novak, Živa Arko, Tatjana Horvat, Tadej Strojnik, Nataša Štandeker, Maruša Mavsar, Nadia Manzoni, Gašper Pirc, Luka Trebežnik, Katja Holnthaner Zorec, Voyko Kavcic, Peter Volasko, Howie Firth, Andraž Ivšek, Janez Potočnik, Teun J. Dekker, Carl Gombrich, Samuel Abraham, Raffaella Santi, Cirila Toplak, Daria Mustić, Paul David Crowther, Peter Seljak. Organisational Board 2024: Jurij Toplak (President), Luka Martin Tomažič (Vice-President), Daniel Siter, Anja Hellmuth Kramberger, Bar-bara Toplak Perovič, Špela Pokeržnik, Miha Jakin, Marko Benčak, Katarina Pernat, Špela Ekselenski Bečič, Petra Braček Kirbiš, Suzanna Mežnarec Novosel, Sebastjan Kristovič, Lenart Škof, Matej Mertik, Cirila Toplak, Ainhoa Lizariturry, Patricija Pongračič, Sašo Bjelić, Anja Jurše. Secretariat 2024: Luka Martin Tomažič, Daniel Siter, Marko Bencak, Katarina Pernat, Suzanna Mežnarec Novosel, Petra Braček Kirbiš, Dijana Štiglic. Honorary Committee 2025: Donato Kiniger-Passigli, World Academy of Art and Science Vice-President; Klaus Mainzer, University Professor, President of the European Academy of Sciences and Arts; Felix Unger, Honorary President of the Europe-an Academy of Sciences and Arts; Ludvik Toplak, Rector of Alma Mater Europaea University; Jurij Toplak, Pro-fessor, Fordham University, Alma Mater Europaea University, President of the Organisational Committee of the It’s About People Conference; Ferenc Miszlivetz, Director of the Institute of Advance Studies Köszeg, Professor, University of Pannonia; Andrei Marga, Professor and Former Rector, Babeș-Bolyai University of Cluj-Napoca; Štefan Luby, Professor, Senior Research Fellow, Slovak Academy of Sciences; Alberto De Franceschi, Professor, University of Ferrara, KU Leuven; Sašo Grozdanov, Researcher at the Higgs Center, University of Edinburgh and Associate Professor, University of Ljubljana; Aleksander Zidanšek, Sašo Džeroski, Milena Horvat, Uroš Cvelbar, Nives Ogrinc, David Kocman, Jožef Stefan Institute; Ioannis Liritzis, Dean of Natural Sciences, European Acade-my of Sciences and Arts, Professor, Henan University, Alma Mater Europaea University. Scientific and Programme Committee 2025: Klaus Mainzer (President), Ludvik Toplak, Felix Unger, Donato Kiniger-Passigli, Jurij Toplak, Ferenc Miszlivetz, Andrei Marga, Štefan Luby, Alberto De Franceschi, Sašo Grozdanov, Aleksander Zidanšek, Sašo Džeroski, Mile-na Horvat, Uroš Cvelbar, Nives Ogrinc, David Kocman, Ioannis Liritzis, Lenart Škof, Jana Goriup, Luka Martin Tomažič, Daniel Siter, Barbara Toplak Perovič, Božidar Veljković, Anja Hellmuth Kramberger, Matej Mertik, Se-bastjan Kristovič, Marija Ovsenik, Edvard Jakšič, David Bogataj, Peter Pavel Klasinc, Uroš Marušič, Svebor Sečak, Rosana Hribar, Polonca Seranno, Tatjana Horvat, Tadej Strojnik, Gašper Pirc, Luka Trebežnik, Voyko Kavcic, Peter Seljak, Mladen Radujković. Organisational Board 2025: Jurij Toplak (President), Luka Martin Tomažič (Vice-President), Daniel Siter, Anja Hellmuth Kramberger, Barbara Toplak Perovič, Špela Pokeržnik, Tanja Angleitner Sagadin, Blaž Podobnik, Miha Jakin, Marko Bencak, Katari-na Pernat, Špela Ekselenski Bečič, Petra Braček Kirbiš, Suzanna Mežnarec Novosel, Sebastjan Kristovič, Lenart Škof, Matej Mertik, Ainhoa Lizariturry, Patricija Pongračič, Sašo Bjelić, Anja Jurše, Jasmina Kristovič, Maruša Mavsar, Katja Holnthaner Zorec. Secretariat 2025: Luka Martin Tomažič, Daniel Siter, Blaž Podobnik, Marko Bencak, Tanja Angleitner Sagadin, Špela Pokeržnik, Katarina Pernat, Petra Braček Kirbiš, Dijana Štiglic, Nataša Štandeker. Editors: Mladen Radujković, Božidar Veljković, Matej Mertik, Daniel Siter Technical Editor: Blaž Podobnik Reviewers: Brano Markić, Mariela Sjekavica, Reinhard Wagner, Mladen Radujković; Daria Mustić, Dinko Bilić, Slobodan Hadžić, Ivan Balabanić; Matej Mertik, Matevž Vremec. Pre-Press Preparation and Graphic Design: Tjaša Pogorevc s.p Edition: 1st Online Edition Place: Maribor Publisher: Alma Mater Europaea University, Alma Mater Press For the Publisher: Ludvik Toplak Year of Publishing: 2026 Available at: https://press.almamater.si/index.php/amp/catalog/category/CONF Kataložni zapis o publikaciji (CIP) pripravili v Narodni in univerzitetni knjižnici v Ljubljani COBISS.SI-ID 263665411 ISBN 978-961-7183-86-3 (PDF) The statements, opinions, claims, and information in this publication are solely those of the authors of the contributions and not of Alma Mater Press and/or the editors. Alma Mater Press and/or the editor(s) disclaim any liability for any injury to persons or property resulting from any idea, method, instruction, or product mentioned in the content. Without the written permission of the publisher, the reproduction, distribution, rental, public communication, adaptation, or any other use of this work or parts thereof, in any form or by any means, including photocopying, printing, or storage in electronic form, is prohibited under the current Copyright and Related Rights Act. The 12th and 13th Annual Conferences of Europe’s Sciences and Arts Leaders and Scholars International Scientific Conferences IT'S ABOUT PEOPLE 2024: In Service of Sustainability and Dignity 2025: Social and Technological Resilience for Health and Sustainable Development Peer-Reviewed Proceedings Book PROJECT MANAGEMENT, STRATEGIC COMMUNICATION MANAGEMENT, WEB AND INFORMATION TECHNOLOGIES 1st Online Edition Editors: Mladen Radujković, Božidar Veljković, Matej Mertik, Daniel Siter Maribor, 2026 TABLE OF CONTENTS EDITORIAL INTRODUCTIONS 9 PROJECT MANAGEMENT 13 2024 15 Renáta Ježková, Karina Benetti 17 PEOPLE MANAGEMENT WITH AN EMPHASIS ON RECRUITING EMPLOYEES IN THE POST-COVID ERA IN THE CATERING SECTOR: CASE STUDY CZECHIA AND SLOVAKIA 2025 29 Anna-Vanadis Faix, Stefanie Kisgen 31 FROM ‘DIGITAL FIRST’ TO ‘DIGITAL FOR PEOPLE’: LEADERSHIP AS AN INTERFACE BETWEEN AI, QUANTUM COMPUTING AND SOCIAL RESILIENCE Salik Ram Maharjan 42 INVESTIGATING THE PROJECTIFICATION OF SOCIAL ENTERPRISES AND ITS IMPACT ON SOCIAL ENTREPRENEURS(HIP): A COMPARATIVE STUDY Jaroslav Viglaský, Milan Fiľa 52 TECHNOLOGY SOLUTIONS OF SHARING ECONOMY AS A TOOL FOR SUSTAINABLE DEVELOPMENT Mario Protulipac, Jelena Kljaić Šebrek 60 ZOON PROJEKTIKON: NAVIGATING THE ROLE OF “PROJECT BEINGS” WITHIN SUSTAINABLE PROJECT MANAGEMENT IN THE AGE OF GENERATIVE AI Senzekile Mofokeng 67 EXPLAINABLE ARTIFICIAL INTELLIGENCE IN THE CREDIT VERIFICATION PROCESS Reinhard F. Wagner, Karolina Novinc, Mladen Radujković 78 THE RISE OF AI IN THE EDUCATIONAL LANDSCAPE FOR PROJECT MANAGERS STRATEGIC COMMUNICATION MANAGEMENT 95 2024 97 Ema Petrušić, Tanja Grmuša 99 HOW DOES GEN Z PERCEIVE SUSTAINABLE FASHION: ATTITUDES OF CROATIAN STUDENTS TOWARDS THE GREEN H&M CAMPAIGN Rebeka Radovanović, Tanja Grmuša 107 THE INFLUENCE OF DIGITAL PLATFORMS ON THE PERCEPTION OF THE QUALITY OF INTERNAL COMMUNICATION IN A NON-PROFIT ORGANIZATION: THE PERSPECTIVE OF TEAM MEMBERS AND LEADERS Anthony Ban, Branka Ličanin 116 HEALTH NAVIGATION: STRATEGIC COMMUNICATION MANAGEMENT IN ISTRIAN HEALTH INSTITUTIONS Radoslav Baltezarević 125 THE EFFECTIVENESS OF DIGITAL POLITICAL COMMUNICATION IN INFLUENCING VOTER BEHAVIOR 2025 137 Pe INTE Eni Lasku 139 er-RRN SOCIOLINGUISTIC DEVELOPMENT OF DIGITAL COMMUNICATION STYLE: evAT SLANGS, MEMES, AND TRANSLATION ISSUES ieIO wN edA Jernej Šilak 147L S Pr THE NEED TO BUILD RESILIENCE AGAINST CLICKBAIT AS CONTROVERSIAL TACTICS oCIE IN ONLINE MEDIA ceN edTIF ingIC C Lana Novoselac, Tanja Grmuša 161 s BoO THE PERCEPTION OF THE STRUGGLE FOR WOMEN’S RIGHTS ON SOCIAL MEDIA: N ATTITUDES OF USERS IN CROATIA okFER : PEN Stjepan Petričević 172 R OCE I CRISIS COMMUNICATION IN HEALTHCARE: IMPLEMENTING THE IDEA-COMMTRUST JET'S A CT MODEL FOR TECHNOLOGICAL RESILIENCE MB AO N Igor Pelaić, Stjepan Petričević 181U AT P G THE RELATIONSHIP BETWEEN MEDIA AND HEALTHCARE INSTITUTIONS IN THE EMEO CONTEXT OF CRISIS COMMUNICATION: TECHNOLOGICAL AND SOCIAL RESILIENCE ENPLE 2 DURING HEALTH CRISES T, S TR024 AT–2 WEB AND INFORMATION TECHNOLOGIES 193 EG IC02 C5 Klotilda Nikaj, Ervis Gega, Margarita Ifti 195 OM STEADY-STATE ANALYSIS OF ONLINE SYSTEMS USING NEURONAL MODELS: M APPLICATIONS IN REAL-TIME SIMULATIONS U N IC Aleksandar Brodschneider, Matej Mertik 201 AT ION DIGITAL MARKETING AND PROMOTION OF SLOVENIAN HIGHER EDUCATION M PROGRAMMES IN INFORMATION AND COMMUNICATION TECHNOLOGIES AT THE A UNDERGRADUATE LEVEL N A G Marko Mikša 211 EM EN EVOLUTION AND APPLICATIONS ACROSS DISCIPLINES OF THE UTAUT MODEL T, W Kennedy Addo 219 EB ARTIFICIAL INTELLIGENCE AUGMENTED SYSTEM IN HEALTHCARE USING DEEP A N LEARNING ALGORITHMS D IN FOR ATM ION EC T H NOL O IEG S 7 EDITORIAL INTRODUCTIONS Pe INTE er-RRN evAT Project management has developed rapidly in recent years. Development is less about further op- ieIO w timising methodology or handling projects more efficiently, and more about improving forms of N edAL S collaboration and the impact of new technologies, such as artificial intelligence, on projects and PrCIE o project management. This volume of conference papers presents a selection of research conducted ceN ed at Alma Mater Europaea University and other research institutions. The research here is cutting-edge TIF ingIC C and highlights key trends and directions in project management that will undoubtedly be of inter- s BoO est to other researchers working in this field. NFE ok In the first article, Anna-Vanadis Faix and Stefanie Kisgen discuss the intersection between AI, quan -R : PEN tum computing, and social resilience. The second article, by Salik Ram Maharjan, examines a par- R OCE I ticular phenomenon, namely projectification, and highlights its impact on social enterprises in Slo - JET'S A CT venia and Nepal. In the third article, Jaroslav Viglaský and Milan Fil’a examine technical solutions in MB AO the sharing economy as a tool for sustainable development. In the following article, Mario Protu- NU AT P lipac and Jelena Kljaić Šebrek also highlight AI’s contribution to sustainable project development, G EMEO using a specific case study. Senzekile Mofok then discusses the application of AI using the example ENPL of a credit verification process. Finally, Reinhard F. Wagner, Karolina Novinc, and Mladen Radujković E 2 T, S describe the results of a study on the impact of AI on the training landscape for project managers. TR024 AT–2 These articles clearly show the extent of AI’s impact on our discipline and, at the same time, call for EG IC02 a redefinition of the role of humans in the digital age. This will certainly also be a topic of discussion C5 OM in the following issues of these conference contributions to “It’s About People.” We hope you gain valuable insights from reading these articles and that they provide new inspiration for projects and MUN the project management profession, serving the community and society at large in terms of devel-ICAT opment and well-being. ION M Assist. Prof. Dr Sc. Reinhard Wagner ANAGEM Deputy Head of AMEU International Doctoral Study in Project ManagementENT, W Prof. Dr Sc. Mladen RadujkovićEB Head of AMEU International Doctoral Study in Project Management AND INFOR ATM ION EC T H NOL O IEG S 9 w N ed addresses current challenges of contemporary communication in digital and social contexts. Al-A L S Pr though thematically heterogeneous, the contributions share a common point of departure: a re-CIE o flection on the role of communication as a key social process that shapes perceptions, attitudes, ce N ed TIF behaviours, and levels of trust among various publics. ing IC C The papers cover several research areas of communication, including digital and political communi-s Bo O N cation, organisational and internal communication, crisis communication in the healthcare system, ok FE R sociolinguistics of digital discourse, as well as socially responsible and ethical communication. Par-: P EN R er-R R About People‘ in 2024 and 2025. N ev AT This edited volume brings together diverse research from the field of communication sciences that ie IO Pe IN Communication Management that were successfully presented at the international conference ‚It‘s TE The submitted foreword provides an overview of the papers from the programme/section Strategic JE networks, digital platforms, new media formats, and technologies that simultaneously offer new T'S A CT M O ticular attention is devoted to communication in the online environment, with analyses of social CE I A O NU AB opportunities while raising ethical and professional dilemmas. T P A common denominator of all contributions is the emphasis on the relationship between communi- EN patients, voters, employees, and the general public. The research highlights the crucial role of trust, PL E 2 T, S EMG cation strategies and their reception among diverse groups, including students, social media users, EO TR 02 transparency, and credibility in communication, especially in the context of health and social crises, EG –2 AT 4 political processes, media commercialisation, and issues of sustainability and human rights. C 5 veys, questionnaires, and qualitative methods, thereby contributing to a better understanding of OM real communication practices and their effects. In this way, the volume positions itself as a rele IC Methodologically, the volume combines theoretical analyses with empirical research based on sur- 02 M - U vant contribution to the development of communication sciences, offering scholarly insights and N IC practical guidelines for improving responsible, strategic, and socially sensitive communication in AT contemporary society. ION M ANAGEM Assoc. Prof. Dr Božidar Veljković EN Head of the Doctoral Study Programme Strategic Communication Management T, W EB AND INFOR ATM ION EC T H NOL O IEG S 10 mental questions about responsibility, trust, and the evolving relationship between humans and w N edA technology. These challenging times require not only technical excellence but also reflection, inter -L S PrCIE disciplinary dialogue, and a strong commitment to human-centred values. o ceN ed Within this context, the Artificial Intelligence and Digital Technologies Department at Alma Mater TIF ingIC C Europaea University positions its research and study programmes at the forefront of applied AI de- s BoO velopment, while remaining critically grounded in ethical, societal, and educational perspectives. N okFE Our approach treats AI not as an isolated technical artefact, but as a socio-technical system shaped R : PEN by human needs and cultural contexts. The contributions presented in these proceedings reflect this consequences for society, comparable to earlier industrial and digital revolutions. AI increasingly er-R RN evAT permeates decision-making, healthcare, governance, education, and everyday life, raising funda- ieIO gence represents not merely another technological advance, but a systemic shift with immersive Pe INTE We are living in a period of profound transformation. The rapid development of artificial intelli- O CE I R direction, presenting applied AI and digital technologies as instruments for responsible, inclusive, JE T'S A CT and meaningful innovation. MB AO The It‘s About People Conference has grown into a vibrant academic community, bringing together NU AT P G doctoral researchers, students from bachelor‘s and master‘s programmes, and experienced scholars EMEO from diverse disciplines. This expanding community is clearly reflected in the 2025 edition. We hope ENPLE 2 that the research collected in these proceedings will not only inform readers but also highlight the T, S importance of education and human-centred technological development in shaping a future where TR024 progress remains firmly connected to people and society. AT–2 EG IC02 C5 OM Matej Mertik, PhD UNM Dean, Department of Artificial Intelligence and Digital Technologies ICAT ION M ANAGEMENT, W EB AND INFOR ATM ION EC T H NOL O IEG S 11 PROJECT MANAGEMENT 2024 PEOPLE MANAGEMENT WITH AN EMPHASIS w N edAL S Pr o ON RECRUITING EMPLOYEES IN THE POST-COVID CIE ceN edTIF ERA IN THE CATERING SECTOR: CASE STUDY ingIC C CZECHIA AND SLOVAKIA s BoON okFER : PEN R Published scientific conference contribution Pe INTE 1.08 Objavljeni znanstveni prispevek na konferenci er-R RN evAT ieIO Renáta Ježková, O CE I PhD, Associate Professor JE NEWTON University, Czech RepublicT'S A CT MB Karina Benetti, PhD AO NU AT P NEWTON University, Faculty of Economics, Czech Republic G EMEO Technical University of Liberec, Czech Republic ENPLE 2 T, S TR02 ABSTRACT 4 AT–2 EG IC02 The paper addresses people management in the catering sector, with a particular focus on em- C5 ployee recruitment in the post-COVID era. Its aim is to analyse the recruitment methods most OM affected by the COVID-19 pandemic, to identify the negative and positive impacts of the pandem- MU ic on people management in this sector in the Czech and Slovak Republics, and to compare the NIC post-COVID situation in gastro businesses with the pre-pandemic period. The paper draws on sta-ATION tistical analysis of a survey conducted among key personnel responsible for people management M in a sample of catering enterprises of various sizes and characteristics across the Czech and Slovak AN Republics. Our main findings highlight several key areas in which approaches to people manage -AG ment differ markedly between the two countries.EMEN Keywords: COVID-19 pandemic, People management, Catering sector, Czech Republic, Slovak T, W RepublicEB AND INFOR ATM ION EC T H NOL O IEG S 17 Pe 1 INTRODUCTION IN TE er-R R The novel coronavirus that causes the disease COVID-19 appeared in early 2020 and has significantly N ev AT changed global society (Parnell et al. 2020). The hospitality and tourism industry is vulnerable to ie IO w social and environmental changes (Dube et al. 2021). The impact of the COVID-19 pandemic has N ed A L S demonstrably and most seriously hit the catering sector as it is reliant on close contact between in- Pr dividuals as part of its business model. The COVID-19 pandemic has severely affected the restaurant o CIE ce N industry due to enforced closures and limitations on social gatherings, prompting restaurateurs to ed TIF innovate and adapt to ensure their businesses' viability. The pandemic has also induced changes in ing IC C our perceptions of safety in public spaces, necessitating the adoption of social distancing and more s Bo O N widespread use of online platforms for purchasing and communication (Chuah et al. 2021, Lo et al. ok FE R : P 2023, Macháček et al. 2020). Businesses relying on close physical interactions have been forced to EN R O CE I shut down, limit or change the nature of their operations (European Commission 2021). Widespread JE T'S A lockdowns with strict governmental interventions would probably be labelled as a pathological CT M B cause of recession (Greene and Rosiello 2020). While crises such as conflict situations have been A O N U found to negatively impact entrepreneurial intentions (Bullough and Renko 2013), in some ways, A T P G they can lead to resource voids that create opportunities for starting or changing businesses. Both EM EO management and employees have come together to craft ways for the business to survive during EN PL E 2 T, S this long-lasting pandemic. During this crisis, companies found creative ways to utilize their core TR 02 4 competencies, stretch the boundaries of their established business models, change the ways hu-AT –2 man capital relies on and utilize digital communication methods. Windows of opportunities that EG IC 02 firms may use for innovating are opened by new basic technologies, such as digitalization, a new C 5 OM type of demand or a major shake-up of existing demand and opportunities created by public inter- M vention (Dannenberg et al. 2020; Lee and Malerba 2017). U N IC Although the Czechs announced the largest entrepreneurial support program in Europe (as well AT as Slovaks did) offering direct aid to entrepreneurs, loan guarantees, interest-free loans and wage ION subsidies for employees that were forced to reduce their work including a tax break package, the M A catering sector with its contact intensive-services has suffered a significant outflow of labour to 'less N A G risky' sectors. It has become unattractive to many prospective employees at the expense of other, EM more stable sectors and attracting those who had been working in the sector for longer. One of the EN opportunities for re-entry to make the catering industry more attractive as a place of interest for the T, W creative potential of job seekers, and at the same time regain the current high interest in operating EB A of catering establishments, could be, except for change in approach to staff, paying attention to em - N D ployees´ motivation factors (Hitka et al. 2022), quality leader (Lee et al. 2017), attractive company IN culture, employer branding (Näppä 2023), owner´s characteristics and hiring practices (Reda et al. FOR 2010), also the employment of foreigners from Ukraine, who have been looking for almost two- M years refuge in the Czech Republic and Slovakia from the war conflict in their country. AT ION EC T 2 PURPOSE AND GOALS H NOL O The aim of the paper (case study) is analysing the ways of recruiting employees that were most IESG affected by the COVID-19 pandemic, identifying the negative and positive impacts of the pandemic on people management in this sector within the Czech and Slovak Republics, and comparing the post-covidian situation in gastro businesses in terms of people management with the situation be-fore the COVID pandemic. It focuses on methods of recruiting employees for gastro establishments, communication channels and technologies, key aspects of hiring employees, using new channels, reaching out to different generations, and ways of solving the lack of required personnel. Important aspects are preferences when compiling job offers, the preferred profile of applicants, experience with agency employees, and the employment of foreigners. 3 METHODS The impact of the post-COVID era on people management in the catering sector with an empha-sis on recruiting employees survey was conducted simultaneously in the Czech Republic and Slo-vakia between October 2022 and May 2023. The questionnaire consisted of three main parts - (1) 18 part concerning the influence of the post-COVID era on human resource management in companies er-R RN evAT in the field of gastronomy. The original data contained 317 companies, but not all files could be ieIO in the Czech Republic or Slovakia), (2) socio-economic characteristics of the respondent and (3) a Pe INTE identification data (year of establishment of the company, number of employees and its operation opened, so in the end, 303 companies were analysed, of which 274 were from the Czech Republic w N edA and 29 from the Slovak Republic. The socio-economic factors in the questionnaire included the type L S PrCIE of gastronomic establishment and a job position. A basic overview analysis of the ratio outputs of o ceN quantitative research was prepared. edTIF ingIC C 4 RESULTS s Bo ON okFER Regarding the age of the firms, the youngest firm had only one year of existence, and the oldest firm : PEN R OCE I has been on the market for 63 years; the modus of the age of the firms was 8 years, the median val - JE ue was 10 years, and the average was 12.6 years. The number of employees for firms ranged from 1 T'S A CT M to 315. The median number of employees was 11, the modal value was 10 and the average number B AO NU of employees per firm was 19.8 (i.e., 20). AT P G EM Socio-economic factors included in the questionnaire included the job position and also the type of EO ENPL catering establishment. In the Czech Republic, most responders came from restaurants (39%), cafés E 2 T, S (22%), pubs (10%), then bistros (8%), bars and other catering establishments (each 7%) and hotel TR024 premises (5%). In Slovakia, we interviewed mostly restaurants (45%), cafés and bars (17% each), AT–2 EG bistros (10%), hotels and pubs (4% each). IC02 C5 In the Czech Republic, members of top management and responsible representatives (each 33%), line OM managers (13%), "cumulative job positions" (11%) and HR managers (7%) were most questioned. In M Slovakia, most responders worked in a position of top management (38%), responsible representa- U N It is interesting to compare the results of the negative vs. positive impacts of COVID-19 on people ION M management (multiple choice):AN tives (31%), line managers and "cumulative job positions" (each 10%) and HR managers (7%). ATIC - The most negative impacts: AG- More than 30% of Czech firms reported that they had experienced a general shortage of em EM -EN ployees (similar to Slovak firms), that they had been forced to combine some positions (more T, W than 40% of Slovak firms) and that they had been forced to use flexible forms of employment EB (more than 40% of Slovak firms); A - More than 27% of Czech firms lost key and talented employees (almost 14% of Slovak firms); N IND the same percentage of Czech firms reported that their employees' productivity had deterio- FOR - The most positive impacts: ATION- More than 50% of Czech firms reported that they had tested the loyalty of clients (almost 45% rated (almost 50% of Slovak firms). M of Slovak firms). EC T - More than 40% of Czech companies have taken up the pandemic as a challenge (more than NOLH 50% of Slovak companies), they have also started to use more information technology (almost OG 38% of Slovak companies) and they have found out how they are doing with the loyalty of IES their employees towards the company (more than 41% of Slovak companies). The companies assessed the overall change in their human resources situation compared to the sit-uation before the COVID pandemic as follows: - Almost 45% of Czech companies felt that applicants were not interested in working in the cater- ing sector, considering that it is a risky field for them (the figure for Slovak companies was more than 55%); - More than 30% of Czech firms reported that there had been no significant changes (more than 41% of Slovak firms); - More than 17% of Czech firms said they had problems filling some key positions (they felt their business was at risk); for Slovak firms it was more than 3%; - More than 6% of firms said that they were unable to respond flexibly to the need to cover vacancies themselves (that is why they turn to agencies), for Slovak firms this was not the case for any firms. 19 w N edA 2. they rely more on younger candidates (32.12%), L S Pr 3. they pay more attention to the opinion of customers (28.47%), o CIE ce N- Slovak companies have indicated (in order of the top 3 by the highest number of indications): ed TIF ing 1. That they pay more attention to the opinion of customers and, in the same proportion, they IC C rely more on younger candidates (37.93%), s Bo O N FE ok 2. they care more about the company‘s image (34.48%), R : P EN 3. they are trying to care more about their employees and in the same proportion they have R er-R RN - Czech firms reported (in order of top 3 by highest number of designations): ev AT 1. That they communicate more on social networks (35.4%), ie IO Pe IN should be noted that firms could choose more than one answer here): TE Firms rated whether they were forced to change the way they recruited employees as follows (it O CE I started to survey customer satisfaction (31.03% recalculated). JE T'S A CT M It is interesting to see how companies use career portals, 18.61% of the Czech companies and 41.38% B A O of the Slovak companies use them. Furthermore, only 0.73% of the Czech companies participate in N U A T P G job fairs, none of the Slovak companies. Only 16.05% of Czech and 10.34% of Slovak companies co-EM EO operate with schools and search for the most skilled graduates. 6.57% of Czech and 3.45% of Slovak EN PL E 2 companies cooperate with schools and contribute to the education of their future employees by T, S TR 02 supporting talents during their studies (scholarships, internships). 21.53% of Czech and 20.69% of 4 AT Slovak companies have incorporated new technologies. Only 4.38% of Czech and 6.9% of Slovak –2 EG IC 02 companies use job sharing. Regarding making the company's conditions for attracting new candi- C 5 dates more attractive, 16.42% of Czech and 24.14% of Slovak companies answered positively. OM M To compare the answers of the surveyed companies from the Czech and Slovak Republics to the U N question of what they focus on when recruiting employees (again, more answers were possible, so IC AT the percentages are converted to the number of companies surveyed) we can obtain: ION - Czech companies focus most (top 3) on: M 1. Verbal references/recommendations from friends (47.67%), A N A G 2. recommendations from their employees (46.24%), EM 3. they hire and train average employees (30.47%). EN - Slovak companies focus most (top 3) on: T, W 1. Combination of internal and external recruitment (48.28%), EB A N 2. word of mouth references/recommendations from friends and, in the same proportion, rec- D ommendations from their employees (44.83%) IN FOR 3. they also hire average employees and train them (41.38%). ATM The services of employment offices are used by 12.9% of Czech and 13.79% of Slovak companies. ION 16.13% of the Czech companies surveyed introduced a monetary reward for employees who recom- EC T mended a worker who proved himself and stayed in the position for a longer period of time, in the H case of Slovak companies it was 24.14% of companies. NOL O School graduates are used by 20.43% of the Czech companies and 27.59% of the Slovak companies. G Employment agencies are used by 10.75% of Czech firms and no Slovak firms. Headhunting is used IE S by only 3.23% of the Czech companies and 17.24% of the Slovak companies. Czech companies use mainly advertisements in regional press (13.14%), advertisements in local radio (8.76%), printed job offers distributed to people's mailboxes in the area (6.57%). Slovak companies use advertise-ments in the regional press, advertisements in the national press and national TV stations (6.90%), advertisements in local press, advertisements on local radio and billboards (3.45%) and other forms are not used by the Slovak companies. Interestingly, 27.01% of the Czech firms surveyed use elec-tronic submission of applications; in Slovakia, it is 31.03% of firms. Czech firms use the least national TV stations, video questionnaires (1.82%) and advertisements in the local press (0.36%, only one Czech firm responded positively). Regarding the use of social networks for recruiting employees, 24.09% of the Czech and 13.79% of the Slovak companies answered negatively. Next, the questionnaire focused on the question of recruiting employees by generations X, Y and Z. From the results, it is clear that most of the surveyed companies focus on Generation Z (born in 1996-2010) when recruiting their employees, namely 48.54% in Slovakia, which is exactly 50% of 20 Lack of required personnel the Czech firms try to solve by employing foreigners (17.88%), by using w N edAL S the services of employment agencies (14.6%) and other ways (7.3%). Slovak companies by using PrCIE o employment agencies (17.24%), employing foreigners (13.79%) and by conducting their own re- ceN ed cruitment (3.45%). Considering the analysed data, it is clear that 57.66% of Czech and 65.52% of TIF ingIC C Slovak companies did not answer this question. s BoO If firms are making a job offer to fill a desired job position (considering the possibility of multiple N okFE answers, percentages are converted to the number of firms contacted for the Czech Republic and R : PEN Slovakia), then: between 1982 and 1995, is targeted by 37.23% of Czech and 25% of Slovak companies. A total of er-R RN evAT 31.02% of Czech and 19.44% of Slovak companies said they target all generations. ieIO i.e., Generation X (born in 1961-1981) when recruiting employees. Generation Y, i.e., those born Pe INTE the companies. Only 9.85% of Czech and 5.56% of Slovak companies focus on the oldest generation, O CE I R - Czech firms place the most emphasis on the positive overall impression that the candidate forms JE T'S A CT on the basis of the offer (47.81%), clear expression of all necessary requirements from the bid - MB AO der (41.97%) and presentation of all the necessary requirements related to the nature of the job NU AT P G (36.5%). EMEO- Slovak companies place the greatest emphasis on the positive overall impression that the bidder ENPLE 2 forms on the basis of the offer (51.72%), clear expression of all necessary requirements from the T, S bidder (44.83%) and the bonuses (employee benefits) offered with the job (37.93%). TR024 AT–2 The results of the analyses show that the biggest difference between Czech and Slovak companies EG IC02 in this area is the transparency of the selection process, which is emphasized by only 7.66% of the C5 OM Czech companies, while in Slovakia it is 27.59% of the companies. M U The most important for Czech firms as a potential employer are: We prefer the youthfulness, vitality N IC and creativity of the employee, whom we are happy to train (51.82%), we prefer expertise and AT professionalism (29.2%) and professionalism is supported by the number of years of experience ION (does not have to be expertise) and we value long years of experience, seniority, reliability and ex- M perience. Age is not a key criterion in the selection process (13.87%). The most important for Slovak ANA companies is: We prefer the youthfulness, vitality and creativity of the employee, whom we are GEM willing to train (68.97%), we prefer expertise and professionalism (27.59%), professionalism, which EN is supported by the number of years of experience (does not have to be expertise) (10.34%).T, W Czech and Slovak companies do not make much use of online interviews when selecting employees EB A – 88.32% of Czech companies and 96.55% of Slovak companies. On the other hand, Czech and Slovak ND firms make the most use of unstructured, unprepared, authentic, intuitive face-to-face interviews IN when selecting candidates – 65.33% Czech and 58.62% Slovak firms. On the contrary, a structured, FOR 24.09% of Czech and 31.03% of Slovak companies. A surprising finding in the surveyed set was that ATION carefully prepared personal interview, allowing comparison of individual candidates, is used by M by only 0.73% of Czech firms (only 2 firms reported this) and none of the Slovak firms. The telephone ECHNOL the quality of available documents from applicants (such as CV and cover letter) is rated as important T interview is used by 12.41% of Czech and 10.34% of Slovak companies. Firms do not use psycho- logical tests much either; only 1.46% of Czech and Slovak firms use them. Behavioural interview OGIE questions are used only by 3.65% of Czech and 3.45% of Slovak firms, and firms do not use stress S situations much in interviews - only 3.28% of Czech firms and no Slovak firms use them. Concrete practical situations are then dealt with in the interview by 15.69% of Czech and 17.24% of Slovak firms. A practical test day is applied by 28.83% of Czech companies and 48.28% of Slovak companies. The disparity of the survey results between Czech and Slovak companies can be seen in the approach to employees, whether employers have noticed in the post-COVID era the need to listen more to their employees - here 87.23% of Czech companies and only 3.45% of Slovak companies mentioned this need. Agency workers are used by 83.94% of Czech and 79.31% of Slovak companies. If firms indicated that they use collaborative employment agencies, they encountered the following barriers/issues: Lack of information about employees, unreliability of employees, unsuitable candidates (not always competent candidates), agency staff are not willing to work and make excuses for the language barrier, they do not want to be accepted in a team. Only four Czech and three Slovak companies 21 w N ed Interestingly, 83.94% of Czech and 79.31% of Slovak firms use agency workers, and only 33.58% of A L S Pr Czech and 20.69% of Slovak firms confirmed their experience of employing foreigners, suggesting CIE o that not all agency workers are foreigners. The majority of foreign workers are Slovaks and Ukrain-ce N ed TIF ians, while companies employ Russians, Poles, and Indians; some companies also employ Italians, ing IC C Ecuadorians, Nigerians, Japanese, Mexicans, and Spaniards. 58 firms (55 Czech and 3 Slovak) had a s Bo O N positive experience with employing foreigners - Ukrainians, 10 firms (9 Czech (3.28%) and 1 Slovak ok FE R (3.44%)) had a negative experience. Regarding firms' experience with employing Ukrainian work-: P EN R er-R R (13.13%) and 5 Slovak (17.24%)) firms were satisfied with agency workers, 27 firms were not (25 N ev AT Czech (9.12%) and 2 Slovak (6.89%)) and the rest of the firms did not answer this question. ie IO Pe IN for new employees so that no serious problems arise. The questionnaire showed that 36 (31 Czech TE reported no problems with agency applicants. One Czech firm said it is critical to set parameters JE barriers included language barriers. Firms reported that they had to pay for language courses in T'S A CT M O CE I ers, 46 Czech (16.78%) and 2 Slovak (6.89%) firms reported that the most common problems and A BO firms), while firms also reported a longer adaptation process, communicating as much as possible, N U order to adapt and integrate them into the work process (9 Czech (3.28%) and 2 (6.89%) Slovak A T P G or arranging accommodation. EN PLE 2 T, S EM EO EG –2 IC02 part in our research were about 12.6 years old with an average number of employees of 20 per firm C 5 which is indicative of the fact that Slovak and Czech gastro firms are predominantly small in nature OM and fall into the category of small firms (up to 50 employees). M U TR 024 On average, companies from the catering sector from the Czech Republic and Slovakia that took AT 5 DISCUSSION N In the Czech Republic and Slovakia, the largest number of gastro establishments was represented by IC AT restaurants, while the smallest number of respondents were from hotels, pubs and bars. More than ION 30% of those responsible for HR are members of management and persons in charge; we asked the M least about HR managers, who in the Czech Republic and Slovakia accounted for only 7% of respond- A N ents for people management. A G EM The most negative impacts on people management were reported similarly by the Slovak and Czech EN companies - more than 30% of them had experienced a general shortage of employees. They had T, W been forced to combine some positions, and they had been forced to use flexible forms of employ - EB ment; more than 27% of Czech firms lost key and talented employees (almost 14% of Slovak firms); A N the same percentage of Czech firms reported that their employees' productivity had deteriorated (al - D IN most 50% of Slovak firms). 27% of Czech and Slovak firms surveyed had to resort to employee benefits. FOR As for most positive impacts, more than 50% of Czech firms reported that they had tested the loyalty M of clients (almost 45% of Slovak firms), more than 40% of Czech companies have taken up the pan - AT ION demic as a challenge (more than 50% of Slovak companies), they have also started to use more in- T formation technology. They have found out how they are doing with the loyalty of their employees EC H towards the company (more than 41% of Slovak companies). NOL O The most significant overall change in human resources situation of the Czech and Slovak gastro es- IEG tablishments compared to the situation before the COVID pandemic is that they felt that applicants S were not interested in working in the catering sector, considering that it is a risky field for them (45% of Czech firms, 55% of Slovak ones). More than 6% of Czech firms said that they were unable to respond flexibly to the need to cover vacancies themselves (that is why they turn to agencies), for Slovak firms this was not the case for any firms. As for changing the way the companies in gastro recruited employees, more than 35% of Czech ones communicate more on social networks and about 32% of them rely more on younger candidates. Slovak companies pay more attention to the opinion of customers and, in the same proportion, they rely more on younger candidates (almost 38%) and in almost 35% of them, they care more about the company image. Using career portals is popular with more than 18% of the Czech companies and about 42% of the Slovak companies use them. No Slovak companies participated in the job fairs and more Czech (16%) than Slovak companies (10%) cooperate with schools and search for the most skilled graduates. 22 employees. In case of Slovak companies during a recruitment process they focus most on combina- w N edAL S tion of internal and external recruitment (in more than 48% cases), word of mouth references / rec- PrCIE o ommendations from friends and also from their employees; and they also hire average employees ceN ed and train them. The service of the employment offices is used in both countries at the same level TIF ingIC C (almost 13% of companies). More Slovak companies (more than 24%) than the Czech ones prefer a s BoO monetary reward for employees who recommend a worker who proved himself and stayed in the N okFE position for a longer period of time. School graduates are used more in the Slovak companies (al-R : PEN most 28%). Almost 11% of Czech firms use employment agencies, no one Slovak firm. Headhunting When recruiting people Czech companies focus most on verbal references (recommendations from er-R RN evAT friends) – more than 47%, recommendation from their employees and they hire and train average ieIO (24.14%) try to make their corporate environment more attractive than Czech ones (16.42%). Pe INTE About 20% of Slovak and Czech companies have incorporated new technologies. Slovak companies O CE I R is much more popular in Slovakia (more than 17% compared to Czech 3.23%). JE T'S A CT As the recruitment channels, Czech companies prefer advertisements in regional press (more than MB AO 13%), advertisements in local radio, printed job offers distributed to people´s mailboxes in the are - NU AT P G as, billboards and advertisements on local TV. In Slovakia the gastro companies prefer these recruit- EMEO ment channels: advertisements in the regional press, in the national press and national TV stations ENPLE 2 (almost 7%), then advertisement in local press, on local radio and billboards and other forms. Gastro T, S companies in Slovakia use more electronic submission of applications then in Czechia (31% to 27%) TR024 and this positive trend also causes use of social networks for recruiting people. AT–2 EG IC02 Although a total of 31% of Czech and almost 19.5% of Slovak companies said they target all gener- C5 OM ations when recruiting employees, from the results it is clear that most of the surveyed companies focus on Generation Z (born in 1996-2010) when recruiting their employees (exactly 50% of the MUN companies). Generation Y (born between 1982-1995) is targeted by 37% of Czech and 25% of Slovak ICAT companies and generation X, the oldest one (born between 1961-1981) is targeted by only 9.85% of ION Czech and 5.56% of Slovak companies. M Lack of personnel required the Czech companies solve by employing foreigners (almost 18%), by ANA using the services of employment agencies and other ways. Slovak companies use employment GEM agencies (more than 17%), employ foreigners and realize their own recruitment. EN If firms are making a job offer to fill a desired job position, then Czech firms place most emphasis T, W on the positive overall impression that candidate forms on the basis of the offer (almost 48%), clear EB A expression of all necessary requirements from the bidder and presentation of all the necessary re -ND quirements related to the nature of the job. In Slovakia, positive overall impression that candidates IN forms and clear expression of all necessary requirements from the bidder are on the same level FOR comparing to Czechia, but the third most important condition are bonuses (employee benefits) of -MAT fered with the job (almost in 38%). The results of the analyses show that the biggest difference be -ION tween Czech and Slovak companies in this area is the transparency of the selection process, which is T emphasized by only 7.66% of the Czech companies, while in Slovakia it is 27.59% of them.ECHNOL The most important things for the companies as potential employers are consistently in both coun- tries: prefer youthfulness, vitality and creativity of the employee, whom they are happy to train OG (almost 69% in Slovakia to 52% in Czechia), preferring expertise and professionalism (27.6% in Slo- IES vakia to 29.2% in Czechia). The answer considering preferences of professionalism is supported by the number of years of experience (13.87% in Czechia to 10.34% in Slovakia). The biggest difference is between the value of long years of experience, seniority, reliability, and experience (13.87% in Czechia to 6.9% in Slovakia). Czech and Slovak firms use unstructured, unprepared, authentic, intuitive, face-to-face interviews when selecting candidates (65.33% Czech to 58.62% Slovak firms). A structured, carefully prepared personal interview, allowing comparison of individual candidates, is used by 24.09% of Czech and 31.03% of Slovak companies. The quality of available documents from applicants is rated as impor-tant by only 0.73% of Czech firms and none of the Slovak firms! Concrete practical situations are dealt with in the interview by 15.69% of Czech and 17.24% of Slovak firms. Practical test day is applied by 28.83% of Czech and 48.28% of Slovak companies. 23 er-R R about employees, unreliability of employees, unsuitable candidates (not always competent), N ev AT agency staff are not willing to work and make excuses for the language barrier, they do not want ie IO Pe IN frequent barriers to using collaborative employment agencies were noticed: lack of information TE Agency workers are used by almost 84% of Czech and about 79% of Slovak companies. The most w N to be accepted in a team. 13% of the Czech and 17% of the Slovak firms were satisfied with agency ed A L S Pr workers; 9% of the Czech and almost 7% of the Slovak firms were not. Not all agency workers are CIE o foreigners. The majority of foreign workers are Slovaks and Ukrainians, while companies employ ce N ed Russians, Poles, Indians, Italians, Ecuadorians, Nigerians, Japanese, Mexicans and Spaniards. More TIF ing IC C Czech than Slovak firms have a positive experience with employing foreigners. In terms of the ok FE included language barriers. The firms paid for language courses in order to adopt and integrate R : P s Bo O firm´s experience with employing Ukrainian workers, the most common problems and barriers N CT T'S A MB AO NU 6 CONCLUSION A T P G O CE I and arranging accommodation. JE R EN them into the work process, which caused a longer adaptation process, intensive communication EN PL the catering sector in the Czech Republic and Slovakia are similar, which confirms the proximity of E 2 T, S EM In many areas, the solutions to the problems related to the impact of the COVID-19 pandemic on EO TR 02 these now two independent republics and, at the same time, the similar corporate culture of their EG in this area, which point to the trends that the catering sector in both republics is following in the IC 02 C AT 4 catering sector. Nevertheless, it is clear from our survey results that there are significant differences –2 OM 5 post-COVID era. M Our results show a more positive attitude of Slovak gastro entrepreneurs towards the impact of the U COVID-19 pandemic on their business. Using career portals is much more popular in the Slovak com- N IC panies than in the Czech ones. On the contrary, participating in the job fairs is more popular among AT ION the Czech firms. More Czech companies cooperate with schools and more Slovak companies try to AN the Czech companies solve by employing foreigners, but Slovak companies use more employment A G M make their corporate environment more attractive than Czech ones. Lack of personnel required EN the transparency of the selection process, which is much more emphasized in Slovakia. A quality of available documents from applicants is rated as important less than 1% of Czech firms and no one EM agencies. The biggest difference between Czech and Slovak companies according to our results is EB of Slovak. Next area with a significant difference is the most important thing for the companies as A potential employers – Czech companies value more long years of experience, seniority, reliability T, W IN ness owners – employers, employees and other stakeholders involved in doing business and people FOR D and experience than Slovakia. We hope these results will serve as a foundation for educators, busi- N M management in catering sector and are able to influence their plans, strategies and trends in the AT coming period. ION Although this study provides valuable insights into post-COVID developments in the Czech and T EC Slovak catering sectors, several areas merit deeper investigation. Future research could examine H NOL longitudinal data to track how recruitment practices and employer–employee expectations evolve O over time, particularly as both labour markets continue to adjust to demographic and technological G IE changes. 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Journal of Small Business & Entrepreneurship 23(3): 445-460. Available at: TE 16. Reda, Barbara, and Linda Dyer. 2010. Finding Employees and Keeping Them: Predicting Loyalty N O nomics of TUL, Czech Republic. In her work, she focuses specifically on statistical analysis and risk U A T P G management and modelling. EM EO EN PL E 2 T, S TR 02 4 AT CT T'S A M Karina Benetti is an assistant professor at NEWTON University in Prague and at the Faculty of Eco-B A JE various types of organizations and sectors in the Czech and Slovak Republics. O CE I R EG –2 IC02 C5 OM M U N ATIC ION M ANAGEMENT, W EB AND INFOR ATM ION EC T H NOL O IEG S 26 2025 FROM ‘DIGITAL FIRST’ TO ‘DIGITAL FOR PEOPLE’: w N edAL S Pr o LEADERSHIP AS AN INTERFACE BETWEEN AI, CIE ceN edTIF QUANTUM COMPUTING AND SOCIAL RESILIENCE ingIC C s BoONFE ok Anna-Vanadis Faix, PhDR : PEN Alma Mater Europaea – ECH Published professional conference contribution Pe INTE 1.09 Objavljeni strokovni prispevek na konferenci er-R RN evAT ieIO O CE I R School of International Business and Entrepreneurship (SIBE), Herrenberg, Germany JE T'S A CT M Stefanie Kisgen, PhD, ProfessorB AO NU Alma Mater Europaea – ECH AT P G School of Business and Entrepreneurship (SIBE), Herrenberg, Germany EMEO ENPLE 2 T, S ABSTRACT TR024 AT–2 The world we live in is becoming increasingly fast-paced. New (technical) innovations are con- EG IC02 stantly creating competitive pressure on the market and for organizations. New technologies, C5 OM such as AI-systems, are already having a far-reaching impact on our lives. And we have barely M entered the digital age when the quantum computer (QC) will soon have a lasting impact. At the U N IC same time, humanity is facing key challenges such as the climate crisis and political instability. AT In our presentation, we want to focus on the interface between the technical innovation of QC, ION AI and leadership. After all, technical innovations offer a wide range of possible applications and M are a tool for meta-innovation. However, not every ‘novelty’ is necessarily a blessing. Our main ANA thesis is therefore: Technological innovation and its potential for meta-innovation requires more GEM innovation quality and therefore leadership. Leadership therefore is always determined by nor -EN mative aspects and should place an increasing focus on ethical aspects to drive (technological) T, W innovations forward in a right manner. This quality should be determined by the well-being of EB individuals and the creation of value in society (not purely profit or GDP). An increase of normative AN (and ethical) aspects of leadership can thus lead to an increase in social-technological resilience.D IN Keywords: Technological revolution, Meta-innovation, Disruptive innovation, (Ethical) Leader-FOR ship, Social welfare MATION EC T H NOL O IEG S 31 Pe 1 INTRODUCTION IN TE er-R R The world we live in is becoming increasingly fast-paced and is characterized by technical innova-N ev AT tions and advances. Above all, artificial intelligence (AI) systems and applications are changing our ie IO w everyday lives but also markets and business structures (Carbon et al. 2021, 175). This effect will N ed A L S be further amplified in the near future by the quantum computer (QC). These developments are Pr already leading to increasing pressure for technical innovation and faster market response. Com-o CIE ce N panies that use AI are already achieving a significant competitive advantage over those that do not ed TIF (Mainzer 2020). Corresponding forecasts can be made for the application of QC and its intelligent ing IC C combination with AI (ibid.). Any company that wants to hold its own must be able to keep up in s Bo O N the long term. 1 ok This process is self-sustaining because AI and QC are not only highly disruptive in-FE R : P novations but also serve as tools for meta-innovations. Within a company, executives are crucial for EN R O CE I the application, implementation, and utilization of technical innovations (Oke et al. 2009; Hagen-JE T'S A dorff 2020). Corresponding effects arise solely from market processes and directly impact the area CT M B of leadership. For example, Smith and Green (2018) consider AI as a new follower of a leader, as A O N U well as workplace shifts and new challenges that arise from them. Huchler et al. (2020) question A T P G the human-centered design in this context. In contrast, Pfeifer et al. (2022) examine the influences EM EO of AI on leadership in a holistic approach. Delponte (2018), on the other hand, integrates AI directly EN PL E 2 T, S into a vision-centered approach to leadership (conceptually defining). TR 02 4 Bourton et al. (2018), Hougaard and Carter (2024) hypothesize that AI can produce better leaders AT –2 EG by making them more creative, innovative, and transformative – AI thus contributes to significant IC 02 C 5 advances in the field of leadership. However, the question remains as to how this opportunity can OM be best utilized by leaders in the light of AI and QC, and what this means in the field of leadership. In M U other words, when will leadership become “better” in the context of current technological develop-N IC ments, and what demands will have to be placed on leadership in this regard? Because it is precisely AT in the context of meta-innovation and the enormous potential associated with it that more and ION more problems arise. Contrary to the usual market paradigm, innovation does not always promote M A prosperity and is not associated purely with positive effects.2 Rather, a consideration of industrial N A G revolutions shows that they are also associated with negative external effects (see Nasrudin 2011; EM Faix 2023). With increased pressure and potential for innovation through technological develop-EN ments, the question of the quality of an innovation in terms of the choices of action of leadership in T, W the company becomes central. For example, approaches such as those of Qwaider et al. (2024) and EB A Malti (2024) raise the question of ethical leadership in the light of AI, but not against the background N D of decisions to act on innovation. They argue that AI at least suggests the possibility of increased nor- IN mative aspects of the task of leadership. However, more in-depth analyses with regard to normative FOR specifications are lacking. So the question remains: What normative requirements arise from AI, QC M and their potential for meta-innovation with regard to innovative action decisions in the leader-AT ION ship area of businesses? The central thesis of this article is that, in the age of AI and QC, the quality T of innovation depends crucially on the normative orientation of leadership, which must integrate EC H ethical considerations and the creation of social values in order to ensure sustainable technological NOL progress and the resilience of society. O G IE S 2 PURPOSE AND GOALS The aim of this paper is to analyze leadership at the interface of AI, QC and the resulting decisions on how to act in terms of innovation. The following main theses will be argued: (T1) On the one hand, the world is becoming more and more fast-paced and AI, QC and their intelligent combination 1 For a specific breakdown of the debate, see the factors of competition that AI can be used to specifically reduce costs and increase speed in companies: Cockburn et al. (2019, 119). 2 The consequences of the negative effects of innovations only become directly apparent through the con- sumption of human energy and resources, as described by Lange et al. (2023). They are also indirectly linked to the so-called risk tipping points, which are reached when a social system can no longer bear risk factors. See UNU EHS (2023). Furthermore, the negative consequences of technical innovations become apparent indirectly (through energy consumption, etc.). See WEF (2022) and IPBES (2019). 32 innovations (network). (T2) er On the other hand, innovations often not only have positive effects, but -R RN evAT also negative externalities. For example, although constant innovation increases people’s stand- ieIO novations are (usually highly) disruptive innovations that, when used correctly, can produce further Pe INTE increase the pressure to innovate in the market and create potential as meta-innovations. Meta-in- ard of living and provides better employment opportunities, it also leads to bottlenecks in resource w N edA use and environmental pollution (Nasrudin 2011) . In view of these negative externalities, there is L S PrCIE also evidence (especially in industrialized countries) of an increasing shift in market demand to- o ce wards greater sustainability and social aspects. 3N The pressure on companies to take these aspects edTIF into account is also increasing, and management must incorporate this into their decisions – also ingIC C ed in the light of technological developments - B AO N . 4U This is done on the basis of Sen (2003). (T4) On this AT P G basis, it should be shown that the quality of an innovation and thus the leadership and its decisions EMEO EN for action are to a large extent shaped by normative (ethical) aspects. Consequently, more (actual) PLE 2 T, S leadership is needed instead of pure management. TR024 AT–2 EG 3 METHODS IC02 C5 OM In order to demonstrate the stated objectives and formulated theses, a qualitative approach was M chosen that follows a literature study design. In conducting the literature review, a philosophical U N is therefore important to ask the question of a possible quality of innovation, instead of just always : P EN R OCE I JE being (incrementally) innovative. This quality is to be generated in the sense of a smart future with T'S A CT M better possibilities for quality of life, as already argued by Lee and Trimi (2008, 1) and to be expand innovation potential and pressure from AI, QC and meta-innovations and market developments, the ok FER focus on management’s decisions to act in this regard is growing. Within the management task, it in the context of trust and credibility (Edelman Trust Barometer 2017). s Bo O (T3) Within the increased N normative frameworks rather than undertaking direct empirical testing. The results and forecast ATION and analytical orientation was applied, with the purpose of systematically exploring concepts and IC ing primary and secondary sources, which serve as the data corpus for analysis (Creswell 2009). ANA The review was carried out systematically across peer-reviewed journals, conference proceedings, G presented in this paper are therefore based on a critical and interpretive engagement with exist- M JSTOR, and SpringerLink were consulted and keywords included “AI and leadership”, “quantum com EN -T, W and selected industry reports published between 2000 and 2025. Database such as Google Scholar, EM technological innovation, leadership, or normative frameworks. Exclusion criteria involved works A puting and innovation” and “ethical leadership”. The inclusion criteria required a clear relevance to EB focusing solely on technical or engineering aspects of AI or QC without explicit reference to innova- ND tion, leadership or the normative dimension. IN FOR rent literature adequately covers the most important developments in AI and QC; (2) that leadership ATION theories can be meaningfully linked to technology-driven innovation processes; and (3) that nor- The assumption guiding this methodical approach can be summarized as follows: (1) that the cur- M mative and ethical aspects of leadership remain underrepresented in current innovation models TEC and therefore require analytical elaboration. Based on these assumptions, inductive reasoning was H NOL used to identify trends and forecasts for AI, QC, and their combined potential as meta-innovations (in OG relation to T1 and T2). The data was compared and coded according to thematic categories, which IES allowed recurring patterns and conceptual relationships to be identified. On this basis, deductive reasoning was used to extend the analysis to the normative determination of innovation quality and leadership (in relation to T3 and T4). The approach thus combines induc-tive insights from the literature with a logical-deductive framework to justify the need for norma-tive-ethical leadership. At the same time, the study follows a thematic investigation and reflexive 3 For more information, see, for example, Statista (2017) or Transfair (2017) for data in Germany. This is also reflected in political pressure, as discussed by Cormier et al. (2005). An analysis of this pressure for more sustainability and sociality in corporate innovation decisions (beyond Germany) can be found in Hall and Vredenburg (2003). 4 The idea that innovations are characterized by their effects on the well-being of society as a whole can al- ready be found in Drucker (1993). Aspects here are to be understood in social, ecological and technological terms, but do not follow a holistic understanding of well-being. 33 w N ed Despite the systematic approach, several limitations and restrictions must be taken into account. A L S Pr First, the analysis is qualitative, interpretative, and philosophical in nature, which means that it CIE o does not claim to be empirically generalizable. Second, the use of existing literature carries the risk ce N ed TIF of bias, particularly in favor of Western and European academic traditions, which may result in di-ing IC C verse cultural or regulatory perspectives not being taken into account. Third, the lack of large-scale s Bo O N longitudinal data on real-world QC applications limits the predictive power of the arguments. Con-ok FE R sequently, the analysis should be viewed as a conceptual investigation rather than an empirically : P EN R er-R R forms the theoretical basis for the central question of when leadership through AI and QC becomes N ev AT “better” leadership and why such an improvement requires a normative orientation. ie IO Pe IN QC developments and their normative implications are systematically linked. This combination TE categorization (Alvesson and Skoldberg 2000), ensuring that both empirical descriptions of AI and JE empirical investigations. Three directions are particularly promising: (a) empirical testing of the T'S A CT M O CE I verified model. Future research should therefore build on these analytical foundations and conduct A BO izational contexts; (b) broadening the scope beyond Western perspectives to include comparative N U proposed relationships between leadership quality and normative innovation outcomes in organ- EM EO bining literature-based analyses with mixed methods such as surveys, interviews, and case studies EN A T P G analyses of leadership and innovation in different cultural and regulatory contexts; and (c) com-T, S PLE 2 to link conceptual and empirical perspectives. Such extensions would help to validate, refine, and TR contextualize the theses presented here and provide a more comprehensive understanding of how 02 4 AT AI and QC interact with leadership in shaping innovation quality. In summary, the methodological –2 EG IC 02 orientation of this study is grounded in a philosophical-analytical literature review and this analyt- C 5 ical stance allows for the development of theoretical arguments and the formulation of normative OM proposition about leadership and social-technological resilience. M U N IC AT 4 RESULTS ION AN has a broad and indispensable influence on our daily lives and many corporate structures. Especially A G M The relevant literature illustrates the development of AI and QC without contradiction. AI already EN encompasses machine learning and neural networks (Argrawal et al. 2009; Heil 2021). Many au- tomated decisions can and are already being taken over by AI because they can map selection pro- EM in recent years, the understanding of AI has shifted from “narrow” to “broad” to “general” and now EB cesses across broad data analysis and processes (Kleesiek et al. 2020). The enormous developments A in the field of AI in recent years are mainly due to the increasing computing power, but also to the T, W IN companies to save costs and speed up processes. On the other hand, it means that the company itself FOR D ever-increasing availability of data itself (Cockbourn et al. 2019, 199). NOn the one hand, this enables M is more likely to be innovative as a result.5 The quantum computer will greatly accelerate this effect AT (see IBM, 2023; Brooking Analysis 2023). Calculating with qubits instead of normal bits increases ION performance and application enormously. 6 This not only enables QC to perform calculations much T faster, but also to solve complex tasks with multiple variables (Mainzer 2020; McMahon 2007). This EC H NOL prognosis emerges also from a review of the literature concerning the question of the use and ap - O plication of quantum computing in a specific company.7 So while there may not yet be any quantum IEG advantages, there is already quantum utility (Bogobowicz et al. 2024). While the former predict the S advantage of QC over conventional systems in the near future, the latter points out that QC is current- 5 One example is the ENN Group, which uses an automated AI platform to support its employees in their daily work with features customized to their individual needs (ENN Group, 2024). Watson and its AI technology also enabled the company Woodside, for example, to reduce its research time by 75% (Watson, 2024). 6 While normal bits can always represent one state [0] or the other [1], qubits can be in both states and infinite states in between at the same time. 7 For example, Kossman et al. (2023) show open-shop scheduling in the sense of optimization problems with QC. While Stühler et al. (2023) present benchmarking for price forecasting. Other examples include the use of QC at Bosch for material design and the industrialization of quantum sensor technology (Bosch 2025), the development of better aircraft surfaces at Boeing (Boeing 2023), the development of chemical designs and hydrocarbons, the simulation of small molecules (JSR 2023), and the global route planning of merchant ships (ExxonMobil 2023). 34 is due to the direct effects of AI and QC (IBM 2023; Chuckburn et al. 2019), On the other hand, this re w N - edAL S sults from the possibility of meta-innovation of AI and QC, as well as their intelligent combination. 8 PrCIE o They are not only highly disruptive in themselves, but also a means of creating further innovations ceN or even networks of innovations. 9 ed As a consequence, this means that not only is the world becoming TIF ingIC C increasingly fast-paced, but it is also constantly progressing within the range of innovations (Carbon s BoO et al. 2021). However, this is not always exclusively positive: as already indicated, innovations give N okFE rise to a number of negative externalities associated with pollution and energy use, as well as other R : PEN factors related to population growth, etc (Nasrudin 2011; Faix 2023). An overview of positive and These developments are increasing the pressure on companies and their management to innovate er-R RN evAT and compete (Iansiti and Lakhani 2023; Gebauer et al. 2011; Kindström 2010). On the one hand, this ieIO power and error approximation (Kim et al. 2023, p.500; Chouwdhury et al. 2024). Pe INTE ly already producing comparable results to those of conventional systems with limited computing O CE I R negative factors of innovation can be summarized as follows, based on Witt (2003) and Nasrudin JE T'S A (2011) across industrial revolutions: 10 CT MB AO NU Figure 1: Positive and negative effects of innovation. AT P G EMEO Positive effects: Negative effects: ENPLE 2 Goods available in abundance & variety Increasing social problems in urban areas T, S TR024 More job opportunities & higher labour product. Environmental pollution & resource depletion AT–2 EG Better education standards & health care Wealth gap & structural unemployment IC02 C5 OM Increase national income & opportunities Increase imports of raw material, goods etc. M Rising standard of living & human rights Negative foreign investment effect U N Trade balance improvement Worker exploitation ATIC More qualified workforce & -place ION More stress & less family time (Source: Authors.) A M So far, the following effects can be summarized: The pressure to innovate in companies is increasing, AN EMG but they also have an increasing number of innovation potentials and orientations (meta-innova-tion). On the other hand, awareness of negative external effects for innovations and requirements EN for them is increasing (Statista 2017; Transfair 2017; Danciu 2013; Gualandris and Kalchschmidt T, W 2014). Both effects are related, and AI, QC and meta-innovation thus intensify social and sustaina EB - AN bility issues Since these questions about innovation and its direction fall within the specific remit of D IN a company’s leaders, and since leadership has the greatest influence on innovation in the company FOR (and indeed makes it possible in the first place), the issue here is specifically an increasing problem M of decision-making regarding action on innovation potential in the management area itself.ATION In the abundance of potential for innovation (meta-innovations) and the forecasts presented, it is T helpful to provide a suitable concept that can map and summarize the requirements. If leadership is ECH to be good, it must be innovative and guide it accordingly. There is a wealth of literature on theoret-NOL ical models of social innovation and responsible innovation (RI). However, these are usually rooted OG in political and legal systems and do not reflect the issues at the interface between AI and QC. If a de -IES cision is to stand up to prevailing market terminology, it must be pro-competitive. An approximation of this can be found in Faix et al. (2015), in which innovation quality is defined as a concept across all social levels as a field of management activity (internal and external). The important aspect here is that an innovation can only be successful if it is also realized and creates value in the long term in the 8 This connection can be aligned directly by coupling AI to the computing power of QC, as well as indirectly by using quantum algorithms in conventional AI (Klaus et al. 2023; Abdelgaber and Nikolopoulos (2020); Rawat et al. (2022). 9 One example of this is the intelligent use in the development of antibiotics and other new medicine. 10 The effects mentioned of increased social and sustainable demand due to increased awareness of global effects (see Chapter I) reinforce the effect in their consequence on companies and the perception of them. It should also be noted that AI and QC can, depending on the application and consumption, promote or not promote sustainability. 35 er-R R broader context, the definition does not appear to be one-sided or contrary. The approach of Sen N ev AT (1997 and 2013) and/or Nussbaum (2013) can provide an important concept that can be used here ie IO Pe IN Since Drucker (1993) and other approaches in economic tradition already define innovation in this TE society. Accordingly, quality is determined by value creation and requires goal-oriented leadership. w N for the extended purpose of the evaluation. The concept criticizes the GDP in distribution issues and ed A L S contrasts it with the capability approach. 11 Pr The central insight is that well-being or value creation CIE o must be understood in normative terms: in the sense of the consequences for all those affected and ce N ed an indirect social consensus (see e.g. Nida-Rümelin 2019). Well-being per se is then neither purely TIF ing IC C economic nor completely contrary, but dependent on various normative determinations of this so- N O take management further and reduce the negative external effects of innovations. In the sense of U A T P G the extended definition of this quality, an orientation towards normative factors – including lead - EM EO ership – is indispensable. This requires more leadership and also more ethical leadership (Faix et al. EN PL E 2 2020; Ciulla 2014). More leadership and, above all, ethical leadership (however this is then further T, S described in detail) is necessary because the implementation of innovations and the setting of inno- TR 02 4 AT vation goals is to be understood in terms of leadership qualities (by definition): more motivational, –2 EG IC 02 disruptive, visionary goals and conditions, instead of targeting organizational, coordinative factors C 5 of the classic management area (Drucker 1993 and 1994). Both the classification of normative fac - OM tors in one’s own actions and their implementation in an organization or company are processes M U N that take place in a social environment and require appropriate leadership in their implementation IC and realization (instead of management). The developments towards an increased importance of R EN Since AI and QC are seriously increasing the pressure for innovation, making it more difficult for man-O CE I JE agement to implement and align innovation, and further fueling it through further market pro-T'S A CT M cesses, the innovation quality defined in this way is an initial fundamental methodology that can B A ok FE corporate orientation and is not a contradiction in terms (Spitzeck et al. 2009). R : P s Bo O ciality (ibid.). Initial studies show that this also brings long-term competitive advantages through N ATION these processes demand more normative leadership aspects and more leadership per se (in the AN market processes of technical innovations, we need leadership in this sense and leadership based A M definitional sense). If we want to shape new technologies for people rather than chasing after the EN effects for all and can, on the other hand, strengthen social-technological resilience (through value creation and meaningful selection mechanisms). T, W EMG on normative standards. This prevents a valueless progression of the fast pace, negative external EB AN 5 DISCUSSION D IN Key points that suggest themselves in the context of the development of an approach towards an FOR increased need for (normative-ethical) leadership and a model of innovation quality in the light of M AT developments in AI and QC require a concluding discussion. On the one hand, there is a wide range ION of concepts of value creation in a social context, as well as countless models of well-being that take T into account factors (beyond pure GDP growth; see e.g. Doyal and Gough 1991). A discussion of EC H NOL these has so far remained open and is due to the broad application of the capabilities approach and O GINI index, as well as his argumentative conviction. However, since the approach is defined in terms IEG of innovation and leadership, it would be questionable whether an extended examination and con- S sideration would be meaningful at all. Factors here would be, if derivable from empirical testing. At this point, therefore, there is a need for more extensive debates that provide practical models for action with concrete instructions. However, it should also be noted at this point that more of leader-ship – in the context under discussion – is oriented towards open situations and cannot specifically prescribe actions (creative and disruptively innovative action). A fundamental discussion can also be found in the concept of innovation, since there are countless definitions and models available here alone and they are discussed inconsistently (Kisgen 2017). The analysis is based on the original definition by Schumpeter (1911), which is taken up again in most modern definitions. She also de-termines the basic definition of leadership uses here. 11 Concrete formulations of these forms of empowerment can be found in the GINI index. See, for example, Federal Statistical Office (2015). Whereby expanded conditions would have to be applied depending on the innovation question in the corporate context against the background of innovation questions. 36 (RI, see e.g. Ruggiu 2019). In a business context, the main focus of RI is on the specific implementa er --R RN evAT tion and models for implementation (Lubberink et al. 2017). The concept is based on the assumption ieIO the discussed normative references of innovation and current approaches of Responsible Innovation Pe INTE A further debate in this direction, which was only briefly touched upon, would be the agreement of that innovations will be produced that are socially desirable and ethically accepted (Sutyliffe 2011; w N edA Von Schomberg 2013), which are usually seen in juxtaposition to the traditional growth objectives, L S PrCIE profit maximization and competitive advantage (Owen et al. 2013; van den Hoven et al. 2014). IR o ceN should initiate a paradigm shift in this regard and the proximity to the model presented can be seen edTIF in the factors (Timmermans, 2020). However, the RI approach always describes a political and legal ingIC C this could be integrated into leadership decisions (without being queried). This is precisely why the A BO NU AT P G normativity of the approach and the ethical conditions of leadership are so important and would EMEO EN ideally be self-regulating (Ciulla 2014, 13).PLE 2 T, S TR024 6 CONCLUSION AT–2 EG IC02 In summary, it became clear that forecasts and current developments in the field of AI and QC require C5 OM more leadership, but above all leadership that takes normative (and ethical) aspects into account. M This applies at least when technological innovations are to be used in a targeted manner—in the U N general, a consensus within a society. The above consideration indirectly suggests references to col- : P EN R OCE I JE lectively rational decisions here. However, this is more difficult to implement from a global perspec -T'S A CT M tive, since political and legal conditions should not be ignored. It remains unclear, however, how is difficult to integrate in the sense presented (Genus and Iskandarova 2018). The most important ok FER factor in the context of the discussion, however, would be how to define a social consensus or, in link in juxtaposition to the traditional economy, and the prognosis from the perspective of AI and QC s Bo ON well-being. Only in this way can innovation be successful as a management task in the long term, ATION sense of the long-term orientation of companies on the market and thus also of the law firm and its IC and targeted implementation. From a normative perspective, leadership then relates to the law ANA firm and the well-being of all those affected (at all levels). Well-being cannot be defined purely in G mitigate negative external effects, and be driven forward through vision, creativity, motivation, M economic terms but must take into account fundamental normative aspects and a variable social EM consensus. Finally, it should be mentioned here that a more conceptual definition of leadership and EN ethically and normatively oriented leadership go hand in hand (Ciulla 2014). The central thesis of T, W this article is therefore that the quality of innovation in the age of AI and QC is not determined sole EB - AN ly by speed or efficiency, but by the normative orientation of leadership decisions. Future research D IN should empirically test whether such normative orientations in leadership actually promote higher FOR innovation quality and socio-technological resilience in different organizational and cultural con -M texts. From a practical perspective, the central recommendation is that managers should introduce ATION framework concepts for innovation quality that explicitly integrate ethical and normative criteria and ensure that AI and QC innovations serve the well-being of society and do not merely follow TEC market-oriented imperatives.HNOL O IEG S 37 Pe REFERENCES IN TE er 1. 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Mono -TE R EN O CE I Stefanie Kisgen is a professor of leadership and future forecasts at the Steinbeis-Hochschule and the JE T'S A CT School of International Business and Entrepreneurship (SIBE) and CEO of the Alma Mater Europaea MB A – ECH. Her research focuses on leadership, leadership education and on trend and future research.O NU AT P G EMEO ENPLE 2 T, S TR024 AT–2 EG IC02 C5 OM M U N ATIC ION M ANAGEMENT, W EB AND INFOR ATM ION EC T H NOL O IEG S 41 w N edAL S Pr INVESTIGATING THE PROJECTIFICATION OF o CIE ce N SOCIAL ENTERPRISES AND ITS IMPACT ON SOCIAL ed TIF ing IC C ENTREPRENEURS(HIP): A COMPARATIVE STUDY s Bo O N FE ok R Salik Ram Maharjan, PhD Candidate : P EN R er-R RN evAT ieIO Pe IN Published scientific conference contribution TE 1.08 Objavljeni znanstveni prispevek na konferenci O Alma Mater Europaea University, Slovenia CE I JE T'S A CT M B A O ABSTRACT N U A T P G This paper presents a comparative study examining the impact of projectification on social en-EM EO terprises (SEs) within the distinct institutional contexts of Nepal and Slovenia. Using a qualitative EN PL E 2 T, S methodology to analyze nine SEs (five from Nepal and four from Slovenia), the research iden-TR 02 tifies a clear contrast in outcomes shaped by the institutional frameworks. Strong EU funding, 4 AT –2 participatory governance, and coherent policies in Slovenia enable SEs to balance project flex-EG IC 02 ibility with long-term stability. Conversely, in Nepal, fragmented support, donor dependency, C 5 OM and inconsistent funding necessitate a strategic shift towards short-term projects, which risks M mission drift and jeopardizes sustainability. The analysis reveals a “projectification paradox,” U N IC where projects foster innovation while threatening organizational stability, particularly in frag- AT ile ecosystems. The study’s main contribution is to highlight the vital mediating role of institu- ION tional structures. It concludes with practical recommendations, proposing blended finance for M Nepal and localized funding for Slovenia to enhance the sustainability and social impact of SE in A N A diverse contexts. G EM Keywords : Projectification, Social Enterprises, Social Entrepreneurship, Comparative Study, So - EN cial Impact T, W EB AND INFOR ATM ION EC T H NOL O IEG S 42 1 INTRODUCTION Pe INTE The modern organizational landscape is increasingly characterized by “projectification”, a pervasive er -RRN trend where work is organized around temporary, short-term projects rather than permanent hier- evAT ieIO archical structures (Kuura 2020; Fred and Godenhjelm 2023b). This phenomenon has profoundly im- wN edA pacted the social economy, fundamentally reshaping how social missions are pursued, funded, and L S Pr implemented, raising critical questions about long-term sustainability and public policy (Jacobsen oCIE ceN 2022). While project-based approaches are lauded for fostering innovation, agility, and responsive- edTIF ness (Lundin 2016), a growing body of research highlights their significant downsides, including a ingIC C shift in focus from long-term objectives to short-term deliverables, an increased administrative bur- s BoON den, and the potential for mission drift (Maylor and Turkulainen 2019; Huaricallo and Lean 2024). okFER This paper examines the dualistic impact of projectification on social enterprises (SEs). The Europe - : PEN R OCE I an Union defines SEs as “operators in the social economy whose main objective is to have a social JE impact rather than make a profit for their owners or shareholders” (European Commission 2022). T'S A CT M These organizations strategically blend social missions with market-based economic activities to B AO NU address persistent societal challenges (Yuangiong et al. 2022). However, the operationalization of AT P G this model and its complex interaction with project-based work are not uniform; they vary consid- EMEO EN erably across different institutional and policy environments. PLE 2 T, S To explore this nexus, this study employs a comparative analysis of two markedly different contexts: TR024 Slovenia, a European Union member state with a structured, supportive ecosystem, and Nepal, a AT–2 EG developing nation with a nascent and donor-driven landscape. Slovenia benefits from robust insti - IC02 C5 tutional support, clear legal frameworks, and access to coherent European Union funding streams OM (SENS Network 2020; OECD 2023). In stark contrast, Nepal’s ecosystem is fragmented, lacking clear M U definitions and policies for SEs, which results in high donor dependence and operational instability N IC (Gautam and Rupakhety 2021; Dangol et al. 2022). AT ION This research argues that the benefits and drawbacks of projectification are not inherent but instead M depend critically on the surrounding institutional framework. It posits a “projectification paradox,” A N wherein projects can simultaneously act as catalysts for innovation and as sources of strategic fra- A G gility. Through a qualitative study of nine SEs, we demonstrate how the macro-level institutional EM context from Slovenia’s EU-aligned policy coherence to Nepal’s donor-driven fragmentation shapes EN T, W the micro-level lived experiences of social entrepreneurs, influencing their capacity for innovation and their pathways to sustainability. EB AND IN 2 LITERATURE REVIEWFOR 2.1 The Concept and Evolution of Projectification MATION goal-oriented teams rather than permanent structures (Midler 1995; Fred and Godenhjelm 2023b). TECH Midler (1995) first defined “projectification” as the trend of organizing work through temporary, ating resource dependence and shifting focus from long-term strategic goals to short-term deliv- OG erables (Maylor and Turkulainen 2019; Huaricallo and Lean 2024). This issue is especially serious in While it promotes innovation and agility, it also introduces significant risks to sustainability by cre- NOL aid-dependent settings, such as Nepal, where excessive reporting pulls resources away from prima- IES ry missions (Dial 2025). 2.2 Social Entrepreneurship. A Global Perspective Social entrepreneurship (SE) is a market-oriented approach to solving social issues, catalyzed by global movements such as Ashoka and Grameen Bank (Hotcubator 2017; Gupta et al. 2020). It com-bines business strategies with social objectives, often engaging marginalized groups (Zahra and Wright 2015; Saebi et al. 2018). Two predominant models exist: the European Model (EMES), which combines economic activity with a social mission and participatory governance, and the American Model, which prioritizes market-based social innovation (Hotcubator 2017; LEED 2025). 43 2.3 Comparative Analysis of Projectification ed N Social Fund (Jalocha and Jacobson 2021). This results in a formalized model characterized by: (a) A L S Pr EU-mandated funding requiring complex budgeting and reporting (Government of the Republic of CIE o Slovenia 2014); (b) hybrid operations that supplement core activities with temporary grants, creat- ce N ed TIF ing dependency (OECD 2023); (c) high professionalism in project management and impact frame- ing IC C works like SROI (Hojnik 2020); and (d) strategic integration of EU projects into their operational DNA s Bo O N (European Commission 2022). FE ev RNAT Slovenia’s projectification is highly institutionalized, driven by EU frameworks, such as the European ie IO w er TE 2.3.1 Projectification in Slovenia-R Pe IN ok : P REN 2.3.2 Projectification in Nepal O CE I R CT MJE Nepal exhibits a transitional projectification shaped by post-conflict and post-earthquake interna- T'S A B tional aid (Khanal and Weber 2017). Its model is defined by: (a) donor-driven agendas from organ- A O N izations like the World Bank and USAID, which compel the use of tools like the logical framework U A T P G (Smith 2021; Karkee and Comfort 2016); (b) a structured, project-based approach to scale impact EM EO across geographic challenges (ILO and FNCCI 2025); and (c) the fusion of global project models with EN PL E 2 community-owned approaches to create unique hybrids (K.C. and Ghimire 2021). Slovenia’s EU-T, S TR 02 backed stability contrasts with Nepal’s vulnerabilities and may provide insights for future govern-4 AT ance reforms (Lundin 2016; Jalocha and Bojtanowska 2016). –2 EG IC 02 C 5 2.4 Social Entrepreneurship. A Comparative Overview of Slovenia and Nepal OM M 2.4.1 The Slovenian Ecosystem U N IC Slovenia has a clear legal framework for SEs, overseen by the Ministry of Economy, Tourism, and AT ION Sport, which grants access to benefits and public procurement (OECD 2023). Support organizations like AN es. Financial mechanisms include start-up subsidies from the Slovenian Enterprise Fund and EU funding A M SEN and the Social Enterprise Network for Training (SENT) offer advocacy and capacity-building servic- EMG streams (Slovenian Enterprise Fund 2024). A national impact measurement model helps attract invest- T, W 2.4.2 The Nepalese Ecosystem EB EN ment (LEED 2025). Challenges remain in securing growth capital and simplifying administration. N Nepalese SEs emerged to address poverty and service gaps, often initiated by donor-funded pro- A IND jects (Rai et al. 2025). Government support includes the Social-Economic Development Plan (SEDP) FOR and the Social Entrepreneurship Act (2014) (Adhikari and Sharma 2022; Government of Nepal, Min- ATM istry of Finance 2021). Funding is provided through programs such as the Micro-Enterprise Develop- ION ment Program (MEDP) and Microfinance institutions. A vibrant support network of incubators (e.g., ECH T Daayitwa) and NGOs exists. The ecosystem’s growth hinges on improving infrastructure, policy im- plementation, and access to larger-scale investment (Omidyar Network Fund 2022; Nirdhan Utthan NOL Bank Limited 2022) O IEG 2.5 Opportunities and Challenges at the Intersection S The impact of projectification is dualistic and shaped by national context. For Slovenian SEs, op-portunities include access to structured EU funding, enhanced organizational capacity, strategic fi-nancial hybridity, and a contextual impact measurement framework (Hojnik 2020; Wu et al. 2020). Challenges comprise competitive grants, short-term project cycles, and constraints on innovation resulting from rigid funding structures, which create a significant administrative burden, dependen-cy, and mission drift (Government of the Republic of Slovenia 2014; Maylor and Turkulainen 2019). For Nepalese SEs, opportunities involve access to essential resources, introduction of management discipline, hybrid innovation, and ecosystem catalysis through donor-built support structures (Kha-nal and Weber 2017; Karkee and Comfort 2016; Joshi, 2021; Rai et al. 2025). Challenges include instability and extractive reporting, donor-driven agenda setting, misaligned Western impact met-rics that hinder investment, and fragmented governance that perpetuates aid dependency (Smith 2021; Upadhya 2024; Lovermore 2021; Godenhjelm et al. 2015). 44 2.6 Synthesis sion sustainability. For Nepal, Slovenia’s experience suggests that building cohesive national pol- ed NAL S Pr icies, strong institutions, and context-appropriate measurement tools is crucial for harnessing the oCIE benefits of projectification without succumbing to its vulnerabilities. ceN edTIF ingIC C 3 PURPOSE AND GOALS s BoONFE ok This study examines how social enterprises influence their strategy, operations, and sustainability, venia’s structured, EU-integrated approach offers stability, while Nepal’s donor-dependent model RNAT ev demands high adaptability. The core tension is balancing project-based agility with long-term mis- ieIO w The literature confirms that the manifestation of projectification is shaped by national context. Slo- TE er -R Pe IN enon. The primary objectives are to: (1) analyze the projectification of social enterprises in Nepal CT M B AO and its effects on their strategic and operational efficacy; (2) assess their societal implications for NU AT P poverty alleviation, community development, and environmental sustainability; (3) conduct a com- G EMEO parative analysis with European models to identify commonalities and transferable practices; (4) ENPL forming the core of a comparative analysis between Nepal and Slovenia. Using a comparative anal- RO CE I JE ysis of Nepal and Slovenia, it explores how different socio-economic contexts shape this phenom -T'S A : P REN identify key challenges (e.g., funding dependencies, short-termism) and propose actionable solu- E 2 T, S tions to enhance resilience; (5) contribute to academic discourse intersecting projectification stud - TR024 ies, social entrepreneurship, and comparative methodology; (6) inform policymakers, donors, and AT–2 EG support organizations with evidence-based recommendations to strengthen the social enterprise IC02 C5 ecosystem; (7) guide future practitioners with practical insights and case studies; and (8) provide OM evidence-based recommendations for cross-cultural collaboration. This study examines the impact M of project-based methods on social enterprises, comparing strategic and operational challenges in U N Nepal and Slovenia. The research aims to inform policy, support practitioners, and contribute to aca- ATIC demic and practical social entrepreneurship scholarship. ION M 4 METHODOLOGY ANAGEM This study employed a qualitative comparative design within an interpretive framework to investi -EN gate the impact of projectification on social enterprises (SEs) in Nepal and Slovenia, analyzing institu -T, W tional, financial, and operational dimensions (Lang and Fink 2019). This approach was selected to cap- EB A ture nuanced dynamics, trace donor pressures, and facilitate a cross-context analysis between Nepal’s ND aid-dependent ecosystem and Slovenia’s EU-integrated environment (Defourny and Nyssens 2021). INFOR A purposive sample of nine SEs, four in Slovenia and five in Nepal, was selected to ensure diversi - ty across sectors, funding models, and exposure to projectification, aligning with the International MAT Comparative Social Enterprise Models (ICSEM) Project framework (Defourny and Nyssens 2017). The ION tor), social inclusion (MOBA Housing and SCE Network), and assistive technology for accessibility ECH Slovenian cases included SEs in social housing (Hisa Drustvo), cooperative development (Zadruga- T (Feelif d.o.o.). The Nepalese cases spanned agricultural technology (Smart Krishi), consulting and NOL capacity building (Biruwa Advisors Private Limited), community development (The Village Café), ed- OG ucation and training (Higher Ground Nepal), and renewable energy (Greenway Nepal). IES Primary data were collected through 60-minute semi-structured Zoom interviews with founders and senior managers, using a protocol to avoid leading questions on mission drift (Naeem and Ranfagni 2023). Interview data were triangulated with document analysis of annual reports, pro-ject proposals, and policy documents (Maksum et al. 2020). Recorded data were inductively cod-ed using NVivo 15, with manual cross-verification in MS Word. Emergent codes were synthesized into thematic categories (e.g., “donor dependency”) and analyzed through the lens of social capital dimensions (bonding, bridging, and linking) using NVivo’s matrix coding function (Lang and Fink 2019). A final cross-case synthesis integrated narrative summaries with institutional-level mapping (Naeem et al. 2023). Rigor was ensured through triangulation, peer debriefing, and reflexive memoing (Lang and Fink 2019). The study adhered to strict ethical protocols, including compliance with the General Data Protection Regulation (GDPR), the use of pseudonyms for anonymity, and approval from the institu- 45 er-R R The findings are also temporally sensitive to Nepal’s federal restructuring and Slovenia’s EU funding N ev AT cycles. Researcher positionality and reflexivity were documented to contextualize interpretations ie IO Pe IN the small sample size, which is addressed through a thick description for analytical transferability. TE tional review board (European Commission 2022). A limitation is the limited generalizability due to w N (Majumdar and Ganesh 2020; Khadka 2025). ed A L S Pr CIE o ce N 5 RESULTS ed TIF ing IC C This section presents the empirical findings on how the institutional ecosystem shapes the manifes- ok FE from Nepal and four from Slovenia). The operational landscape for Nepalese social entrepreneurs is R : P s Bo O tation and impact of projectification in social entrepreneurship, comparing a total of nine SEs (five N CT T'S A short-term projects with predefined deliverables. Organizations reported spending 30-50% of their M B A operational capacity on proposal writing and donor reporting, a significant diversion of resources O N U A T P from their core mission. This creates a cycle of short-termism that hinders long-term planning for G O CE I pendency and strategic constraints. Funding for Nepalese social enterprises is predominantly tied to JE R EN profoundly shaped by international donors and a project-based funding model, resulting in high de- EN PL nancial viability, social enterprises like Smart Krishi and Greenway Nepal often run multiple discon-E 2 T, S EM social entrepreneurs. The projectification model causes operational fragmentation. To ensure fi- EO TR 02 nected projects simultaneously, leading to inefficiencies. Strategically, it forces a reactive posture, EG preferences. The broader ecosystem lacks robust support structures. Social entrepreneurs face lim- IC 02 C AT 4 where a coherent, internally driven vision is frequently replaced by one shaped by donor trends and –2 OM 5 ited access to non-project-based capital (e.g., impact investment), an underdeveloped regulatory framework, and a shortage of managerial talent, which exacerbates the challenges of operating U within a projectified environment. M N ATIC In contrast, Slovenian social enterprises leverage project funding as a strategic tool within a mature, ION supportive, and EU-integrated institutional environment. A clear legal framework, such as the Social AN opment. EU structural funds, channelled through national programs, catalyze strategic alignment and A G M Entrepreneurship Act, defines the status of social enterprises and provides incentives for their devel- EN The institutional system mitigates the inherent volatility of projectification through co-financing re- quirements, technical assistance, and a growing emphasis on standardized social impact measure EM capacity building, enabling enterprises like Feelif d.o.o. and Hisa Drustvo to use projects for growth. EB ment (e.g., SROI). This scaffolding enables entities such as Zadrugator, MOBA Housing, and SCE Net- A work to pursue innovation with greater stability and confidence. Despite the robust system, Slovenian N T, W - IND social entrepreneurs still face challenges, including bureaucratic complexities in accessing EU funds, FOR competition for public contracts, and a need to professionalize impact measurement practices. AT neurship, mediated by the strength of the institutional ecosystem. Projectification demonstrates a M The cross-case comparison reveals a central paradox in how projectification affects social entrepre- ION EC same project-based model is a primary source of strategic and operational fragility for social enter- H NOL T dual nature. In Slovenia, projects act as catalysts for innovation and scaling impact. In Nepal, the prises. The fundamental difference lies in the strength of the supporting ecosystem. Slovenia’s struc- O tured, multi-stakeholder system provides a “scaffolding” that absorbs uncertainty and manages the G IE risks associated with projectification. Nepal’s donor-driven ecosystem amplifies these uncertainties, S pushing risks onto individual enterprises and entrepreneurs. Social enterprises in both contexts face pressures of mission drift. Slovenian entities, such as SCE Network, are better equipped to resist them due to their clear legal identity and established support mechanisms. Nepalese enterprises, like Biruwa Advisors and The Village Café, are more susceptible to shifting their activities toward fundable themes for mere organizational survival. The findings yield distinct policy lessons for each context, alongside a universal warning about over-re-liance on projectification. For Nepal, policy must focus on developing a formal legal framework, cre-ating alternative financing vehicles (e.g., impact investment funds), and building managerial capac-ity. An example of innovation includes piloting localized impact metrics to align project funding with community needs. For Slovenia, the country offers transferable practices, including a clear legal status for social enterprises, the strategic use of public/EU funds for capacity building, and the mandating of impact measurement. A key innovation would be simplifying EU fund application processes for small- 46 that the progress of social entrepreneurship depends on context-specific innovation grounded in its w N edA institutional determinants. The future hinges not on the management of isolated projects, but on L S PrCIE transforming fragile ecosystems into resilient, supportive, and adaptive ones. o ceN edTIF ingIC C 6 DISCUSSION s BoON This study reveals the central paradox of projectification: it is simultaneously a vital source of re - okFER sources and innovation for social enterprises (SEs) and a significant threat to their long-term sustain - : PEN R funding allowances and mentorship programs, are needed to help social entrepreneurs navigate pro- er-R RN evAT jectification without compromising their long-term vision. In conclusion, the analysis demonstrates ieIO carries inherent risks of bureaucratic capture and mission dilution. Universal safeguards, such as core Pe INTE er, rural enterprises to enhance inclusivity. Both contexts demonstrate that over-reliance on projects ability and integrity of mission. This research demonstrates that a strong institutional environment O CE I bility). However, this study finds that balancing these is not merely a matter of chance or managerial EN PLE 2 skill. The institutional context is the decisive mediating variable, determining an SE’s ability to cap- T, S TR02 ture benefits while mitigating downsides.4 AT–2 EG In Nepal’s weak institutional ecosystem, the risks of projectification dominate, forcing SEs into a de - IC02 pendent cycle as “grant-preneurs.” This is driven by three key factors: (a) donor dominance, where C5 OM skewed power dynamics compel SEs to align with shifting donor priorities over community needs, M U leading to mission drift; (b) policy fragmentation, as a lack of cohesive government policy or legal N IC frameworks forces SEs to navigate complex project requirements without a safety net, amplifying AT administrative burdens; and (c) inadequate metrics, where pressure to report quantifiable, short- robust framework and Nepal’s fragmented ecosystem shows that institutions determine whether B AO NU projects empower or entrap SEs. Projectification presents SEs with a universal set of opportunities AT P G (financial capital, innovation, scaling impact) and risks (mission drift, administrative burden, insta - EMEO mediates this paradox, which is not inherent to projectification. The comparison between Slovenia’s T'S A JE CT M ION formation, exacerbating the divergence from the organization’s mission. ANAG term outcomes to international donors comes at the expense of measuring long-term social trans- M Slovenia’s structured, EU-integrated environment enables SEs to harness projectification effective- EM ly. Key institutional strengths include: (a) integrated policy frameworks, where alignment with EU EN policies provides a clear legal identity (e.g., social cooperatives) and access to structured funding, T, W reducing transactional costs and increasing stability; (b) participatory governance, as institution- EB A al designs that mandate stakeholder participation (e.g., in cooperatives) act as a bulwark against ND external donor pressures, anchoring SEs to their social mission; and (c) advanced impact measure- IN ment, where focusing on “impact management” over “output reporting,” driven by EU and state FOR Theoretically, these findings extend social enterprise and institutional theory (Defourny and Nyssens ATION standards, helps align project goals with long-term social value creation. M ing that model functioning is contingent on institutional embeddedness. Practically, solutions must ECH 2016a) by showing how macro-level institutions directly influence micro-level practices, confirm- T be systemic and context-specific. For Nepal, the focus should be on building institutional capacity NOL by developing a national SE policy, creating catalytic public funding, and fostering local platforms OG for collective donor engagement. For Slovenia, the focus should be on refining existing systems by IES streamlining administrative procedures for EU funds and promoting knowledge sharing on impact measurement and evaluation. The qualitative, small-N design limits generalizability, though it provides a template for analytical transferability. Given Nepal’s federal restructuring and evolving EU funding cycles, the findings are also temporally sensitive. Future research should employ longitudinal studies to track the evolu-tion of SE and use quantitative, large-n surveys to test correlations between institutional variables (e.g., legal frameworks, public funding) and the sustainability of SE across countries. Institutional strength profoundly shapes the impact of projectification. Slovenia’s robust framework allows its SEs to leverage projects for growth, while Nepal’s fragile ecosystem traps its SEs in dependency. This contrast expands our theoretical understanding of how institutions mediate project-based work. The central takeaway is that supporting SEs requires moving beyond project-level interventions to build the supportive institutional ecosystems that allow them to thrive. 47 Pe 7 CONCLUSION IN TE er-R R This study concludes that the impact of projectification on social enterprises (SEs) is not inherent but N ev AT is fundamentally mediated by the strength of the surrounding institutional ecosystem. The compar-ie IO w ative analysis reveals this stark contrast: projectification functions as a trap in fragile institutional N ed A L S settings (Nepal) and as a tool in robust ones (Slovenia). SEs achieve sustainable, mission-aligned Pr impact within strong, supportive ecosystems, not through isolated efforts. Slovenia’s integrated o CIE ce N policy framework, strategic public and EU funding, participatory governance, and advanced impact ed TIF protocols create an environment where SEs can harness project-based work for innovation while ing IC C maintaining stability. Strong institutions absorb the risks of projectification, allowing SEs to capture s Bo O N its benefits. Conversely, Nepal’s ecosystem, characterized by fragmented funding, policy voids, and ok FE R : P weak governance, amplifies the vulnerabilities of projectification, trapping SEs in a cycle of donor EN R O CE I dependency and strategic precarity that undermines their long-term social goals. JE T'S A CT These findings offer critical guidance. For developed economies, Slovenia’s model provides a blue- M B A print, demonstrating that cohesive support systems—including legal recognition, catalytic public O N U A T P funding, and capacity building are a prerequisite for a thriving social economy, not a luxury. For the G EM Global South, Nepal’s challenges underscore an urgent need for targeted institutional strengthen-EO EN PL ing. International aid must shift from funding discrete projects to investing in foundational struc-E 2 T, S tures: national policies, local community foundations, impact investors, and advocacy platforms. TR 02 4 The goal is to transform fragility into resilience. Ultimately, the future of the social economy de-AT –2 EG pends less on managing individual enterprises and more on architecting the ecosystems in which IC 02 C 5 they operate. 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Jou- rnal of Management Studies 53(4): 610–629. 51 er-R RN evAT ieIO Pe IN Published scientific conference contribution TE 1.08 Objavljeni znanstveni prispevek na konferenci w N edAL S Pr TECHNOLOGY SOLUTIONS OF SHARING ECONOMY o CIE ce N AS A TOOL FOR SUSTAINABLE DEVELOPMENT ed TIF ing IC C R EN Milan Fiľa, PhD, Associate Professor O CE I JE College of Applied Psychology, Czechia T'S A CT M B A ok FE University of Zilina, Slovakia R : P s Bo ON Jaroslav Viglaský, PhD Candidate N OU AT P ABSTRACT G EM EO The sharing economy, enabled by advances in digital technologies, represents a paradigmatic EN PL E 2 T, S change in how we consume and use resources. Our contribution focuses on the potential of tech-TR 02 nological solutions within the sharing economy to contribute to sustainable development, which 4 AT –2 consists of more efficient use of resources through the sharing of goods and services, reducing EG IC 02 emissions through shared mobility, and increasing the sustainability of consumption through the C 5 OM use of various platforms, as well as in the different social and economic benefits provided by M the sharing economy (e.g. creating new job opportunities, supporting local communities and in- U N creasing social inclusion). To fully exploit this potential, it is necessary to ensure a comprehensive IC AT approach to their successful implementation, which considers not only economic but also social ION and environmental aspects. M Keywords: A The sharing economy, Sustainable development, Technology, Efficient use of resourc - N A es, Reducing emissions, Sustainable consumption G EM EN T, W EB AND INFOR ATM ION EC T H NOL O IEG S 52 1 INTRODUCTION Pe INTE The sharing economy has become a very popular phenomenon in recent years and its importance is er -RRN immensely increasing. In the next lines, we will look closer at this phenomenon. evAT ieIO wN 1.1 Sharing economy edAL S PrCIE The sharing economy is seen as a modern phenomenon in politics, society, and the economy, and o ceN one that situates the principle of exchange, sharing, and lending at the center of all interactions and edTIF ing transactions (Mossman 2019, 30). Sharing economy became an umbrella term for the different des -IC C s BoO ignations used to characterize the new economy such as collaborative, circular, on-demand, or ze-NFE ro-marginal-cost (Bas 2022, 1). From a broad perspective, the sharing economy includes traditional okR : P government-to-peer (G2P) (e.g. public libraries, transportation, parks, and land) and business-to-peer EN R OCE I (B2P) initiatives: however, much of the attention has focused on peer-to-peer (P2P) or collaborative JET'S A consumption-based initiatives (Albinsson and Perera 2018). Oskam (2019) suggests the definition of CT MB sharing by Rachel Botsman, who defines it as the more efficient use of underutilized assets. Based on AO NU Botsman`s and Rogers’s opinions Sundararajan (2016) mentions that in the 21st century, we can speak AT P G about collaborative consumption, where its access is driven by community and sharing and the collab- EMEO EN oration may be local and face-to-face, or it can use the Internet to connect, combine, form groups, and PLE 2 T, S find something or someone to create “many-to-many” peer-to-peer interactions. Simply put, people TR02 are sharing again with their community – be it an office, a neighborhood, an apartment building, a 4 AT–2 school, or a Facebook network. As Arvidsson (2019, 10) points out, the sharing economy constitutes a EG IC02 new combination of market exchange, commons-based sharing, and capitalist profit-seeking. Strøm - C5 OM men-Bakhtiar and Vinogradov (2020) mention the definition of the Norwegian Ministry of Local Gov - M ernment and Regional Development, which defines the sharing economy as coupling between indi - U N IC viduals and/ or legal entities through digital platforms that facilitate the provision of services and/ or AT sharing of assets/ property, resources, expertise or capital without transferring ownership rights. In ION other words, it is a digital platform-based business model, where these platforms have dramatically M reduced transaction costs, which in turn have opened the door to a world of innovations. ANAG 1.2 Sustainable DevelopmentEMEN As Rogers, Jalal, and Boyd (2012, 22) mention, sustainable development is defined as development T, W that meets the needs of the present without compromising the ability of future generations to meet EB A their own needs. Another definition mentions that it is a development that is sustained in the sense ND that it endures over a period of time, but it is more commonly understood as development causing IN little or no damage to the environment and therefore able to continue for a long time (French and FOR of prosperity between the various parts of today`s world, and also the distribution of that prosperity ATION Kotzé 2018, 21). As Roorda (2017, 9) points out, sustainable development involves the distribution M able development to be achieved, it is crucial to harmonize three interconnected core elements: ECH economic growth, social inclusion, and environmental protection. The optimistic news is that every between humans today and humans of tomorrow. As Zielinsky et al. (2017, 2) mention, for sustain- T NOL year, more affordable and reliable solutions appear and thus people are able to turn into cleaner, OG more resilient economies. As Kimura (2024) reports, the guiding principle for sustainable develop-IES ment is encapsulated by the five P’s: People, Planet, Prosperity, Peace, and Partnerships, where each of these elements represents a critical aspect of human and planetary well-being:- People: Ensuring no individual, group, nation, or region is left behind.- Planet: Living within Earth’s environmental boundaries.- Prosperity: Extending the benefits of modern education and technology globally.- Peace: Coexisting under the principles of the UN Charter and international law, advocating for non-intervention and peaceful conflict resolution. - Partnerships: Collaboration among governments, civil society, and businesses to achieve shared global goals. These principles can be also found in the 2030 Agenda for Sustainable Development, adopted by all United Nations Member States in 2015, which provides a shared blueprint for peace and prosperity for people and the planet, now and into the future (United Nations, 2025). 53 1.3 Sharing Economy as a Tool for Sustainable Development er TE As Aref (2024) mentions, the sharing economy, supported by digital platforms, efficiently matches -R Pe IN ie IO tries is offering a new path to sustainable resource consumption. Zygmunt (2020) suggests that the w N ed A primary goal of the sharing economy is to minimize the consumption of resources and services used L S Pr to perform company operations while achieving maximum outcomes. The undertaking of sharing ev RNAT the demand and supply of underused resources. Expanding globally and impacting different indus- ing TIF cial well-being of the stakeholders), environmental benefits (reduced negative environmental im- IC C pacts of business practices), and economic benefits (reduced total costs, enhanced marketing, and s Bo ce N economy practices contributes to the three types of SDGs, with many social benefits (increased so-ed o CIE CT M ciency. Based on their opinion the sharing economy offers a route to long-term development based B A O N U on resource efficiency and stronger social links. The sharing economy, which makes it possible to A T P G use the resources already put into circulation and do it efficiently both from an economic and an EM EO environmental point of view, is often considered a component of sustainable consumption (Lyas- EN PL E 2 kovskaya and Khudyakova 2021). As Zhang et al. (2023) mention the sharing economy is another T, S TR 02 focus of world attention, as it relates to the economy and sustainability. It is commonly framed as: 1) 4 AT –2 an economic opportunity; 2) a better and more sustainable form of consumption; and 3) a pathway EG : P R sustainable economic activity. It combines information technology and management methods to EN R develop a new culture in which resources are used more efficiently. As a result, it provides an inno - O CE I JE vative framework that may pave the way for long-term economic development and energy effi - T'S A ok N increased profits). Also Sadiq et al. (2023) see the sharing economy as a phenomenon that supports FE O IC to an equality-based and sustainable economy. As Karobliene and Pilinkiene (2021) point out, some 02 C 5 OM authors have argued for the importance of the sharing economy as a phenomenon that generates M sustainable value creation, which highlights the relevance of the sharing economy from the per- U N spective of reducing consumption and resource and energy usage, thus potentially supporting the IC achievement and improvement of the Sustainable Development Goals. AT ION AN 2 PURPOSE AND GOALS M G The main purpose of this paper was to answer the elementary research question – If the technolog- EM A EN ical solutions of the sharing economy can be used as a tool of sustainable development? EB - What is the sharing economy and its position in sustainable development? A N D T, W To achieve this purpose we looked first at the sub-goals: IN ing economy?- Which are the best countries due to SDG achievements and which cities are the best for the shar-FOR M - Is there any existence of the sharing economy activities, that can be related to SDG? ATION T 3 METHODS ECHNOL To create this paper we used comparative analysis to analyse various documents, literature, and O research papers to bring the best overview of the sharing economy, sustainable development, and G the concept of the sharing economy as a sustainable development tool. We also used the Report of IE S Sharing Economy Index 2024 and the Sustainable Development Report 2024 to look at the rank of the best countries due to SDG achievements and sharing economy friendliness. We used it to com-pare the benefits of the sharing economy to the sustainable development of the cities. As the last, we analysed the various forms of the sharing economy possibilities, that can be used as a solution for the concrete Sustainable development goal. 4 RESULTS In Table 1 we can see the top 10 countries based on the ranking published in the Sustainable De-velopment Report 2024. Countries are ranked by their overall score. The overall score measures the total progress towards achieving all 17 SDGs. The score can be interpreted as a percentage of SDG achievement. A score of 100 indicates that all SDGs have been achieved. 54 Table 1: Top 10 countries with the best score of SDG achievement Rank Country Score TE er-R Pe IN 1 RNAT Finland 86.35 ev ieIO w 2 Sweden 85.70 N edAL S Pr 3 Denmark 85.00 oCIE 4 Germany 83.45 ceN edTIF 5 France 82.76 ingIC C 7 ok FE Norway 82.23R : P 6 s Bo O Austria 82.55N R EN 8 Croatia 82.19 O CE I 9 United Kingdom 82.16 CT T'S A JE 10 Poland 81.69 O NU AT P A B M In Table 2 we can see the top 10 most sharing economy-friendly cities worldwide based on the EN PLE 2 Sharing Economy Index 2024. The research was made by the Consumer Choice Center, that ranked T, S (Source: Sustainable Development Report 2024, 2024) GEM EO 60 cities worldwide to help consumers pick the destination that best fits their sharing economy TR 024 AT–2 preferences. They examined several variables ranging from ride-hailing, professional car-sharing, EG IC02 car-pooling, and flat-sharing to gym-sharing, ultra-fast delivery apps, and e-scooters (Panzaru and C5 OM Aun, 2024). M Table 2: Top 10 most sharing economy-friendly cities worldwide U N ATIC Rank Country City Composite index score ION 2 AN Argentina 1 M Lithuania Vilnius 16.01 Buenos Aires 15.18 A 3 Spain Madrid 14.97 EN EMG 4 Serbia Belgrade 14.96 T, W 5 United Kingdom London 14.79 EB AN 5 USA Washington DC 14.79D IN 7 Netherlands The Hague 14.75FOR 9 AT Finland 8 USA Nashville 14.74 M Helsinki 14.55 ION 10 Czech Republic Prague 14.54 TEC 10 H Sweden Stockholm 14.54NOL 10 Switzerland Zurich 14.54 O IEG 10 USA Dallas 14.54 S (Source: Panzaru and Aun 2024) In Table 3 we used the Research of Pérez-Pérez et al. (2021), to bring an overview of possible actions of the sharing economy which can bring benefits not just for communities where they take place. But they can also support the fulfillment of the SDG in the countries. 55 Table 3: SDG and examples of the Sharing Economy actions/ solutions related to them -R RN sharing resources of local people with others users to AT ev No powerty generate extra income and by reducing the barriers to ie IO w er TE SDG goals Examples of the sharing economy solutions Pe IN ed N entrepreneurship A L S Pr shared urban gardens or food sharing among members o CIE Zero hunger ce N of community ed TIF ing IC C s Bo ON Good health and well-being sharing of medical equipment ok FE R : P EN R O CE I JE for example platforms such as Skillshare or Sharing T'S A CT Quality education M academy and communities around them B A O N U A T P G EM EO Due to the no-discrimination policies of the platforms are Gender equality EN PL the services and products available to everyone E 2 T, S TR 02 4 for example platforms such as Gridmates or Vandebron AT –2 Affordable and clean energy help to reduce energy poverty, as well as facilitate access EG IC 02 to renewable energies C 5 OM M Decent work and economic growth digital platform workers U N IC AT ION M Industry, innovation and infrastructure SE platforms challenge traditional business models ANAGEM reducing inequalities by granting access without EN Reduced inequalities ownership T, W EB AN Sustainable cities and communities shared transportation D IN FOR sharing of used goods or for example Vinted ( a peer-to-M Responsible consumption and production peer marketplace and community for second-hand AT ION fashion) EC T H Climate action reducing polution by shared transportation NOL O IEG S SE platforms can forge trust and social understanding Peace, justice and strong institutions among users (Source: Authors’ own elaboration based on Pérez-Pérez 2021) 5 DISCUSSION As we can see in Table 1, all the top 10 countries with the best ranking in the Sustainable Devel-opment Report are situated in Europe. The first place with the highest score of 86.35 belongs to Finland, closely followed by Sweden and Denmark. In the fourth place, we can see Germany with a score of 83.45 points followed by France with a score of 82,76 points. The 82 points limit is also reached by Austria in the 6th place, Norway (7th place), Croatia (8th place), and the United Kingdom in the 9th place. In the 10th place we can still see Poland that fulfils the SDG by 81.69%. 56 SDG achievements, but also to the 10 top sharing economy friendly economies. But when we look er-R RN evAT further on the Sharing Economy Index, we can see that also the remaining countries from the top 10 ieIO sinki and Sweden with Stockholm belong not just to the top 10 countries with the best score of Pe INTE When we look at Table 2 we can see that just the United Kingdom with London, Finland with Hel- countries can be found in the Sharing Economy Index ranking. Most countries are represented in the w N edA ranking by only a single city—for example Denmark (Copenhagen, 51st place), France (Paris, 35th), L S PrCIE Austria (Vienna, 27th), Norway (Oslo, 16th), Croatia (Zagreb, 40th), and Poland (Warsaw, 49th). In o ceN contrast, Germany is represented by four cities, making it one of the most strongly featured coun- edTIF tries: Cologne (23rd), Berlin (27th), and Munich and Hamburg (both ranked 31st). ingIC C tation (Zipcar, BlaBla Car, Bolt, …) can help with the air pollution reduction – SDG 13. One of the SDG A O NU AT P G EM areas is Good Health and Well-being (SDG 3). In this area, it is necessary to point out the possibilities EO ENPL of shared economy tools to support and create a healthy and health-promoting work environment E 2 T, S and corporate culture (e.g. Virgin Pulse, Strove). As stated by Tóthová and Nemec (2024), these will TR024 ensure an atmosphere of support for employees, which will also positively affect their subsequent AT–2 EG performance and well-being in the workplace. Various volunteer platforms, where volunteers can IC02 C5 also find opportunities for short-term mission trips to the developing countries that can help with OM the fulfilment of SDG 2. M U N IC 6 CONCLUSION United Nations. When we look further in Table 3, we can see, that there exist also other sharing EN R OCE I economy activities, that can help to fulfil some other of the Sustainable Development Goals, such as JET'S A CT sharing of the second-hand fashion (for example platform Vinted) or sharing of various goods can MB help with the reduce of consumption and with better use of the resources – SDG 12. Shared transpor- can be associated with SDG 3, 10, 11, and partially SDG 8. There are 17 SDGs that are defined by the ok FER : P As we know, the Sharing Economy Index examines just some areas of the sharing economy, that s Bo ON ATION countries to better fulfil the Sustainable Development Goals defined by United Nations. In the last ANA years we can see that the sharing economy platforms offer not just opportunities for sharing of As we can see, the sharing economy brings various opportunities that can help communities and M EMG underused resources or services, but there are various platforms that offer opportunities for ed- EN ucation, volunteering, finding friends/ buddies, shared transportation, sharing of spaces not just T, W office areas or accommodation places (Airbnb) but also for example sharing of meals or urban or EB A community gardens. ND As we have also found, these platforms are a technical tool that helps to bring together different IN stakeholder groups as well as communities of like-minded people who are interested in exploiting FOR community in which they live. At the same time, it is an ideal technical solution that helps individ- ATION under-used resources, reducing over-consumption, and also want to give something back to the M Development Goals defined by UN Members. ECHNOL uals and communities to more easily meet their goals, which often overlap with the Sustainable T O IEG S 57 Pe REFERENCES IN TE er 1. Albinsson, Pia A., and B. Yasanthi Perera. 2018. The Rise of the Sharing Economy: Exploring the -R R N ev AT Challenges and Opportunities of Collaborative Consumption. Bloomsbury Publishing USA. ie IO w 2. Aref, Mayada. 2024. Sharing Economy from the Sustainable Development Goals Perspective: N ed A L S A Path to Global Prosperity. Journal of Internet and Digital Economics 4(2): 116-138. https://doi. Pr org/10.1108/JIDE-02-2024-0007. o CIE ce N ed 3. Arvidsson, Adam. 2019. Situating the sharing economy: between markets, commons and ca-TIF ing IC C pital. In: Handbook of the Sharing Economy, ed. Russell W. Belk, Giana M. Eckhardt, and Fleura ok FE 4. Bas, Enric. 2022. Sharing and Collaborative Economy: Future Scenarios, Technology, Creativity and R : P s Bo O Bardhi, 10-26. Cheltenham: Edward Elgar Publishing. N CT T'S A mentation. Edward Elgar Publishing. M B A O 6. Karobliene, Vilma, and Vaida Pilinkiene. 2021. The Sharing Economy in the Framework of Susta-N U A T P G O CE I 5. French, Duncan, and Louis J. Kotzé. 2018. Sustainable Development Goals: Law, Theory and Imple-JE R EN Social Innovation. Springer Nature. EM EO https://doi.org/10.3390/su13158312. EN inable Development Goals: Case of European Union Countries. Sustainability 13(15): 8312. T, S PLE 2 7. Kimura, Yuki. 2024. UN Sustainable Development Report 2024. Available at: https://www.global- TR 02 society.earth/post/un-sustainable-development-report-2024. (June 19, 2024). 4 AT –2 8. Lyaskovskaya, Elena, and Tatyana Khudyakova. 2021. Sharing Economy: For or against Sustain-EG IC 02 able Development. Sustainability 13(19):11056. https://doi.org/10.3390/su131911056. C 5 OM 9. Mossman, Phillip C. 2019. Resource Use? The historical honeycomb of the sharing economy. In: M Perspectives on the Sharing Economy, ed. Dominika Wruk, Indre Maurer, Achim Oberg, 30-38. U N Cambridge: Cambridge Scholars Publishing. IC AT 10. Oskam, Jeroen A. 2019. The Future of Airbnb and the ‘Sharing Economy’: The Collaborative Consu- ION mption of Our Cities. Channel View Publications. M 11. Panzaru, E., and Aun, A. 2024. Sharing Economy Index 2024. Available at: https://consumerchoi- A N A cecenter.org/sharing-economy-index-2024/. G EM 12. Pérez-Pérez, Cristina, Diana Benito-Osorio, Susana María García-Moreno, and Andrés Martínez - EN -Fernández. 2021. Is Sharing a Better Alternative for the Planet? The Contribution of Sharing Eco- T, W nomy to Sustainable Development Goals. Sustainability 13(4): 1843. https://doi.org/10.3390/ EB A su13041843. N D 13. Rogers, Peter P., Kazi F. Jalal, and John A. Boyd. 2012. An Introduction to Sustainable Development. IN Routledge. FOR 14. Roorda, Niko. 2017. Fundamentals of Sustainable Development. New York: Taylor & Francis. M AT 15. Sadiq, Muhammad, Massoud Moslehpour, Ranfeng Qiu, Vu Minh Hieu, Khoa Dang Duong and ION Thanh Quang Ngo. 2023. Sharing economy benefits and sustainable development goals: Em - T EC pirical evidence from the transportation industry of Vietnam. Journal of Innovation & Knowledge H NOL 8(1):100290. O 16. Strømmen-Bakhtiar, Abbas, and Evgueni Vinogradov. 2020. The Impact of the Sharing Economy on G IE Business and Society: Digital Transformation and the Rise of Platform Businesses. Routledge. S 17. Sundararajan, Arun. 2016. The Sharing Economy: The End of Employment and the Rise of Crowd-Ba- sed Capitalism. MIT Press. 18. Sustainable Development Goals. n.d. UNDP. Available at: https://www.undp.org/sustainable-de- velopment-goals. 19. Sustainable Development Report 2024. n.d. Available at: https://dashboards.sdgindex.org/. 20. United Nations. n.d. The 17 Goals. United Nations Department of Economic and Social Affairs. Av- ailable at: https://sdgs.un.org/goals. 21. Tóthová, Veronika, and Filip Nemec. 2024. The Influence of Modern Performance-oriented Cor- porate Culture on the Health of Managers. Applied Psychology 9(17): 1482-1497. 22. Zhang, YunQian, Li Li, Muhammad Sadiq, and Feng Sheng Chien. 2023. Impact of a Sharing Eco- nomy on Sustainable Development and Energy Efficiency: Evidence from the Top Ten Asian Eco-nomies. Journal of Innovation & Knowledge 8(1): 100290. 58 24. Zygmunt, Justyna. 2020. The effect of changes in the economic structure on entrepreneurial acti Springer. er-R RN evAT- ieIO 23. Zielinski, Tymon, Iwona Sagan, and Waldemar Surosz. 2017. Interdisciplinary Approaches for Sustainable Development Goals: Economic Growth, Social Inclusion and Environmental Protection. Pe INTE AUTHOR BIOGRAPHIES vity in a transition economy: the case of Poland. Equilibrium. Quarterly Journal of Economics and w N edAL S Economic Policy 15(1): 49-62. PrCIE o ceN edTIF ingIC C on the Sharing Economy and Sharing platform in the field of transport, tourism and support services. EN R OCE I Milan Fi ľ a is an associate professor of Economy and Management at The College of Applied Psychol- JET'S A CT ogy in Prague and Terezin, Czech Republic. His professional work focuses specifically on the business MB A Zvolen, Slovakia and external Ph.D. student on University of Žilina, Slovakia. His research is oriented ok FER : P Jaroslav Viglaský s Bo O is a CEO of the business accounting and business advisory company Betria, s.r.o. in N development, business environment, HR project management and Innovations. He has a more then O NU AT P five years of experiences as a director of regional business centre. G EMEO ENPLE 2 T, S TR024 AT–2 EG IC02 C5 OM M U N ATIC ION M ANAGEMENT, W EB AND INFOR ATM ION EC T H NOL O IEG S 59 w N edAL S Pr ZOON PROJEKTIKON: NAVIGATING THE ROLE o CIE ce N OF “PROJECT BEINGS” WITHIN SUSTAINABLE ed TIF ing IC C PROJECT MANAGEMENT IN THE AGE OF s Bo O N GENERATIVE AI ok FE R : P EN R er-R RN evAT ieIO Pe IN Published scientific conference contribution TE 1.08 Objavljeni znanstveni prispevek na konferenci O CE I Mario Protulipac, PhD Candidate JE T'S A CT Alma Mater Europaea University, Slovenia M B A O N Jelena Kljaić Šebrek, PhD U A T P G WYG savjetovanje, Croatia EM EO EN PL E 2 T, S ABSTRACT TR 02 4 AT –2 Generative AI is already widely present in project management. In addition to commonly used EG IC 02 tools, the amount of input these tools use increases and provides higher quality. However, the C 5 OM question arises to what extent AI tools can help project managers solve certain situations relat- M ed to the project’s contribution to sustainable development, either without context or within a U N defined contextual setting; in other words, whether the Generative AI tools impact project man - IC AT agers to be less Zoon Projektikon (“Project being”). The paper is based on a case study in which ION different situational questions concerning planet, people, and prosperity contributions were M asked of project managers and generative AI tools. The analysis of the responses showed that A N A generative AI tools provide different proposals for solving situations, just like project managers. G The difference arises when the three separate situations are in a shared context. In this case, the EM EN generative AI tools showed different answers in contrast to the proposed solutions offered by the T, W project manager. The conclusion is that, at the moment, AI can be a helpful tool that project man- EB agers will use to simulate options analysis for individual situations; however, when the problem A N is more complex and contextual, project managers provide more complete solutions. D IN Keywords: Sustainable Project Management, Generative AI, Zoon projektikon (“project being” or FOR “project animal”) M AT ION EC T H NOL O IEG S 60 1 INTRODUCTION Pe INTE Artificial intelligence has become an integral part of many aspects of human activity, including pro - er -RRN ject management. AI has been effectively utilized for predictions, particularly in project planning. evAT ieIO For instance, generative AI can assist project managers in identifying risks, creating a work break- wN edA down structure, and planning resources. However, one must consider the extent to which artificial L S Pr intelligence is prepared to engage in decision-making within complex project situations. Can AI tru- oCIE ceN ly replace the uniquely human traits that stem from our social nature? Human decision-making is of - edTIF ten informed by knowledge, experience, values, and a broader understanding of the social context. ingIC C More than 2,000 years before Aristotle, humans built the Great or Cheops Pyramid, which can be : P EN R OCE I JET'S A CT considered a demanding construction project even from today’s perspective. If humans have been MB managing the most complex projects that have built our civilization for 5 millennia, can we say that mined by their sociality. Humans are social beings who shape and are directed towards a communi- ok FER ty. Therefore, they are necessarily political beings (or political animals). Aristotle coined the term Zoon Politikon some 2,350 years ago, describing humans as beings deter s Bo O -N we are also a ZOON PROJEKTIKON (project animals)? A O NU AT P G EMEO “Projektikon” is a fictional term that does not exist in ancient Greek. The neologism Zoon Projek- ENPLE 2 tikon is introduced to evoke the characteristics of man as a being endowed with projective thinking. T, S Our decisions are significantly influenced by our nature as social beings, which also affects how we TR024 make choices in projects. If we heavily utilize generative AI that doesn’t account for the nuances of AT–2 EG IC02 social interaction, will we compromise the quality of our decision-making? If so, to what extent? C5 Bredillet et al. (2015). in their paper “What is a good project manager? An Aristotelian perspective” OM gave an answer to the question of what a competent project manager should be. A “good” PM is MU a “wise” PM and conversely acts “rightly” or does “good” action in context. That is what a “good” NIC PM is expected to “do” regarding the purpose s(he) pursues and the role s(he) fulfils in this very ATION situation (Bredillet et al., 2015). To what extent is the role of the project manager changing in the M digital era? Many factors influence project managers’ competencies, including working in a virtual AN environment, multicultural projects, and the increasing use of generative AI. Andre Ribeiro points AG out that Industry 4.0 and digitization will affect the soft and hard competencies of the project man -EM ager. In soft competencies, communication skills, authority, team management, management of ENT, W unforeseen events and negotiation skills are highlighted, in hard competencies, full comprehension of Cyber-physical systems from the project manager along with deep domain knowledge while the EB A implementation is mainly delegated to project team experts or virtual assistants. The most impor-ND tant hard skill for project managers is experience with innovative technologies and projects, big IN data analysis and predictive algorithms that will help them to manage projects correctly and fo-FOR arrival and application of AI in project management. When an AI system is applied to the knowledge cused on the objectives to be achieved. (Ribeiro, et al. 2021). A new major shift occurred with the MAT ION be automated making it much more efficient and therefore leading the project manager to have a ECHNOL management system, the process by which relevant information is accessed and displayed could T lot of information regarding who performed well on which task, what were the main drainers of the budget and what were the success factors giving him/her the ability to make the best out of the OG recorded experiences and make the most effective decision contributing to higher project success IES (El Khatib, M. and Al Falasi, A. 2021). The category of GPT refers to Large Language Models (LLMs) that use deep learning techniques for extensive training with tremendous amounts of data (Cascella et al., 2023). The capabilities of ChatGPT are enabled by generative AI, which refers to a type of AI that can generate human-like text and creative content, as well as consolidate data from different sourc-es for analysis (Dasborough, 2023). There are several articles that analyse the applicability of generative AI to certain processes in pro-ject management. The top-ranked functions in Project management to be supported by AI are: cre-ate a project schedule, analyse implications of missing deadlines, create a WBS/tasks list, create a project budget, update project progress and schedule, identify scope creep and deviations, produce a dynamic risk map, extract deliverables, prioritize tasks, and allocate team members (Holzmann et al. 2022). AI-generated plans serve as efficient starting points, often introducing novel insights, especially in areas like risk management. However, they should not be viewed as final deliverables. 61 w N plying AI. This is because generative AI can develop new, innovative, and more targeted solutions. ed A L S Pr Here, the collected knowledge in the company and far beyond is used through trained data and CIE o knowledge pools. At the same time, AI can largely avoid human errors or cognitive biases (Wag-ce N ed ner, 2024). TIF ing IC C Despite the undoubted advantages that the application of generative AI brings to project manage-s Bo O N ment, research also recognizes some advantages, risks and limitations of use that may arise. The ok FE R number of scientific papers that problematize the use of AI in the context of its impact on humans : P EN R er-R R uniquely qualified to provide context and address potential gaps in AI-generated plans (Barcaui, N ev AT 2023). In addition to the efficiency gain, the effectiveness of projects can also be improved by ap-ie IO Pe IN ager’s domain knowledge, understanding of industry standards, and best practices make them TE Human expertise remains vital for validating and refining these AI outputs. A human project man- JE is associated with multi-faceted social, environmental, and economic consequences. These include T'S A CT M O CE I and sustainability in general is growing. Rohde et al. emphasize that the increased use of AI systems A BO consumption and greenhouse gas emissions in AI model development and application, and an in-N U non-transparent decision-making processes, discrimination, increasing inequalities, rising energy EM EO effects of Generative AI on the individual, of which he particularly emphasizes: Increased delegation EN A T P G creasing concentration of economic power (Rohde et al. 2023). Clarke R. points out several negative T, S PLE 2 of authority to automated facilities, and increased difficulty in reviewing and reversing unfair deci- TR sions (“the computer says no”), based on original Adensamer et al. (2021). 02 4 AT –2 EG 1.1 Purpose and goals IC 02 C 5 OM The purpose of this paper is to assess to what extent AI tools can help project managers solve certain M situations related to the project’s implementation, either without context or within a defined con- U N textual setting. Based on the literature review, the following research questions arose: IC AT - Do the Generative AI tools impact project managers to be less Zoon Projektikon? ION - To what extent AI tools can help project managers solve certain situations related to the project M implementation? A N A G - Can AI efficiently replace project managers in project planning and implementation? EM - What are key advantages of AI and human PMs in solving problems? EN - How could AI and human PMs knowledge and skills be integrated to increase quality and efficien - T, W cy in project management? EB A N D IN 2 METHODS FOR This study employs primarily qualitative methodology to analyse and assess responses of Genera - M AT tive AI tools and project managers. For this purpose, three project situational questions from project ION implementation phase were answered by three Generative AI tools (ChatGPT, Perplexity and Infini - T ty) as well as by three well-experienced project managers from different sectors. In order to provide EC H NOL more comparable and concise responses, the respondents were asked to limit their responses to O maximum of 800 characters. The situational questions cover different problems that project man- IEG agers face during the project implementation. The first question describes the situation when pro- S ject manager is dealing with difficult client who neglects project deliverables. The second situation deals with very common situation when one of the project team member is conflict person and having difficulties to follow some of project tasks. The third situation is about making decision on project management method to be used. The list of situational questions is presented in the Table 1. 62 Table 1: List of situational questions Situational question 2 (S2) tageous. The responsible persons in the client’s organization do not approve your outputs - w N edAL S Pr due to their allegedly poor quality, although you suspect that the dissatisfaction stems from o the fact that they did not contract the company they expected. CIE ceN ed What are the three steps you will take?TIF ingIC C You have a conflicting person in your project team. He is a technical project manager, an s BoO experienced engineer who thinks he is always right. He does not perform his administrative N ok Situational question 1 (S1) You are implementing a project management service that you have been awarded based TE er-R Pe IN on a public procurement procedure. The public sector client that hired you originally want- RNAT ev ed to work with another company, but due to legal obligations, was obliged to carry out a ieIO procurement procedure in which your offer was assessed as the most economically advan tasks (TSs). However, his knowledge and experience are hard to replace. RFE (Source: Authors’ interpretation) Situational question 3 (S3) What three steps would you take to resolve the conflict situation : P ? EN R OCE I You are implementing a project in which you will have a lot of typical infrastructure inter- JET'S A ventions (installation of typical equipment in the energy sector). In addition to infrastruc-CT M ture interventions, you are developing new software that needs to monitor losses in the B AO N energy system. PMO offers the use of traditional methods using MS Project as the basic tool U AT P G or agile methods according to the Kanban working method. EMEO What is your decision and three arguments on which you base the decision. ENPLE 2 T, S TR02 The assessment was conducted against 8 criteria, 7 general criteria and 1 derived from IPMA Indi-4 AT–2 vidual Competence Baseline (IPMA ICB4) framework. The list of assessment criteria is shown in the EG IC02 Table 2. C5 OM Table 2: Assessment criteria MUNIC Assessment Criteria AI advantages Human advantagesATION Accuracy / Relevance • Potentially vast database – precise, fast and • More time is needed to provide solution M of data / Speed fact-based answers • Accuracy can be limited due to individual A • Dependency on accuracy of data base experience and incomplete informationNAG Critical thinking / • Excel in solving structural problems • Better context awarenessEM Problem solving / • May struggle with complex, novel, or ambig-• Better adjustment of answers to the contextEN Context uous situations that require creative solutions • Subjectivity due to individual experienceT, W Creativity / Flexibility • Efficient at common scenarios but lacks true • May bring unique and creative perspective EB A / Adaptability creativity that is crucial for unexpected situationsND IN Emotional • Lack of true emotional intelligence • Adapting answers to interpersonal dynamics FOR intelligence / Ethical • Ethical framework designed by developers’ and leadership styles aspects guidelines • Ethical evaluations influenced by personal MAT values and organizational ethics, could also be biasedION Collaboration H oration by using project management tools leadership styles to resolve conflicts and NOL foster teamwork • Lack of understanding of true team dynamics O Communication / • Able to facilitate project management collab- • Tailor approach to fit team needs and adjust EC T and interpersonal conflicts • Potentially biased by personal values, charac- G ter and experience IES Risk management • Based on historical data and predictive models • Broader perspective, using judgment and experience to make decisions in uncertain environments Cost and Efficiency • Potential of reducing costs and improving • Potentially higher costs (salaries, training) efficiency in repetitive situations and potential inefficiencies in handling large- scale data IPMA ICB4 Criteria • n/a • n/a (Source: Authors’ interpretation) 63 er TE-RRN 2. Interviews with experienced project managers to select 3 situational questions to be responded ev AT by both AI and project managers Pe IN 1. Initial development of situational questions based on the literature review and authors’ experience The research includes the following steps: ie IO wN edA 3. Online questionnaire with situational questions L S Pr 4. Data collection from both types of respondents o CIE ce N 5. Data analysis using Multi Criteria Analysis method ed TIF ing 6. Results interpretation and conclusions IC C ok FE Multi Criteria Analysis. The responses were rated on a 3-point scale (1- poorly aligned with the crite-R : P s Bo ON The collected responses were analysed by the authors as professional project managers by using the CT T'S A petence area and Alignment with at least 1 competence element indicator to obtain 3 points. If only M B A O one criterium was met, the response gained 2 points. N U A T P G O CE I with IPMA ICB4 criteria included both alignment with more than 1 competence element within com-JE R EN ria, 2- average alignment with the criteria, 3 – completely aligned with the criteria). The alignment EM EO 3 RESULTS EN PL E 2 T, S The research showed that Generative AI tools obtained better results in two of three situations. The TR 02 4 detailed results are shown in the Table 3. AT –2 EG IC 02 Table 3: The MCA research results C 5 OM M S1 S2 S3 Total U Total AI N Human AI Human AI Human AI Human IC AT Accuracy / Relevance of data / Speed 3 1 3 1 3 1 9 3 ION M Critical thinking / Problem solving / 2 1 2 3 3 2 7 6 A Context N A G Creativity / Flexibility / Adaptability 2 2 1 3 3 2 6 7 EM EN Emotional intelligence / Ethical aspects 2 3 1 3 1 1 4 7 T, W Communication / Collaboration 3 3 2 3 1 1 6 7 EB A Risk management 2 2 1 1 1 1 4 4 N D Cost and Efficiency 3 2 3 1 1 2 7 5 IN FOR ICB criteria 3 3 2 2 2 2 7 7 Total 20 17 15 17 15 12 ION Average 2,50 2,13 1,88 2,13 1,88 1,50 T EC ATM (Source: Authors’ interpretation) H NOL The AI tools gained higher scores in Situation 1 (2,50) and Situation 3 (1,88). The Human project O managers gained higher score in Situation 2 (2,13). In general, the higher scores were achieved in G IE Situation 1, and both respondents groups achieved lower scores in Situation 3. When it comes to S assessment criteria, The AI scored higher in the following criteria: Accuracy, Relevance of data and Speed, Critical thinking, Problem solving and Context and Cost and Efficiency. On the other hand, hu-man project managers scored better at the criteria Creativity, Flexibility and Adaptability, Emotional intelligence and Ethical Aspects and Communication and Collaboration. Both respondents’ groups gained same scores at the criteria Risk management and ICB criteria. 4 DISCUSSION The research results proved that Generative AI tools can be very useful asset in problem solving situations in project implementation. The AI can achieve great results in well structured and re-petitive situations. This confirms the literature review findings and research results from some of the previous research. Furthermore, AI tools excelled in criteria speed, cost and efficiency. It 64 for fast analysis of large amounts of data but further development of problem solutions should be w N edA left to human project managers.L S PrCIE o On the other hand, human project managers excel in criteria communication, creativity, emotional ceN ed intelligence which also confirms the findings from previous research. This result is expected as AI TIF ingIC C tools do not have true emotional intelligence and can not replace humans when it comes to emo- s BoO tions and empathy. In all of the human responses it is visible that they prioritized team dynamic, N okFE opinions of other team members and empathy. The results prove that human responses tend to be R : PEN more affected by individual personal experience which in some situations may be limited and not efficiency when proposing measures to solve the problem which can be beneficial in less complex er-R RN evAT situations or can be used as a good starting point to discuss in complex situations. AI can be used ieIO to human project managers. Most of the AI responses took into consideration potential costs and Pe INTE provided very detailed, to the point and accurate responses in a short period of time compared O CE I R leading to the optimal problem solution. JE T'S A CT The limitations of this research can be found in small number of both problem situations and num- MB AO ber of respondents which may lead to limited possibilities of generalization. NU AT P G EMEO 5 CONCLUSION ENPLE 2 T, S In general, it can be concluded that AI tools neither minimize nor replace the role of human pro- TR024 ject managers as Zoon Projektikon. On the contrary, AI tools make a great asset to project manag - AT–2 EG ers when implementing projects. AI can help project managers in solving some repetitive, simple IC02 C5 situations, saving time and effort of project managers to focus more on complex situations. In any OM case, AI solutions should be considered only as a starting point that should be discussed and critically M analyzed before accepted and implemented. U N it would be good to see how the AI assesses the responses of human project managers to test the ION M ability of critical thinking. Furthermore, it would be beneficial to compare results among different AN The research results brought into focus possibilities for future research. Namely in future research ATIC geographies, sectors and respondents’ profile but also to apply similar methodology to a specific AG type of project (narrowing). Lastly, since AI tools are constantly changing and advancing, the same EM problem situations should be assessed to test whether AI-generated responses provide improved EN models in a near future. T, W EB AND INFOR ATM ION EC T H NOL O IEG S 65 Pe REFERENCES IN TE er 1. Adensamer Angelika, Rita Gsenger, and Lukas D. Klausner. 2021. “Computer says no”: Algorith--R R N ev AT mic decision support and organisational responsibility. Journal of Responsible Technology 7-8 (Oc-ie IO tober 2021) 100014. w N ed A L S 2. Barcaui, André, and André Monat. 2023. Who is better in project planning? Generative artificial Pr intelligence or project managers? Project Leadership and Society 4: 100101. o CIE ce N ed 3. Bredillet, Christophe, Stephane Tywoniak, and Ravikiran Dwivedula. 2015. What is a good pro-TIF ing IC C ject manager? An Aristotelian perspective. International Journal of Project Management 33(2): ok FE 4. Cascella, Marco, Jonathan Montomoli, Valentina Bellini, and Elena Bignami. 2023. Evaluating the R : P s Bo O 254–266. N CT T'S A 5. Clarke, Roger. Principles for the Responsible Application of Generative AI. Available at SSRN: http:// M B A O dx.doi.org/10.2139/ssrn.5104484. N U A T P G O CE I nal of Medical Systems 47(1): 1–5. JE R EN feasibility of ChatGPT in healthcare: An analysis of multiple clinical and research scenarios. Jour- EM EO field of organizational behavior. Journal of Organizational Behavior 44(2): 177–179. EN 6. Dasborough, Marie T. 2023. Awe-inspiring advancements in AI: The impact of ChatGPT on the T, S PLE 2 7. Holzmann, Vered, Daniel Zitter, and Sarah Peshkess. 2022. The Expectations of Project Managers TR 02 from Artificial Intelligence: A Delphi Study. Project Management Journal 53(5): 438–455. 4 AT –2 8. El Khatib, Mounir, and Ahmed Al Falasi. 2021. Effects of Artificial Intelligence on Decision Making EG IC 02 in Project Management. American Journal of Industrial and Business Management 11: 251–260. C 5 OM 9. Ribeiro, André, António Amaral, and Teresa Barros. 2021. Project Manager Competencies in the M context of the Industry 4.0. Procedia Computer Science 181: 803–810. U N IC 10. Rohde, Friederike, Josephin Wagner, Andreas Meyer, Philipp Reinhard, Marcus Voss, Ulrich AT Petschow, and Anne Mollen. 2023. Broadening the perspective for sustainable AI: Sustainability ION criteria and indicators for Artificial Intelligence system. Computer Science, Computer and Society. M arXiv preprint arXiv:2306.13686. https://doi.org/10.48550/arXiv.2306.13686. A N A 11. Wagner, Reinhard. 2024. The transformative power of Artificial Intelligence applied to the field of G EM project management. International Project Management Association (IPMA). EN 12. Wagner, Philipp, and Reinhard Wagner. 2024. The Evolution of Technology in Artificial Intelli-T, W gence and Its Impact on Project Management. In: Innovative Methods in Computer Science and EB A Computational Applications in the Era of Industry 5.0. ICAIAME 2023, eds. Hemanth, D.J., Kose, U., N D Patrut, B., Ersoy, M., 268-293. Engineering Cyber-Physical Systems and Critical Infrastructures, vol IN 10. Springer, Cham. FOR ATM ION EC T H NOL O IEG S 66 Published scientific conference contribution Pe INTE 1.08 Objavljeni znanstveni prispevek na konferenci er-R RN evAT ieIO EXPLAINABLE ARTIFICIAL INTELLIGENCE w N edAL S Pr o IN THE CREDIT VERIFICATION PROCESSCIE ceN edTIF ingIC C Alma Mater Europaea University, Slovenia ok FER : P Senzekile Mofokeng, PhD Candidate s Bo ON R EN ABSTRACT JE T'S A CT O CE I Credit offering has formed part of sustainable development over the years, as it provides access to B M A O NU A economic opportunities for the underprivileged. Explainable Artificial Intelligence (XAI) plays a T P G high predictive accuracy, the AdaBoost algorithm has been criticised for its lack of interpreta- TR 024 bility, which can hinder its adoption in sensitive domains such as credit verification. This study AT–2 EG aims to explore the integration of the XAI technique using Local Interpretable Model-agnostic IC02 Explanations (LIME) to enhance the transparency of AdaBoost-based credit verification models. C5 OM We analyse the key features driving model predictions using a publicly available credit dataset ensuring regulatory compliance, and mitigating biases in financial decision-making. Despite its EN PLE 2 T, S vital role in credit scoring, where transparency and interpretability are crucial for fostering trust, EM EO and assess the trade-off between interpretability and predictive performance. UM N The findings reveal that XAI methods can effectively decompose the complex decision-making ATIC processes of AdaBoost, providing clarity into the factors (which were Debt to income ratio, delin- ION quency and the credit age) influencing credit decisions for specific customers while maintaining MAN high classification accuracy. However, the study highlights certain limitations, including utilising AG publicly available data instead of real data; further, large language models may be beneficial EM in making the models understandable through natural language. These insights contribute to ENT, W advancing the development of explainable credit scoring models, ensuring their alignment with ethical and regulatory requirements while maintaining robust predictive capabilities. EB A Keywords: XAI, Credit Verification, LIME, Machine learningND INFOR ATM ION EC T H NOL O IEG S 67 Pe 1 INTRODUCTION IN TE er-R R The current drama within the OpenAI board is interesting; the substance of the debate is whether N ev AT OpenAI is committed to creating safe AI (Roush 2023). OpenAI is an organisation that has height-ie IO w ened research on generative AI, thus introducing ChatGPT in early 2021. The scholarly debate on N ed A L S safe AI has been topical and has been discussed in multiple disciplines. In law, the question remains Pr on the accountability when AI errs (Engstrom and Haim 2023, 290). In social science, concerns are o CIE ce N raised about fairness and whether AI can be trusted (Kellogg, Valentine, and Christin 2020, 371). ed TIF Computer scientists have developed explainable AI, which addresses the black-box nature of al-ing IC C gorithms by promoting transparency and safeguarding against bias (Shin 2021, 2). An industry that s Bo O N could substantially benefit from transparent AI is the financial services industry; as this industry is ok FE R : P highly regulated, customer trust is key to sustaining profitability, and financial risk needs to be al-EN R O CE I ways managed. A process that poses the greatest financial risk to the point where a financial servic-JE T'S A es organisation can be closed is the credit verification process (Jovanovic et al. 2024, 1). The credit CT M B verification process assesses a customer’s historic credit profile to predict whether a customer will A O N U not default on future credit facilities or loans (Jovanovic et al. 2024, 1). A T P G EM The objective of this study is to evaluate the transparency of the credit verification process when EO EN PL machine learning algorithms are used to predict customer credit facility defaults. E 2 T, S Trust plays a vital role in the recommendations made by AI systems in critical sectors such as health-TR 02 4 AT care, banking, and criminal justice. A key challenge lies in comprehending the intricate nature of –2 EG IC 02 machine learning models. While these models can decipher complex relationships between input C 5 variables and outcomes, understanding their underlying processes can be complex (Alblooshi et al. OM 2024, 2). The black-box nature of algorithm processes has led to calls for research on explainability M U N in AI, particularly as there has been increasing pressure to give the right explanation on how and IC why a result was provided (Shin, 2021, p. 1). It is widely acknowledged that eXplainable AI (XAI) is AT ION essential for establishing trust in classifier algorithms. Nonetheless, varied theoretical frameworks AN datasets (Alblooshi et al. 2024, 2). A M and approaches exist in different research studies. XAI effectively elucidates biased and unbalanced EMG EN 1.1 Purpose and Goals T, W The study’s main goal is to evaluate the efficacy of the eXplainable Artificial Intelligence (XAI) model, EB known as Local Interpretable Model-agnostic Explanations (LIME), in explaining the results of our A N experimental trials. It aims to demonstrate the viability of incorporating LIME into the assessment D of credit scores. The primary research question is: “Is it feasible to assess the transparency of the IN FOR machine learning models in credit scoring applications?” ATM This study is practically significant as it can assist managers in organisations in managing credit ver- ION ification risk using XAI. Furthermore, the study will assist managers in managing financial risk spe- EC T cifically caused by offering customers loans which they cannot afford to pay back (Alblooshi et al. H 2024, 1). The study is theoretically relevant as it furthers knowledge in XAI specifically using LIME NOL in evaluating credit verification models. Furthermore, it seeks to pinpoint any obstacles and con- G straints that may arise when utilising LIME in credit scoring analysis. Credit managers and customers O IES are not acquainted with XAI models but can converse in natural language. The study is organised as follows. The introduction outlines the research problem, objectives, and contributions. Followed by a literature review. Thereafter discusses the methodology. Following the analyses and discussion of the results, the study provides recommendations for future research. 2 LITERATURE REVIEW The literature review’s structure is as follows: It commences with exploring explainability, interpret-ability, and understandability. Subsequently, it addresses the classification models utilised in credit verification for this study AdaBoost will be utilised. Following this, it provides an elucidation of LIME, and it concludes with a comprehensive summary of the chapter. 68 2.1 Explainability, Interpretability and Understandability rather than delving into the decision-making process itself (Chinnaraju 2025, 176). Explainability ed NAL S Pr involves the ability to express a machine learning model and its results in a way that is easily un- oCIE derstandable to individuals. It requires a comprehensive examination of the logical constructs that ceN ed underlie the system’s decision-making processes. By ensuring that insights from a machine learning TIF ingIC C model can be effectively communicated using precise and accessible language, explainability plays s BoON a crucial role (Adadi and Berrada 2018, 52140). okFER fidelity within the field of machine learning. Despite often being used interchangeably, these terms RNAT ev have nuanced differences. Explainable AI focuses on explaining the reasoning behind decisions ieIO w This section explores the interconnected relationships among explainability, interpretability, and TE er -R Pe IN Interpretable AI provides insight into how decisions are made but may not necessarily provide ex- : P EN R planations for the specific criteria selected (Vishwarupe et al. 2022, 870). Interpretability allows for OCE I JE understanding the results of learning models by revealing the rationale behind their decisions (Mill-T'S A CT M er 2019, 2). Interpretable systems are considered explainable when humans can comprehend their B AO N processes, highlighting the close relationship between explainability and interpretability (Adadi U AT P G and Berrada 2018, 52141). Interpretability and completeness (fidelity) are fundamental aspects of EMEO explainability (Gilpin et al. 2018, 2). ENPLE 2 T, S A comprehensive explanation should be human-comprehensible (interpretability) and accurately TR02 represent the model’s behaviour across the entire feature space (fidelity). Interpretability refers 4 AT–2 to the extent to which humans can comprehend the connections between input variables and the EG IC02 resultant model predictions, thereby ensuring transparency and relevance of AI decision-making C5 OM processes for relevant stakeholders (Chinnaraju 2025, 176). Simply put, The principle of fidelity M addresses the level of accuracy with which explanations depict the true computational reasoning U N IC of AI models, thus protecting users from erroneous understanding based on excessively simplified AT or approximate accounts (Chinnaraju 2025, 190). The primary objective of eXplainable AI (XAI) is ION to enhance the interpretability of deep learning and machine learning models (Dastile, Celik, and M Vandierendonck 2022, 69544). ANAG 2.2 AdaBoost in Credit ScoringEMEN AdaBoost, or Adaptive Boosting, has emerged as a robust machine learning algorithm for improving T, W predictive accuracy in credit scoring while handling complex and high-dimensional datasets. As an EB A ensemble learning method, AdaBoost combines the outputs of multiple weak classifiers often deci -ND sion stumps, into a single, strong classifier, progressively refining its predictive capabilities through IN iterative adjustments to misclassified instances (Freund and Schapire 1997, 156).FOR AdaBoost overcomes the limitations of individual classifiers as a weighted ensemble model by MAT assigning greater emphasis to incorrectly classified instances during each iteration. This adaptive ION more, AdaBoost’s simplicity and flexibility make it applicable to a wide range of credit datasets, ECH weighting mechanism allows the model to focus on difficult cases, enhancing its accuracy. Further- T even those with imbalanced distributions, which are common in credit scoring scenarios (Rokach NOL 2010, 5). AdaBoost also supports interpretability through post-hoc explainability techniques, which OG provide insights into the model’s decision-making process. Using methods such as feature impor- IES tance visualisations through SHAP (SHapley Additive exPlanations), the contributions of individual variables to predictions can be quantified (Lundberg and Lee 2017, 1) 2.3 XAI Models Complex machine learning models often lead to black-box models, necessitating explanations through either post-hoc, ante-hoc, or instance-based approaches (Dastile, Celik, and Vandierendon-ck 2022, 69544). Post-hoc explanations involve utilising additional models such as Shapley Additive explanations (SHAP) and Local Interpretable Model-Agnostic Explanations (LIME). These methods, commonly known as eXplainable Artificial Intelligence (XAI) models, are frequently applied to elu-cidate underlying machine learning credit scoring models. On the other hand, ante-hoc explanation involves inherently interpretable models like Decision Trees. Instance-based explanations rely on specific instances to explicate the behaviour of a black-box model (Dastile, Celik, and Vandieren- 69 w N edAL S 2.4 Local Interpretable Model -Agnostic Explanation (LIME) Pr CIE o ce N The Local Interpretable Model-Agnostic Explanation (LIME) framework is a publicly available re-ed TIF source designed to enhance trust in machine learning models by elucidating their decision-mak-ing IC C ing mechanisms (Alblooshi et al. 2024, 3). LIME is structured to concentrate on specific data points, s Bo O N aiming to render models interpretable while remaining model-agnostic. This framework provides ok FE R valuable insights into model operations, enabling the identification of critical areas within images : P EN R er-R R models is crucial as it enables us to grasp their inner workings, identify the most critical attributes N ev AT influencing them, and comprehend the rationales behind their predictions (Alblooshi et al. 2024, 2). ie IO Pe IN ligence that aims to enhance the interpretability of machine learning models. Understanding these TE donck 2022, 69544). Explainable Artificial Intelligence (XAI) is a research area within artificial intel- O or highlighting important features. Its key functionalities span image interpretation, text analysis, CE I JE and evaluation of tabular data (Carmona, Dwekat, and Mardawi 2022, 10). T'S A CT M The increasing reliance on machine learning for credit scoring has necessitated the adoption of ex- B A O N U plainability techniques, such as Local Interpretable Model-agnostic Explanations (LIME), to enhance A T P G model transparency. Several studies have explored the efficacy of LIME in explaining credit scoring EM EO models, highlighting both its advantages and limitations. EN PL E 2 T, S The authors noted that LIME successfully highlights important features that affect credit decisions, TR 02 4 enhancing the model’s interpretability. Nevertheless, they observed that the effectiveness of LIME’s AT –2 explanations is heavily influenced by its parameter settings, which can result in inconsistencies. Ad - EG IC 02 ditionally, LIME’s local focus might fail to fully represent the model’s overall behaviour (Gramegna C 5 OM and Giudici 2021, 2). M U Similarly, LIME improves model transparency by offering clear explanations for specific predictions. N IC However, it raised issues about LIME’s applicability to the entire dataset and the computation- AT al expense of producing numerous local explanations (Aljadani et al. 2023, 15). In a recent study, ION researchers utilised LIME on neural network models, showing that it enhances trust in model out- M AN puts by providing clear, instance-based explanations. Nonetheless, the research revealed that LIME A G is less effective with highly imbalanced datasets frequently encountered in credit scoring (Chen, EM Calabrese, and Martin-Barragan 2024, 359). Furthermore, choosing the right parameters for LIME is EN crucial for delivering meaningful explanations (Nguyen and Truong 2024, 322). By integrating LIME T, W with neural networks, the authors found that LIME helps interpret intricate models by emphasising EB A key features. However, they pointed out that although LIME delivers localised interpretability, it fails N D to understand the neural networks’ overall behaviour comprehensively. Additionally, the explana- IN tions produced by LIME were inconsistent when tested on various data subsets (Munkhdalai et al. FOR 2019, 409). Another relevant study evaluated LIME’s stability with imbalanced datasets. The findings M AT indicated that as class imbalance increases, the reliability of LIME’s explanations diminishes, which ION is a frequent issue in credit scoring models. This research emphasised the need for additional strat - T egies to ensure LIME’s interpretations remain consistent across different data distributions (Chen, EC H NOL Calabrese, and Martin-Barragan 2024, 358). O One limitation of using Local Interpretable Model-agnostic Explanations (LIME) is that it requires hu- G IE man interpretation of its outputs, which can be subjective, time-consuming, and prone to errors, S especially for complex models (Ribeiro, Singh, and Guestrin 2016, 1137). This limitation can be mitigated by employing Large Language Models (LLMs), which can process and summarise LIME’s explanations in a more human-like manner, making the results more accessible and interpretable for non-experts (Suh et al. 2025, 2). By leveraging LLMs, the interpretability of LIME can be enhanced, allowing for a more efficient and scalable approach to model explainability. 2.5 Summary of the Literature Review The study will focus on using AdaBoost, which has been found to provide the best results in cred-it verification. LIME is also quoted as being able to explain AdaBoost models (Lundberg and Lee 2017, 2). 70 3 METHODOLOGY Pe INTE 3.1 Datasets er -RRN evAT The dataset used for the experiment in this study was the Home Equity dataset (HMEQ) used to pre- ieIO wN dict clients who default on their loan. The dataset can be accessed publicly from Kaggle. The data edAL S was selected as it was the most recent data set at the time of the experiment as of January 2025. It Pr oCIE had a usability score of 7,65 and 5960 rows and 13 columns. There were missing values in the data ceN ed which were adequately treated. TIF ingIC C The confusion matrix is crucial for evaluating classification models, offering a detailed breakdown ok FER : P 3.2 Performance Measures s Bo ON R EN of predicted versus actual outcomes. O CE I (Source: Author’s own work. The same applies to all subsequent tables and figures.) Actual Positive PL True Positive False NegativeE 2 T, S TR02 Negative False Positive True Negative4 AT–2 EG IC02 In the confusion matrix presented in Table 1 , positives represent defaults, whereas negatives repre- C5 OM sent non-defaults. The matrix categorises predictions into four outcomes: M U - True Positives (TP): Instances where the model accurately identifies applicants as “bad” credit risks. N IC This means that the customer was predicted to have defaulted, and they actually have defaulted. Table 1: Confusion Matrix M B A CTJE T'S A Predictions N OU AT P G EM Positive NegativeEO EN - ATION True Negatives (TN): Cases where the model correctly classifies “good” credit risks. This means Recall centres on the model’s ability to capture true positive cases. the customer was predicted as having no defaults, and they actually did not default. MANAG- False Negatives (FN): Cases where the model fails to classify actual “bad” credit risks properly, EMEN misclassifying them as “good” credit risks. This means that the customer is predicted to have not T, W defaulted, whereas in actual fact, they have defaulted. EB- False Positives (FP): Instances where the model inaccurately classifies “good” credit risks as “bad.” AN This means that the customer is predicted to have defaulted, whereas, in actual fact, they did not. D IN Recall is a particularly valuable metric for assessing model performance in credit scoring using the FOR Home Equity (HMEQ) dataset. Recall, also referred to as sensitivity or the true positive rate, measures MAT the proportion of actual “bad” credit risks correctly identified by the model. This metric is especially ION significant in credit scoring, where failing to identify high-risk applicants can lead to substantial fi - T nancial losses. Recall is defined as:ECHNOL Recall = TP / (TP + FN). Failing to identify “bad” credit risks (false negatives) incurs a higher cost to financial institutions O IEG than mistakenly flagging “good” applicants as “bad” (false positives). False Negatives (FN): These S errors represent applicants who are classified as “good” credit risks but default on loans. This situ-ation results in direct financial losses and undermines the institution’s risk management strategy. False Positives (FP): While these errors may lead to lost business opportunities or dissatisfied cus-tomers, the financial impact is usually less severe than that of false negatives. Financial institutions can minimise the risk of loan defaults by prioritising recall, thereby ensuring a more robust credit scoring process. A recall-focused approach in credit scoring underscores the model’s capability to identify high-risk applicants, leading to fewer defaults. The confusion matrix and recall provide crit-ical insights into the performance of credit scoring models applied to the HMEQ dataset. Financial institutions can effectively mitigate the risks associated with false negatives by concentrating on recall, enhancing their capacity to manage credit risk. Nonetheless, the trade-offs between recall, precision, and other metrics must be carefully evaluated to ensure the model aligns with broader business objectives and operational requirements. 71 3.3 Workflow er TE Data preparation included data exploratory data analysis. There were outliers in the data set. There -R Pe IN ie IO the median was used; the mean was not used as it would cause skewness in the data distribution. w N ed A However, the median maintained the distribution of the data to be representative of its original L S Pr distribution. For categorical data, the mode was utilised to impute missing values, thus providing ev RNAT were missing values in 11 of the 13 columns. To impute missing values for continuous variables, ing TIF data set comprised 80% of the data with 4768 rows and 16 columns. The testing dataset comprised IC C of 20% of the original data with 1192 rows and 16 columns . Additional columns were a result of s Bo ce N a similar data distribution. The data was separated into training and testing data sets. The training ed o CIE CT During model training, various models were trained to identify the best one. In Figure 1, we com- M B pare different models using Recall as a performance measure in the test set. Based on the Recall A O N U A score, the logistic regression model had the lowest performance, whereas the random forest had T P G the highest performance. EM EO EN PL E 2 T, S Figure 1: Algorithm comparison TR 02 4 AT –2 : P R ing whether the client defaulted or paid the loan. This column was converted into numerical data: 1 EN R representing defaulted clients and 0 representing loans repaid. O CE I JE T'S A ok N one-hot-encoding for categorical variables. The target variable was the column titled BAD indicat- FE O EGIC 02 C5 OM M U N ATIC ION M ANAGEMENT, W EB AND INFOR ATM ION EC T H NOL O IEG S The AdaBoost credit scoring model will be evaluated using recall in the confusion matrix as a perfor- mance indicator. The model with higher recall is considered better; in this case, Random Forest has the highest recall score. 4 RESULTS The credit verification process initially employed Logistic Regression, Bagging, Random Forest, Gra-dient Boosting Machines. The results showed poor performance in these models as logistic regres-sion provided the lowest recall, and the other modules were overfitting. The training recall score was significantly higher than the validation recall score. The study evaluated the transparency of credit verification processes using machine learning, spe-cifically comparing AdaBoost and Gradient Boosting models with explainability techniques. After addressing overfitting issues through SMOTE oversampling and hyperparameter tuning, AdaBoost 72 tio, delinquencies, and credit age (CLAGE) as the most critical predictors of loan default. The LIME (Lo er --R RN evAT cal Interpretable Model-agnostic Explanations) technique was applied to provide instance-specific ieIO recall versus 76% for Gradient Boosting). Feature importance analysis identified debt-to-income ra Pe IN -TE was selected as the optimal model due to its superior generalisation performance (84% validation explanations, revealing that for a particular defaulted customer, a high debt-to-income ratio (>37), w N edA multiple delinquencies, and adverse credit reports were the primary factors driving the default L S PrCIE prediction. However, the study highlighted a significant limitation: LIME outputs proved difficult to o ceN interpret in natural language, making them cumbersome for credit risk managers to use in prac- edTIF tice. The research concluded that while XAI methods like LIME can effectively decompose complex ingIC C 5 DISCUSSION : P EN R OCE I JET'S A CT MB A integrating large language models to translate technical outputs into more accessible, human-un- ok FER derstandable explanations for business users. decision-making processes and maintain high classification accuracy, future work should explore s Bo ON The trained models indicate a high recall score, as illustrated in Table 2 below. The model with the N OU AT P G highest recall is Gradient Boosting, tuned with oversampled data, followed by the AdaBoost classifi - EMEO er, tuned with oversampled data. Although random forest showed the best performance compared ENPLE 2 to other models, it was significantly overfitting with a training set recall of 95% and on the valida - T, S TR02 tion set a recall of 81%. Hence, we opted for gradient boosting and AdaBoost comparisons as they 4 AT–2 were showing less overfitting. EG IC02 C5 OM Table 2: Training Performance Comparison Performance Matrix AdaBoost classifier tuned NIC with oversampled data with oversampled dataAT Gradient Boosting tuned UM Accuracy 0.975 0.956 ION Recall 0.974 0.954 A M Precision AN F1 EM 0.975 0.976 0.958 G 0.956 EN T, W The criterion selected by the researcher for an overfitting model is 10%. Please note that this value EB A was arbitrary and not scientifically determined, as this is the author’s choice. A difference greater ND than of 10% between the training performance score and the validation performance score would IN result in the model not being considered for further analysis. The validation performance compari-FOR son indicates a lower score, as illustrated in Table 3 below. Gradient Boosting tuned with oversam-MAT pled data indicates a recall score of 76% compared to 97% in the training data set. This indicates that ION the model is overfitting; therefore, the predictions may not be accurate compared to the actual data T set. AdaBoost classifier tuned with oversampled data indicates a recall score of 84% compared to ECH 95% in the training data set. This is less than 10% of the selected threshold; therefore, the data is not NOL overfitting, and AdaBoost is the selected model. OGIES Table 3: Validation performance comparison Performance Matrix Gradient Boosting tuned AdaBoost classifier tuned with oversampled data with oversampled data Accuracy 0.884 0.910 Recall 0.756 0.845 Precision 0.692 0.742 F1 0.723 0.790 The feature importance indicated in Figure 2 below indicates that the most important feature is the debt-to-income ratio; a ratio of less than 1 indicates that a client has lower debt compared to their income. A higher than one ratio would indicate that the customer is over-indebted. 73 Figure 2: Feature Importance er TE-R Pe IN ie IO wN edAL S PrCIE ev RNAT ceo ed TIFN ing IC C ok FER : P s Bo ON R EN O CE I CTJE T'S A N OU AT P A B M EMG EN PLE 2 T, SEO TR 024 AT–2 EG IC02 C5 OM M U N ATIC ION A The second important feature is delinquencies, which indicate the number of days a customer has M A not paid their debt from the due date. A number less than 30 days would indicate that the customer N EMG is still within a calendar month of paying an overdue debt. A number above 30 days adversely re- EN flects that the customer’s debt has been overdue for more than a month. The third important feature EB the debt is likely to be multiple years. A N D T, W is CLAGE, which indicates the age of the debt; as this data set represents home equity, the duration of IN 5.1 LIME FOR M LIME is a single instance explanation technique, which means that we only look at one data point AT at a time and explain it. The selected data below is a defaulted customer. The item’s actual features ION are represented in Figure 3 below. T EC H Figure 3:LIME results NOL O IEG S The model predicts a 75% probability for the instance being classified as Default” and a 25% prob-ability for “non-default.” Since the “Default” probability is higher, the model predicts this instance as “Default.The bar chart on the right explains how individual features contribute to the prediction. Orange bars push the prediction towards “Default,” while blue bars push it towards “non-default. 74 - DELINQ (Delinquencies> 0) er TE -RRN evAT- DEROG (DEROG > 0) (Adverse reports) - DEBTINC (Debt-to-Income Ratio> 37.00) Pe IN The key features pushing towards “Default” are: - JOB Office (<= 0) ie IO wN edAL S Pr It is not easy to explain the outputs in natural language or in a humanly understandable manner, so oCIE ceN a credit risk manager might find it cumbersome to interpret the outcome for an applicant/ customer. edTIF However, this is the explanation for this instance. ingIC C as highly likely to default. Moreover, two recorded derogatory remarks (DEROG) in the customer’s A O NU AT P G credit history—indicating severe adverse credit events such as bankruptcies or charge-offs—slightly EMEO EN increase the probability of default. These findings highlight the significant influence of financial sta -PLE 2 T, S bility and past credit behaviour in assessing default risk. TR024 AT–2 EG IC02 6 CONCLUSION C5 OM This study aimed to enhance the explainability of credit verification processes using AdaBoost, with M Local Interpretable Model-agnostic Explanations (LIME) as an explainable AI tool. The methodology U N used the publicly available Home Equity (HMEQ) dataset to develop credit verification models, includ - IC AT likelihood of default. Additionally, a history of seven instances of delinquent behaviour—where the EN R OCE I customer has failed to meet payment obligations on time substantially increases the probability of JET'S A default. The presence of more than one adverse credit report, which typically indicates severe finan - CT MB cial distress, such as accounts sent to collections or legal judgments, further classifies the individual come ratio at 37 is the most significant predictor of loan default for this customer, contributing to the ok FER : P The Local Interpretable Model-agnostic Explanations (LIME) analysis confirms that a high debt-to-in s Bo O -N ing logistic regression, bagging, random forest, and gradient boosting machines (GBM). However, ION these models exhibited overfitting. To address this, the data was balanced using the Synthetic Minority M Over-sampling Technique (SMOTE), and both a tuned Gradient Boosting model and an AdaBoost classi- ANA fier were trained on the oversampled data. AdaBoost was ultimately selected as it demonstrated im -GEM proved generalisation without overfitting, making it a more reliable choice for credit risk assessment.EN The findings from the feature importance analysis and the LIME results highlight key factors con -T, W tributing to loan default, but they differ in their level of specificity and the factors they emphasise. EB A Both methods identify the debt-to-income ratio and delinquent behaviour as significant predictors ND of default, demonstrating consistency in their financial risk assessment. However, the LIME results IN provide a more detailed, instance-specific explanation by assigning a specific contribution rate to FOR the debt-to-income ratio (37) and highlighting additional factors such as adverse reports and de-MAT rogatory credit history. In contrast, the feature importance analysis identifies credit age as a key ION determinant of default risk, which is not explicitly emphasised in the LIME results for this particular T customer. This suggests that while LIME is useful for understanding individual cases, feature impor-ECH tance provides a broader, more generalised view of the most influential variables across multiple NOL customers. Together, these methods offer complementary insights into credit risk assessment. OG It proved difficult to explain the prediction only using LIME. The outputs are not easy to explain in IES natural language or in a humanly understandable manner. As a result, a credit risk manager might find it cumbersome to interpret the outcome for an applicant/ customer. 6.1 Limitations and Future Research The research used publicly available data, which provided a simulation of the real environment. The research findings would be different if real data had been used, which would provide better insight into how explainable AI models can explain complex models. The research project would further provide different insights if deep learning models were utilised for credit verification pur-poses. As explainability is defined as humans understanding complex models in human language, an interesting future study would be the interpretation of the results of a credit verification model using natural language processing models using large language models. Due to time limitations the researcher was not able to perform LLM experimentations. 75 Pe REFERENCES IN TE er 1. Adadi, Amina, and Mohammed Berrada. 2018. Peeking Inside the Black-Box: A Survey on -R R N ev AT Explainable Artificial Intelligence (XAI). IEEE Access 6: 52138–60. https://doi.org/10.1109/ ie IO ACCESS.2018.2870052. w N ed A L S 2. Alblooshi, Maryam, Maher Alaraj, Hessa Alhajeri, and Meera Almatrooshi. 2024. 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AT –2 EG IC02 C5 OM spective.” In 02 Proceedings of International Conference on Industry Sciences and Computer Science TR4 Vishal Pawar. 2022. “Explainable AI and Interpretable Machine Learning: A Case Study in Per- T, S M search focuses specifically on explainable AI models in natural language processing using large lan- ATION guage models, advancing transparency and interpretability in AI systems. Her work aims to bridge M the gap between complex AI architectures and human understanding. Senzekile Mofokeng NU is a PhD student in Applied Artificial Intelligence at Alma Mater Europea. Her re- IC ANAGEMENT, W EB AND INFOR ATM ION EC T H NOL O IEG S 77 er-R RN evAT ieIO Pe IN Published scientific conference contribution TE 1.08 Objavljeni znanstveni prispevek na konferenci w N edAL S Pr THE RISE OF AI IN THE EDUCATIONAL o CIE ce N LANDSCAPE FOR PROJECT MANAGERS ed TIF ing IC C N OU Alma Mater Europaea University – Faculty ECM, Slovenia A T P G EM EO EN PL E 2 ABSTRACT T, S TR 02 4 The application of artificial intelligence (AI) is increasingly being incorporated into projects and AT –2 EG project management. This trend is driven by the potential benefits that AI can bring to project IC 02 C 5 management. However, since project managers still have limited competence in using AI technol-OM ogies, educational opportunities are increasingly in demand. However, the specific requirements M U AI users have for projects remain unclear as to which training programs are effective. Therefore, N IC our research aimed to identify the requirements, the training programs offered, and the need for AT R EN Karolina Novinc, Associate O CE I JE University of Applied Sciences ‘Lavoslav Ružička’ in Vukovar, Croatia T'S A CT M B Mladen Radujković, PhD, Professor A ok FE Alma Mater Europaea University – Faculty ECM, Slovenia R : P s Bo ON Reinhard F. Wagner, PhD, Assistant Professor ION education to utilize AI in project management. Ultimately, we sought to clarify how appropriate M educational offers could effectively improve the application of AI in project management. AN Based on a systematic literature analysis, we researched the requirements of AI users in educa- A G tion projects and the courses currently available. The analysis reveals that integrating AI technol- EM ogies is transforming the landscape of project management. Studies indicate that professionals EN must develop technical and soft skills to leverage AI tools effectively. This dual focus is crucial T, W as AI enhances decision-making, resource allocation, and risk management processes. Overall, EB A our results confirm that educational programs should be refined and AI application competences N D should become an integral part of project management curricula. IN FOR Keywords : Artificial Intelligence, Project Management, Education, Technology Acceptance ATM ION EC T H NOL O IEG S 78 1 INTRODUCTION Pe INTE AI is becoming increasingly important in almost all areas of the economy. New applications in re- er -RRN search and practice are also being reported in project management. However, these applications evAT ieIO are mainly driven by technically adept experts. Most users still lack sufficient knowledge of AI’s tech - wN edA nological possibilities or the necessary application-related understanding. For this reason, our study L S Pr examined the impact of AI on the educational landscape in terms of project management. This reso- oCIE ceN nates with research findings that assert the introduction of AI into higher education (Crompton and edTIF Burke 2023), on the one hand, and with the demand for digital competences for project managers ingIC C as a “must-have” in contemporary times (Marnewick and Marnewick 2021) on the other. Initial ap - s BoON proaches to enriching higher education offerings with AI generally relate to education, rather than okFER explicitly to education in project management (Chan 2023; Clegg & Sarkar 2024), but have been : PEN R called for several years (Auth et al. 2019). Students are also increasingly demanding this (Chan and OCE I JE Hu 2023; Smit et al. 2025). Our research aims to bridge this gap by identifying the current require -T'S A CT M ments for the application of AI in project management and showing what impact this may have on B AO N future educational offerings for project managers. As research has so far examined these questions U AT P G in a non-systematic manner, we set out to conduct a systematic literature review to determine the EMEO current prevalence of AI in higher education and to identify the requirements for corresponding ed - ENPLE 2 ucational offerings in project management. This provides an essential basis for future research in T, S TR02 this field and gives continuing education institutes and teachers important insights into which offer -4 AT–2 ings could be helpful. Finally, it also helps project managers understand which educational offerings EG IC02 could benefit them in the context of AI. After this introduction, the purpose and objectives of our C5 OM investigation are described. The methods section and the presentation of the results follow, which are then discussed and finally concluded. MUNICAT 2 PURPOSE AND GOALSION identify requirements for future educational offerings. Furthermore, we were interested in the gen AN - Our study aimed to analyze the diffusion of AI in educational offerings for project managers and to M A eral application of AI in project management as well as the potential limitations and challenges re- GEM lated to the people involved. The following research questions were the focus of our study: 1. What EN educational opportunities for project managers address AI? 2. Which requirements for the compe- T, W tences (primarily technical and human) of a project manager should be addressed in education? 3. EB A To what extent is AI already integrated into project management today, and what challenges does ND this pose for the people involved? INFOR 3 METHODS MAT ION and thematic content analysis to investigate the application of AI in project management, with a ECH This study employs a qualitative research approach, utilizing a systematic literature review (SLR) T focus on educational requirements, necessary skills, and learning programs. The review process NOL involved designing a comprehensive search strategy, clearly defining inclusion and exclusion cri O -G teria, and carefully identifying relevant resources. This research followed a systematic literature re- IES view (SLR) approach to collect relevant studies, adhering to the PRISMA 2020 guidelines (Page et al. 2021). This ensures transparency, consistency, and reproducibility of findings. By systematically searching, selecting, and analyzing existing studies, the research investigates how AI is applied in project management, particularly in the context of education and skill development. The research analyzed existing academic articles, industry reports, and case studies using the SLR methodology to gain comprehensive insights into AI’s role in project management. Data collection took place during September and October 2024. The study was conducted globally, without limiting the analysis to a specific geographic region, as the selected databases include research from around the world. For-mal ethical approval was not required since this study is based on secondary data from published papers and reports. However, the research adheres to ethical principles, ensuring all sources are cor-rectly cited and paraphrased to comply with academic integrity and copyright standards. This study relies solely on publicly available sources, ensuring that no personal or sensitive data is collected. 79 3.1 Identification er TE All relevant studies have been collected from three academic databases: Semantic Scholar, Web of -R Pe IN ie IO AI+PM was used to identify resources, ensuring that only studies explicitly addressing both topics w N ed A defined in this research (AI in PM, excluding other matters or individual topics) were included. In L S Pr these search engines, besides the mentioned two obligatory terms “Artificial Intelligence” or “AI” ev RNAT Science, and Scopus. The ultimate starting condition is that the study title includes both components. ing TIF diverse terminology was used within titles as well: “Education”/”Requirements” or “Training/Learn- IC C ing Needs”/”Skills” or “Competence Development” targeted literature discussing necessary skills for s Bo ce N and “Project Management” or “PM”, for initial explorations across existing reviews, the following ed o CIE CT M AI is integrated within project management education. B A O N U A T P G Figure 1: PRISMA 2020 flow diagram for SLR AI in PM EM EO EN PL E 2 T, S TR 02 4 AT –2 EG : P R exploring specific AI tools and applications in project management: “Curriculum Development” or EN R “Education”/”Training” focused on educational frameworks, encompassing formal curricula or other O CE I JE forms of informal education, such as online courses or lifelong learning training, investigated how T'S A ok N AI within project management; “AI Applications” or “AI-Driven Tools”/“Challenge” included studies FE O C 5 OM IC 02 M U N ATIC ION M ANAGEMENT, W EB AND INFOR ATM ION EC T H NOL O IEG S (Source: Created by the authors) The aim was to identify publications that study the relationship between AI and PM, with an explicit focus on the impact of AI in PM, its applications, and how it relates to the competences, skills, knowl- 80 were also included to broaden the scope and identify more relevant studies. In the first step of the er-R RN evAT systematic literature review, built-in automation tools within the academic databases (Semantic ieIO of education and training for the competences needed for AI in PM. Synonyms and related terms Pe INTE edge, and training required during this transition. This includes studies exploring the availability Scholar, Web of Science, and Scopus) were used to automatically exclude records that did not meet w N edA predefined criteria ensuring that only relevant publications were retained for further screening. The L S PrCIE research was filtered according to the following inclusion criteria: publication period (2020–2024), o ceN research fields (Economics, Business, Computer Science, and Education), and the language set to edTIF English only. Studies that did not meet these criteria were excluded from further analysis. This rigor- ingIC C 3.2 Screening, analytical methods, and tools for data analysis : P EN R OCE I JET'S A CT MB A the selection strategy chart based on the PRISMA guidelines. As a result, 65 papers were included in ok FER this literature review. ous search and selection process ensured that the review included relevant studies. Figure 1 shows s Bo ON QDA Miner Lite was used for thematic content analysis, while data organization was managed in O NU AT P Microsoft Excel. The 65 studies that were collected were catalogued in an Excel table and presented G EMEO as a list of authors. For each author (defined as “case”), the following details were displayed in sep - ENPL arate rows according to the column headings (defined as “variables”): ordinal number, author, title, E 2 T, S and abstract. The cleaned data was imported into QDA Miner Lite for further data analysis. Firstly, TR024 the data was extracted. The review was done by reading the abstracts of each author, extracting key AT–2 EG information relevant to the researcher’s topic and pertinent details (research proposal, study meth- IC02 C5 od, location, and sample) as initial coding to gain insight into the sample scope. Then, the coding OM process was conducted to identify authors whose studies addressed key themes defined within the MU four categories: 1. AI in PM Expertise and Education – addresses questions related to educational and NIC training programs and the need for AI in PM competences; 2. Requirements for AI in PM – examines AT the key requirements, including technical and soft skills, necessary for successfully implementing ION project management practices, and 4. Considerations of AI in PM - Indicate what the authors of the ANA AI in project management; 3. AI application in PM – focuses on identifying how AI is adapted within M reviewed literature have identified as constraints and highlight potential areas that require more GEM attention in the future. Codes were assigned manually in the QDA software variable based on the EN main themes identified in each source, aligning with the key topics addressed in the respective lit- T, W erature. An overview of the codes, along with their descriptions, is presented in Table 1. EB AN Table 1: Framework for Categorization and Coding of AI in Project ManagementD INFOR Category Code Description Educational Programs Discussion of educational trainings and programs related to AI in project MAT and Education T AI Competences Required expertise or educational needs in the field of AI.EC AI in PM Expertise management. ION H Technical Skills The technical skills required to effectively use AI tools in project management. NOL Requirements O The interpersonal and cognitive skills necessary for AI-driven project Soft SkillsG for AI in PM management.IES Human Need Identified human needs or contributions in the context of AI in PM AI in PM The application of AI in project management. Application of Adaptation The process of accepting/adopting AI within project management practices AI in PM Integrating AI in PM The incorporation of artificial intelligence into project management workflows. Limitations of AI Identified, recognized, or recommended limitations of AI in PM Considerations of AI in PM Identified challenges associated with AI implementation in project Challenges management. (Source: Created by the authors) 81 w N As this is a qualitative study, no statistical methods were applied. Instead, thematic content analysis ed A L S Pr was conducted using QDA Miner Lite, with results presented through a descriptive analysis of key CIE o theme findings. The presentation of findings by reference authors is provided in Appendix I. ce N ed TIF ing IC C 4 RESULTS s Bo O N FE ok 4.1 Overview of source publications R : P EN R er-R R tion of the findings. This thematic analysis was conducted to identify trends and the current state of N ev AT research in this field, providing insights into requirements, training offered, and education needs. ie IO Pe IN discussions and conclusions were analyzed to confirm the codes and provide a descriptive presenta-TE The final analysis included a detailed review of selected studies available in PDF form, during which O This search identified 65 studies from Semantic Scholar, Web of Science, and Scopus. Based on an CE I JE analysis of the study abstracts, three key categories were considered to gain a sample scope: geo- T'S A CT M graphical distribution, sample size, and research method. The dominating codes are shown in Fig- B A O N U ure 2. A T P G EM EO Figure 2: Sample scope distribution EN PL E 2 T, S TR 02 4 AT –2 EG IC 02 C 5 OM M U N ATIC ION M ANAGEMENT, W EB AND INFOR ATM ION EC T H NOL O IEG S (Source: Authors, based on primary data) Geographical Distribution: Nearly 80% of studies do not specify a research location, reflecting the nature of Literature Reviews, which compile global data without a regional focus. The remaining 20% includes various regions, ensuring diverse perspectives and international relevance for AI in project management. Sample Size: In 66% of studies (43 sources), the sample size is not explicitly mentioned, likely due to the use of qualitative or review-based methodologies. Among those that report sample sizes, 14% use large samples (100+ units), 7.7% use medium-sized samples (51–100), and about 6% each use small samples (up to 50 or 10). This diversity balances broad trends with detailed case studies, making findings applicable across different research contexts. No standard thresholds exist for clas-sifying the size of systematic literature reviews. Wang et al. (2023) report a median of 57 studies 82 Research Methods: The most common method is a Literature Review (29.9%), which is crucial for w N edAL S mapping existing knowledge. “Other Methods” (32.8%) include theoretical analyses, framework PrCIE o development, and practical evaluations. Surveys (16.4%) offer quantitative insights, while mixed ceN ed methods (9.0%) ensure comprehensive analysis. Case studies (7.5%) and interviews (4.5%) provide TIF ingIC C deep, qualitative perspectives. The dominance of quantitative research, supported by mixed meth - s BoO ods, ensures a well-rounded examination of AI in project management. The research sample en-N okFE compasses various methodologies and perspectives, providing a comprehensive and industry-wide R : PEN understanding of AI applications in project management. The findings provide a foundation for the large (>100) reviews. This categorization is transparent, context-specific, and supports meaningful er-R RNAT differentiation in review scope and complexity. ev ieIO studies). Accordingly, to facilitate interpretation we define small (≤50), medium (51–100), and Pe INTE per review in software engineering, which aligns with our definition of a ‘medium’ review (51–100 matic analysis, highlighting the need for structured data to enhance research clarity and practical AI - RO CE I JET'S A CT applications. MB AO NU 4.2 Thematic Analysis Findings AT P G EMEO In the reviewed publications, several key themes emerged regarding AI applications in project man- ENPLE 2 agement, necessary educational competences, and the challenges associated with AI integration in T, S PM. Those themes represented by a code were grouped into four main categories, as summarized TR024 AT in Table 1 from Section 2. The following graph in Figure 3 illustrates the distribution of codes found.–2 EG IC02 C5 Figure 3: Distribution of Codes in AI Project Management (PM) OM M U N ATIC ION M ANAGEMENT, W EB AND INFOR ATM ION EC T H NOL O IEG S (Source: Authors, based on primary data) The most frequent code is “AI in PM”, accounting for 25%, indicating that AI applications in project management have received the most research attention among the reviewed studies. This is fol-lowed by “Challenges” at 21% and “Technical Skills” with a slightly lower frequency of 14%. The lowest frequency is observed for “Human Need”, at just 2.6%. The next, additional figure presents the distribution of studies or case analyses based on the themes (set codes) they investigated. It is important to clarify that some studies address multiple themes si-multaneously—for example, a study may explore both human needs and challenges related to AI in project management. Therefore, in this graph (Figure 4), a single study may be assigned more than one code, which means that the total frequency of codes does not correspond exactly to the number of studies, and the cumulative percentages do not add up to exactly 100%. 83 Figure 4: Distribution of Cases in AI Project Management (PM) er TE-R Pe IN ie IO wN edAL S PrCIE ev RNAT ceo ed TIFN ing IC C ok FER : P s Bo ON R EN O CE I CTJE T'S A N OU AT P A B M EMG EN PLE 2 T, SEO TR 024 AT–2 EG IC02 C5 OM M U N ATIC ION M (Source: Created by the authors) ANAG The distribution of cases aligns with the frequency of codes, reflecting the key areas of focus in EM the reviewed studies. This indicates which topics the authors emphasized the most. The follow- EN ing section provides a descriptive interpretation of the results, categorized into the four thematic T, W groups mentioned. EB A N D 4.2.1 AI in Project Management: Expertise and Education IN FOR The findings indicate a growing emphasis on AI-related education and competency development AT grams, with none exclusively focusing on AI education within the project management domain ION M among project management professionals. However, only 8% of studies address educational pro- EC portance of structured AI training and competency-building initiatives (Obana 2024). Furthermore, H NOL T (Hossain et al. 2024; Aggrawal and Dittman 2023). Nonetheless, several studies emphasize the im- 11% of studies emphasize the essential nature of AI-related competences, particularly in areas such O as decision-making, automation, and predictive analytics (Paparić and Bodea 2024; Müller et al. G IE 2024; Merdžanović et al. 2023). The findings suggest that the current landscape of AI education is S fragmented, with inconsistencies across academic institutions, which limits the establishment of a standardized framework for AI skill development (Deshpande 2023). A global study by Müller et al. (2024) reports that more than 50% of surveyed project management professionals possess limited knowledge of AI, further underscoring the nascent stage of AI adoption in this field. With the increasing prevalence of generative AI, Deshpande (2023) advocates for educational pro-grams that balance technical expertise with interpersonal competences. Similarly, Oyekunle et al. (2024) emphasize agility, cross-functional collaboration, and data-driven decision-making as crit-ical competences in AI-driven project environments. Obana (2024) further highlights the need for a balanced approach integrating both hard and soft skills to ensure effective AI implementation in project management. These findings align with the Report on the Impact of Artificial Intelligence on Project Management, which projects significant disruptions necessitating comprehensive change management and leadership coaching (Belharet et al. 2020). 84 4.2.2 Core Requirements for AI Integration in Project Management prominent theme in 34% of reviewed studies. The core technical skills identified include data anal RN - evAT ysis and predictive analytics, Fundamentals of machine learning and artificial neural networks ieIO w Technical competences essential for successfully integrating AI in project management were a TE er -R Pe IN (ANNs), AI-driven risk assessment, and the interpretation and utilization of AI-generated reports ed NAL S Pr for decision-making. Additionally, the Integration of AI tools into project workflows is emphasized oCIE (Niederman 2021; Rathod and Sonawane 2022). ceN edTIF While project managers are not required to be IT specialists, they must possess proficiency in lev - ingIC C eraging AI technologies for strategic decision-making, resource allocation, and team leadership s Bo ON (Niederman 2021). AI facilitates productivity improvements through automation and optimization, okFER necessitating familiarity with web technologies, data processing, and refinement of AI models (Pa - : PEN R parić and Bodea 2024). Rathod and Sonawane (2022) further emphasize the role of artificial neural OCE I JE networks in predicting project-related risks, particularly within the construction sector.T'S A CT MB Beyond technical expertise, 17% of studies emphasize the importance of soft skills, including da- AO NU ta-driven decision-making, effective communication of AI-related insights, interdisciplinary collab - AT P G oration, and digital leadership (Fridgeirsson et al. 2021; Zahaib Nabeel 2024; Hossain et al. 2023; EMEO EN Diao 2023; Odeh 2023; Alshaikhi and Khayyat 2021). Critical thinking, emotional intelligence, and PLE 2 T, S adaptability are fundamental for managing AI-driven project environments (Deshpande 2023). TR02 Moreover, 5% of studies examine the indispensable role of human expertise in conjunction with 4 AT–2 AI advancements. Fridgeirsson et al. (2021) argue that leadership, stakeholder engagement, and EG IC02 team development rely on human judgment, emotional intelligence, and contextual understand- C5 OM ing. While AI enhances operational efficiency, human intervention remains critical in complex pro - M ject management scenarios (Sahadevan 2023). U N IC AT 4.2.3 AI Applications in Project Management ION AI applications in project management were examined in 54% of reviewed studies, with the most MA frequently analyzed implementations including resource optimization: AI improves scheduling and NAG resource allocation (Zahaib Nabeel 2023); Risk management: Predictive models facilitate risk iden -EM tification and mitigation (Crawford et al. 2023; Merdžanović et al. 2023); Decision-making support: EN AI-powered tools enable enhanced project planning and real-time decision-making (Fridgeirsson T, W et al. 2021; Taboada et al. 2023). EB A Additionally, AI has demonstrated significant potential in minimizing project delays and optimizing ND cost efficiency, particularly within the construction sector (Rathod and Sonawane 2022). However, INFOR despite its advantages, 23% of studies highlight key barriers to AI adoption, including high imple- mentation costs, system complexity, and limited expertise among project professionals (Sarafanov MAT et al. 2023; Buschmeyer et al. 2022). ION The level of AI adoption varies across industries, as reported in 11% of studies, with financial and tech T -EC nical constraints frequently impeding progress (Alshaikhi and Khayyat 2021; Belharet et al. 2020). AI HNOL technologies are still in the early stages of integration, with limited applications in areas such as stake-O holder management, procurement, and project communication (Hashfi and Raharjo 2023).GIES 4.2.4 Considerations and Limitations of AI in Project Management 11% of studies explored the challenges associated with AI implementation, with primary concerns including Bias in AI-generated decision-making, High costs associated with AI adoption, Regulatory and compliance challenges, and Ethical concerns related to data privacy and automation (Zahaib Nabeel 2024; Sahadevan 2023). Despite technological advancements, 35% of projects reportedly fail due to the immaturity of AI technologies (Nenni et al. 2024). Additional barriers include resistance to change within organi-zations and the substantial training requirements necessary for effective AI utilization (Engel et al. 2021; Müller et al. 2023). While AI significantly enhances project management efficiency, it does not replace human-centric skills such as leadership, stakeholder engagement, and strategic decision-making (Fridgeirsson et 85 er-R RN evAT ieIO Pe IN rather than replacing it (Sahadevan 2023). TE al. 2021). AI should, therefore, be viewed as a complementary tool that augments human expertise w 5 DISCUSSION N ed A L S The research conducted undoubtedly confirms that AI is a hot topic in research, but it is still in its Pr CIE o initial phase, with much of the research focused on qualitative analyses. Researchers are aware that ce N ed the emergence and application of AI represents a milestone after which several practices or princi-TIF ing IC C ples confirmed so far should be re-examined. Given that the topic is new and complex, differences ok FE ining the macro aspect to see the impact of AI on the totality of existing knowledge and practices. R : P s Bo O in approach and research goals can be observed. Part of the researchers’ approach involves exam-N CT T'S A It can be asserted that the complexity of the subject of AI has, in some way, shaped the current topic, M B A O such that some researchers focus their research on the question of how AI can best assist us in our N U A T P G O CE I offers in the development of a particular topic. JE R EN Meanwhile, some researchers take a micro view, studying the potential new opportunities that AI current practices and principles of work. In contrast, some researchers question whether the advent EN PLE 2 on the topic of the influence and possible imbalance of the human-centric system due to the emer-T, S EM EO of AI can or should change certain aspects. Until now, there has been the least amount of research TR gence of AI, i.e., the complete takeover of a part of human creative work by AI. This is entirely un- 02 4 derstandable because the mentioned topic represents a key and complex question that has social, AT –2 EG IC 02 humane, legal, technical, and business aspects so that answers will be sought in future research C 5 over a more extended period. OM M The research conducted confirms the above statements for the field of education, including project N management. A paper by a group of well-known researchers sparked discussions about the rise U AT of AI in project management education and training. While setting the call for the further research IC ION they indicated an illustrative list of potential aspects to be addressed: Transformative impact of AI, AI M and new technologies in Project Management learning in different contexts, Assessment and peda- A N gogics, new competences and skills of educators, ethical considerations, innovative technologies in A G education, project management learning and training in business context (Mariani et al. 2024.). Our EM EN research aligns with this framework, and the primary aim was to present findings on opportunities, T, W requirements, and challenges. EB Our results show that the topic of AI in PM has a global research presence, with overviews and qual- A N itative research dominating, mostly from secondary sources. In a way, this is expected and confirms D IN that the topic is still in the initial phase of opening and that there is a lack of more exact quantita - FOR tive research, i.e., case studies. The speed with which new research results appear confirms that M researchers believe in an essential role of AI in facilitating learning in the PM area (Konstantinou et AT ION al. 2023). The results of this research also confirm that in the thematic sense, AI is still treated as a ECH T new topic dominated by the concept of broad questioning of the topic (i.e., “AI in PM”) and associat- NOL ed challenges, with an inevitable shift towards researching the role of AI in the domain of technical skills. In contrast, topics that combine “AI & soft skills” are still poorly represented, probably because O they are incredibly complex. However, researchers are aware that the soft side of AI in PM must be G IES equally developed in parallel with the technical part of skills (Obana 2024). The results related to AI in Project Management: Expertise and Education demonstrate the synergy of opinions regarding needs and importance, while also highlighting the fact that relatively little has been done in this area (Deshpande 2023; Müller et al. 2024). Regarding core requirements for AI integration in project management, it is clear that support from AI specialists is necessary, as well as project managers understanding the possibilities, conditions, and limitations of AI use to a certain extent. Even when AI is used for problems familiar to project managers, such as resource optimiza-tion, risk analysis, or decision-making, they must first perfect a new way of thinking, an “AI-driven mindset.” Namely, it is challenging to combine the old logic of work and thinking without harmo-nizing it with AI, even if AI is viewed as just a new technology (and it is much more). Obviously, the central question for the future will be the potential gap between human-centric and AI approaches, and their coexistence in creating greater value that is realized through the process of project de-livery. The results of our research indicate that AI is in the initial phase of integration into today’s 86 formal education of project managers who will work in the future needs to be continuously aligned er-R RNAT with the development of AI. Given the magnitude of change and the rapid pace of AI development, ev ieIO the profession, which, at this moment, we cannot fully see or describe. This is precisely why the Pe INTE project management, and a dynamic of activity is emerging that foreshadows a different future for adjustments are necessary for the higher education curriculum and training throughout the process w N edA of continuous learning. It is by no means learning additional new facts, but rather the ability to de-L S PrCIE velop a different way of thinking, according to a scenario in which, in the future, AI will be “an equal o ceN member of the project team when deciding on important issues. In our opinion, project managers edTIF of the future will have to know even better all areas of PM competences to lead delivery projects ingIC C and the community. ok FER : P with the help of, or together with AI, towards creating greater value and benefit for stakeholders O s BoN R EN 6 CONCLUSION O CE I CTJE T'S A important topics for researchers and practitioners in the project management profession. The topic N OU AT P The results of our research show that the emergence and application of AI are highly current and MA B of AI is still in its initial stage of research, globally present, but primarily through initial research EMG and application results, which reveal some standard issues that project managers encounter daily, EN PLE 2 such as resource utilization optimization, risk management, and decision-making in complex situ-EO competencies, while the human-centric elements have been overlooked. It is undeniable that the AT –2 EG IC02 issue of the relationship between human intelligence and AI will be central to future development, C5 OM including the project management profession. Viewed from the community’s perspective, this issue ations. It appears that research and application are currently focused on the technical aspects and TR 024 T, S is complex and encompasses social, human, regulatory, normative, business, and other aspects, all M U of which require extensive research. N ATIC We believe that the education process would benefit from a faster and more effective approach by ION help and partnership of AI. An insight into the activities so far in this matter indicates a serious gap. ANA This is not just about a one-time, top-notch education that is the foundation, but about the system- harmonizing the curriculum and training project managers to work in new circumstances with the M EMG atic maintenance of top-notch competences through times of turbulent and rapid change. Suppose EN we do not adequately educate and re-educate future project managers for new challenges and sit- T, W uations. In that case, we can already ask ourselves who will be the project manager of the future: EB A human or AI? The solution is undoubtedly in the harmony of work that results in project deliveries, N benefiting both project stakeholders and the community in which the project is implemented.D INFOR ATM ION EC T H NOL O IEG S 87 Pe REFERENCES IN TE er 1. Aggrawal, Sakhi, and Kevin C. Dittman, ed. 2023. Preparing Engineers for the Future: Project -R R N ev AT Management for Developing Generative AI. Paper presented at 2023 Fall Mid Atlantic Conferen-ie IO ce: Meeting our students where they are and getting them where they need to be, Ewing, New w N ed A Jersey. https://doi.org/10.18260/1-2--45127. L S Pr 2. Alevizos, Vasileios, Ilias Georgousis, Akebu Simasiku, Sotiria Karypidou, and Antonis Messinis. o CIE ce N 2024. 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T https://www.researchgate.net/publication/372280735_How_Many_Papers_Should_You_Re-ECHNOL view_A_Research_Synthesis_of_Systematic_Literature_Reviews_in_Software_Engineering. 60. Zahaib Nabeel, Muhammad. 2024. AI-Enhanced Project Management Systems for Optimizing OG Resource Allocation and Risk Mitigation. Asian Journal of Multidisciplinary Research & Review 5(5): IES 53-91. https://doi.org/10.55662/AJMRR.2024.5502. 91 Pe APPENDIX I IN TE er-R R Category Code Relevant Authors Summary Explanation N ev AT ie AI in PM Educational Hossain et al. (2024), Parekh et al. (2024), Engel These authors emphasize the IO w N Expertise and Programs et al. (2023), Oyekunle et al. (2024), Aggrawal need for education and the devel-ed A L S Education and Dittman (2023) opment of educational programs Pr to prepare professionals for work-o CIE ce N ing with AI technologies. ed TIF AI in PM AI Competences Paparić and Bodea (2024), Obana (2024), Emphasizes the need to develop ing IC C Expertise and Sahadevan (2023), Belharet et al. (2020), Desh-AI competences among project s Bo O N Education pande (2023), Oyekunle et al. (2024), Mülleret managers. FE ok al. (2024), Merdžanović et al. (2023) R : P EN R Requirements Technical Skills Vărzaru (2022), Fridgeirsson et al. (2021), Indicate the technical skills O CE I for AI in PM Zahaib Nabeel (2024), Hossain et al. (2024), needed for AI tools in project JE T'S A CT Diao (2024), Odeh (2023), Alshaikhi & Khayyat management. M (2021), Niederman (2021), Lakshminarasimham B A O N (2024), Paparić and Bodea (2024), Sahadevan U A T P G (2023), Davahli (2020), Sarwar and Rahman EM EO (2024), Wachnik (2022), Deshpande (2023), EN PL Jayaram et al. (2024), Joshi (2024), Rathod and E 2 T, S Sonawane (2022), Bahi et al. (2024), Crawford et al. (2023), Oyekunle et al. (2024), Merdžano-TR 02 4 AT vić et al. (2023), Aggrawal & Dittman (2023) –2 EG Requirements Soft Skills Fridgeirsson et al. (2021), Zahaib Nabeel (2024), Explores the soft skills required for IC 02 C 5 for AI in PM Hossain et al. (2024), Diao (2024), Odeh (2023), AI in PM, including communication OM Alshaikhi & Khayyat (2021), Paparić and Bodea and leadership. M (2024), Alevizos et al. (2024), Deshpande U N (2023), Oyekunle et al. (2024), Aggrawal and IC Dittman (2023) AT ION Requirements Human Need Fridgeirsson et al. (2021), Alshaikhi and Khayyat Examines human needs and per- ANA M for AI in PM (2021), Sahadevan (2023) ceptions regarding AI acceptance. G AI in PM Hashfi and Raharjo (2023), Fridgeirsson et al. project management, including EM Application of AI in PM Holzmann et al. (2022), Taboada et al. (2023), Explores the application of AI in EN (2021), Auth et al. (2021), Zahaib Nabeel (2024), resource optimization, risk man- T, W Hossain et al. (2024), Parekh et al. (2024), agement, predictive analytics, and N (2024), Obana (2024), Hofmann et al. (2020), D Sahadevan (2023), Čančer et al. (2023), Belharet IN et al. (2020), Lai et al. (2024), Sarwar and Rah-FOR man (2024), Kiani (2024), Alevizos et al. (2024), EB Lakshminarasimham (2024), Paparić and Bodea A Diao (2024), Alshaikhi and Khayyat (2021), automation. AT al. (2023), Vegar and Mijac (2024), Jayaram et al. ION M Nenni et al. (2024), Engel et al. (2021), Shang et (2024), Rathod and Sonawane (2022), Bahi et EC T al. (2024), Karamthulla et al. (2024a), Crawford H et al. (2023), Merdžanović et al. (2023), Müller NOL et al. (2024), Aggrawal & Dittman (2023) O Application of Adaptation Vărzaru (2022), Parekh & Mitchell (2024), Alshai- Explores the process of AI adop-G AI in PM IE khi & Khayyat (2021), Skinner (2021), Belharet tion in project management. S et al. (2020), Felicetti et al. (2024), Sarwar and Rahman (2024), Davahli (2020), Engel et al. (2021), Wachnik (2022), Sarafanov et al. (2023), Shang et al. (2023), Bahi et al. (2024), Buschmeyer et al. (2022), Čančer et al. (2023), Karamthulla et al. (2024a) Application of Integrating AI Hashfi and Raharjo (2023), Parekh et al. (2024), Explores AI integration in PM deci-AI in PM in PM Alshaikhi and Khayyat (2021), Mahmood et al. sion-making and AI tools. (2023), Joshi (2024), Auth et al. (2021), Najdawi and Shaheen (2021), Merdžanović et al. (2023) Considerations Limitations of AI Zahaib Nabeel (2024), Parekh et al. (2024), Als- Indicate the limitations and of AI in PM haikhi an Khayyat (2021), Alevizos et al. (2024), challenges of AI in project man- Wachnik (2022), Müller et al. (2024) agement. 92 Considerations Challenges Vărzaru (2022), Hashfi and Raharjo (2023), Indicate AI challenges, including Pe IN of AI in PM Zahaib Nabeel (2024), Hossain et al. (2024), biases, technical, ethical, and TE er Parekh et al. (2024), Diao (2024), Alshaikhi and organizational issues.-RRN Khayyat (2021), Lakshminarasimham (2024), evAT Paparić and Bodea (2024), Sahadevan (2023), ieIO wN Davahli (2020), Belharet et al. (2020), Pereira edA et al. (2024), Alevizos et al. (2024), Engel et L S Pr al. (2021), Wachnik (2022), Sarafanov et al. oCIE (2023), Shang et al. (2023), Joshi (2024), Rathod ceN ed and Sonawane (2022), Bahi et al. (2024), TIF ing Karamthulla et al. (2024a), Čančer et al. (2023), IC C s Bo Karamthulla et al. (2024b), Crawford et al. ON (2023), Merdžanović et al. (2023), Müller et al. okFE (2024), Aggrawal & Dittman (2023)R : PEN R OCE I JET'S A CT MB AO NU AT P G EMEO ENPLE 2 T, S TR024 AT–2 EG IC02 C5 OM M U N ATIC ION M ANAGEMENT, W EB AND INFOR ATM ION EC T H NOL O IEG S 93 STRATEGIC COMMUNICATION MANAGEMENT 2024 HOW DOES GEN Z PERCEIVE SUSTAINABLE w N edAL S Pr o FASHION: ATTITUDES OF CROATIAN STUDENTS CIE ceN edTIF TOWARDS THE GREEN H&M CAMPAIGN 1 ingIC C s BoONFE ok Ema Petrušić, Digital Marketing SpecialistR : PEN CROZ, Croatia Published scientific conference contribution Pe INTE 1.08 Objavljeni znanstveni prispevek na konferenci er-R RN evAT ieIO O CE I R ABSTRACT EO ENPLE 2 T, S The phrase ˝sustainable fashion˝ is increasingly heard in the media and among consumers. A TR02 literature review indicates that environmental awareness is greatly influenced by the concept 4 AT–2 of greenwashing, which plays a central role in the communication strategies of numerous. In EG IC02 the theoretical part, the concept of fast fashion and the sustainability question are analysed from C5 OM social, economic, environmental, and ethical perspectives. Furthermore, the paper provides a M Zagreb School of Business, Croatia B AO NU AT P G EM Tanja Grmuša, JE PhD, Assistant Professor T'S A CT M review of previous research on fast fashion in the Croatian market, which served as a stimulus UNIC to this research. The second part of the paper presents a study aimed at examining how students AT in Croatia perceive the green campaign of one of the world’s leading fast fashion brands, such as ION H&M. The research was conducted from October 10, 2022 to October 16, 2022, through an online M questionnaire with a sample of 162 students from three Croatian universities in Zagreb, Rijeka, ANA and Osijek. The research results show that students in Croatia are aware of the impact of fast GEM fashion on society as a whole and the communities to which they belong. On the other hand, the EN results of the conducted research indicate that the green campaign does not significantly affect T, W their consumer habits and behaviour.EB A Keywords: Sustainable fashion, Environmental awareness, Greenwashing, Students, H&M cam-ND paign INFOR ATM ION EC T H NOL O IEG S 1 This paper is based on the research conducted by Ema Petrušić as a part of her final thesis at the graduate uni- versity study program in Communication Studies. The thesis titled Perception of the Impact of the Green H&M Campaign on Students in Croatia was made under the mentorship of Tanja Grmuša, PhD, Assistant Professor, and defended at the Faculty of Croatian Studies in September 2023. 99 Pe 1 INTRODUCTION IN TE er-R R Ample attention was paid to the problems of the fast fashion industry back in 2013. A tragedy oc-N ev AT curred in the Rana Plaza building collapse in which 1,134 people lost their lives and nearly 2,600 ie IO w were injured (Rana Plaza, n.d.). The eight-story building was improperly used as a clothing manu-N ed A L S facturing centre. Biočina (2016, 59–60) points out that, among other manufacturers, Benetton, Man- Pr go, Primark and Walmart produced their goods in the building, and such factories in Bangladesh can o CIE ce N also find more luxurious brands such as Armani, Ralph Lauren, Michael Kors or Hugo Boss, research ed TIF from 2020. The year shows how the general working conditions have improved since then: the min-ing IC C imum wage of workers has increased, but all other conditions have not been fully met (Bossavie et s Bo O N al. 2020). This event serves as a powerful reminder of the hidden costs of fast fashion and the need ok FE R : P for greater transparency and accountability in the industry. But it was also the inspiration for this EN R O CE I research paper that explored the habits of young consumers in Croatia and their attitudes about fast JE T'S A fashion on the example of the H&M brand. This research paper is based on an MA thesis written by CT M B the same author. A O N U A T P G EM EO 2 FAST FASHION AND SUSTAINABILITY: BETWEEN PROFIT DEMANDS AND ET-EN PL E 2 HICAL DILEMMAS T, S TR 02 4 Fast fashion is an expression that has been increasingly mentioned in the media in recent years as AT –2 a considerable problem on a global scale. Stephanie Buck believes that the very beginning of the EG IC 02 fast fashion trend began in the sixties of the last century. Specifically, 1966 was the year in which C 5 OM disposable dresses in America experienced great success among consumers thanks to a marketing M campaign, Scott Paper Company wanted to increase sales of its new napkins and toilet paper, which U N IC were manufactured from a combination of paper napkins and viscous fibres (Buck 2017). More as a AT joke than a serious campaign, the women were offered a choice of two cuts of garments made of ION that material at a cheap price of $1,25 (Buck 2017). What was originally conceived as a mockery be- M came a huge success when they sold 500,000 disposable dresses in eight months, according to Buck A N A (2017). It did not take much until other companies jumped on the profit wagon and started produc - G EM ing a wide range of disposable clothing made of cheap materials. Until the middle of the twenti- EN eth century, fashion was more focused on practicality, unlike today, but most importantly, fashion T, W as an industry knew four seasons: spring, summer, autumn, and winter. In contrast to fast fashion, EB there is what could be called slow fashion – it is sustainable and focuses on ethical production and A N consumption by consumers and producers to reduce production and the negative influences that are D IN more related to it, and puts quality before quantity in the forefront, but in the literature sustainable FOR fashion is often called an oxymoron because the idea of sustainability is contradictory to the ethos of M fashion, which is constantly evolving and new trends are coming (Mandarić et al. 2022). AT ION 2.1 The impact of fast fashion on society, economic movements and the individual T EC H NOL Šimunić (2021, 2) points out several negative impacts of fast fashion: contribution to the climate O crisis, harmful chemicals, an increasing amount of textile waste, consumption of water and non-re- G newable energy and raw materials, and space occupancy. She states that every second a quantity of IE S one full truck of discarded clothing is being burnt, and washing clothes made of artificial materials produces 500,000 tons of microfiber that end up in the ocean (Mandarić et al. 2022). With the constant development of society, more and more people moved from agricultural occu-pations to factory work. Cotton production was efficient and cheap, this allowed more people to participate in trade, thus increasing production, also creating a working class that participated in the economy. Biočina (2016, 39) believes that industrialization and capitalism developed on the back of women who were exploited as labour in industries that were on average paid significantly less. Radner Linden (2016, 9) states in his paper that this may be one of the reasons why cotton is still predominantly present in the production of clothing and mentions the first problem of fast fashion – which is that the production of cotton started because of slavery. Thus, mass production in America was extremely cheap. It began to mass export cotton as a raw material - more precisely, before the beginning of the Civil War, 61% of exports out of state were made of cotton (Radner Linden 2016, 10). The paper fashion industry in the context of green industry states that: “the fashion industry 100 is described by competitiveness on the market due to the increased supply of different clothing” Pe IN (Šimunić 2021, 7). By moving production to countries where production is extremely cheap due to TE er-RR poor conditions and an underskilled and underpaid workforce, it created the opportunity for fast N evAT fashion to flourish, as young people in Europe and America were able to follow fashion trends for ieIO w the first time at a low price (Radner Linden 2016, 3-5). Linden notes that there is another problem of N edAL S fast fashion, besides exploitation, which is pollution and waste. Before that, manufacturers had to PrCIE o order a certain amount of goods, which they had to put on seasonal discounts and store them, if they ceN failed to sell them during the intended season. With the advent of brands such as Zara, Mango, C&A, edTIF ingIC C H&M, New Yorker, Stradivarius and many others, the whole process of forecasting, designing, mak- s BoO ing and selling is drastically accelerated to the point that new collections are produced almost every NFE ok week. “Take it now or regret it later” is a principle that is stated in the description of consumers’ R : PEN attitude towards fast fashion because prices are so affordable that they often do not need discounts, R OCE I and trends rotate so quickly that, if this opportunity is not used, on the next purchase the same item JET'S A may be “out of style”, which especially affects the younger population (Brstilo Lovrić et al. 2021). CT MB Grgurinović (2021) for faktograf.hr states that 85 % of textiles produced after 2015, were thrown out AO NU every year. This industry used 79 billion cubic metres of water in a year, and clothing and footwear AT P G EM production accounted for 10% of global greenhouse gas emissions. EO ENPL The point is that environmental pollution does not only occur in the production and use of harmful E 2 T, S chemicals, pollution also occurs when transporting goods. Some of the brands that have a bad rep- TR024 utation when it comes to production are Shein and ASOS – which are also popular in Croatia, where AT–2 EG they publish from 500 to 5000 new pieces of clothing on their website daily (Grgurinović 2021). In IC02 C5 her article Grgurinović (2021) quotes a sustainable fashion lover Dunja Jovanović who points out OM that consumerism has become a way of life today – shopping centres are our place for socialising MU and relaxation, and research shows that today we are buying 60% more than 20 years ago, and NIC the quality of clothing is decreasing and there are fewer natural and degradable materials. When AT it comes to Croatia, Perković (2021, 11) states that young consumers (Generation Z) have become ION aware of the bad influences of the fashion industry on our environment and that fashion serves to MA show them their own identity.NAG The third problem is creating an image of oneself – that is, the influence of fashion on the perception EMEN of a young individual. Often, young people are the group most involved in spending when it comes to T, W fast fashion, and it is said that this is probably due to postmodernist consumer conflicts. Young people EB create their own identity and try to build an individualistic image of themselves as an individual A through consumerism, while at the same time, they want to fit in with their peers, following fashion ND trends (Brstilo Lovrić et al. 2021). In addition to influencing consumers and their pockets, the fashion INFOR industry greatly influences young people’s perception of themselves and their bodies, which is best seen by starving models to fit into size 0 clothing (Šimunić 2021, 9-14). MAT Greenwashing has been singled out as a separate fast fashion issue because within that concept ION there are many more problems. Greenwashing is a marketing technique used by companies to TEC make their products or services look more environmentally friendly than they are. The term was HNOL first coined and used by environmentalist Jay Westerveld, who used it to describe the hotel industry’s O practice of encouraging guests to reuse towels to save water, ignoring larger environmental issues. GIE In the late 1990s, the word officially entered the Oxford English Dictionary (Oxford English Diction -S ary) (Watson 2016). Greenwashing can take many forms, such as using vague or misleading terms such as “natural” or “en-vironmentally friendly”, making unverifiable claims about environmental benefits, or emphasizing a small environmental aspect of a product while ignoring its greater environmental impact. The Prob-lem with greenwashing is that it can mislead consumers into believing they are making environmen-tally responsible decisions, even though in reality, they are not. This can lead to a false sense of security and a lack of motivation to make significant changes to reduce their environmental impact. 2.2 Overview of the current research on fast fashion in the Croatian market Mandarić at al. (2022) in their paper address that the combination of cheap goods and constantly changing trends has created a culture of impulsive shopping where consumers need to point out 101 er-R R the Croatian market was conducted through the online Google form in January 2021. Respondents N ev AT were selected by the snowball method via email, social media, and personal contacts, as the survey ie IO Pe IN healthy environment. Quantitative research on the consumption of sustainable consumer fashion in TE the difference between the consequences of fast fashion and altruistic interests in maintaining a w N was not publicly available. The target group was Croats who work and have payment power, and ed A L S Pr the questionnaire was based on a previous survey by Shen et al. in 2013. and 2019 Ceylan research CIE o paper (Mandarić et al. 2022). In short, the conclusion of the research is in line with previous research ce N ed on foreign markets – consumers do not make purchasing decisions based on their environmental TIF ing IC C impact, but the decision is more influenced by other factors. However, consumer awareness has in- ok FE some steps to make their business model more partially sustainable. Some of them began supply-R : P s Bo O fluenced some changes for the better, as many major fast fashion manufacturers have introduced N CT T'S A M questionnaire that examined views on the sustainable business of brands. As in the previously men-B A O tioned research, Mandarić (2021, 53-54) found that her respondents also agree with the idea of N U A T P G O CE I Another study conducted on a similar topic in Croatia is from 2021. 263 respondents took part in a JE R EN ing goods by local producers to reduce their carbon footprint (Omazić et al. 2017). EM EO tice, when deciding to buy fast fashion and sustainable fashion, other factors such as price prevail. EN consuming sustainable fashion, which is confirmed by world research, but when it comes to prac-T, S PLE 2 TR 024 3 H&M RETAIL CHAIN-SUSTAINABILITY AT THE HEART OF COMMUNICATION AT –2 EG AND MARKETING STRATEGY IC 02 C 5 OM The Swedish retail chain H&M belongs to a larger conglomerate described on its official website as M a “family of brands and companies”. It has over 150,000 employees in 4,200 stores across 72 coun- U tries. They state their core values as team uniqueness, faith in people, entrepreneurship, continuous N IC improvement, awareness, directness, and simplicity. On their website, they immediately highlight AT ION important figures. They mention their goal for 2030: to produce clothes exclusively from recycled AN recycled or sustainable sources (Research H&M Group, n.d.). A M materials, noting that they have already started with their cotton, which is entirely sourced from EMG Under the “sustainability” section on its website, H&M highlights the environmental and community EN impact of fashion and reflects on its role in the entire sustainability chain. They claim to be the first T, W in the world to have a recycling device called “Looop” installed in their Stockholm store. In addition, EB they are striving to maintain sustainability through greater transparency. In 2019, they launched an A N app where customers can check where products are made, with additional information. They state D that, although they do not own the factories where they manufacture clothes, they aim to create a IN FOR safe environment for everyone involved in the production process. They point out the “Garment Col - ATM lecting program”, which is also implemented in Croatia, and that it is the largest initiative of its kind ION in the world, introduced globally in 2013 (Dress the Whole World & help ensure the sustainability ECH T of fashion, n.d.). NOL 4 RESEARCH METHODOLOGY O IEG S The subject of this quantitative research is a sample of students from three Croatian universities. The survey used a non-probabilistic sample and was conducted from October 10, 2022, to October 16, 2022, through online forms found on social networks (Student Facebook and WhatsApp groups). A total of 162 students from the Universities of Zagreb, Osijek, and Rijeka responded to an anonymous survey in four parts. The survey started with general data and moved towards specific data relevant to this research. 4.1 Objective, research questions and hypotheses The main goal of the paper is to explore how important ecology is to the young population of Croa-tia (students) when it comes to fashion and production. The paper will explore the following issues: 1. What impact did the H&M brand campaign have on students in Croatia? 2. How did the campaign impact students’ spending habits? 3. How did the campaign affect students’ trust in the brand? 102 2. What is the difference in student attitudes regarding their field of study and gender? er TE -RRN evAT 3. How important is it to students that the products they consume are environmentally and ethically 1. What is the student’s familiarity with the concepts of “ecological and ethical production”? Pe IN Auxiliary issues in the work are: Based on the questions, the following hypotheses of the work are posed: produced? ie IO wN edAL S Pr oCIE ceN 1. Given the brand’s attempt to position itself as a brand that recycles and belongs to the “Green edTIF Wave”, students believe that the H&M Green campaign is true and effective. ingIC C 3. This campaign has boosted students’ confidence in the brand itself. EN R OCE I JE 4.2 Method and sampleT'S A CT MB A 2. The campaign did not increase the number of purchases of this brand among the student popula- s Bo ON tion of Croatia. ok FER : P The survey was conducted anonymously with 162 respondents, of whom 112 were women (69.1%) O NU AT P and 50 were men (30.9%). The largest number of respondents were between the ages of 24 and 26 G EMEO – 59 (36.4%) and between 18 and 20 – 58 (35.8%). Furthermore, 37 respondents (22.8%) were be- ENPL tween 21 and 23 years old, and 8 (4.9%) were between 26 and 30 years old. No survey respondents E 2 T, S were over 30 years old at the time the survey was conducted. TR024 The majority of respondents belonged to the University of Zagreb. A total of 106 (64.5%) studied in AT–2 EG IC02 Zagreb, followed by the University of Osijek with 44 (27.2%) respondents, and 12 (7.4%) were from C5 the University of Rijeka. Almost half of the respondents were from the field of Social Sciences, name - OM ly 77 (47.5%). They were followed by engineering students with 28 members (17.3%). Biomedicine MU and health were studied by 20 respondents (13%), the arts by 17 (10.5%), humanities by 10 (6.2%), NIC natural sciences by 7 (4.3%), and biotechnical sciences by 2 (1.2%). ATION More than half of the respondents, 125 (77.2%), said they were familiar with the term ‘fast fashion,’ M which the survey briefly described as cheap clothing produced quickly in response to high demand for AN fashion trends by mass retailers. The majority of respondents stated that they buy fast fashion prod-AG ucts, more precisely – 75 (46.3%) buy these products but try to control the number of purchased items, EMEN 42 (25.9%) also buy them, while as many as 45 (27.8%) do not buy them at all. Only 2 respondents had T, W never heard of this brand nor shopped at their stores, while the rest (98.8%) were aware of the H&M EB brand and purchased their products. More than half of the respondents, 94 (58%), had heard of the AN green H&M campaign, while the remaining 68 (42%) had not heard of it before completing the survey.D IN Respondents to the survey answered questions on a Likert scale, where for each statement they FOR could choose one of the offered options on a scale from 1 to 5, with 1 signifying complete disagree -M ment and 5 signifying complete agreement with the statement. The main criterion for participation ATION in the survey was that the respondents were students at one of the three listed universities. The T results were processed partly online with the help of analytics provided by Google Forms, as the ECH survey was compiled in this program, and partly in SPSS (Statistical Package for the Social Sciences), NOL a computer program for statistical data analysis. OGIE 4.3 Showing the results of the researchS More than 70 % of respondents said they fully or partially consider H&M to be a fast fashion brand, with over 70 % of the total number of women in the survey and 40 % of the total number of men agreeing. Regarding attitudes towards the field of study, students of natural and technical sciences showed the most agreement with the statement. Over 60 % of respondents partially or completely considered this campaign, along with their recycling program, a good step for the brand towards a sustainable way of doing business – women and men voted equally on this issue. Interestingly, almost all groups of students were inclined to this response, while students in the arts were mostly restrained. Over 50 % believed partially or completely that the program was true and effective; again, the majority who considered it were women, with over 50% of the total choosing this answer, while 38 % of men felt the same. This belief is mostly held by students of biomedicine and health, social sciences, humani-ties, and natural sciences, while students of arts and technical sciences predominantly gave neutral answers. When asked if they had ever heard of the green H&M campaign, 58% of students answered 103 er-R R their final product. The current survey found that over 58% of people believe partially or completely N ev AT in the truthfulness and effectiveness of this program, but the downside is that a large percentage of ie IO Pe IN before completing the survey. Over 60% of students are unfamiliar with the brand’s activities beyond TE yes, so it is important to consider the large number of people who had not heard of this campaign w N respondents were not aware of the campaign before completing the survey. Considering that this is ed A L S Pr the number of people who claim to have seen that campaign, we consider this hypothesis to be con-CIE o firmed. Given that many respondents were not aware of the brand’s green campaign before complet-ce N ed ing the survey, additional research is necessary with a group of people familiar with the campaign to TIF ing IC C determine with certainty whether the students believe the campaign is true and effective. s Bo ON Table 1: Responses to the 30th survey question based on the field of study. ok FE R : P EN R Field of Study I believe that this program is truthfull and effective. Total number of O CE I responses JE T'S A 1 2 3 4 5 CT M B Biomedicine and Health 1 0 6 8 6 21 A O N U A T P Biotechnical Sciences 0 1 0 0 1 2 G EM EO Social Sciences 5 10 25 24 13 77 EN PL E 2 T, S Humanities 0 1 2 2 5 10 TR 02 4 Natural Sciences 0 0 2 4 1 7 AT –2 EG Technical Science 4 3 11 6 4 28 IC 02 C 5 OM Artistic Field 4 3 6 2 2 17 M Total number of responses 14 18 52 46 32 162 U N IC AT Less than 15 % of respondents said that because of the green H&M campaign they buy their products ION more often, while over 50 % said that the campaign did not affect the frequency of purchases with M that brand, with the opposite opinion mostly held by students of natural sciences. More than 60% of A N A respondents say that they do not buy the H&M brand more often than other brands, with only about G EM 15% of respondents preferring this brand, where students of natural sciences stand out, among whom EN no one considers it. Even the brands’ attempt to motivate customers to bring in old recycling goods, T, W where they would receive discount coupons in return, did not significantly affect the student popula-EB A tion, as just under 30 % said that these coupons made them more likely to buy at H&M stores. On the N D other hand, over 50% did not find it motivating enough to go to that store. Students also claim that IN they do not buy items from an eco-collection more often compared to a regular collection – only less FOR than 20% of respondents claimed to have such a practice, while over 50% do not make a difference. M The proportion of students who buy exclusive items that are labelled as part of the eco collection is AT ION even lower – there are only over 10% of them. Because of these results, we believe that the second hy-EC T pothesis has been confirmed, just as in previous papers, where it states that although there is a certain H level of awareness of sustainability, it does not play the most important role in purchasing. NOL IES Field of Study O Table 2: Responses to the 32nd survey question based on the field of study. G Due to that campaign, I shop more frequently at H&M stores. Total number of responses 1 2 3 4 5 Biomedicine and Health 5 6 3 4 3 21 Biotechnical Sciences 1 1 0 0 0 2 Social Sciences 26 20 24 3 4 77 Humanities 2 3 3 0 2 10 Natural Sciences 1 1 3 1 1 7 Technical Science 9 7 8 4 0 28 Artistic Field 9 3 5 0 0 17 Total number of responses 53 41 46 12 10 162 104 ing questions such as: “I consider clothing made of recycled materials as good as clothing made of er-R RN evAT new materials,” and “I want more environmentally friendly products from this brand,” we see that ieIO successful for this brand, and at least the technical students agree with this statement. From answer- Pe INTE Over 50% of respondents in the survey believe partially or completely that the green campaign was there is an interest in students in environmentally friendly fashion solutions, because in both cases w N edA over 50 % of respondents chose the option according to which they fully or partially agree with the L S PrCIE above statements. When it comes to the general frequency of buying this brand, the answers are o ceN quite neutral and evenly distributed by categories: for, against, and in-between. Less than 20% of edTIF people claim to follow some brand activities outside of their merchandise or follow them on so- ingIC C business, we would say that the third hypothesis is confirmed. In this question, students of arts and : P EN R OCE I JE engineering, who have a large number of neutral or negative answers, stand out again.T'S A CT MB A advertisements, 30% of them believe that the products of this brand are of quality, and over 70% of ok FER respondents claim that they consider this campaign a good step towards a sustainable way of doing cial media. Given that over 40% of respondents believe that this brand has quality campaigns and s Bo ON Table 3: Responses to the 37th survey question based on the field of study. N OU AT P G EMEO Field of Study I want more environmentally friendly products from this brand. Total number of EN responsesPLE 2 1 2 3 4 5 T, S TR02 Biomedicine and Health 0 1 7 5 8 214 AT–2 Biotechnical Sciences 0 1 1 0 0 2 EG IC02 C5 Social Sciences 6 4 28 14 25 77 OM Humanities M 0 1 2 3 4 10UN Natural Sciences 0 0 0 4 3 7ICAT Technical Science 3 2 10 5 8 28ION From the confirmed hypotheses, we can see how the green campaign of the H&M brand has impact Artistic Field M 0 0 5 4 8 17AN Total number of responses 9 9 53 35 56 162AGEMEN-T, W ed students by improving the brand’s image in their eyes, but it has not significantly influenced their EB consumer habits. This is not surprising, as similar results have been obtained in previous surveys AN across different markets, where consumer awareness has consistently been proven, but without a D IN corresponding change in consumer habits.FOR 5 CONCLUSION MATION perception of H&M’s Green campaign, which aims to position the brand as a part of the “Green Wave” HNOL The research confirms three hypotheses. The first hypothesis focuses on the student population’s TEC and a proponent of recycling. A majority of the respondents view H&M as a fast fashion brand. Addi-tionally, they believe the brand’s green campaign and recycling program are positive steps toward O IEG sustainable business practices. However, the fact that a significant number of respondents were un- S aware of this campaign before the survey suggests a need for further research among those already familiar with the campaign to assess its credibility and effectiveness. The second hypothesis examines the green campaign’s influence on students’ purchasing frequency with H&M. The survey findings indicate that less than 15% of respondents have increased their pur-chases from the brand due to the green campaign. Furthermore, the majority reported that the cam-paign did not alter the frequency of their purchases. The respondents also exhibited limited interest in the discount coupons offered for recycling old clothing, implying that sustainability awareness is not a primary factor in their purchasing decisions. The third hypothesis pertains to the student’s overall perception of the brand. Most respondents perceive the green campaign as successful for H&M. They also show a keen interest in environmentally friendly products and generally regard the brand’s campaigns and advertisements as high quality. These out-comes point to an enhanced perception of the brand among students following the green campaign. 105 Pe REFERENCES IN TE er 1. Biočina, Ivana. 2016. Tiranija mode: ukrašavanje kao potraga za identitetom. Zagreb: Planetopija.-R R N ev AT 2. Bossavie, Laurent, Yoonyoung Cho, and Rachel Heath. 2020. The effects of international scrutiny ie IO w on manufacturing workers: Evidence from the Rana Plaza collapse in Bangladesh. Journal of De-N ed A L S velopment Economics 163(2020): 103107. 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Mandarić, Doroteja, Anica Hunjet, and Dijana Vuković 2022. The impact of fashion brand sustain-4 AT ability on consumer purchasing decisions. Journal of Risk and Financial Management 15(4): 176. –2 EG IC 02 Available at: https://www.mdpi.com/1911-8074/15/4/176 (May 10, 2023). C 5 OM 8. Mandarić, Doroteja. 2021. Održiva moda: Utjecaj održivog poslovanja modnih marki na odluku M potrošača pri kupnji odjevnih proizvoda. Graduate thesis. Varaždin: University North. University U N centre Varaždin. Department of Business Economics. Available at: https://zir.nsk.hr/islandora/ IC object/unin%3A3880/datastream/PDF/view (May 29, 2023). AT ION 9. Odjeni čitav svijet & pomozi osigurati održivost mode. (n.d.) Available at: https://career. M hm.com/hr-hr/sustainability/ (July 26, 2022). A N A 10. Omazić, Mislav Ante, Alica Grilec, and Irena Šabarić. 2017. Razvoj koncepta održivog razvo - G EM ja u modnoj industriji–pregled literature. In Zbornik Ekonomskog fakulteta u Zagrebu ed. Anita EN Pavković 15(2): 165-177. Available at: https://hrcak.srce.hr/en/191085 (May 29, 2023). T, W 11. Perković, Maria. 2021. Socijalizacija u maloprodaji brze mode. Undergraduate thesis. University EB A of Zagreb. Faculty of Economics and Business. Department of Trade and International Business. N D Available at: https://zir.nsk.hr/islandora/object/efzg:7923 (11 May 2023). IN 12. Rana Plaza. (n.d.) cleanclothes.org. Available at: https://cleanclothes.org/campaigns/past/ra- FOR na-plaza (August 21, 2022). M AT 13. Šimunić, Ana. Modna industrija u kontekstu zelene industrije. 2021. Graduate thesis. Zagreb: ION University of Zagreb. Faculty of Economics and Business. Available at: https://zir.nsk.hr/islando - T ra/object/efzg:6961 (May 10, 2023). EC H NOL 14. Watson, Bruce. 2016. The troubling evolution of corporate greenwashing. TheGuardian.com. O Available at: https://www.theguardian.com/sustainable-business/2016/aug/20/greenwash- IEG ing-environmentalism-lies-companies (May 1, 2023). S AUTHOR BIOGRAPHIES Ema Petrušić is a digital marketing specialist at CROZ, holding a master’s in communication and me-dia studies at the Faculty of Croatian Studies at the University of Zagreb. Her interests are the impact of fast fashion on ecology and the nuances of slow fashion in the industry. Tanja Grmuša is an assistant professor and head of the Marketing and Communication Department at the Zagreb School of Business. She also teaches at the Faculty of Croatian Studies at the University of Zagreb. Her scientific interests are communication studies, intercultural communication, business communication, media management, journalistic practices and mass media effects. 106 THE INFLUENCE OF DIGITAL PLATFORMS w N edAL S Pr o ON THE PERCEPTION OF THE QUALITY OF CIE ceN edTIF INTERNAL COMMUNICATION IN A NON-PROFIT ingIC C ORGANIZATION: THE PERSPECTIVE OF TEAM s BoON okFE MEMBERS AND LEADERS Published scientific conference contribution Pe INTE 1.08 Objavljeni znanstveni prispevek na konferenci er-R RN evAT ieIO Rebeka Radovanović, 1 R : PEN R OCE I JET'S A CT MA in Communication Science MB AO Digital Marketing Specialist at Schneider Electric NU AT P G Tanja Grmuša, PhD, Assistant Professor EMEO Zagreb School of Business, Croatia ENPLE 2 T, S TR024 ABSTRACT AT–2 EG IC02 Effective internal communication is integral to the success of any organization, prompting a C5 OM growing emphasis on measurement and researching its effectiveness. This study, conducted in M 2023, delves into the perception of internal communication quality within the non-profit stu - U N IC dent organization FSB Racing Team. Grounded in theoretical frameworks and previous research AT on internal communication, conducted research uses a mixed methods approach, utilizing both ION quantitative survey on a sample of 48 participants and qualitative in-depth interviews on a sam - M ple of three respondents. The primary objectives were to assess how members of the FSB Racing ANA Team perceive the quality of internal communication and to examine the dynamics of commu -GEM nication within the organization. The findings reveal that, despite some shortcomings, internal EN communication is generally perceived as satisfactory by members. The study highlights the Mi-T, W crosoft Teams online platform as a valuable tool, facilitating more efficient information flow and EB organized storage of relevant reports for knowledge transfer. AND Keywords: Non-profit organization, Internal communication, Satisfaction with communication, IN Organizational culture, Online platform. FOR ATM ION EC T H NOL O IEG S 1 This paper is based on the research conducted by Rebeka Radovanović as a part of her final thesis at the graduate university study program in Communication Studies. The thesis titled ,,Perception of the quality of internal communication on the example of the FSB Racing Team“ was made under the mentorship of Tanja Grmuša, PhD, Assistant Professor, and defended at the Faculty of Croatian Studies in September 2023. 107 Pe 1 INTRODUCTION IN TE er-R R In accordance with the definitions of various authors, communication is the process of exchanging N ev AT information, and its significance manifests in all segments of life (Fox 2001, 13). Within the organi-ie IO w zational context, effective communication is a pivotal factor, particularly for successful business out-N ed A L S comes. Research shows that high-quality internal communication positively influences employee Pr motivation and productivity, while on the other hand, inadequate communication may develop dis-o CIE ce N satisfaction, frustration, and organizational failure (Tkalac Verčič et al. 2009, 176). In light of these ed TIF considerations, the objective of this study was to assess the perception of internal communication ing IC C quality among members of the s Bo O FSB Racing Team and explore the communication practices within N the organization. Employing a mixed-methods approach, the research encompassed survey ques ok-FE R : P tionnaires and in-depth interviews with key individuals occupying leadership roles within the team. EN R O CE I The success of any organization, including the FSB Racing Team , lies in effective internal commu-JE T'S A CT nication. Through an examination of members’ perspectives and an evaluation of communication M B A practices, this paper provides an analysis of communication dynamics within the team. The Microsoft O N U A T P Teams online platform emerged as the most important communication channel, which displayed a G EM positive influence on internal communication and facilitating the organization of information and EO EN PL data. The findings of this research can serve as benchmarks for further investigations within the E 2 T, S team and may apply to other organizations. Moreover, these results provide a basis for the devel-TR 02 4 opment and implementation of targeted communication strategies that encourage cooperation, AT –2 EG motivation, and productivity within the FSB Racing Team. IC 02 C 5 OM 2 THEORETICAL FRAMEWORK AND OVERVIEW OF PREVIOUS RESEARCH M U N IC Communication, as a process of information exchange, is a fundamental activity of managing organ-AT izations. As asserted by Clampitt and Downs, “the ramifications of quality internal communication ION extend positively towards enhanced productivity, diminished absenteeism, heightened innovation, M decreased incidence of strikes, improved product and service quality, augmented reputation, and A N A G curtailed business costs” (Sušanj Šulentić 2014, 61). Recognizing the pivotal role of internal com-EM munication in organizational success, numerous organizations initiated the evaluation of commu-EN nication quality in the early 1970s, with a primary focus on the communication climate, particularly T, W within employee-management relationships (Tkalac Verčič et al. 2009, 176). EB A Numerous perspectives of many scholars upon the connection between internal communication and N D organizational success are cited, and Tkalac Verčič et al. (2009, 176) explain that internal communi- IN cation results with heightened productivity, diminished absenteeism, elevated service and product FOR quality, increased innovation, reduced strikes, and overall lowered costs. On the other hand, low-qual M-AT ity internal communication has a negative effect on an organization’s business performance. ION The assessment of internal communication satisfaction, conducted in 2015, measured satisfaction T EC levels of internal communication within a public institution (Ćorić and Musa 2015, 157). The meas-H NOL uring tool used for this purpose was the CSQ, namely, the Communication Satisfaction Questionnaire O designed by Downs and Hazen, where internal communication is conceptualized as a multidimen- G IE sional construct. Specifically, the study identified the lowest level of satisfaction in the domain of S “Data on personal success,” indicating a dissatisfaction of the organization’s members regarding feedback. In order to improve this identified deficiency, the authors proposed formulation of an internal communication program that encourages more needed two-way communication. Among the other factors of satisfaction with internal communication, the communication climate had the highest level of correlation. The importance of the communication climate is also emphasized in the research conducted by Tamara Sušanj Šulentić (2014), wherein she tried to establish a correlation between the internal communication climate and employee satisfaction and loyalty (2014, 71). The outcomes of the conducted research confirmed the hypothesis that the “internal communica-tion climate is essential for employee satisfaction and loyalty,” signifying that that quality internal communication positively affects the efficiency and loyalty of employees (Sušanj Šulentić 2014, 75). Both mentioned studies share their limitations, notably referring to a constrained sample size from a singular organization and restricted to internal participants, thereby suggesting caution in gener-alizing the findings. 108 communication in the selected city administration (Štelk et al. 2022). The results of this research er-R RN evAT emphasize the employees’ acknowledgment of internal communication as essential for mutual un- ieIO conducted in 2022 by Štelk, Katavić, and Vukić, which endeavored to determine the level of internal Pe INTE Among the other inquiries within the domain of internal communication, noteworthy is the study derstanding. Nevertheless, a significant share of dissatisfaction with internal communication was w N edA substantiated, which consequently has an impact on overall job satisfaction (Štelk et al. 2022, 165). L S PrCIE Consequently, the discontent with internal communication, particularly in the interactions between o ceN superiors and employees, has a significant influence on workplace satisfaction. This, in turn, reso - edTIF nates on employee efficacy and the operational success of the organizational entity. ingIC C According to the authors Kunczik and Zipfel (2006), it is said that “without communication, organized EN R OCE I action would not be possible” (cited in Ćorić 2019, 12). The main function of the communication net - JET'S A CT work within an organization extends beyond the internal exchange of information, while the imper- MB A 2.1 Organizational communication and organizational culture s Bo ON ok FER : P ative lies in identifying and implementing the optimal communication model. Accordingly, a nuanced O NU AT P understanding of the communication process and its alignment with the organizational context is G EMEO considered crucial for organizational sustainability in a competitive market milieu (Ćorić 2019, 11). ENPLE 2 Every society nurtures its own customs and culture, therefore one of the important aspects of an T, S organization is precisely its culture. Culture, a complex entity with many definitions, in the societal TR024 AT context is conceptualized as “a series of fundamental values, beliefs, and norms that are common to –2 EG IC02 members of a society” (Bedeković and Lukačević 2011, 16). So, when describing the culture within C5 organizations, we are talking about the general patterns of behavior, common beliefs, and values OM of the members of that organization. Moreover, culture includes “processes of learning and trans- MU mission of knowledge, beliefs and behavioral patterns during a certain period” (Topić Stipić and NIC Tomaš 2021, 259). Considering that organizational culture, like the broader concept of culture, is a ATION multidimensional construct, explanation of organizational culture can be undertaken through two M integral aspects: the visible and the invisible. The invisible part of the organization includes “the AN system of values, understandings, beliefs, ethical principles, lifestyles and personalities within the AG organization”, whereas the visible dimension includes the behavioral patterns exhibited by the or -EMEN ganization’s members (Bedeković and Lukačević 2011, 17–18).T, W Nowadays, organizations frequently encounter dynamic shifts in market trends which force organ -EB izations to prompt responses and adaptability to the evolving environment (Belak and Ušljebrka AN 2014, 81). Organizations need be ready for change, with the aim of progression of the organiza-D IN tional entity where the management of an organization has a pivotal role in orchestrating chang-FOR es which should ensure business success. In order for organizational change to be implemented, it M must begin and end with transformations in the behaviors of individuals who are as members of an AT organization, most influenced by the organizational culture (2014, 81).ION EC T 2.2 The role of online platforms in internal communication HNOL With the development of technology, new forms of communication have also developed with digi- OG tal technology as a medium. Since the inception of the Internet, online communication, or comput-IES er-mediated communication, has become prevalent. This form of communication markedly differs from face-to-face interaction as it is exclusively text-based in nature (Prapotnik 2007, 87). When it comes to Internet-mediated communication, social networks are taking precedence (Pri-morac and Primorac Bilaver 2022, 100). Social networks offer notable advantages such as accessibility, speed, the maintaining of relationships, and a sense of connection and belonging. However, there are certain lowlights such as the absence of face-to-face communication, which can potentially negatively affect cognitive and behavioral communication skills (Primorac and Primorac Bilaver 2022, 104–106). Social networks and online communication became the most prominent during the pandemic, where their immediacy and rapidity made them the simplest and most effective forms of communication during periods of complete social closure (Primorac and Primorac Bilaver 2022, 101). In addition to social networks, online platforms gained significant importance during the pandemic, particularly for hybrid teaching. Noteworthy platforms in this context, among others, included Micro- 109 er-R R teractive platforms for the implementation of online classes in the era of the pandemic caused by the N ev AT Covid-19 virus” (Dragosavac and Jakica 2022, 57–58), showed satisfactory performance of both plat-ie IO Pe IN online platforms in education, such as the study titled “Analysis of the impact and importance of in-TE soft Teams and Zoom (Pauković and Krstinić 2021, 131–132). Research focusing on the significance of w N forms in remote teaching. Highlighted advantages included interactivity, ease of use, and the ability ed A L S Pr to establish direct contact. On the other hand, the research also identified some disadvantages of the CIE o platforms, such as microphonics and noise. Additionally, Pauković and Krstinić (2021, 132) outlined ce N ed additional advantages of online platforms including real-time presentation and the capacity to store TIF ing IC C all data and teaching content. Research by the New York Times confirmed the success of implement- R EN The above observations can be extended to draw connections with organizations. Specifically, the O CE I JE possibility of using online platforms as a supplement to traditional communication within the or-T'S A CT M ganization has its advantages such as speed, the ability to store information and data, but also to B A ok FE even surpass their results in traditional teaching settings (Pauković and Krstinić 2021, 131). R : P s Bo O ing online platforms in traditional education, indicating that student success in hybrid classrooms may N N O segment information according to the topic. Furthermore, these platforms can function as an in- U A T P G tranet and internal communication channel within organizations, contributing to accelerated infor- EM EO mation flow and streamlined data storage. EN PL E 2 T, S TR 02 4 3 RESEARCH METHODOLOGY AT –2 EG IC 02 3.1 Quantitative research C 5 OM 3.1.1 Objectives, research questions and hypotheses M U The primary aim was to assess how FSB Racing Team N members perceive the quality of internal com-IC munication. This overarching goal can be broken down into specific research objectives: 1. Explore AT ION the internal communication quality concerning information; 2. Analyze the speed at which informa- AN satisfaction with communication and duration of time spent within the organization; 4. Investigate A M tion flow among team members within the team workspace; 3. Establish the relationship between G whether satisfaction with private life influences satisfaction levels with internal communication. EM EN Aligned with the research’s primary goal, the main research question was posed: How satisfied are T, W team members with internal communication? Additionally, supplementary research inquiries were EB also defined: What is the difference in satisfaction with communication based on the duration of time A N spent in the team? In what way does the speed of information flow influence satisfaction with com - D munication? How does the quantity of information impact satisfaction with communication? What IN FOR correlation exists between satisfaction with internal communication and satisfaction with private life? ATM Derived from the primary goal and research question, the main hypothesis of the study was formu- ION lated: Hypothesis 1: Team members perceive communication within the team to be at a satisfactory H sis 2: There exists a variance in satisfaction with internal communication based on the time spent in NOL the team, Hypothesis 3: Team members believe that a faster flow of information requires physical O EC T level. Supplementing this main hypothesis, auxiliary hypotheses were identified and set; Hypothe- IESG presence in the team’s workspace, Hypothesis 4: Satisfaction with private life has an impact on the overall satisfaction with internal communication. 3.1.2 Method and sample Using the questionnaire method, the research aimed to delve into team members’ perceptions of communication quality within the organization. The questionnaire comprised 28 questions organ-ized into four segments: the influence of information on internal communication quality, the impact of communication on quality, the relationship between satisfaction with private life and internal communication satisfaction, and the connection between communication satisfaction and work willingness. Most of the questions in the questionnaire were closed-ended, utilizing a Likert scale format for responses. Respondents could select one of five possible answers, indicating their agree-ment or disagreement with statements (1 - completely disagree, 2 - disagree, 3 - neither agree nor disagree, 4 - agree, 5 – I completely agree). Additionally, the questionnaire included an open-ended question, providing participants with the opportunity to freely express their thoughts. 110 ganization members, ultimately contributing to the overall growth and success of the organization. w N edAL S The investigation into the perception of internal communication quality took place within a PrCIE o non-profit student organization which the FSB Racing Team project operates. The team has approx- ceN ed imately sixty members (officially 65 during the questionnaire), and the research was conducted on TIF ingIC C a sample of 48 active participants, constituting around 73.85% of the organization’s total member- s BoO ship. Notably, the research participants were current members of the team, and concurrently stu-N okFE dents across various disciplines at the University of Zagreb. A majority of the participants (52.1%) R : PEN were enrolled in the Faculty of Mechanical Engineering and Naval Architecture, underscoring the that proficient internal communication is the basis of organizational success. This effectiveness can er-R RN evAT enhance teamwork, encourage a positive work environment, and elevate the productivity of or- ieIO Racing Team organization. A brief examination of the theoretical framework led to the conclusion Pe INTE Specifically, this paper focused on internal communication and satisfaction levels within the FSB O CE I R notable presence of students from this faculty within the FSB Racing Team. The second highest rep- JE T'S A CT resentation came from the Faculty of Electrical Engineering and Computing, making up 35.4% of the MB sample. These results highlight a significant presence of technical students within the organization, AO NU A aligning with the engineering nature of the FSB Racing Team. The type of sample is intentional con-T P G EM sidering that the participants were chosen based on their involvement in the project, i.e., member-EO ENPL ship in the FSB Racing Team and familiarity with the team’s operational dynamics.E 2 T, S TR02 3.2 Qualitative research4 AT–2 EG IC02 3.2.1 Objectives and research questions C5 OM The primary objective of the research was to examine the communication dynamics within the FSB M Racing Team organization. Derived from this overarching goal, specific aims were outlined, includ - U N IC ing the analysis of communication deficiencies, investigation into the effects of a large amount of AT information and data on work processes, assessment of manager’s satisfaction with team organi- ION zation, exploration of conflict resolution methods, examination of possibilities for improvement of M communication, and evaluation of the effectiveness of online platforms in internal communication. ANAG In alignment with the defined objectives of the research, a set of research questions was formu -EM lated. The main research question focused on offering understanding regarding the dynamics of EN communication within the team. Among additional research queries were: What deficiencies char -T, W acterize the communication process? How does the substantial volume of information impact work? EB A To what extent is the manager satisfied with the team’s organization? What is the practice for con -ND flict resolution? What are the possibilities for communication improvement? And, finally, what is the IN efficacy of the online platform in internal communication?FOR 3.2.2 Method and sample ATM ION view method was conducted. For the purposes of this research, an in-depth interview guide was ECH Following the completion of the quantitative survey, qualitative research using the in-depth inter- T created, comprising 22 questions categorized into four main units corresponding to the research NOL inquiries: a general overview of communication dynamics within the team, information flow, on O -G line communication platforms, and conflicts within the team. These in-depth interviews took place IES in May 2023, right before the competition season. The research was conducted within the leadership of the FSB Racing Team, involving three in-depth interviews with key figures within the organization. Key individuals of the organization were se-lected for the examination of internal communication within the FSB Racing Team: the team’s or-ganizational leader, the project manager, and the leader of the Driverless team responsible for au-tonomous vehicle development. These individuals were selected due to the critical functions they perform within the organization, managing different facets of the team, which makes their insight into internal communication valuable and relevant. The organizational team leader oversees the overall functioning of the FSB Racing Team, the project manager plays a key role in planning and monitoring the tasks status, and the Driverless team leader manages a specific team, offering an additional perspective within the leadership. Despite the small sample size, the selection serves a specific purpose. Namely, the purposive sample ensures that participants represent key roles and 111 er-R R team management and project execution. Their extensive responses contribute to a deeper under-N ev AT standing of communication dynamics within the organization. ie IO Pe IN them a comprehensive understanding of how internal communication impacts various aspects of TE influential persons within the organization. Their responsibilities and time spent in the team afford w N edAL S Pr 4 RESULTS AND DISCUSSION o CIE ce N ed The organization primarily relies on the online platform for information distribution and mutual TIF ing IC C internal communication, especially in group settings. Almost 90% of members confirmed that the ok FE cate that members feel well-informed in a timely manner, with the platform effectively delivering R : P s Bo O Microsoft Teams platform facilitates information flow within the organization. Survey results indi-N CT T'S A In addition to utilizing the online platform, the organization also practices face-to-face communica- M B A O tion channels, mainly during weekly team meetings. The claim “At the general meeting, I can find N U A T P G O CE I by the organization for internal communication purposes. JE R EN all necessary information. The online platform not only facilitates communication but is also utilized out all the necessary information for further work” is defined by the fact that general meeting, held TR (56.25%) of participants believe they receive all the necessary information for performing tasks at 02 4 the general meeting, while a smaller portion (20.83%) disagrees. Notably, a significant percentage AT –2 EG IC 02 (23%) neither agrees nor disagrees with the statement, indicating uncertainty about the adequacy C 5 of information received. To complement this point of view, sub-team meetings were organized to OM delve into the details of each member’s tasks. EN PLE 2 al value of information members receive through this channel. According to the results, a majority T, S EM EO weekly to update the team, serves this specific purpose. This statement aims to measure the actu- M N In addition to using official channels such as the online platform and meetings, a significant amount U AT of information flows through the team’s workspaces. The statement “I believe that I miss a lot IC ION of information if I’m not in the team’s workspace” aimed to explore whether members find it M important to frequent the team’s workspace not only for task completion but also for staying up- A N dated. Just under a half of the participants (41.67%) agreed with this statement, while a quarter A G (25%) didn’t feel they missed much information by not being in the team’s workspace. A notable EM EN portion (33%) neither agreed nor disagreed with the statement, suggesting that many members T, W do not perceive a disadvantage or advantage in visiting the team’s workspace for additional in- EB formation. This outcome could be explained by the unique circumstance this season, specifically, A N the team’s relocation outside the Faculty of Mechanical Engineering and Naval Architecture due D to the extensive building reconstruction. During this period, team premises were unavailable, IN FOR potentially explaining the nuanced responses observed at the beginning of the calendar year. The ATIONM results are illustrated in the graph. Over 66% of participants believe that internal communication deserves an excellent to very good ECH T rating, supporting Hypothesis 1 that states, “Team members perceive communication within the NOL team to be at a satisfactory level.” The t-test results confirmed Hypothesis 2, indicating a difference in satisfaction with internal communication based on the time spent in the team. These findings O suggest that newer team members view their initial experience with internal communication as G IES satisfactory, perceiving it as organized without encountering communication obstacles. The results also imply that a significant portion of surveyed team members believes crucial information circu-lates in the workspace, and irregular attendance may result in missing out. Consequently, Hypothe-sis 3 stating “Team members believe that a faster flow of information requires physical presence in the team’s workspace” can be considered confirmed. Satisfaction with private life shows little corre-lation with satisfaction with internal communication, and there is no statistical evidence supporting the idea that satisfaction with private life affects satisfaction with internal communication. Thus, Hypothesis 4 “Satisfaction with private life has an impact on the overall satisfaction with internal communication” was rejected. 112 Figure 1: Informational flow regarding the communication channel er TE -R Pe IN ie IO wN edAL S PrCIE ev RNAT ceo ed TIFN ing IC C ok FER : P s Bo ON R EN O CE I CTJE T'S A N OU AT P A B M EMG EN PLE 2 T, SEO TR 024 AT–2 EG IC02 C5 OM (Source: Radovanović 2023) M U N On the other hand, team leadership also places significance on utilizing online platform as a key ATIC of information according to the relevant topic is ensured. In-depth interview participant states “We MAN have everything in one place, everything is connected to SharePoint and OneDrive. We can find all internal communication strategy. By using such a digital tool, the systematicity and categorization ION A the documents sent there. Somehow all our information is grouped”. Notably, digital tool offers GEM significant time saving advantage, as a single message can reach a large number of team members EN simultaneously, avoiding the need for multiple individual communications. In addition, participant T, W also claims that “You can find a lot of information in one place much faster”” The efficiency of the on- EB A line platform not only increases productivity, but also allows team members to focus on their tasks ND and responsibilities. Easy access to relevant information, data, documents, and reports promotes an IN informed work environment, ultimately saving time for both individual members and the team as FOR a whole. MAT In spite of the numerous advantages associated with the online platform for internal communica- ION ment and interest among members during online communication. These drawbacks may be the HNOL tion, certain disadvantages have been highlighted. One such disadvantage is the lack of engage- TEC result from various factors, such as distractions, difficulties in concentration, technical obstacles, or a preference for traditional “face-to-face” communication. Although the online platform facilitates O IEG collaboration and allows for flexibility, some team members express a perception that virtual meet- S ings may at times be less effective than in-person interactions. Second in-depth interview partici-pant claims “I mean, somehow, communication is much more difficult then. When we are online there is no discussion”, and third states that ““omeone can ignore the message”. Furthermore, on-line communication can tend to become one-way, especially in the absence of feedback and dy-namic discussions that are inherent in traditional face-to-face communication. 5 CONCLUSION This research emphasizes the pivotal role of internal communication in efficient organizational man-agement and its correlation with business success, as shown in previous research outlined in this paper. The primary focus was exploring the perception of internal communication quality within the FSB Racing Team and to analyzing communication patterns that prevail among its sixty members. 113 er-R R gagement was linked to the organizational climate’s impact on individual motivation, highlighting N ev AT the importance of cultivating positive and good interpersonal relationships. Within this context, or-ie IO Pe IN minority of members showed high activity and availability at a certain time. This difference in en-TE The research findings pointed to a notable challenge within the organization, revealing that only a w N ganizational leadership emerged as a key factor in maintaining quality internal communication, ed A L S Pr ensuring members’ satisfaction and motivation. Although the research indicated an overall satisfac-CIE o tory level of internal communication, it also revealed areas for improvement. Specifically, there was ce N ed a recognized need for better information segmentation and enhanced knowledge transfer. Despite TIF ing IC C the positive contribution of the Microsoft Teams online platform to internal communication and in- R EN ing up opportunities to conduct similar research in different settings, with its results serving as a O CE I JE benchmark for future research exploring perceptions of internal communication quality in various T'S A CT M contexts and organizational structures. The study emphasizes the pivotal role of internal communi-B A ok FER One of the implications of this research is its potential applicability to other organizations, open-: P s Bo O formation organization, traditional “face-to-face” interaction remains prioritized. N N O cation in successful organizational management. By highlighting both strengths and weaknesses U A T P G of communication within the FSB Racing Team, it sets the stage for future enhancements that can EM EO boost member motivation and overall organizational success. As organizations continue to evolve EN PL E 2 and adapt to changing circumstances, effective internal communication remains a cornerstone for T, S gaining a competitive advantage in the marketplace. TR 02 4 AT –2 EG IC 02 C 5 OM M U N ATIC ION M ANAGEMENT, W EB AND INFOR ATM ION EC T H NOL O IEG S 114 REFERENCES Pe INTE 1. Bedeković, Vesna, and Vlatka Lukačević. 2011. 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ATION EC T AUTHOR BIOGRAPHIES HNOL Rebeka Radovanović holds a Master of Arts in Communication Science from the Faculty of Croatian OG Studies at the University of Zagreb. Currently, she’s employed at Schneider Electric as a Digital Mar -IES keting Specialist. Tanja Grmuša is an Assistant Professor and Head of the Marketing and Communication Department at the Zagreb School of Business. She also teaches at the Faculty of Croatian Studies at the University of Zagreb. Her scientific interests are: communication studies, intercultural communication, busi-ness communication, media management, journalistic practices and mass media effects. 115 er-R RN evAT ieIO Pe IN Published scientific conference contribution TE 1.08 Objavljeni znanstveni prispevek na konferenci w N edAL S Pr HEALTH NAVIGATION: STRATEGIC COMMUNICATION o CIE ce N MANAGEMENT IN ISTRIAN HEALTH INSTITUTIONS ed TIF ing IC C ok FE Alma Mater Europaea University, Slovenia R : P s Bo ON Anthony Ban, PhD Candidate R EN Pula General Hospital, Croatia CT M Alma Mater Europaea University, Slovenia B A O N Pula General Hospital, Croatia U JE Branka Ličanin, PhD Candidate T'S A O CE I A T P G EN PLE 2 ABSTRACT T, S EM EO TR 02 Research on strategic communication management in healthcare institutions in Istria studies key 4 AT –2 strategies and challenges in communication. The focus is on the specifics of the health sector in this EG IC 02 area, exploring communication approaches and implementing strategic practices to improve re- C 5 OM lationships with patients, staff and the community. The research aims to identify and analyze the M potential relationship between applied communication management strategies and the level of U N patient satisfaction in health care institutions in Istria, with an emphasis on providing a deeper IC AT understanding of the factors that influence patients’ perception of the quality of communica - ION tion in the health care environment. Three research hypotheses were set: H o : The application of M strategic communication practices in healthcare institutions in Istria significantly correlates with A N A increased patient satisfaction; H 1 : There are statistically significant differences in the perception G of the effectiveness of communication strategies in healthcare institutions in Istria in relation to EM EN the gender of the respondents; H 2 : There are statistically significant differences in the perception T, W of the effectiveness of communication strategies in healthcare institutions in Istria in relation EB to the age of the respondents. The research sample consisted of 130 patients. The research was A N conducted in Pula and Rovinj (Istria, Croatia). The scaling technique was used in the research part D of the work. For the purposes of this research, the Assessment Scale of Strategic Communica- IN FOR tion Management in Healthcare Institutions was constructed. Based on the results of the research ATM conducted, all three hypotheses were confirmed. First, the implementation of strategic commu- ION nication practices significantly correlates with increased patient satisfaction. Also, statistically EC strategies in relation to the gender and age of the respondents, which indicates the importance H T significant differences were observed in the perception of the effectiveness of communication NOL of adapting communication practices according to the individual characteristics of patients in Is- O trian healthcare institutions. G IES Keywords: Health institutions, Istrian, Patients, Satisfaction, Strategic communication manage- ment 116 1 INTRODUCTION Pe INTE The fact that the World Health Organization recognized communication as one of the five basic skills er -RRN necessary to maintain a healthy and satisfied life also speaks of the importance of communication evAT ieIO (Tomaš 2022, 73). For a clearer insight into the communication process, it is necessary to recognize wN edA the key components that make it up. The central elements or ingredients of the communication L S Pr process include the sender, the message, and the receiver. In addition to these basic elements, other oCIE ceN important factors are included in the communication process, such as the means of communication edTIF (channel), feedback and possible interference that can affect the effectiveness of communication ingIC C (Tomaš 2022, 76; Lamza-Maronić, Glavaš, 2008, 10 ). s BoON Strategic communication has received several different definitions, which, like many definitions re - okFER lated to the concepts of strategy and communication, differ from each other (Thomas et al. 2015, : PEN R OCE I 4). Strategic communication represents the conscious use of communication by an organization to JE achieve its mission (Hallahan et al. 2007, 3). Ensuring effective communication with patients and T'S A CT M their families is a key foundation for providing high- quality healthcare (Practical Approaches to B AO NU Building a Patient-Centered Culture, 2008 in Cingi et al. 2015, 82). Lack of effective communication AT P G is clearly documented as one of the key factors contributing to medical errors and adverse patient EMEO EN outcomes. Communication problems often result in errors in the provision of medical therapy, de-PLE 2 T, S lays in treatment, and even unintended fatal outcomes (Brand et al. 2015). The satisfaction of health TR02 service users, especially patients, depends on various factors. The quality of healthcare, education, 4 AT–2 physical environment, processes, individual approaches and communication contribute to shaping EG IC02 patient satisfaction in the hospital context (Ruliyandari et al. 2019, 106). Below are the results of C5 OM research conducted on the topic of the impact of communication on patient satisfaction. M U Cingi et al. (2015, 82) point out that effective communication is the key to patient satisfaction, includ - N IC ing understanding their feelings and careful monitoring of verbal and non-verbal communication. It AT is important not only what health professionals say, but also how they say it, so that patients feel sup- ION techniques is essential to defuse tension. (Cingi et al. 2015, 82). Considering the constant increase in ANA ported and cared for. In situations with angry or anxious patients, using appropriate communication M sentinel and harmful events caused by ineffective communication, Burgener (2020, 128) states the key GEM need for healthcare organizations to focus on improving effective communication. This improvement, EN according to Burgener (2020, 128), will result not only in greater safety and patient experience, but T, W also in the final improvement of results. Research conducted by Sari et al. (2021, 241) points out that EB A effective communication plays a key role in patient satisfaction in the hospital environment. Through ND the application of effective communication between nurses and patients, a sense of trust is created in IN the ability of nurses to help patients with their health problems. This trusting relationship contributes FOR to patient satisfaction and, ultimately, can increase overall patient trust in the hospital. In addition, it is MAT emphasized that effective communication plays a key role in supporting the development of high-qual -ION ity health care programs, which leads to the provision of excellent services and increased patient satis- T faction (Sari et al. 2021, 241). Research conducted by Pelletier et al. (2019, 9) emphasizes the essential ECH connection between the dimensions of communication and patient satisfaction, while identifying key NOL factors that shape their overall experience. These results indicate a logical alignment between different OG aspects of communication and satisfaction, further underlining the importance of a holistic approach in IES understanding patient experiences (Pelletier et al. 2019, 9). Research conducted by Touati et al. (2022, 115) emphasizes the importance of involving patients in the decision-making process in order to im-prove patient satisfaction with aesthetic dental treatments. Using additional communication tools in addition to conventional verbal communication improves patient satisfaction with treatment results, improves the quality of care provided, and builds a better relationship between patients and dentists. With the increased use of digital tools in cosmetic dentistry, communication with patients and shared decision-making may further advance in the future (Touati et al. 2022, 115). The results of research con-ducted by Altin and Stock (2016, 8) point out that German adults with a high level of health literacy and a positive orientation of general practitioners towards patients, including joint decision-making, show greater satisfaction with the health care provided. These results highlight the key role of communication and a participatory approach in achieving high patient satisfaction and recommend that healthcare or-ganizations should develop comprehensive strategies that respond to health literacy needs to improve patient experience (Altin and Stock 2016, 8). 117 Pe 2 PURPOSE AND GOALS IN TE er-R R The purpose of research on strategic communication management in healthcare institutions in Istria N ev AT is to study key strategies and challenges in communication, with a special focus on the specifics of ie IO w the healthcare sector in the region. The aim of the research is to explore communication approach-N ed A L S es and the implementation of strategic practices to improve relationships with patients, staff and Pr the community. Through the identification and analysis of the potential relationship between the o CIE ce N applied communication management strategies and the level of patient satisfaction, the research ed TIF aims to provide a deeper understanding of the factors that influence patients’ perception of the ing IC C quality of communication in the healthcare environment. s Bo O N FE ok As part of the research, three hypotheses were set. The first hypothesis (Ho) claims that the appli-R : P EN cation of strategic communication practices significantly correlates with increased patient satisfac-R O CE I tion. The second hypothesis (H1) assumes statistically significant differences in the perception of the JE T'S A CT effectiveness of communication strategies in relation to the gender of the respondents, while the M B A third hypothesis (H2) implies that there are statistically significant differences in the perception of O N U A T P the effectiveness of communication strategies in relation to the age of the respondents. G EM EO EN PL E 2 3 METHODS T, S TR 02 4 This research paper applies a quantitative approach to studying strategic communication manage-AT –2 EG ment in healthcare institutions in Istria. The research instrument is the Assessment Scale of Strategic IC 02 C 5 Communication Management in Healthcare Institutions, which measures different dimensions of OM communication management. The statements in the assessment scale reflect different aspects of M U communication and their potential impact on patient satisfaction. These statements provide insight N IC into the subjective perception of patients about different communication strategies and their con-AT tribution to the overall experience in the healthcare environment. Before conducting the research, ION ethical permits were obtained from the relevant ethics committees, along with permits from the M organizations where the research takes place. Anonymity of participants and voluntary participa-A N A G tion are guaranteed. EM Data were collected in health institutions in Pula and Rovinj (Croatia) during October and November EN 2023. The research sample consisted of 130 patients. Data analysis was performed using the statis-T, W tical software platform SPSS23 and included dimensions such as sample size and basic descriptive EB A statistics, including frequencies, arithmetic mean, standard deviation, and minimum and maximum N D values. The Kolmogorov-Smirnov test was used to evaluate the data distribution. The identification IN of statistically significant differences in the respondents’ answers according to the first independent FOR variable (gender of the respondents) was carried out using the Mann-Whitney U test. Furthermore, M AT the Kruskal-Wallis test was applied in order to determine statistically significant differences in the ION respondents’ answers in relation to another independent variable (age of the respondents). T EC H NOL 4 RESULTS O G 4.1 Descriptive statistics results IE S Of the total number of respondents, 90 % of respondents said that they agree and completely agree with the statement defining clear communication goals contributes to my satisfaction; for state-ment structured information management increases my satisfaction 83.8 % of respondents; for statement effective internal communication within healthcare institutions directly affects my sat-isfaction 88.5 % of respondents; for statement practicing individualized communication with me through a strategic approach contributes to my satisfaction 83.1 % of respondents; for statement integrating patient feedback into strategic communication strategies improves my satisfaction 82.3 % of respondents; for statement transparency regarding the quality of services provided is part of strategic communication management and contributes to my satisfaction 93.8 % of respondents; for statement the focus on my education through strategic communication management contributes to my better understanding and satisfaction 90 % of respondents; for statement proactively resolving potential misunderstandings as part of a communication management strategy maintains a pos- 118 respondents; and for statement regular evaluation and adjustment of communication practices as er-R RNAT part of strategic management enables continuous improvement and increases my satisfaction 79.2 ev ieIO communication culture contributes to my sense of connection with the healthcare facility 83.1 % of Pe INTE itive perception of me as a patient 88.5 % of respondents; for statement developing an inclusive % of respondents. The lowest arithmetic mean (M=4.2000) is recorded by the statement regular w N edA evaluation and adjustment of communication practices as part of strategic management enables L S PrCIE continuous improvement and increases my satisfaction, which also has the highest standard devia- o ceN tion (Sd=.80116) (table 1). edTIF ingIC C Table 1: Descriptive statistics of statements about the impact of strategic communication practices s Bo ON in healthcare institutions on patient satisfaction okFER : PEN Statement f(1) f(2) f(3) f(4) f(5) N М Sd Min Max R OCE I JE Defining clear communication goals contributes 0 1 12 35 82 130 4.5231 .69567 2 5T'S A CT to my satisfaction. MB AO Structured information management increases NU 0 1 20 46 63 130 4.3154 .75775 2 5 AT P my satisfaction. G EMEO Effective internal communication within ENPLE 2 healthcare institutions directly affects my 0 1 14 50 65 130 4.3769 .70728 2 5 T, S satisfaction. TR024 Practicing individualized communication with AT–2 EG me through a strategic approach contributes to 0 1 21 50 58 130 4.2692 .75522 2 5 IC02 my satisfaction. C5 OM communication strategies improves my U 0 1 22 53 54 130 4.2308 .75265 2 5N satisfaction. Integrating patient feedback into strategic M ATIC Transparency regarding the quality of services ION management and contributes to my satisfaction. ANA provided is part of strategic communication 0 0 8 60 62 130 4.4154 .60725 3 5 M communication management contributes to my 0 1 12 47 70 130 4.4308 .69258 2 5 EM The focus on my education through strategic G better understanding and satisfaction. EN Proactively resolving potential T, W misunderstandings as part of a communication EB 0 1 14 45 70 130 4.4154 .71294 2 5 A management strategy maintains a positive ND perception of me as a patient. INFOR Developing an inclusive communication culture healthcare facility. ATION contributes to my sense of connection with the 0 1 21 43 65 130 4.3231 .76973 2 5 M Regular evaluation and adjustment of T communication practices as part of strategic 0 2 25 48 55 130 4.2000 .80116 2 5EC management enables continuous improvement HNOL and increases my satisfaction. (Source: Own research, 2023) O IEG S 4.2 Kolmogorov-Smirnov test results All aspects included in the evaluation of the impact of strategic communication practices in health-care institutions on patient satisfaction were subject to Kolmogorov-Smirnov testing. The results presented in Table 2 indicate that none of the variables have a normal distribution, which is con-firmed by the statistically significant results of Kolmogorov-Smirnov test at the significance level of p < 0.05. As a result, in further research, non-parametric tests will be used to examine statistically significant subsamples, given that they do not require the assumption of a normal distribution of the variables in the analysis (Pallant 2017, 205). 119 w N edA Defining clear communication goals contributes to my satisfaction. .384 130 .000 .687 130 .000 L S Pr Structured information management increases my satisfaction. .301 130 .000 .776 130 .000 CIE o Effective internal communication within healthcare institutions ce N .311 130 .000 .762 130 .000 ed TIF directly affects my satisfaction. ing IC C Practicing individualized communication with me through a .280 130 .000 .791 130 .000 s Bo O strategic approach contributes to my satisfaction. N Integrating patient feedback into strategic communication ok FE .262 130 .000 .801 130 .000 R strategies improves my satisfaction. : P EN R er-R RN Statement Kolmogorov-Smirnov Shapiro-Wilk ev AT ie Statistic df p Statistic df p IO Pe IN munication practices in healthcare institutions on patient satisfaction TE Table 2: Results of the Kolmogorov-Smirnov test of claims about the influence of strategic com- O Transparency regarding the quality of services provided is part CE I of strategic communication management and contributes to my JE .309 130 .000 .738 130 .000 T'S A CT satisfaction. M B A The focus on my education through strategic communication O N U management contributes to my better understanding and .333 130 .000 .742 130 .000 A T P G satisfaction. EM EO Proactively resolving potential misunderstandings as part of EN PL E 2 a communication management strategy maintains a positive .332 130 .000 .746 130 .000 T, S perception of me as a patient. TR 02 4 Developing an inclusive communication culture contributes to my AT –2 EG sense of connection with the .310 130 .000 770 130 .000 IC 02 healthcare facility. C 5 OM Regular evaluation and adjustment of communication practices as U and increases my satisfaction. N IC M part of strategic management enables continuous improvement .264 130 .000 .807 130 .000 AT (Source: Own research, 2023.) ION M 4.3 Mann-Whitney U test results AN Based on a detailed analysis of the results of the Man-Whitney U test, which is shown in table 3, sig- A G nificant statistical differences were recorded in the respondents’ perceptions of the impact of stra - EM tegic communication practices in healthcare institutions on patient satisfaction, taking into account EN T, W their gender (p<0.05). EB A Table 3. Mann-Whitney U test – The difference in the attitudes of respondents in relation to gender N D regarding claims about the influence of strategic communication practices in healthcare institu- IN tions on patient satisfaction FOR M Statement Mann- Wilcoxon W AT Z p Whitney U ION Defining clear communication goals contributes to my satisfaction. 725.500 1505.500-6.243 .000 T EC Structured information management increases my satisfaction. 602.000 1382.000-6.506 .000 H NOL Effective internal communication within healthcare institutions directly 491.000 1271.000-7.215 .000 affects my satisfaction. O IEG Practicing individualized communication with me through a strategic 470.500 1250.500 -7.185 .000 S approach contributes to my satisfaction. Integrating patient feedback into strategic communication strategies 483.500 1263.500 -7.090 .000 improves my satisfaction. Transparency regarding the quality of services provided is part of strategic 978.500 1758.500 -4.541 .000 communication management and contributes to my satisfaction. The focus on my education through strategic communication 624.500 1404.500 -6.549 .000 management contributes to my better understanding and satisfaction. Proactively resolving potential misunderstandings as part of a 483.500 1263.500 -7.328 .000 communication management strategy maintains a positive perception of me as a patient. Developing an inclusive communication culture contributes to my sense 521.000 1301.000 -6.971 .000 of connection with the healthcare facility. Regular evaluation and adjustment of communication practices as part of 450.000 1230.000 7.227 .000 strategic management enables continuous improvement and increases my satisfaction. (Source: Own research, 2023) 120 4.4 Kruskal-Wallis test results statistical differences were observed in the respondents’ attitudes regarding age in the context of RNAT ev claims about the connection between strategic communication practices in healthcare institutions ieIO w Based on a careful analysis of the results of the Kruskal-Wallis test, shown in Table 4, significant TE er -R Pe IN and patient satisfaction (p<0.05). ed NAL S Pr ing the claims of the influence of strategic communication practices in health care institutions on TIF ingIC C patient satisfaction s Bo Table 4: Kruskal-Wallis test – The difference in attitudes of respondents in relation to age regard- ce N ed o CIE O Defining clear communication goals contributes to my satisfaction. R 49.011 3 .000 : PEN R Structured information management increases my satisfaction. 63.243 3 .000 O Statement Chi-square df p ok FEN CE I (Source: Own research, 2023) Effective internal communication within healthcare institutions directly affects my JE 65.496 3 .000 T'S A CT satisfaction. MB A Practicing individualized communication with me through a strategic approach 73.037 3 .000O NU contributes to my satisfaction. AT P G EM Integrating patient feedback into strategic communication strategies improves my 76.370 3 .000EO satisfaction. ENPLE 2 Transparency regarding the quality of services provided is part of strategic 34.081 3 .000 T, S TR communication management and contributes to my satisfaction.024 The focus on my education through strategic communication management contributes 60.003 3 .000 AT–2 EG to my better understanding and satisfaction. IC02 C Proactively resolving potential misunderstandings as part of a communication 62.241 3 .0005 OM management strategy maintains a positive perception of me as a patient. M Developing an inclusive communication culture contributes to 78.447 3 .000 U N IC my sense of connection with the healthcare facility. AT Regular evaluation and adjustment of communication practices as part of strategic 80.637 3 .000 ION management enables continuous improvement and increases my satisfaction. M A N A G EM EN 5 DISCUSSION T, W As part of the research, three hypotheses were put forward that were the subject of analysis in order EB A to examine the connection between strategic communication practices in healthcare institutions ND and patient satisfaction, and possible statistically significant differences in the perception of the ef - IN fectiveness of communication strategies in relation to the gender and age of the respondents.FOR The first hypothesis (Ho) claims that the implementation of strategic communication practices sig M -AT nificantly correlates with increased patient satisfaction. The results of descriptive statistics show ION tices. For example, even 90 % of respondents declared that they agree or completely agree with the HNOL high average values for all statements related to the application of strategic communication prac- TEC statement that defining clear communication goals contributes to my satisfaction. Similarly, high average values were recorded for other claims. These results support the first research hypothe O - IEG sis, indicating a significant positive correlation between the application of strategic communication S practices and patient satisfaction. The second hypothesis (H1) assumes statistically significant differences in the perception of the ef-fectiveness of communication strategies in relation to the gender of the respondents. Mann- Whit-ney U test analysis reveals significant statistical differences in respondents’ attitudes in relation to gender for all statements about the impact of strategic communication practices on patient satisfac-tion. This diversity in perception may indicate different needs and expectations of patients according to their gender, which requires adaptation of communication strategies. The third hypothesis (H2) implies that there are statistically significant differences in the percep-tion of the effectiveness of communication strategies in relation to the age of the respondents. The results of the Kruskal-Wallis test confirm significant statistical differences in respondents’ attitudes in relation to age for all statements. This indicates the need to adapt communication strategies in accordance with different generational preferences and perceptions. 121 w N ed We compare our research on the impact of communication in healthcare institutions on patient sat-A L S Pr isfaction with the works of relevant authors in order to gain a deeper insight into our results. Burge-CIE o ner (2020, 128) emphasizes the necessity of improving communication in healthcare organizations, ce N ed TIF which perfectly coincides with our conclusions. We recognize the key role of continuous evaluation ing IC C and adaptation of communication practices, which we share with Burgener. Our analysis coincides s Bo O N with the research of Sari et al. (2021, 241), which emphasizes the importance of effective commu-ok FE R nication, especially between nurses and patients. Thus, we confirm the importance of building trust : P EN R er-R R menting strategic communication practices that will be adapted to different groups of patients, in N ev AT order to increase their satisfaction. ie IO Pe IN portant implications for practice in healthcare institutions, emphasizing the necessity of imple-TE In conclusion, the obtained results confirm all three research hypotheses. These findings have im- JE findings of Sari et al. Pelletier et al. (2019, 9) identify an association between different aspects of T'S A CT M O CE I through communication as a key factor for increasing patient satisfaction, in accordance with the A BO holistic approach in understanding patient experiences, which further confirms the identified key N U communication and overall patient satisfaction, supporting our findings. Both studies emphasize a EM EO ship between health literacy, physician orientation and patient satisfaction reveals similarities in EN A T P G factors in our research. A comparison with research by Altin and Stock (2016, 8) on the relation-T, S PLE 2 approach. Our analysis takes into account the perception of patients by gender and age, suggesting TR the need to adapt strategies to meet the specific needs of different groups of patients, which is in 02 4 AT line with the recommendations of Altin and Stock. Research by Touati et al. (2022, 115) on aesthetic –2 EG IC 02 dental treatments supports our conclusions about the importance of involving patients in the deci- C 5 sion- making process and applying additional communication tools. Both studies highlight the role OM of shared decision-making in improving the patient experience. Ultimately, the comparison with M U N relevant authors provides additional context and confirms the key findings of our research on the IC importance of communication in healthcare institutions to achieve high patient satisfaction. AT ION The first limiting factor relates to the sample size used in the research. Given that the sample con - M sisted of 130 patients, there is a risk that the results are not fully representative of the wider popula- A N A tion. Increasing the sample would contribute to increasing the reliability and generalization of the G results. Second, the research is focused only on one geographical area, Pula and Rovinj in Istria, Cro- EM EN atia. This limitation may lead to questions about the transferability of the results to other regions or T, W countries, especially considering potential variations in the culture and practices of healthcare facil- EB ities. Also, it should be taken into account that the data were collected through self-reporting by the A N respondents through an assessment scale. This methodology can lead to biased responses, where D respondents may tend to give answers that are socially acceptable instead of honest answers. The IN FOR time limit is also significant, considering that the research was conducted in a certain period of time. ATM This limitation may affect the generalizability of the results to other time periods, given the possible ION changes in the circumstances in the healthcare facilities over time. Furthermore, although the as- EC aspects of communication in healthcare institutions, which may affect the overall evaluation. H NOL T sessment scale used is specific to the research, there is a possibility that it does not cover all relevant Bearing in mind the mentioned limitations of the research, relevant recommendations are made in G order to overcome the challenges and improve future research and practice of communication man- O IES agement in healthcare institutions. First, in order to overcome the limitation of small sample size, it is recommended to expand the sample of respondents in future research. Increasing the number of participating patients would contribute to greater representativeness of the results and enable the generalization of the findings to a wider patient population. In order to eliminate the limitation of focusing on only one geographical region, it is recommended to expand the geographical scope of the research. The inclusion of more health institutions from different regions or even countries would contribute to a better understanding of the diversity of approaches to communication man-agement. Given the limitation of respondents’ self-reporting via assessment scales, the inclusion of different data collection methods is recommended. Combining the rating scale with interviews or focus groups could provide deeper insight into patient experiences and provide additional valida-tion of the results. Regarding the limitation of the time period, it is recommended to conduct lon-gitudinal research that would monitor changes in the perceptions of patients over a longer period. This would enable monitoring the long-term effects of implemented communication strategies. In 122 of the results. In order to further enrich the analysis and obtain information about the factors that er-R RN evAT can influence the perception of communication, it is recommended to include additional variables ieIO tical methods adapted to the analysis of non-parametric data, which would ensure the reliability Pe INTE order to overcome the lack of normal data distribution, it is recommended to use additional statis- such as the socioeconomic status of the patients. Furthermore, in order to overcome practical chal- w N edA lenges in implementing the results, the development of specific guidelines to improve communi -L S PrCIE cation with patients is recommended. These guidelines should be adapted to the specific needs of o ceN patients, and healthcare institutions should actively work on implementing the recommendations edTIF in their communication management practices. ingIC C 6 CONCLUSION ok FER : P s Bo ON R EN This research on strategic communication management in healthcare institutions in Istria provides O CE I lation between the application of strategic communication practices and patient satisfaction. EN PLE 2 T, S The analysis of the research results provides an insight into the high level of agreement of patients TR024 with the claims about the positive impact of strategic communication practices on their satisfaction. AT–2 EG For example, over 90 % of respondents agree that defining clear communication goals contributes IC02 to their satisfaction, while high marks are also given to statements related to transparency, individ- C5 OM ualized communication, inclusion of patient feedback and other aspects of communication man- M U agement. N IC However, it is important to take into account the identified research limitations that may affect the AT ION sis on the specifics of the healthcare sector in the region. Our goal was to explore communication B AO NU approaches and the implementation of strategic practices with a focus on improving relationships AT P G with patients, staff, and the community. The key findings of this research confirm the positive corre - EMEO a deeper understanding of key strategies and challenges in communication, with special empha- T'S A JE CT M generalization of the results. Limitations related to sample size, geographic coverage, data collec- tion methodology, and time period suggest the need for future research that will carefully consider MAN these aspects.AG In addition, the analysis of differences in the perception of communication according to the gender EMEN and age of patients indicates the need to adapt communication strategies according to the specifici -T, W ties of different groups. This has implications for practice in healthcare settings, highlighting the im -EB portance of an approach that takes into account the individual needs and expectations of patients. AN In accordance with the results obtained, we propose several recommendations for practice and fur-D IN ther research. First, an expansion of the patient sample is recommended to increase the represent-FOR ativeness of the results. Also, we suggest including different geographic areas to get a broader per -M spective. A combination of data collection methods, such as surveys, interviews and focus groups, ATION can provide a deeper understanding of patient experiences. Furthermore, future research should T pay attention to a longitudinal approach in order to monitor the long-term effects of implemented ECH communication strategies. In addition, the use of additional statistical methods adapted to the anal-NOL ysis of non-parametric data is recommended to strengthen the analysis.OG In order to improve the practice of communication management in healthcare institutions, we sug-IES gest the development of specific guidelines adapted to the needs of different groups of patients. These guidelines should be aligned with identified patient satisfaction factors and actively imple-mented in daily practice. In the final conclusion, this research contributes to the understanding of the key aspects of com-munication management in healthcare institutions, providing a basis for improving the quality of services and patient satisfaction. However, further research and practical initiatives should take into account the identified recommendations and limitations in order to achieve sustainable and com-prehensive progress in the field of health communication management. 123 Pe REFERENCES IN TE er 1. Altin, Sibel Vildan, and Stephanie Stock. 2016. The impact of health literacy, patient- centered -R R N ev AT communication and shared decision-making on patients’ satisfaction with care received in Ger-ie IO man primary care practices. BMC Health Services Research 16(1): 1–10. https://doi.org/10.1186/ w N ed A s12913-016-1693-y. L S Pr 2. Brand, Shari, Kristen Slee, Yu-Hui Chang, Meng-Ru Cheng, Christopher Lipinski, Rick Arnold, and o CIE ce N Stephen Traub. 2015. Team strategies and tools to enhance performance and patient safety ed TIF training: The effect of training on both nursing staff perceptions regarding physician behaviors ing IC C and patient satisfaction scores in the ED. Journal of Hospital Administration, 4(2): 48-53. https:// s Bo O N doi.org/10.5430/jha.v4n2p48. ok FE R : P EN 3. Burgener, Audrey. 2020. Enhancing communication to improve patient safety and to increase R O CE I patient satisfaction. The Health Care Manager 39(3): 128–132. JE T'S A CT 4. Cingi, Can Cemal, Deniz Hanci, and Nuray Bayar Muluk. 2015. Will communication strategies in M B A patient relations improve patient satisfaction. International Journal of Communication and Health O N U A T P 7: 82–87. G EM EO 5. Hallahan, Kirk, Derina Holtzhausen, Betteke van Ruler, Dejan Verčič, and Krishanamurthy Sri-EN PL E 2 ramesh. 2007. Defining strategic communication. International Journal of Strategic Communica-T, S tion 1(1): 3–35. https://doi.org/10.1080/15531180701285244. TR 02 4 AT 6. Lamza-Maronić, Maja, and Jerko Glavaš. 2008. Poslovno komuniciranje . Osijek: Sveučilište Josipa –2 EG IC 02 Jurja Strossmayera, Ekonomski fakultet u Osijeku. C 5 OM 7. Pallant, Julie. 2017. SPSS – priručnik za preživljavanje. Beograd: Mikro knjiga. M 8. Pelletier, Daniel, Isabelle Green-Demers, Pierre Collerette, and Michael Heberer. 2019. “Mode- U N ling the communication-satisfaction relationship in hospital patients. SAGE open medicine 7. IC https://doi.org/10.1177/2050312119847924. AT ION 9. Ruliyandari, Rochana. 2019. Strategy Management Using SWOT Analysis on Patient Satisfaction M Rate in Dr. Sardjito Central General Hospital. JMMR (Jurnal Medicoeticolegal dan Manajemen Ru- A N A mah Sakit) 8(2): 106–110. https://doi.org/10.18196/jmmr.8295. G EM 10. Sari, Dwi Ratna, Dhian Kartikasari, and Nurnaningsih Herya Ulfah. 2021. Impact of Effective Com - EN munication on the Quality of Excellent Service and Patient Satisfaction in the Outpatient Depart- T, W ment. KnE Life Sciences: 232-244. https://doi.org/10.18502/kls.v0i0.8883. EB A 11. Thomas, Gail Fann, and Kimberlie Stephens. 2015. An introduction to strategic com- N D munication. International Journal of Business Communication 52(1): 3–11. https://doi. IN org/10.1177/2329488414560469. FOR 12. Tomaš, Antonia. 2022. Komunikacijski menadžment . Zagreb: AT Communication Story. M AT 13. Touati, Romane, Irena Sailer, Laurent Marchand, Maxime Ducret, and Malin Strasding 2022. Com- ION munication tools and patient satisfaction: A scoping review. Journal of Esthetic and Restorative T Dentistry 34(1): 104–116. https://doi.org/10.1111/jerd.12854. EC H NOL O AUTHOR BIOGRAPHIES IEG S Anthony Ban is a PhD Candidate at Alma Mater Europaea University in Maribor, and subspecialist in plastic and reconstructive surgery, employed as a general and plastic surgeon in Central operating block in Pula General Hospital, Croatia. His work focuses specifically on aesthetic, reconstructive and plastic surgery and strategic communication management Branka Ličanin is a PhD Candidate at Alma Mater Europaea University in Maribor, and a univ. mag. med. techn., employed as scrub nurse in Central operating block in Pula General Hospital, Croatia. Her work focuses specifically on aesthetic, reconstructive, and plastic surgery and strategic commu-nication management. 124 THE EFFECTIVENESS OF DIGITAL w N edAL S Pr o POLITICAL COMMUNICATION IN INFLUENCING CIE ceN edTIF VOTER BEHAVIOR 1 ingIC C s BoONFE ok Radoslav Baltezarević, PhD, Professor, Senior Research FellowR : PEN Institute of International Politics and Economics, Republic of Serbia Published scientific conference contribution Pe INTE 1.08 Objavljeni znanstveni prispevek na konferenci er-R RN evAT ieIO O CE I R CTJE T'S A The development of digital technologies has changed and improved the methods of political N U AT P G EM ABSTRACT MA BO communication. Today, digital political communication has become a powerful weapon of EN PLE 2 politicians and their parties in political campaigns, which can ensure the desired outcome in EO the building of desired attitudes among voters and additionally motivate them to spread pos- AT –2 EG02 itive electronic word of mouth (eWOM) to other Internet users in order to directly encourage IC C5 OM the formation of positive political opinion towards a specific political candidate and/or party. political elections. Communication in a digital environment can more effectively influence 02 TR4 T, S However, digital political content published on social media must be properly and intelligent- MUN ly developed and regularly altered in order to improve communication with voters and have ICAT a more comprehensive impact on the ultimate results of political elections. In recent years, ION political marketing professionals have employed credible political influencers in social media M (primarily experts in this field) to influence voter attitudes and, as a result, affect the creation AN of desired positive political perceptions.AGEM Keywords : Digital Political Communication, Electronic Word of Mouth (eWOM), Political Influenc -EN ers, Digital Environment, VotersT, W EB AND INFOR ATM ION EC T H NOL O IEG S 1 The paper presents findings of a study developed as a part of the research project “Serbia and challenges in international relations in 2024”, financed by the Ministry of Science, Technological Development and Inno-vation of the Republic of Serbia, and conducted by Institute of International Politics and Economics, Belgrade during year 2024. 125 Pe 1 INTRODUCTION IN TE er-R R Communication can be defined as the process of sending messages by one person to other peo-N ev AT ple in order to talk, change attitudes, opinions or behavior, orally (directly) or through the media ie IO w (indirectly). In this process, a reciprocal relationship is necessary between the communicator and N ed A L S the communicants, that is, between the delivery of messages and the recipients (Hasbullah et al. Pr 2018). Political communication, on the other hand, is an activity that reflects the presentation of real o CIE ce N and potential consequences that can regulate people in conflict conditions (Junaedi 2013). In many ed TIF cultures, however, remaining silent throughout a communication process is a way to avoid conflict, ing IC C stress, and awkward circumstances s Bo O N FE ok (Baltezarević et al. 2022). Interpersonal relations and politics could not function without the process R : P EN of communication (Gerstle and Piar 2016). Skilled communication is a feature of good politics, so R O CE I political communication can be presented as a requirement for the functioning of a broadly defined JE T'S A CT public space (Wolton 2015). M B A O If there is a clear desire for democracy to function well in a country, citizens need true information N U A T P G about politics. Only in the case when people have knowledge about political actors, or about var-EM EO ious social situations, they can act meaningfully and have informed opinions as citizens. However, EN PL E 2 it is unclear exactly how much people need to be informed in order for democracy to function. Cer-T, S tainly, there is no doubt that those citizens who are well informed are better able to participate TR 02 4 AT in social and political issues and to more adequately choose political representatives who are in –2 EG IC 02 line with their political views (Patterson 2013). The modern environment, fueled by the increasing C 5 proliferation of digital, mobile and social media, has significantly influenced fundamental changes OM in the media environment and political communication systems, but also reduced the influence of M U N traditional media (Vowe and Henn 2016). Traditional cultural values and their content appear to be IC suppressed by digital media and contemporary technologies (Baltezarević et al. 2019a). Howev-AT ION er, it is not advised to rely solely on technology during the digital transformation process, though, AN today’s democratic and political processes, the concept of political marketing, branding and com- A M as human-machine coexistence produces superior outcomes (Papakonstantinidis et al. 2021). In EN the main success factor in political campaigns. Political communication combines: micro-targeting, (where potential voters are sent highly customized emails, based on previously collected and ana- T, W EMG munication goes beyond winning political elections. Strategic communication, in its many forms, is EB lyzed personal data), the use of social media in political campaigns to motivate action and voter A participation, and the use of social networking platforms (such as Facebook, Twitter or Instagram) N D for communication and/or fundraising, presenting political candidates, but also for promoting the IN ideology, vision and values that the political option stands for (Bendle 2018). FOR ATM Several studies can be found in the literature that show that the mass media is still the most impor- ION tant source of information about current events and politics (Mitchell et al. 2016; Newman et al. EC utable to differences in the political information environment (Banducci et al. 2016). One of the top-H NOL T 2016). These studies suggest that cross-country differences in political knowledge are partly attrib- ics relevant to political communication that certainly deserves more detailed research is a deeper O understanding of the determinants of people’s reactions to messages on social networks (Bursztyn G IE et al. 2020). There are many benefits of social media, which is considered an excellent marketing S tool for retailers and marketers, because it can enable them to engage with existing customers, build good relationships and, of course, create awareness of their brand (Taneja and Toombs 2014). Social media offers unique experiences to its users regarding various political topics, as well. A key role in the exchange of information is represented by random posts shared by users, but also promi-nent algorithms that work behind the scenes of websites with political themes (Vraga 2016). Social media offers a better and more efficient platform for various political topics than forums or ses-sions where users attend in person (Bode 2016). As an interactive platform, social media is primarily intended to improve communication through the exchange of photos, videos and ideas, both be-tween individuals and between corporations, have become an integral part of modern marketing strategies and can completely replace traditional marketing activities (Vera and Trujillo 2017). The digital media and marketing ecosystem has transformed the way companies promote their prod-ucts and services and influence consumer behavior on a global level, of course this could not bypass 126 all the methods that were used in this sphere before. It is, also, evident that the innovations, that are er-R RN evAT still in the experimental phase, will contribute even more to these processes in the near future (WARC ieIO of digital political marketing are today sophisticated, more complex, effective and far-reaching than Pe INTE the field of politics and the processes of political campaigns. The technologies, strategies and tools 2017). With the development of internet technologies, political campaign operatives began to use w N edA digital technologies and tools to engage members of the younger population, mobilize voter turnout, L S PrCIE raise money and support various grassroots operations on the ground (Kreiss 2016). In addition to o ceN the above-mentioned advantages that new media offer to political marketing experts, it should be edTIF mentioned that more and more attention is being paid to digital games, which, although are not yet in ingIC C that they want to put into practice (Enli and Skogerbø 2013). A O NU A Today, almost all political parties have T P G EM reformed traditional communication channels and integrated digital communication methods. In EO ENPL addition to their active presence and participation on social media platforms, by creating specific E 2 T, S blogs and websites, they convey their political opinions directly and more effectively to the audi - TR024 ence (Serrano et al. 2018). The recommendation is that the content on social networks, in connec- AT–2 EG tion with political topics, is repeated from time to time, because it can encourage users to express IC02 C5 their political opinion more freely. However, it is necessary to adapt the content, so that it is not per- OM ceived as offensive or as too sensitive a topic, in order to discuss it openly (Halpern and Gibbs 2013). M U Advances in the data industry and in advertising technology have made available the services of a N IC growing infrastructure of specialized companies that offer more extensive data collection resources The interaction of politicians on social media with Internet users can positively influence the par EN - R OCE I ticipation of citizens in a certain political topic (Kruikemeier et al. 2013). A study conducted a few JET'S A CT years ago, states that politicians use social media to promote themselves, as a political party official, MB but also as individuals. In interaction with other users, they mainly propagate ideas and policies has the capacity to influence attitudes and generate new voters (Baltezarević et al. 2019b). ok FER : P focus as a key political medium, it is only a matter of time when they will be recognized as a place that s Bo ON (like data marketing clouds) and precise voter targeting. Clouds, developed today by well-known ATION global companies such as Adobe, Nielsen and IBM, sell valuable political data together with de- MAN tailed information about consumers, for example, personal interests, frequency of credit card use, AG television viewing patterns, etc. (Salesforce DMP 2021). In political operations, Facebook and Goog-EM le play an important role, offering specialized advertising products, created for political purposes, ENT, W but also a whole range of commercial digital marketing tools and techniques (Bond 2017). Spend- ing on political advertising in the United States in 2022 will be close to $10 billion. Only during EB A the midterm elections (in August), the purchase of political advertisements exceeded 3.5 billion US ND dollars, which surpasses the election cycle of 2020, when the campaigns between Trump and Biden IN reached a record for advertising expenditures (Statista 2022a).FOR In the 2016 American elections, the social networking site Facebook played a particularly impor- MAT tant role. Facebook, with the help of its registered members (they had to give their correct names), ION access a huge number of users (more than 162 million) and to target them individually according to HNOL created a powerful identity-based targeting paradigm. In this way, it allowed political parties to TEC gender, age, congressional district, and interests. Instagram is also a widely used social networking platform that helps track individuals and collect their data using various tactics. Not surprisingly, O IEG today specialized companies are increasingly forming teams of in-house staff aligned with each S of the major political parties in order to provide technical assistance or any other services to polit-ical candidates and their campaigns at all times (Kreiss and Mcgregor 2018). Cambridge Analytica (CA), a well-known behavioral communications and data analysis company, was a key player in the 2016 US election, and was instrumental in Donald Trump’s victory. In order to determine the per-sonality of every adult in the United States of America, the company used the so-called five-factor personality model (known as OCEAN) (Albright 2016). This model, using digital data, voter history and marketing resources, rated personalities based on five key traits: openness, conscientiousness, extroversion, agreeableness and neuroticism. The digital data used in this assessment was provided by leading companies such as Acciom, Experian, Nielsen, Aristotle, and Facebook. Based on the anal-ysis of the obtained data, it was possible to understand more precisely the preferences and needs of the voters, and as an epilogue, convincing advertising content was launched on several digital channels (Nix 2017). 127 w N litical ads, while 60 percent of them believe that political advertising is unethical and that regula-ed A L S Pr tion of political ads on social media is needed (close to 77 percent). Most importantly, 64 percent of CIE o respondents believe that consumer data should not be available to political advertisers, in order to ce N ed prevent misuse (Statista 2022c). TIF ing IC C A less formal means of communication than a typical website is a political candidate’s blog, which s Bo O N contains daily entries in a text format (often enriched with images) that can be accessed by all who are ok FE R interested. Very often a blog of a political party publishes articles by several people who are respon-: P EN R er-R R on Google and Facebook, while the rest was spent on connected TV (CTV) (Statista 2022b). Over N ev AT three-quarters of voters polled in 2022 in the United States said they tend to ignore or turn off po-ie IO Pe IN first half of 2022 alone. Of the total sum, close to 400 million was allocated to political campaigns TE In terms of digital political advertising, about US$700 million was spent in the United States in the JE their blogs in order to express their subjective views on certain political situations, try not to cross the T'S A CT M O CE I sible for activating and stimulating the entire blog community. Those political candidates, who use A BO is to publish a biography or irrelevant details about a political candidate’s private life. However, strictly N U border, so as not to damage their political image. What is not appropriate during a political campaign EM EO tician should always be socially accessible and available to the people, to create a feeling of intima-EN A T P G providing only formal election information is also not advised. The recommendation is that the poli-T, S PLE 2 cy in the relationship between the voter and the candidate, only in this way he/she can significantly TR strengthen his/her political image (Karwacka 2017). Another advantage of a blog in an election po- 02 4 AT litical campaign is that it facilitates contact with journalists. Politicians, with adequate and interesting –2 EG IC 02 blog content, can stimulate the interest of the media in all aspects, which is the effect that politicians C 5 want to achieve during the pre-election period or during the campaign (Marketingwpolityce 2020). OM M Political candidates, who want to achieve success in elections, most often communicate with the local U N community by commenting on current events, using Twitter, live casts and live streaming services (Mi- IC otk 2016). The findings of the study show that the use of social networking sites in terms of perceived AT ION ease of use, usefulness, but also the need to belong to the community, have a positive effect on the M involvement of voters in politics, which can affect their attitude towards voting and their trust in the A N A decisions they made (Lee 2020). Given that the virtual space is, in many cases, the first place where G people will look for information in the decision-making process, in order to satisfy their needs and de- EM EN sires, experts in the field of political marketing are increasingly communicating with the public by cre - T, W ating audio-visual content. In addition to social networking sites, blogs and discussion forums, experts EB have recently been hiring social media influencers, opinion makers, who, due to their expertise and A N experience in a certain field, are perceived by followers as credible sources of information. However, D the audio-visual messages, which they place through the digital environment, and which influence IN FOR the attitudes of their followers, are in most cases pre-created by the client, and in some cases, the time ATM frame when they should be launched is also precisely defined (Baltezarević 2022). Although influenc- ION ers most often comment on lifestyle topics with their followers, they have recently begun to increas- EC started to significantly affect the content of their posts and communication on social media platforms H NOL T ingly integrate political content into their posts. Given that they have a large audience, this change has (Riedl et al. 2021). According to a study conducted in Germany a few years ago, traditional influenc- O ers are very effective when it comes to product promotion and over 30 percent of social media users G IE discovered a new product through an influencer’s recommendation (Wulff et al. 2018). As influencer S marketing is still in its infancy, only a few related scientific studies are available in the literature, how-ever, political influencers are not conceptualized uniformly in all studies. In any case, in order to avoid the impression that the content seems superficial or fake, which can damage the reputation, it is nec-essary to produce content that is more politically significant (Casero-Ripolles 2021). Among the political influencers of social media there are several examples of those who stood out in the past few years and became part of the global political landscape. What characterizes these influencers are certainly the topics they discuss on their channels, such as issues of sustainability, feminism, the rights of the LGBT community and other current sensitive issues, while others have a more conservative approach or right-wing views (Wood 2021). Some of them engage in institu-tional politics and encourage their followers to vote, and there are also examples of them publicly supporting a certain political ideology or party (Shmargad 2022). In order for politicians to position themselves as authentic outsiders, and not as part of the populist elite, they need to build the per- 128 al brand (Whitmer 2021). Although political influencers have a certain influence on their followers, er-R RN evAT it cannot be claimed that this influence is direct and undeniable (Sinanan et al. 2014). Weeks at al. ieIO encers, authenticity is key if they want to create and maintain their own original and unique person Pe IN -TE ception of voters towards them as real and reliable (Enli 2017). The same applies to political influ- (2017) showed in their quantitative study that a small number of internet users influence the major- w N edA ity through active mutual sharing of political content. According to this research, more than 23% of L S PrCIE Facebook users (members of the younger population) published original political content, almost o ceN 32% shared other people’s political content, and about 52% regularly followed political news on the edTIF social media platform. A study conducted in Australia, USA, and Great Britain by Vromen at al. (2016), ingIC C Electronic word-of-mouth (eWOM), that is, information people receive from social networking sites A BO NU AT P G EM from other Internet users, can have a stronger influence on a consumer’s purchase decision than EO ENPL standard marketing techniques. A message shared by another consumer in a digital environment is E 2 T, S considered more authentic and credible than messages sent by an advertiser. Another consumer’s TR024 review of a particular product or service will always be respected and taken into account in the AT–2 EG process of making purchase decisions. The ability of consumers to freely share their experience with IC02 C5 a brand at any time with their circle of friends and acquaintances through social media networks OM (such as Facebook, Twitter and Instagram), makes eWOM a very effective marketing tool. Influencers M U on social networks are those who, in the process, give their followers guidelines for making the fi - N at work to undertake certain activities on a specific political issue. A study conducted in February : P EN R OCE I JE 2020 among influencers in the United States showed that 65% of respondents confirmed that it is a T'S A CT M good idea for presidential candidates to use influencers in their political campaigns (Statista 2020). with their digital political topics. 34% of them posted links to certain political news, 31% directly ok FER persuaded their peers for whom to vote, or not to vote at all, while 35% influenced their colleagues had similar conclusions. The proactive younger population influenced the persuasion of their peers s Bo ON nal decision (De Veirman et al. 2017). Companies that hire influencers on social networks to recom IC -AT mend their brands to their followers, in order to have more control over communication activities, ION as the time frame when the message should be launched. In this way, the risk of negative electronic ANA often provide in advance the content that they want the influencers to convey to consumers, as well M word of mouth (eWOM) is reduced (Kwiatek et al. 2021). In order to communicate primarily with GEM the younger population, experts in the field of political marketing are increasingly engaging influ- EN encers on social networks and taking advantage of electronic word of mouth (eWOM). If their posts T, W are perceived by followers as credible, then they tend to become viral, and spread exponentially EB A through the virtual environment. Political influencers, who have the power to encourage followers ND to engage in discussion about a particular political issue, can encourage their audience to share IN such information with other Internet users, thereby indirectly strengthening the image of political FOR candidates by presenting them as charismatic, ordinary people who do not differ much from other MAT representatives of their community (Baltezarević and Baltezarević 2022). ION Content posted on social media platforms is critical to the success of campaigns (Chaudhari and Bhorn- TEC ya 2022). It is believed that over 80% of global internet traffic is reserved for video content (Ahmad HNOL 2016). In today’s digital environment, information on social media, enriched with multimedia content, is more visual than in previous years. This kind of content has a stronger and more effective influence OG on Internet users, due to the possibility that through interaction with the content they can contribute IES to the modifications of the content published by other users. In this way, in cooperation with others, a continuous process of improving information is enabled (Calderaro 2018). Consumers trust the re-views posted on the Internet by experts in a particular field. The recommendation for organizations is to publish the best reviews on their organization’s website, but also to enhance the site’s attractive-ness by further decorating the site with photos, graphs, videos, maps, and the like. Such contents are intended to interest potential consumers and motivate them to visit content-oriented websites more often (Wawrowski and Otola 2020). Marketing experts must find a way to use the brand to provoke consumers to talk about it among themselves and, based on the conversation, to better understand the needs and desires of consumers. To motivate continuous consumer conversations, published con-tent must be captivating and embellished with infographics, videos and images, newsletters, and the like (Du Plessis 2017). Images play a very important role in online content and are considered key to engaging companies with their target market (Feldman 2016). According to marketing experts, if the 129 w N thus the probability that they will be engaged increases significantly. Information will be easier to ed A L S Pr remember if it is accompanied by an image, according to research, 65% of information with images CIE o will be remembered three days after encountering it, in the case of text that is not accompanied by an ce N ed image, the percentage drops to only 10% (Lifelearn 2015). TIF ing IC C The purpose of the research in this paper is to determine the impact of digital political communica-s Bo O N tion on the creation of positive perceptions of voters towards a certain political party or candidate ok FE R during a political campaign. The main goal of this study is to offer political and marketing experts : P EN R er-R R According to one study, 93% of the most interesting posts on Facebook are reserved for posts contain-N ev AT ing photos (Walter 2014). Internet users will spend more time on a post if it contains a relevant image, ie IO Pe IN be significantly higher. Most importantly, this goal is much easier to achieve when images are used. TE audience identifies with the story you are telling, there is a greater chance that user engagement will JE ment, and to communicate more purposefully with Internet users (their voters), in order to increase T'S A CT M O CE I new knowledge that would help them create more effective political content in the digital environ- A T P G 2 METHODS EM EO EN PL E 2 The research for the purposes of this paper was conducted through a closed questionnaire that was T, S sent electronically to email addresses saved in the research database. 234 questionnaires were sent, TR 02 4 A BO NU their chances and have better results in political elections. AT of which 185 were correctly and completely filled in, and they were used for further processing. The –2 EG IC 02 second part of the Questionnaire contained statements (15 in total) that tested the respondents’ atti- C 5 tudes. To verify the research questions posed in this paper, three hypotheses were defined, the justifi - OM cation of which was checked with the help of SPSS software for research in the field of social sciences. M U N IC AT 3 RESULTS ION M The first part of the questionnaire, which asked for demographic data on the respondents, indicated AN that n=85 (45.9%) male respondents, and n=100 (54.1%) female respondents participated in the A G research. The age structure shows that most respondents n=90 (48.6%) are from the youngest age EM group, which participated in the research 18-25 years old, n=43 (23.2%) aged 26-35 years, n=23 EN (12.4%) aged 36-45, while the representation of older respondents is significantly lower, i.e. n=21 T, W (11.4%) aged 46-55 and n=8 (4.3%) aged 56-65. Regarding the educational structure, the analysis EB A of the questionnaire showed that among the respondents, the most represented respondents were N D those with secondary education n=61 (33.0%), with a university degree n=57 (30.8%), with a mas- IN ter’s degree n=55 (29.7%) and the least, with a doctorate n=12 (6.5%). FOR ATIONM The results of the hypothesis testing are as follows: H1: If digital political communication is applied for the purposes of a political campaign, the greater ECH T the chance that voters’ perceptions of the political party will be positive. NOL Testing H1 showed that the hypothesis was founded and confirmed because the results of the Chi- O Square Tests X2 (16, 1) = 172.344a, p> 0.01 indicated that there is a statistically significant correlation G between the tested variables. IE S Table 1: Symmetric Measures for H1 Symmetric Measures Value Asymp. Std. Errora Approx. Tb Approx. Sig. Gamma .715 .056 9.262 .000 Ordinal by Ordinal Spearman Correlation .590 .054 9.884 .000c Interval by Interval Pearson’s R .591 .061 9.910 .000c N of Valid Cases 185 a. Not assuming the null hypothesis. b. Using the asymptotic standard error assuming the null hypothesis. c. Based on normal approximation. 130 H2: If credible political influencers on social networks are engaged in a political campaign, the more w N edAL S likely it is that positive electronic word of mouth (eWOM) will be initiated among voters in the dig- PrCIE o ital environment. ceN ed Testing H2 showed that the hypothesis was founded and confirmed because the results of the Chi-TIF ingIC C Square Tests c 2 (16, 1) = 226.019 a , p> 0.01 indicated that there is a statistically significant correlation s BoON between the tested variables. okFER : PEN Table 2: Symmetric Measures for H2 the level of acceptance of the first claim improves the prediction of acceptance of the second claim er-R RN by 71.5 %. evAT ieIO relation of ranks also gives positive high correlation. A Gamma value of .715 indicates that knowing Pe INTE Pearsons R= .715 shows that there is a positive high correlation and H1 is confirmed. Spearman Cor- O CE I R Symmetric Measures JE T'S A CT Value B M Asymp. Std. Errora Approx. Tb Approx. Sig. A O NU A Interval by Interval .516 .080 8.155 .000c EN PLE 2 T, S Pearson’s R .503 .080 7.867 .000 c TR024 N of Valid Cases Ordinal by Ordinal EM EO Spearman Correlation Gamma T P .578 .081 6.896 .000 G Pearsons R= .503 shows that there is a positive high correlation and H2 is confirmed. Spearman Cor a. Not assuming the null hypothesis. 185 AT –2 EG IC02 C5 b. Using the asymptotic standard error assuming the null hypothesis. OM c. Based on normal approximation M U N IC- AT relation of ranks also gives positive high correlation. A Gamma value of .578 indicates that knowing ION the level of acceptance of the first claim improves the prediction of acceptance of the second claim M by 57.8 %. ANAG H3: If during the political campaign the multimedia content posted on social networks is adapted EM to the needs of the target market, the more likely it is that the political party will have more votes EN in the political elections.T, W Testing H3 showed that the hypothesis was founded and confirmed because the results of the Chi- EB A Square Tests c 2 (16, 1) = 112.592 a , p> 0.01 indicated that there is a statistically significant correlation ND between the tested variables. INFOR Table 3: Symmetric Measures for H3 MATION Symmetric Measures Value Asymp. Std. Errora Approx. Tb Approx. Sig. EC T Gamma NOLH Ordinal by Ordinal O Spearman Correlation .619 .064 7.811 .000 .518 .059 8.187 .000c GIE Interval by Interval S Pearson’s R .536 .061 8.590 .000 c N of Valid Cases 185 a. Not assuming the null hypothesis. b. Using the asymptotic standard error assuming the null hypothesis. c. Based on normal approximation. Pearsons R= .536 shows that there is a positive high correlation and H3 is confirmed. Spearman Cor-relation of ranks also gives positive high correlation. A Gamma value of .619 indicates that knowing the level of acceptance of the first claim improves the prediction of acceptance of the second claim by 61.9%. 131 Pe 4 DISCUSSION IN TE er The results of the research in this paper are in line with the data that can be found in the available scien--R R N ev AT tific literature. In general, the use of digital political communication can be considered a powerful tool ie IO w that can influence the positive perceptions of voters towards a political party, especially if it is used for N ed A the purpose of a political campaign. Political experts have been using public opinion makers for many L S Pr years to influence other members of the community and their views on various political issues. Now o CIE ce N they have got the opportunity to engage such personalities in the virtual world, and if such personalities ed TIF (influencers) are people of credibility on social networks involved in a political campaign to support a ing IC C certain political option, there is a high probability that they will start positive electronic word of mouth s Bo O N (eWOM), that is, to encourage their followers (voters) to share information and their political beliefs with ok FE R other Internet users. Of course, it is recommended that the party ordering the services, choose the po-: P EN R O CE I litical influencer wisely (to be adapted to the preferences of the target audience), in order to avoid any JE T'S A unforeseen situation (negative electronic word of mouth), which could damage the political campaign CT M B and the image of the political party and/or candidate. It is also recommended that the party ordering A O N U services from a political influencer independently and in a timely manner, creates and delivers content A T P G to him/her and determines the best timing for posting that content. Finally, as can be seen both from EM EO the literature and from the results of the research, it is necessary to enrich political posts on social media EN PL E 2 T, S with multimedia content, because in this way the message will be differentiated and remembered for TR 02 a longer time, and it will occupy the user’s attention longer than simple text content, which can directly 4 AT –2 affect obtaining a greater number of votes and the success of the political party in the elections. EG IC 02 Unfortunately, it seems that insufficient studies have been done in the specific field of digital politi- C 5 OM cal communication, which is certainly a limitation, however, considering that this whole field is still M U in its infancy, the near future will, with new research, eliminate the current ambiguities. N IC AT 5 CONCLUSION ION New digital communication and the creation of an interactive relationship with voters can have a M A positive effect on the target audience, on their attitudes towards certain political issues, on a posi- N A G tive perception towards political candidates and parties and influence a favorable outcome in the EM elections. Of course, the content offered to the public must be accurate and purposeful, and politi - EN cians are expected to build their image by presenting themselves as a “man of the people”, who T, W does not differ in many respects from an ordinary member of the social community, in order to be EB A more easily accepted by the masses. Such an approach is a good way for democracy to survive in a N D country. However, studies show that each market has its own preferences, for this reason, it is neces- IN sary to adequately adapt the political content that is placed through social media to each audience. FOR From the review of the literature, it can be seen that digital technology has been of great help in this M AT regard for the past few years, that is, that the huge databases on the specific characteristics and needs of ION voters, which specialized companies collected, enabled a more precise and efficient design of political T activities. In addition to political websites, social network platforms such as Twitter, Facebook, Instagram, EC H NOL LinkedIn, above all, but also the creation of political blogs, have become a means of regular two-way O communication with voters. It is recommended, based on the review of the literature, but also on the IEG results of the research in this paper, that such content should be enriched with multimedia content, be- S cause in that way it will attract more attention of the audience, but will also be remembered for a longer time. Political influencers can provide great help towards achieving political success in the elections. If their communication is adapted to the needs of their followers on many political issues, there is a real chance that this type of interaction will motivate eWOM, that is, that Internet users (voters) will continue to spread positive information among themselves. Political parties, in order to have this process under control, often deliver content to political influencers and define the exact time when they want such content to be launched, in order to avoid the possible appearance of negative word of mouth, which is difficult to control and which can threaten the intended political goal in the elections. Current early experimental research, which with the help of virtual reality devices and neuromar-keting methods, tries to analyze the hidden needs of consumers (that is, voters). A better under-standing of their needs and desires would improve political digital communication and political promotional activities before and during the campaign, which would become far more effective, and the outcome of political elections would be less uncertain. 132 REFERENCES Pe INTE 1. Ahmad, Irfan. 2016. Top Digital Marketing Trends of 2016 [Infographic]. 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Wood, Rachel. 2021. ‘What I’m not gonna buy’: Algorithmic culture jamming and anti-consumer O IEG politics on YouTube. New Media & Society 23(9): 2754–2772. S 60. Wulff, Christian, Stephanie Rumpff, Susanne Arnoldy, and Simon Bender. 2018. Zwischen Enter- tainer Und Werber – Wie Social Media Influencer Unser Kaufverhalten Beeinflussen. Available at: https://www.pwc.de/de/handel-und-konsumguter/pwc-zwischen-entertainer-und-werber. pdf. (December 21, 2022). AUTHOR BIOGRAPHY Radoslav Baltezarević, PhD. is a senior research fellow and full professor at the Institute of Interna-tional Politics and Economics, Center for International Law and Economics. In addition to 18 mono-graphs and more than 150 scientific papers published in both national and international journals, he has also participated in several scientific projects. His research interests include business commu-nication, digital marketing, political marketing, global economics, and consumer behavior. 135 2025 SOCIOLINGUISTIC DEVELOPMENT OF DIGITAL w N edAL S Pr o COMMUNICATION STYLE: SLANGS, MEMES, CIE ceN edTIF AND TRANSLATION ISSUES ingIC C s BoONFE ok Eni Lasku, PhD CandidateR : PEN Faculty of Foreign Languages, University of Tirana, Albania Published scientific conference contribution Pe INTE 1.08 Objavljeni znanstveni prispevek na konferenci er-R RN evAT ieIO O CE I R CTJE T'S A In the vast tapestry of human communication, the emergence of the Internet has proven to be N U AT P G EM ABSTRACT MA BO a transformative force. The Internet is a thriving melting pot of cultures, and within this digital EN PLE 2 cosmos, memes and slangs stand as powerful symbols of modern communication. They capture EO formats. However, their cultural specificity presents unique challenges for translation. AT –2 EG IC02 In this article we will try to elaborate translation challenges because of Memes, Slangs and the C5 OM linguistic labyrinth that they create. Memes, often humorous and always relatable, convey com- the zeitgeist, condensing complex societal sentiments into easily digestible, often humorous TR 024 T, S plex societal sentiments through images and limited text. The rapid evolution and virality of M U memes lead to quick adoption and adaptation of new words or phrases, some of which make N ATIC their way into everyday language. Digital communication’s speed often means relying on these ION tools, leading to misunderstandings or the stripping away of cultural nuance. M To conclude, memes and slangs are emblematic of the digital age’s dynamic linguistic landscape. ANA For translators, this represents an exciting yet challenging frontier. As we continue to forge a GEM global digital community, the art of translating will need to evolve, ensuring that in the midst of EN laughter and shared moments, no one is left out of the joke.T, W Keywords: Sociolinguistic, Translation challenges, Memes, Slangs EB AND INFOR ATM ION EC T H NOL O IEG S 139 Pe 1 INTRODUCTION IN TE er-R R The advent of the internet has revolutionized communication, particularly with the emergence of N ev AT memes and internet slang, which have become integral to the way we interact in digital spaces. ie IO w These phenomena are not merely fleeting trends but represent powerful sociolinguistic tools that N ed A L S capture the essence of contemporary culture. Memes, with their humorous and often relatable con- Pr tent, and internet slang, with its rapid evolution, embody a unique blend of language, image, and o CIE ce N shared cultural knowledge. However, this digital linguistic landscape poses significant challenges ed TIF for translation, as these expressions are often deeply embedded in specific cultural contexts. As ing IC C memes and slang transcend national borders and language barriers, they require translators to nav s Bo O-N igate the complexities of meaning, humor, and cultural nuances. This article aims to explore the ok FE R : P translation challenges posed by internet memes, slang, and their sociolinguistic evolution, high-EN R O CE I lighting the need for creative adaptation in the process of global digital communication. JE T'S A CT Aim: M B A O The aim of this research is to explore the sociolinguistic evolution of internet memes and slang and N U A T P G the challenges they present for translation. Through a comparative study of digital language use EM EO across cultures, particularly focusing on Albanian, the research will investigate how the rapid spread EN PL E 2 of memes and slang affects language and identity. It will also explore the translation strategies re-T, S quired to maintain the essence and humor of these digital expressions, taking into account cultural TR 02 4 AT specificity, multimodality, and the evolving nature of online communication. –2 EG IC 02 Research Questions: C 5 OM 1. How do internet memes and slang reflect and influence sociolinguistic identity in digital commu- M nication? U N IC 2. What are the primary translation challenges associated with conveying the humor, cultural refer-AT ences, and context of internet memes and slang across languages? ION 3. How can translators adapt multimodal elements (e.g., images, text, and cultural context) in M memes and slang to ensure effective communication and cultural relevance in target languages? A N A G EM 2 LITERATURE REVIEW EN T, W 2.1 The Rise of Internet Language EB A As digitalization reshapes language and identity, language learning also continues to evolve. Stu-N D dents participate in the new spaces of socialization offered by the digital and continue to discover IN FOR and engage in new ways of representing themselves through language and other modalities. For AT sense of who they are and how they relate to the world. ION M Norton (2013: 4), when students talk, they not only exchange information, but also reorganize their ECH T Recognizing how technology has dramatically transformed language, identity and learning in the 21st century, this article will outline key ideas and issues in language and identity research that have NOL emerged from an ever-changing digital landscape. How have new language structures evolved O from digitally mediated communication? G IES The evolution of digital media with its shift from page to screen (Snyder 2003) intensifies the use of a multiplicity of modes, including the visual, aural, gestural and spatial, for conveying meaning. Lan-guage loses its privileged position in the digital world as the meaning of a message is increasingly constituted by a range of modes such as videos, clips, images etc. One specific example through which learners have been able to express themselves using multiple modes is digital storytelling. Through brief personal narratives told through images, sounds and words and assembled using new media (Norton 2013), learners are able to identify and reflect on pivotal moments of their life and find new opportunities for creation and collaboration. 2.2 Sociolinguistic Insights In the digital age, the study of sociolinguistics has found itself at the forefront of an evolving lin-guistic landscape, driven in large part by the influence of internet memes and slang. These linguistic phenomena are not just humorous or trendy expressions; they provide unique insights into how 140 a condensed form of language and culture, often relying on shared knowledge and references. For w N edAL S sociolinguists, memes showcase how language can be repackaged to fit the digital age. An Internet PrCIE o meme is considered to be a complex, multi-layered, and intertextual combination of image and ceN ed text that is mimicked, copied, and circulated on the internet through social media networks via dig-TIF ingIC C ital participatory culture (Laineste and Voolaid 2017). The term Internet meme originates from the s BoO Meme theory proposed by biologist Richard Dawkins in his groundbreaking book, The Selfish Gene, N okFE first published in 1976 (Dawkins 2006).R : PEN Internet slang is a dynamic linguistic phenomenon. It emerges and evolves rapidly in response to companied by examples that illustrate the changing linguistic landscape. er-R RN evAT Internet memes have redefined how we communicate complex ideas and emotions. They represent ieIO article delves into sociolinguistic insights gleaned from the world of memes and internet slang, ac- Pe INTE language evolves, how it reflects social identities, and how it shapes our interconnected world. This O CE I R digital culture. It’s not just about linguistic innovation; it’s about identity and community. Sociolin- JE T'S A CT guists have noted how online communities use slang to create a sense of belonging. MB AO N In the linguistic context, memes are units of culture that spread from person to person, developing U AT P G and adapting along the way, mostly through the use of images and keywords. This memetic trans- EMEO mission has accelerated the rate of language change. Through digital opportunities, people are able ENPLE 2 to create multiple identities online, such as blogger, photographer, or designer, having the opportu- T, S TR02 nity to transmit feelings, thoughts or even desires through different modalities. Bringing in this way 4 AT–2 the embodiment of the famous expression, ‘a picture is worth 1000 words’. EG IC02 The evolution of digital media with its shift from page to screen (Snyder 2003) intensifies the use C5 OM of a variety of modes, including visual, auditory, gestural, and spatial, for conveying meaning. Lan- M guage loses its privileged position in the digital world, as the meaning of a message is increasingly U N IC created in a variety of ways. AT “LOL” (Laughing Out Loud) is one of the most iconic and widely used internet acronyms that has tran - ION internet culture, specifically within text-based communication platforms like chat rooms, forums, ANA scended online communication to become a part of everyday speech. It originally emerged in early M and later, social media, as a way to convey laughter or amusement in response to something funny. GEM Sociolinguistic Implications of “LOL”: EN - Universal Appeal: “ T, W LOL” has achieved global recognition and is often used across cultures and lan - guages. In fact, many languages have adopted “LOL” directly into their lexicon, even when the EB A literal translation of “laughing out loud” doesn’t exist in the same form. It’s a perfect example of ND how internet culture creates linguistic phenomena that can bypass traditional language barriers, IN making it an international form of expression. This is part of the shift in sociolinguistic norms FOR - Changing Use and Meaning: driven by the internet: an emphasis on speed, ease, and universal understanding. MAT While “LOL” originally signified actual laughter, over time, its mean -ION in situations where the person isn’t literally laughing at all but rather acknowledging some- HNOL ing has become more nuanced. It can now indicate light amusement, sarcasm, or even be used TEC thing humorous in a casual way. In many contexts, “LOL” is often used as a filler in conversation, akin to saying “haha” or “smiling” in a face-to-face chat, regardless of whether the person is O IEG actually laughing. S - Language Evolution: The spread of “LOL” reflects a larger trend in internet language where abbre- viations and acronyms are used to quickly express emotions, ideas, or reactions. This change in language is driven by the need for efficiency in digital communication, where brevity and speed are often prioritized over formal language use. It also reflects how social media and messaging platforms shape communication by encouraging shorthand and informal expressions. - Translation Challenges: When it comes to translation, “LOL” can present challenges because its meaning often goes beyond the literal “laughing out loud.” It may be used in a context where laughter isn’t literal but is meant to convey a lighthearted acknowledgment of something. In some languages, it’s not simply a matter of finding an equivalent phrase but also considering the cultural context in which humor is expressed. Translators must understand whether the intent is to reflect genuine laughter or just a casual, digital way of expressing amusement, which might not always be easily conveyed in another language. 141 w N where the influence of internet culture seeps into language practices. ed A L S Pr CIE o 2.3 Translation Challenges ce N ed TIF In a globalized world, where digital interactions connect people from diverse linguistic back-ing IC C grounds, accurate translation is essential for effective communication. Misunderstandings arising s Bo O N from poorly translated memes or slang can lead to confusion or even offense. ok FE R Sociolinguists and translators are tasked with deciphering the cultural and linguistic subtleties em-: P EN R er-R R how language functions in a connected, globalized world. This slang shapes both formal and in-N ev AT formal interactions, as seen in advertising, media, and even in academic or professional contexts, ie IO Pe IN on the internet. It’s part of a larger trend of internet slang, memes, and acronyms that redefine TE- Cultural Impact: “LOL” has contributed to the digital lexicon and influenced how people interact M translation to ensure that the essence and impact of the original content are preserved. B A O N U A In order to further develop the research related to the translation challenges related to the foreign T P G language, I would like to analyze the word “troll”. The first meaning of the word “troll” is “a dwarf EM EO EN JE that are inherent to memes and slang. This often involves creative adaptation rather than literal T'S A CT O bedded in these digital expressions. They must consider cultural references, wordplay, and humor CE I T, S PL or giant in Scandinavian folklore that lives in caves or hills.” The transformation that the meaning of E 2 this word has undergone in the age of social networks is still a little far from the original meaning. TR 02 4 After the 2000s, ‘trolls’ are widely known on the Internet as people (and again here we are dealing AT –2 EG with a new concept, where in the Internet language, individuals are known as “personal accounts”), IC 02 C 5 i.e. individuals, who deliberately publish inflammatory comments, or offensive or other disruptive OM content. During the translation of the book Putin’s Trolls - In the Frontline of the information war M U against west (Aro 2022a, cf. 2022b), there was a need to translate the term troll. N IC The first challenge was obviously conveying the message in the right way without damaging its AT ION original meaning. So, we had to take into account the connotation of this word and the way it would M describe later in the book not only the meaning but also the connotation with which it would be A N colored, as the events were presented. A G EM The second challenge was to adapt the word in the Albanian language, which would also give the EN meaning of almost the entire message of the book (that is, the fact that Mr. Putin uses social net- T, W works to attack the truth of the information of the West through propaganda) and to achieve this EB goal he used falsely created personal accounts to publish false information. A N D The third challenge was to find a word that would include both first challenges, but this time, giv - IN en the fact that it would be used for the title of the book, it would also have to be attractive to the FOR reader’s interest. Under these conditions, ‘Trolls’ was brought into the Albanian language as Putin’s M Bait (Karrem). We also noticed that for the sake of a more direct impact on the reader, since we are AT ION talking about the title, Trolls’ is used in the singular. EC T H 2.4 Translation and multimodality NOL O Multimodality in composition writing refers to the integration of multiple literacies—textual, audi- IEG tory, linguistic, spatial, and visual—within a single medium to convey meaning. Examples include S comic books, advertisements, brochures, posters, digital slide presentations, and social media. Claire Lutkewitte defines multimodal composition as “using multiple modes that work purposely to create meaning” (Lutkewitte 2013, 2). Similarly, Gunther Kress emphasizes that multimodal texts use a combination of modes, such as written language, imagery, and spatial design, where each mode serves a specific function (Kress 2010, 423). With the rise of the internet, multimodality has grown significantly as text presentation shifted from print to digital screens. Modern writers often create fragmented, informal texts using images, colors, and sounds (Kress 2003). In translation studies, multimodality explores how non-verbal semiotics and meaning-making re-sources affect translation and interpreting behavior. Research areas include audiovisual translation (Gambier & Gottlieb 2001) and comic translation (Kaindl 2004). Sara Dicerto addresses the gap in analyzing multimodal source texts with her model in Multimodal Pragmatics and Translation: A New 142 is essential for translators and proposes a framework based on Relevance Theory for multimodal er-R RN evAT analysis (Dicerto 2018, 51). ieIO tems, verbal, visual, or aural (Dicerto 2018, 18). Dicerto argues that understanding multimodality Pe INTE Model for Source Text Analysis. She defines multimodal texts as combining at least two semiotic sys- 3 METHODOLOGY w N edAL S PrCIE o ceN The methodology combines qualitative analysis with comparative sociolinguistic and translation edTIF case studies. The study adopts a content analysis approach to identify linguistic patterns, cultural ingIC C texts. The aim is to uncover how cultural and linguistic subtleties are navigated in translation, and A O NU AT P G EM how global phenomena, like memes and internet slang, are localized into the Albanian context.EO ENPLE 2 T, S TR02 4 EMPIRICAL ANALYSIS4 AT–2 Dicerto’s approach (used in this empirical part) is designed to work with all types of multimodal EG IC02 texts and to be adaptable to the needs of translators. For dynamic moving text and audio informa- C5 OM tion, the entire model additionally consists of the columns phase and Aural. However, in Dicerto’s M book, the focus is on static, non-dynamic text, which is relevant to this study, and these columns are U N IC left out owing to redundancy. The following table and explanation are based on Dicerto approach: The research employs a comparative framework, contrasting the sociolinguistic and translation : P EN R OCE I JET'S A challenges observed in global contexts with those specific to Albania. This is complemented by CT MB interviews with Albanian translators, linguists, and sociolinguists, as well as analysis of translated forms, including popular Albanian and global memes, online slang usage in forums and social me- ok FER dia, and published translations of books or articles dealing with digital communication. nuances, and challenges in translating internet memes and slang. Data is sourced from digital plat- s Bo ON Table 1: Translation Challenges and Strategies in Memes and Multimodal Texts ATION M Meme AN Content Relevance/ Multimodal Analysis Translation Challenges Albanian Translation A Context (Dicerto’s Approach) and Strategies ExampleGEM Meme “you all Highlights Text–Image Interaction: Cultural Adaptation: “Ti / Të gjithë lajmet EN with the the serious the contrast The meme relies on Translators must consid-serioze / Ky artikulli T, W Confused news stories between the interplay between er how the contrast be-i parëndësishëm për EB Boyfriend this trivial serious news text (‘serious news’ vs. tween serious and trivial meme” (The translation A article about a and trivial ‘trivial article’) and the content is perceived in preserves the contrast N meme” content (e.g., image. The humor arises the target culture. The between “serious news” D IN memes). from the juxtaposition image may need to be and “trivial article,” FOR of formal and informal modified to align with adapting it to Albanian Meme with ION “You said I Represents Dialogue and Visual Pragmatic Equivalence: “Ti the s’ka me barishte, T Crying said, No more a playful or Context: The text is part Translators must ensure Jo, unë thashë, më EC registers. the translated text. while maintaining the M humorous tone.) AT and the NOL Woman plants! No, conflicting of a dialogue, and the the playful tone and shumë barishte!” (The H more plants!” dialogue, image likely provides conflict in the dialogue translation captures the Cat possibly about visual context (e.g., are preserved. The playful tone and repe- OG plants or sus-facial expressions, visual context may need tition in the dialogue, IE tainability. gestures). to be adapted to match adapting it to Albanian S the translated text. while preserving humor and conflict.) Empirical Dicerto’s ap- Describes the Static vs. Dynamic Text: Modality-Specific Trans- Dicerto’s approach Analysis proach works methodol- Dicerto’s framework lation: Translators must works with multimodal with multi- ogy used in distinguishes between consider the limitations texts, adaptable for modal texts, the study, static (e.g., images, of static text and ensure translators. For dynamic adaptable for emphasizing text) and dynamic (e.g., that translated text text/audio, the columns translators. For adaptability audio, moving text) aligns with the visual ‘phase’ and ‘Aural’ are dynamic text/ and focus on elements. elements. added. (The transla- audio, col- static text. tion explains Dicerto’s umns ‘phase’ approach in Albanian, and ‘Aural’ are maintaining the techni- added. cal and empirical tone.) 143 Pe Translation ‘Troll’: Refers Karremi i Pu- - Linguistic Layer: Trans-IN -R als posting bait’), em- loses the folkloric R N inflammatory phasizing the meaning while focusing ev er TE of ‘Jargon’ to individu- tinit (‘Putin’s lating ‘troll’ as ‘karrem’ ed N content, e.g., meaning. ‘bait.’ - Cultural Layer: A L S ‘Putin’s Trolls.’ Including folklor- Pr ic associations could o CIE ie or disruptive metaphorical on the metaphorical IO w AT ce N resonate with Albanian ed TIF traditions, where myth-ing IC C ical creatures symbolize s Bo O mischief. - Adaptation N Challenge: Balanc-ok FE R ing modern internet : P EN slang with traditional R O CE I connotations ensures JE T'S A full comprehension and CT M tone consistency. B A O N Digital Sto-Personal Short clips - Linguistic Layer: Humor U A T P G rytelling narratives humorously and colloquial expres-EM EO on platforms addressing sions tied to dialects EN PL like TikTok, Albanian must be adapted to E 2 T, S Instagram, daily life, e.g., maintain impact. - Visual or YouTube, traffic jams or Layer: Gestures, facial TR 02 4 AT combining bureaucracy. expressions, or cultural –2 EG visuals, text, background elements IC 02 and audio. (e.g., traffic chaos) need C 5 OM localization for foreign M audiences. - Cultural U Layer: Stories rely on N IC shared experiences, AT requiring explanation ION or substitution to M ensure relatability in A translation. N A (Source: Author’s analysis based on Dicerto 2018) G EM EN Dicerto’s multimodal pragmatics approach provides a valuable framework for analyzing and trans-T, W lating various types of multimodal texts, including memes, internet slang, terms, and digital story-EB A telling. This approach emphasizes the interaction between linguistic, visual, and cultural layers in N D static, non-dynamic texts to ensure accurate and culturally resonant translations. Below is an anal- IN ysis of translation challenges within four categories, highlighting the complexities of multimodal FOR translation. The analysis of the memes using Dicerto’s approach illustrates the intricate interplay M between text, image, and cultural context, emphasizing the significance of multimodal elements in AT ION translation. The meme with the confused boyfriend highlights the contrast between serious news T and trivial content, where the humor emerges from the juxtaposition of formal and informal regis- EC H ters, compelling translators to consider cultural perceptions of seriousness. NOL O In contrast, the crying woman and cat meme showcases a playful dialogue that relies on visual IEG context, such as facial expressions, to enhance the humor and conflict present in the text. This ne- S cessitates pragmatic equivalence in translation, ensuring that the playful tone is preserved while adapting to cultural nuances. Furthermore, Dicerto’s framework distinguishes between static and dynamic texts, with a primary focus on static elements in this analysis. The approach underscores the need for modality-specific strategies in translation, as visible interactions in memes require careful consideration to maintain the original message’s integrity and humor when rendering it into a tar-get language. Overall, Dicerto’s adaptable methodology provides a comprehensive framework for navigating the complexities inherent to translating multimodal texts effectively. The translation of the term “troll” illustrates the complexities of maintaining dual meanings. In Eng-lish, “troll” refers to both an online agitator and a mythical creature. Translating it into Albanian as “karrem” (“bait”) captures the metaphorical meaning of internet trolling but loses the folkloric asso-ciation. This challenge highlights the importance of balancing modern connotations with traditional meanings. Retaining the folkloric undertone might better resonate with Albanian audiences, where mythical creatures symbolize mischief or disruption, aligning with the essence of the original term. 144 gestures, and shared experiences. Translating these narratives requires not only linguistic adap- w N edA tation but also localization of visuals and non-verbal cues to ensure they resonate with the target L S PrCIE audience. These elements are culturally embedded, making direct translations insufficient with - o ceN out contextualization. edTIF ingIC C Dicerto’s approach underscores the need to consider linguistic, visual, and cultural elements in mul- s BoO timodal translation. By addressing these layers holistically, translators can maintain the integrity, N okFE humor, and meaning of texts, ensuring effective communication across cultures.R : PEN R cultural and linguistic adaptation during translation. For example, Albanian clips humorously ad- er-R RN evAT dressing daily life—such as traffic jams or bureaucratic inefficiencies—rely on local colloquialisms, ieIO cultural realities. Global platforms like TikTok and Instagram host personal narratives that require Pe INTE Finally, digital storytelling integrates visuals, text, and audio to share narratives, often reflecting 5 CONCLUSION JE T'S A CT O CE I In the realm of cross-cultural communication, the translation of internet language takes on a B M A O NU A heightened significance. Misinterpretations or failures to capture the nuances of memes and slang T P G increasingly interconnected through digital channels, the ability to bridge linguistic and cultural di- EN PLE 2 T, S can lead to confusion, miscommunication, or, at worst, cultural insensitivity. As our world becomes EM EO vides becomes paramount. TR 024 Translators and sociolinguists undertaking the challenge of internet language translation must em- AT–2 EG brace creativity, adaptability, and a deep appreciation for the nuances of digital culture. Translation IC02 C5 is not merely a mechanical process of rendering words from one language into another; it is an art OM that requires an understanding of cultural references, wordplay, and humor, as well as the ability to M preserve the impact and essence of the original content. U N nature of language itself. As our digital world continues to evolve, so too must the field of transla ION - M tion adapt to these challenges, ultimately serving as a bridge that connects people, cultures, and AN In conclusion, the translation challenges posed by internet language are a testament to the dynamic ATIC ideas in an increasingly interconnected global society. Embracing these challenges with creativity AG and cultural sensitivity will ensure that the essence of internet language is not lost in translation but EM rather becomes a vibrant and integral part of our diverse linguistic tapestry. EN The comparative analysis underscores the dynamic interplay between global and local digital lin- T, W guistic phenomena. While memes, slang, and digital storytelling share universal features, their EB AN cultural embedding significantly influences how they are understood, adapted, and translated. For D IN Albanian translators and sociolinguists, embracing cultural nuances and creative adaptability is es-FOR sential to preserving the essence of these digital expressions. This highlights the broader sociolin-M guistic principle that language is not only a tool for communication but also a reflection of cultural ATION identity and shared experiences. TECHNOL O IEG S 145 Pe REFERENCES IN TE er 1. Aro, Jessikka. 2022a. Putin’s Trolls: On the Frontline of Russia’s Information War Against the West. Ig -R R N ev AT Publishing. ie IO w 2. Aro, Jessikka. 2022b. Karremi i Putinit: Në vijën e parë të luftës informatike kundër Perëndimit. Tira-N ed A L S na: FFaqeqe. Pr CIE o 3. Bonny Norton. 2013. Identity and Language Learning: Extending the Conversation. 2nd ed. Bristol: ce N ed Multilingual Matters. TIF ing IC C 4. Danesi, Marcel. 2018. Language, Society, and New Media: Sociolinguistics Today. New York: Routledge. N OU 8. Gambier, Yves, and Henrik Gottlieb, eds. 2001. (Multi)Media Translation: Concepts, Practices, and A T P G Research. Amsterdam: John Benjamins Publishing. EM EO 9. Kaindl, Klaus. 2004. Translation and Comics. In Übersetzung: Ein internationales Handbuch zur EN PL E 2 T, S Übersetzungsforschung, edited by Harald Kittel et al., 491–494. Berlin: De Gruyter. TR 02 4 10. Kress, Gunther. 2003. Literacy in the New Media Age. London: Routledge. AT –2 EG 11. Kress, Gunther. 2010. Multimodality: A Social Semiotic Approach to Contemporary Communication. IC 02 C 5 London: Routledge. OM 12. Laineste, Liisi and Piret Voolaid. 2017. Laughing Across Borders: Intertextuality of Internet Memes. The M U European Journal of Humour Research 4(4): 26–49. https://doi.org/10.7592/EJHR2016.4.4.laineste N IC 13. Lutkewitte, Claire. 2013. Multimodal Composition: A Critical Sourcebook. Boston: Bedford/St. Martin’s. AT R EN Amsterdam: John Benjamins Publishing. O CE I JE 7. Eckert, Penelope, and John R. Rickford. 2001. Style and Sociolinguistic Variation. Cambridge: T'S A CT M Cambridge University Press. B A ok FER 6. Dicerto, Sara. 2018. Multimodal Pragmatics and Translation: A New Model for Source Text Analysis. : P s Bo ON 5. David Crystal. 2001. Language and the Internet. Cambridge: Cambridge University Press. ION 14. Meme, ‘You Can Never Have Enough Plants’ (Crying Woman and Cat). 2025. Catster. https:// AN 15. Schiffrin, Deborah. 1994. Approaches to Discourse. Oxford: Blackwell. A M www.catster.com/lifestyle/woman-yelling-at-cat-memes/ (October 14, 2025) EMG 16. Snyder, Ilana. 2003. Page to screen: Taking literacy into the electronic era. Routledge. EN 17. You All the Serious News Stories, This Trivial Article About a Meme. The Guardian, August 30, EB cted-boyfriend-meme-have-split-up. A N D T, W 2017. https://www.theguardian.com/media/2017/aug/30/the-team-that-made-the-distra- IN AUTHOR BIOGRAPHY FOR ATM Eni Lasku is a linguist, translator, and lecturer at the University of Tirana, where she is pursuing doc-ION toral studies in Linguistic Sciences and Communication. She also serves as PR and Media Specialist ECH T and Coordinator for the Right to Information at the High Prosecutorial Council of Albania. Her aca- demic interests include media discourse, translation studies, and intercultural communication. Eni NOL has translated several acclaimed works, including Putin’s Trolls by Jessica Aro and novels by Cathe- O rine Bybee and Lauren Asher. G IES 146 Published scientific conference contribution Pe INTE 1.08 Objavljeni znanstveni prispevek na konferenci er-R RN evAT ieIO THE NEED TO BUILD RESILIENCE AGAINST CLICKBAIT w N edAL S Pr o AS CONTROVERSIAL TACTICS IN ONLINE MEDIACIE ceN edTIF ingIC C Alma Mater Europaea University, Slovenia ok FER : P Jernej Šilak, PhD Candidate s Bo ON R EN ABSTRACT JE T'S A CT O CE I As new technologies continue to shape journalism, media outlets face increasing pressure to B M A O NU A adopt controversial tactics, such as clickbait, to attract readers and sustain their business models. T P G and how journalists, in turn, are often compelled to use such tactics due to the market-driven TR 024 demands of modern journalism. Focusing on Slovenian media, the research examines the role AT–2 EG of clickbait, its origins, and the underlying business models that make it a necessary evil for me- IC02 dia survival. It delves into how these clickbait practices shift journalism away from objective C5 OM reporting toward a focus on sensationalism and marketing-driven content. Furthermore, the in online media. It investigates how the trust of readers is increasingly exploited by advertisers EN PLE 2 T, S This paper explores the urgent need to build resilience against the growing reliance on clickbait EM EO study assesses current self-regulatory measures in Slovenia, including the Slovenian Chamber UM of Advertising (SOZ) and the Slovenian Journalistic Honorary Tribunal (NČR), and explores the ICN public’s perception of clickbait. Through a questionnaire (N = 150), the research seeks to under AT -ION regulations are needed to counter its negative impact on journalism. This study highlights the ANA importance of fostering resilience against such tactics to preserve the integrity and credibility of stand whether citizens recognize the prevalence of clickbait and whether they believe stronger M EMG the media. EN Keywords: Resilience, Clickbait, Media regulation, Online advertising, Market-oriented journal- T, W ism, Commercialisation, Controversial tactics EB AND INFOR ATM ION EC T H NOL O IEG S 147 Pe 1 INTRODUCTION IN TE er-R R 1.1 Scoping and Problem Description N ev AT Recent analyses of Slovenian digital journalism show that the contemporary online news environ-ie IO w N ed ment is shaped by a rapid flow of information, intensified competition for audience attention and a A L S Pr growing reliance on audience metrics. Kaluža and Slaček Brlek (2020) demonstrate that real-time o CIE analytics now inform decisions about which stories are highlighted and how homepages are struc-ce N ed TIF tured, and that this can foster the growth of trivial and banal content as well as “controversial ways ing IC C of attracting audiences”, including clickbait headlines (Kaluža and Slaček Brlek 2020). Building on a s Bo O N broader historical perspective, Amon Prodnik (2020) shows that sensational and misleading head-ok FE R lines have long been tied to commercial pressures and the advertising-funded model of the press, : P EN R but that in the digital environment each click can be precisely measured and converted into adver-O CE I JE tising income, making clickbait a structurally attractive strategy for online media (Amon Prodnik T'S A CT M 2020). Taken together, these accounts suggest that the boundary between journalism oriented to-B A O wards the public interest and content primarily optimised for market performance is increasingly N U A T P G difficult to maintain. EM EO The widespread use of clickbait—sensational headlines or content crafted to provoke curiosity and EN PL E 2 drive traffic—has become a significant concern for media ethics. The reliance on metrics like clicks T, S TR 02 and views as key indicators of success places financial survival at the forefront, often compromis-4 AT –2 ing the integrity of journalistic practices (Scott, 2021). This shift from traditional, objectivity-focused EG IC 02 journalism to market-driven content threatens the credibility of news sources and undermines the C 5 OM trust of readers, as the lines between factual reporting and marketing blur (Hamada 2018). M As Poler Kovačič (1997) notes, the growing influence of advertisers, multinational corporations, U N IC and public relations firms on journalism leads to a gradual erosion of editorial independence. In AT this environment, clickbait tactics proliferate, often leading to exaggerated or distorted content ION designed to attract attention rather than inform. The challenge, therefore, is not just to recognize M the problem but to build resilience against these tactics in order to safeguard the quality and re A - N A liability of journalism. G EM This study aims to investigate the recognition of clickbait as a phenomenon in Slovenia and to evalu- EN ate the current regulatory frameworks in place to address its use. By examining the role of self-reg- T, W ulation and ethical codes in the Slovenian media landscape, this research seeks to explore the ur- EB A gent need for stronger measures to resist the commercialization of journalism and the negative N D impact of clickbait on public trust and media integrity. IN FOR 1.2 Purpose and Objectives of the Research M AT This study is situated within the field of communication studies, focusing on the critical analysis of ION contemporary media tactics and their influence on public communication. By addressing the grow - T EC ing concern of clickbait as a controversial tactic in online media, this research also incorporates H NOL Slovenian legal frameworks to explore the current state of regulation and legal accountability re- O garding online content. In addition, the study will delve into the role of online advertising in shap- G IE ing these media tactics, as content dissemination strategies in online platforms are often driven by S commercial interests. The primary goal of this research is to investigate whether the phenomenon of clickbait is recog-nized as a problem within Slovenia and to evaluate the legal landscape surrounding its use. The research will focus on the urgent need to build resilience against clickbait by highlighting its detri-mental impact on journalistic integrity and public trust. The specific objectives of the study are as follows: 1. To examine whether the clickbait phenomenon is recognized in Slovenia and how this lack of recognition contributes to the absence of a legal framework. 2. To explore how insufficient regulation of clickbait paves the way for the use of other controver- sial tactics in online media. 3. To emphasize the need for stronger legal and regulatory measures that can help build resilience against clickbait and protect the integrity of online journalism. 148 media environment. er-R RN evAT ieIO against controversial tactics like clickbait, fostering a more resilient and ethically responsible online Pe INTE By addressing these objectives, the study aims to underscore the critical need for a clear legal stance 2 THEORETICAL BASIS w N edAL S PrCIE In the evolving landscape of digital media, clickbait has emerged as one of the most controversial o ceN tactics, fundamentally reshaping how information is consumed online. Clickbait refers to sensa- edTIF tionalized headlines or misleading content designed to attract clicks and drive traffic, often without ingIC C critical to restoring trust in media and ensuring that journalism maintains its core principles of truth, : P EN R OCE I JE transparency, and public service.T'S A CT MB Clickbait operates by exploiting human curiosity (Loewenstein’s 1994, 75) and using exaggerated, creasing page views, its widespread use has led to significant concerns regarding the integrity and ok FER credibility of online journalism. The need to build resilience against clickbait and similar tactics is delivering on the promises made. While it has proven effective in generating ad revenue and in- s Bo ON often misleading headlines that compel users to click on the link. These headlines typically promise A O NU AT P G EM sensational, shocking, or highly emotional content, which may not be reflected in the article itself. EO ENPL According to Scott (2021, 56) and Chen et al. (2015, 15) this tactic thrives on the “curiosity gap,” a E 2 T, S psychological trigger that motivates people to seek closure by clicking on content that purports to TR024 answer an intriguing question or offer critical information. AT–2 EG This process of exploiting this gap is best described in a step-by-step model in Bazaco et al. (2019, IC02 C5 98–99) OM Table 1: Analytical model for the defining variables of clickbait UM N ATIC ION M ANAGEMENT, W EB AND INFOR ATM ION EC T H NOL O IEG S (Source: Bazaco et al. 2019, 98– 99) While clickbait may result in high engagement rates, it diminishes the value of the content itself, prioritizing profit over meaningful, well-researched reporting. Although ‘clickbait’ can bring more attention in the short term, research shows that such content does not provide substantial business benefits and can lower a news outlet’s perceived credibility; in advertising-driven models, news-rooms therefore often sacrifice content quality for reach. (Muddiman & Scacco 2019; Filloux 2016; McManus 1994) 149 er-R R engagement as their primary metrics for success. This has led to a focus on short-term gains, of-N ev AT ten at the cost of journalistic integrity (Filloux 2016; McManus 1994). Journalists and editors, faced ie IO Pe IN advertising revenue wanes, news organizations have increasingly turned to page views and user TE The rise of clickbait is symptomatic of the financial pressures on digital media outlets. As traditional w N with the challenge of generating revenue in an oversaturated digital market, are often pushed to ed A L S Pr prioritize viral content over substantive reporting. Research shows that while sensational, ‘click-CIE o bait’-style headlines can capture short-term attention, they are associated with lower perceived ce N ed credibility and diminished assessments of journalistic quality—pressuring outlets to privilege atten-TIF ing IC C tion over more balanced, thoughtful reporting (Muddiman & Scacco 2019; Molyneux & Coddington R EN exposure to misleading or exaggerated headlines—often packaged as clickbait—erodes confidence O CE I JE in news outlets by lowering perceived credibility and contributes to broader distrust across the me-T'S A CT M dia ecosystem (Muddiman & Scacco 2019; Molyneux & Coddington 2020). This erosion of trust ex-B A ok FER The prevalence of clickbait has a detrimental impact on the public’s trust in journalism. As Repeated : P s Bo O 2020; Jung et al. 2022). N N O tends beyond individual news organizations to the broader media ecosystem. Evidence shows that U A T P G exposure to misleading or clickbait-style headlines reduces perceived credibility and can spill over EM EO into lower trust in news more broadly, reinforcing a cycle of skepticism that weakens the media’s EN PL E 2 public-forum role (Muddiman & Scacco 2019; Molyneux & Coddington 2020). This creates a cycle of T, S distrust that undermines the ability of the media to serve as an informed, democratic public forum. TR 02 4 AT –2 Building resilience against clickbait requires a multifaceted approach. First, media literacy must be EG IC 02 emphasized to help audiences recognize and resist misleading headlines. Educating readers on C 5 OM how to critically evaluate the credibility of sources and the quality of information is essential to M reducing the impact of clickbait (Council of Europe 2023; Guess et al. 2020; Moore & Hancock 2022; U N Jones-Jang et al. 2021; Kanižaj et al. 2022). Second, media organizations must reevaluate their busi - IC ness models. As online ad revenue ties payouts to traffic metrics like pageviews, many publishers AT ION optimize for attention—fueling the use of sensational, ‘clickbait’-style headlines at the expense of M quality (Christin 2018). By diversifying revenue streams and investing in quality journalism, outlets A N A can prioritize substance over sensationalism. Lastly, stronger regulatory frameworks are needed to G ensure that ethical standards are upheld in digital media. As Poler Kovačič and Kerševan (2020), EM EN Čufar (2021) suggest, self-regulation within the media industry, combined with external oversight, T, W can help mitigate the harmful effects of clickbait and protect the public interest. EB In conclusion, clickbait represents a significant threat to the credibility and trustworthiness of online A N journalism. Its prevalence underscores the need to build resilience against these controversial tac- D IN tics through public education, ethical media practices, and regulatory efforts. By prioritizing integri - FOR ty over profit and fostering critical media literacy, society can better navigate the complexities of the M digital age and ensure that journalism remains a pillar of democracy. AT ION 2.1 Lack of proper regulation of online media T EC H NOL The lack of proper regulation in online media, particularly concerning clickbait, is a significant is - O sue that undermines the credibility and integrity of digital journalism. As noted in the preceding G chapter, clickbait remains a poorly defined phenomenon, especially in Slovenia, where it is not rec- IE S ognized in the national dictionary (SSKJ) nor universally acknowledged as a specific online media tactic. This lack of a clear, unified understanding of clickbait complicates the challenge of regulating it effectively. Without a formal legal definition, it becomes difficult to regulate clickbait in a way that ensures accountability and safeguards journalistic standards. Kristina Čufar’s work Legal Aspects of Content Moderation on Social Networks in Slovenia (2021) offers a partial understanding of clickbait, defining it simply as flashy headlines designed to attract atten-tion and clicks, often followed by inconsequential content. Čufar suggests that while clickbait does not necessarily spread misinformation, it can contribute to the spread of disinformation and infringe on personal rights, especially when readers consume information uncritically. However, this defi-nition fails to account for the broader context in which clickbait operates, particularly its role as an advertising tactic rather than merely a journalistic tool. This distinction is critical, as clickbait often stems from the marketing-driven objectives of online media outlets, prioritizing revenue genera-tion over ethical journalism (Poler Kovačič 2002). 150 Media Law (ZMed), which imposes certain obligations and penalties. However, online content, es- w N edA pecially content published by social media platforms, remains largely unregulated. The fact that L S PrCIE social networks like Facebook are not subject to the same regulatory oversight as traditional media o ceN creates a significant gap in the legal system. edTIF ingIC C An illustrative example of clickbait can be seen in a post by the Slovenian online media outlet Siol.net, s BoO published on Facebook. This misleading post showcases the challenges posed by the “double nature” N okFE of online media, where traditional media operate within Slovenia’s legal framework while platforms R : PEN like Facebook, based in the United States, adhere to their own set of rules. Due to the lack of clarity in dia regulations remain consistently behind the development of social networks and the corporate er-R RN evAT practices of online platforms (Čufar 2021, 188). Traditional media in Slovenia are governed by the ieIO does not adequately address the issue of clickbait. As Čufar observes, Slovenian and European me Pe IN -TE The research into Slovenia’s media and legal landscape reveals that the country’s legal framework O CE I R Slovenian and European legislation, the Siol.net post does not violate any existing laws or regulations. JE T'S A CT The example we have obtained for the purpose of showing the nature of clickbait is a post by the MB AO online media Siol.net on Facebook. NU AT P G EMEO Figure 1: Example of clickbait on Siol.net ENPLE 2 T, S TR024 AT–2 EG IC02 C5 OM M U N ATIC ION M ANAGEMENT, W EB AND INFOR ATM ION EC T H NOL O IEG S (Source: Facebook page of Siol.net Novice, obtained on December 18, 2023) The issue of regulating clickbait is further complicated by the reliance on self-regulation. Čufar sug-gests that social networks should take more responsibility for the content they host, advocating for increased transparency and user control over the algorithms that dictate the content they see (Čufar, 2021). Meanwhile, Zhou (2021), Kerševan Smokvina and Poler Kovačič (2020, 194) and Čufar (2021) argue that the responsibility should be placed on the individual, promoting rational thinking and media literacy to help users critically evaluate content. However, both views share the recognition that regulation by technology companies alone is unlikely to address the problem of clickbait with-out significant changes to business models and media practices. 151 w N to clickbait, as evidenced by the lack of official recognition or legal action against such practices. ed A L S Pr Even institutions like the Slovenian Advertising Arbitration Court (SOZ) and the Journalistic Honorary CIE o Tribunal (NČR) do not address clickbait as a legal or ethical issue. ce N ed TIF In conclusion, the absence of clear regulation in the Slovenian legal framework, coupled with the ing IC C reliance on ineffective self-regulation, creates a significant gap in the media landscape. To tackle s Bo O N the issue of clickbait, Slovenia must develop more robust regulations that address the complexities ok FE R of online content, ensuring that media outlets and social networks are held accountable for their : P EN R er-R R ulation is crucial, but its effectiveness depends on widespread acceptance and public awareness. N ev AT Unfortunately, self-regulation in Slovenia’s digital media space is largely ineffective when it comes ie IO Pe IN its voluntary nature and the lack of enforceable sanctions. The industry’s commitment to self-reg-TE Kerševan Smokvina and Poler Kovačič (2020) highlight that self-regulation is problematic due to JE to empower users to recognize and resist clickbait, ultimately reducing its influence in the digital T'S A CT M O CE I practices. Furthermore, a stronger emphasis on media literacy and public awareness is necessary A T P G 3 EMPIRICAL RESEARCH EM EO EN PL E 2 3.1 Summary of the study T, S TR 02 4 A BO NU media ecosystem. EG –2 online media. It assumes that clickbait is a deceptive practice originating from online advertising, 02 AT This study explores the growing need to build resilience against clickbait as a controversial tactic in IC which undermines public trust in media. The research highlights the absence of effective regulation C 5 OM and legal frameworks in Slovenia, where self-regulation is insufficient to address the problem. The M study’s theoretical section reviews contemporary journalism and the prevalence of clickbait, testing U N IC the hypothesis that it is not recognized as a significant issue in Slovenia. It also examines the current AT regulatory framework and its failure to prevent controversial tactics like clickbait. ION The empirical section of the study involves a survey (N = 150) we used a Likert scale to assess the fre- M A quency of clickbait exposure and public opinions on the need for stronger regulation. Using Spear- N A G man correlation analysis, the study tests the hypothesis that clearer legal regulation is necessary to EM control clickbait. The conclusions of the study suggest that effective regulation is essential to protect EN journalistic integrity and public trust, proposing solutions for better legislative frameworks and me- T, W dia accountability. EB A The research calls for greater resilience against clickbait through legal and regulatory measures that N D prevent its harmful impact on the credibility of online media. IN FOR 3.2 The results M AT ION 3.2.1 Introduction EC T This research investigates the absence of appropriate regulations concerning clickbait in Slovenia’s H media space. The study confirms the following hypotheses: NOL O 1. Clickbait is widely present and recognized as misleading content. IEG 2. There is a general public consensus that clickbait contributes to misinformation. S 3. A clearer legal framework is required to regulate online media tactics. 3.3 Research Methodology A survey with 150 participants was conducted through the portal https://1ka.arnes.si/. The survey was divided into three sections: 1. Clickbait recognition (Q1 - Q6) 2. Regulatory awareness and need for intervention (Q7 - Q9) 3. Demographics (Q10 - Q12) 152 3.4 Key Findings - ev RNAT Q1 : 88% of respondents have encountered clickbait and identified it as misleading. ieIO w 3.4.1 Clickbait Recognition TE er -R Pe IN Figure 2: How many people has encountered with clickbait? ed NAL S Pr ce N ed o CIE ing TIFIC C ok FER : P s Bo ON R EN O CE I CTJE T'S A N OU AT P A B M EMG EN PLE 2 T, SEO TR 024 AT–2 EG IC02 C5 OM M U N ATIC (Source: Author’s own research. This applies to all subsequent figures.) ION M - AN Q2 : Among those who encountered clickbait, 53% reported frequent encounters, and 35% re -AG ported occasional encounters.EMEN Figure 3: Frequency of encounters with misleading newsT, W EB AND INFOR ATM ION EC T H NOL O IEG S 153 - Q3: 48% of respondents come across clickbait several times a day, closely aligning with Q2 findings. -R RNAT ev ieIO w er TE Figure 4: Frequency of encounters with clickbait Pe IN ed NAL S Pr ce N ed o CIE ing TIFIC C ok FER : P s Bo ON R EN O CE I CTJE T'S A N OU AT P A B M EMG EN PLE 2 T, SEO TR 024 - Q4: 58% of respondents avoid clicking on clickbait content. AT Figure 5: How often they avoid clicking on clickbait –2 EG IC 02 C 5 OM M U N ATIC ION M ANAGEMENT, W EB AND - Q5: 77% reported encountering clickbait in Slovenian media, a high percentage compared to the IN 88% for all web content. FOR ATM Figure 6: Frequency of clickbait in Slovenian media ION EC T H NOL O IEG S 154 - Q6: Most respondents agreed that clickbait contributes to misinformation. Figure 7: Clickbait headlines/content contribution to the spread of misinformation TE er -R Pe IN ie IO wN edAL S PrCIE ev RNAT ceo ed TIFN ing IC C ok FER : P s Bo ON R EN O CE I CTJE T'S A N OU AT P A B M EMG 3.4.2 Regulatory Needs EN PLE 2 T, SEO - Q7: 124 out of 150 respondents (82.6%) believe stricter regulations are necessary. TR 024 AT–2 Figure 8: Stricter regulations should be put in place to deal with clickbait in Slovenian media EG IC02 C5 OM M U N ATIC ION M ANAGEMENT, W EB AND INFOR ATM - Q8: Only 4% believe current regulatory authorities adequately address clickbait. ION Figure 9: Sufficiency of clickbait treatment in Slovenia EC T H NOL O IEG S 155 er TE-RRN - 33% support a clear legal definition of clickbait. ev AT ie Pe IN - 41% advocate penalizing sites using clickbait.- Q9: Respondents suggested various regulatory measures: w ION Figure 10: Regulatory measures that would be effective in combating clickbait ed A L S Pr CIE o ce N ed TIF ing IC C ok FER : P s Bo ON R EN O CE I CTJE T'S A N OU AT P A B M EMG TR 02 3.5 Statistical Analysis 4 AT –2 EG The study used Spearman correlation analysis to examine the relationship between experiencing IC 02 C 5 clickbait (Q5) and supporting stricter regulations (Q7). The correlation coefficient (0.968) indicates a OM very strong positive correlation, confirming that those who frequently encounter clickbait strongly EN PLE 2 T, SEO U support regulation. M N ATIC 3.6 Conclusion ION AN ents believe that clickbait spreads misinformation and that current regulations are insufficient. A M The study confirms that clickbait is a significant issue in Slovenian media. The majority of respond- G Most respondents support stricter legal measures, including penalties and clearer definitions. Given EM the strong statistical correlation, the study concludes that Slovenia needs an improved regulatory EN T, W framework to address clickbait in online media. EB AN 4 DISCUSSION D IN The growing prevalence of clickbait in online media represents a significant challenge to the in-FOR tegrity of journalism, with its roots deeply tied to the commercialization of the industry. As Poler M AT Kovačič (2003) emphasizes, the commercialization of journalism, driven by oversaturation of con-ION tent, has led to a deprofessionalization of the field. This process undermines the core values of jour- T EC nalism, including objectivity and investigative rigor. According to Poler Kovačič (2003), experienced H NOL journalists warn that the commercialization of journalism could lead to the decline of investigative O reporting, which, despite its value, no longer captivates the contemporary audience. The rise of IEG clickbait, a tactic designed to maximize clicks and engagement, exacerbates this issue by prioritiz- S ing sensationalism over substantive content. Kaluža and Slaček Brlek (2020) further show that in a 24/7 digital production cycle the homepage of a news site must be continuously updated so that returning users are repeatedly presented with new stories, a pressure that has intensified with the rise of mobile access and short, frequent visits (Kaluža and Slaček Brlek 2020). Web analytics play a central role in this process: editors monitor clicks, reading time and user paths through the site in order to decide which items to move up or down the page and how to adjust titles and formats. While such metrics can help refine the user experience, the authors stress that in tightened market conditions they are never neutral; they in-crease the temptation to prioritise highly clickable content, to produce clickbait and to shift attention towards popular topics that are not necessarily the most relevant, thereby encouraging the spread of trivial and banal content and controversial ways of attracting audiences (Kaluža and Slaček Brl-ek 2020). This diagnosis resonates with broader critiques of the commercialisation of news, which 156 model, pointing out that the industry’s reliance on advertising revenue has led to a situation w N edAL S where the content created is heavily influenced by market interests. Journalism, once a tool for in - PrCIE o forming the public, now operates within a market-driven framework where content must cater to ceN ed the interests of advertisers rather than uphold the ethical standards that have traditionally guided TIF ingIC C the profession. This transformation of journalism into a market-oriented enterprise contributes s BoO to the rise of clickbait as a controversial and manipulative tactic, undermining its credibility and N okFE ethical foundations.R : PEN Analysts argue that falling ad revenues pushed many outlets to optimize for pageviews and en- 2020; Vobič 2021; Pickard 2020). er-R RN evAT Fisher (2021) raises critical questions about the current definition of journalism and its funding ieIO value rather than normative standards such as truthfulness, relevance and independence (Splichal Pe INTE argue that journalism is increasingly evaluated according to engagement metrics and advertising O CE I R gagement, encouraging clickbait tactics and short-term gains at odds with editorial standards (Fil- JE T'S A CT loux 2016). Contend that the commercialization of journalism has led the industry to the “ethical MB AO brink,” where practices like clickbait pose serious challenges to journalistic integrity (Pickard 2020; NU AT P G McManus 1994; Esser 1999; ONA Ethics). As journalists are increasingly driven to produce high vol- EMEO umes of content to meet the demands of the digital advertising economy, the pressure to deliver ENPLE 2 sensationalized headlines intensifies. This process inevitably erodes the quality of journalism, as the T, S pursuit of clicks and engagement supersedes the production of accurate, reliable news. TR024 AT–2 This thesis has explored the implications of clickbait in the Slovenian media landscape, demonstrat- EG IC02 ing that the phenomenon is not sufficiently recognized or regulated within the existing legal and C5 OM regulatory frameworks. The research revealed that both the Zmed and regulatory bodies like the NČR have not adequately addressed clickbait as a distinct issue. This oversight allows clickbait to MUN thrive unchecked, further complicating efforts to protect journalistic integrity.ICAT Through empirical research, this thesis has confirmed that Slovenian media consumers are highly ION aware of the misleading nature of clickbait and overwhelmingly support stronger regulations to M combat it. The results of the survey indicate that the public perceives clickbait as a harmful tactic that ANA spreads misinformation, calling for clearer definitions and more robust regulatory measures.GEM In conclusion, building resilience against clickbait in online media is essential to protect the ethical EN values of journalism. The commercialization of journalism has led to the rise of clickbait as a contro-T, W versial tactic that undermines trust in the media. As the findings of this research indicate, stronger EB A regulations, clearer legal definitions, and a commitment to journalistic ethics are crucial in curbing ND the influence of clickbait. 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O CE I Conference on Social Development and Media Communication 2021, 1544–1547. Atlantis Press. CTJE T'S A N OU AT P A B M EMG EN PLE 2 T, SEO TR 024 AT–2 EG IC02 C5 OM M U N ATIC ION M ANAGEMENT, W EB AND INFOR ATM ION EC T H NOL O IEG S 160 THE PERCEPTION OF THE STRUGGLE FOR w N edAL S Pr o WOMEN’S RIGHTS ON SOCIAL MEDIA: CIE ceN edTIF ATTITUDES OF USERS IN CROATIA ingIC C s BoONFE ok Lana Novoselac, MAR : PEN R Published scientific conference contribution Pe INTE 1.08 Objavljeni znanstveni prispevek na konferenci er-R RN evAT ieIO Tanja Grmuša, PhD, Assistant Professor O CE I JE Zagreb School of Business, Croatia T'S A CT MB AO NU AT P ABSTRACT G EMEO EN The struggle for women’s rights represents a very long and complex story about achieving equal -PLE 2 T, S ity for women that can be observed in different contexts - individual, economic, educational, TR02 professional and social. With the development of social networks, it seems that the topic of 4 AT–2 women’s rights is more present in the media space, but also in people’s minds. At the same time, EG IC02 social networks are increasingly used for social activism in order to draw attention to the position C5 OM of vulnerable groups in society, but also to strengthen the resistance of social network users to M the use of socially harmful forms of communication such as sexism and hate speech. The paper is U N IC divided into two parts - theoretical and research. The theoretical part of the paper analyzes the AT significance of the concept of gender equality, as well as the issue of the struggle for women’s ION rights in the real, but also in the virtual environment. Furthermore, an analysis of the role of so- M cial networks in monitoring social unrest in Iran in 2022 following the death of Mahsa Amini as a ANA consequence of the global struggle for women’s rights is also presented. The second part of the GEM paper presents the results of a study aimed at investigating user preferences for the use of social EN networks in Croatia, users’ perceptions of the struggle for women’s rights in Iran, and the role of T, W social networks in monitoring the aforementioned case. The study was conducted using an on-EB line survey questionnaire in 2022 on a sample of 118 respondents. The results showed a positive AN correlation between social networks and the struggle for women’s rights, as well as that the D IN majority of respondents see social networks as an important channel for spreading awareness FOR about gender equality.MAT Keywords: Gender equality, Social networks, Attitudes, Users, SurveyION EC T H NOL O IEG S 161 Pe 1 INTRODUCTION IN TE er-R R The topic of this paper is the role of social networks in the fight for women’s rights as one of the N ev AT longest-standing and most important topics in the social sciences, encompassing a wide range of ie IO w perspectives - from women’s individual autonomy to social and institutional equality. The first part N ed A L S of the paper is based on a theoretical framework that encompasses the state of women’s rights in Pr the real environment, then the fight for women’s rights in the virtual environment, and the social o CIE ce N unrest in Iran in 2022 as a consequence of the global fight for women’s rights. ed TIF ing IC C Social networks are an inevitable part of everyday life, and in addition to entertainment, they are ok FE power was recorded during the protests in Iran in 2022, sparked by the death of Mahsa Amini, when R : P s Bo O increasingly used as a tool in social activism and public mobilization. A special example of their N CT T'S A M The second part of the paper presents the results of a survey conducted among social network users B A O in Croatia. The aim of the research was to investigate user preferences for using social networks in N U A T P G O CE I darity and raising awareness about gender inequality. JE R EN the protests pointed to the key role of digital platforms in spreading information, encouraging soli- EM EO monitoring the aforementioned case. The research was conducted using an online survey question-EN Croatia, users’ perceptions of the fight for women’s rights in Iran, and the role of social networks in T, S PLE 2 naire in 2022 on a sample of 118 respondents. TR 024 AT–2 2 THEORETICAL FRAMEWORK EG IC 02 C 5 The theoretical framework is divided into three main thematic units: women’s rights in the real en-OM vironment, the struggle for women’s rights in the virtual environment, and social unrest in Iran as a M U consequence of the global struggle for women’s rights. N IC AT 2.1 Women’s rights in the real world ION M Prejudice and discrimination against an individual based on their sex or gender is a behavior that A N A is unfortunately often observed in modern society. It affects all spheres of society, from institu - G tions and governments, to private and interpersonal relationships. Given the common occurrence EM EN of sexist behaviors in society, it can be said that it has consequently greatly influenced women’s T, W rights. When it comes to professional development, women often earn less than men in the same EB or similar positions, which is the result of systematic differences in salaries and promotions in the A N workplace. Assumptions or beliefs according to which women and men should behave or look are D the result of deeply rooted values, attitudes and norms in society, and serve to justify and maintain IN FOR historical relations between men and women, i.e. relations in which men have dominance over ATM women, which prevents progress in terms of gender equality. Gender stereotypes are closely linked ION to violence against women (Bates 2019; Barilli, Grembi & Rosso 2021), stereotypical notions of mas- EC ket (Rosenfeld & Kallenberg 1991; Blau 2024) and encourage further marginalization of women H NOL T culinity and femininity negatively affect all genders, promote women’s inequality in the labor mar- and other groups, and also influence the portrayal of women in the media and the spread of hate O speech (cf. Dujmović 2020). G IES Furthermore, the difference in the portrayal of women and men in the media is more than obvious (Žene i mediji 2020), while men are mostly masculine, muscular, superior and ready for conquering new challenges, the portrayal of women is reduced to different parts of her body or presents certain ideals of beauty in order to “sell” a certain product or service (Giles 2003; Globan, Plenković & Var-ga 2018). By continuously reinforcing gender stereotypes in the media, society internalizes them, shaping an image of women that is often inaccurate or not representative of all individuals of that gender. However, once these gender stereotypes become entrenched in the minds of the recipient, they are very difficult to change, and a “manipulated” image of a woman can have harmful conse-quences on the recipient and their perception of themselves and their environment (Bubalo & Jelić 2015), and thus on the system of values that we cherish as a society (cf. Lubina & Brkić Klimpak 2014: 214). What can be said with certainty is that the presentation of women in the media (Sever & Andraković 2013; Car et al. 2017) is a reflection of their position in contemporary society - a society that is still 162 2.2 The fight for women’s rights in the virtual environment w N edAL S Pr Women are generally underrepresented in the media, and the emergence of social media has also oCIE created an opportunity for a more equal distribution of representation, thus providing women of ceN ed different backgrounds and appearances with a space in which their voices can be heard: TIF ingIC C “Social media has the potential to advance the feminist movement by giving women’s rights s BoON issues greater visibility, enabling effective communication, helping people organize, edu - okFER cating about women’s history and current events, and inspiring people to fight for greater as sexual objects, and thus their own identity is taken away. er-R RN evAT ieIO these principles and needs. For this reason, women are subordinate to men, most often portrayed Pe INTE patriarchal and in which male principles and needs come first, while the role of women is to satisfy The social media phenomenon #MeToo is a global social movement that emerged in response to equality for all. However, social media can also potentially endanger the movement by ex : P EN R - OCE I JE posing it to online harassment and misinformation, constant comparison with others, and a T'S A CT distorted image of one’s own body due to imposed beauty standards and weakened critical MB AO thinking.” (Kamei 2022) NU AT P G EMEO the high prevalence of sexual assault and harassment in today’s society, especially in the workplace ENPLE 2 (Zhang et al. 2020), which could lead to revolutionary cultural changes, as stated by Cossins (2020). T, S TR02 It highlighted sexism in many industries and gave women a platform to speak out about sexual 4 AT–2 assault. The movement became globally visible in 2017 when many women, but also men, dared EG IC02 to share their experiences on social media (Stubbs-Richardson et al. 2023). The movement has also C5 OM sparked numerous discussions about consent to sexual acts, patriarchal patterns of power and its M abuse, and the importance of providing support to victims of sexual violence and/or harassment. U N Many celebrities and people in positions of power in various industries (Field et al. 2019; Franssen IC AT 2020) have been accused of sexual assault after victims decided to go public with their stories (Field ION et al. 2019). M As a result, the movement has sparked major changes around the world, with the number of peo- ANA ple coming forward with their experiences of sexual harassment raising awareness of the pressing GEM issue. This is evidenced by the increase in Google searches for the terms sexual harassment and sex-EN ual assault (Kaufman et al. 2021), as well as the growth in media interest in the topic, although the T, W way in which coverage is monitored varies depending on editorial policy and context (Ghosh et al. EB 2022). However, the greatest impact that the #MeToo revolution has had is cultural (Cossins. 2020), AN although the perception of the revolution by gender differs, as do the motives for joining it (Men -D IN egatti et al. 2022). Thanks to the stories of brave women, people have realized how widespread FOR sexual harassment really is and how big a problem it is in society, other women have finally realized M that they are not alone and that they can share their story with others, and people who have not en-ATION countered this form of violence so far have realized that their numerous acquaintances, colleagues, T family members - unfortunately, have (cf. North 2019). The #MeToo movement is still active, and ECH continues its fight for social change regarding sexual abuse and harassment, both in the workplace NOL and in other life situations. OGIE 2.3 Social unrest in Iran as a consequence of the global struggle for women’s rightsS In recent years, Iranians have been protesting across their country, resisting the government’s rad-ical moves, and the protests, which have been surprisingly long-lasting and led by women, have been triggered by the death of a young girl named Mahsa Amini; Mahsa was arrested for not wear-ing a hijab (Arafat & Khamis 2025) (a hair covering, mandatory for all women in Iran), and was de-clared dead after three days in custody. Given the unclear circumstances of the young girl’s death, the unrest quickly spread to the rest of the country, and grew into the largest demonstrations in re-cent years. The Iranian authorities have been particularly brutal in their efforts to quell the protests - the police have responded to the protests with gunfire and tear gas, and the media has reported the presence of bloodshed on campuses. At the same time, they are trying to downplay the serious-ness of the situation by controlling the media, and the BBC and other independent media outlets are prohibited from reporting from Iran (cf. BBC 2023). 163 er-R R to exchange opinions, ideas and openly criticize the regime under which they live (Alami Fariman & N ev AT Hakiminejad 2024), and that is exactly why the authorities control them in detail and occasionally shut ie IO Pe IN are of great importance during demonstrations in Iran (Marks 2023) because they allowed people TE Despite or perhaps because of media control, censorship, and internet shutdowns, social networks w N down access to the Internet. The biggest role of social networks during the demonstrations in Iran is ed A L S Pr the development of the feminist idea (Cai 2023) and the strengthening of transnational digital activ-CIE o ism in the fight against the violation of women’s rights (Elmore 2024). On the other hand, it is creating ce N ed an opportunity for humanity to witness such events and thereby calls for solidarity on a global level, TIF ing IC C while on the level of Iran it encourages action and mobilization, but it would be unrealistic to expect ok FER : P s Bo O social networks to shape the movement and determine its direction. (cf. Alterman 2022). N O CE I R EN 3 RESEARCH METHODOLOGY CTJE T'S A The conducted research examined user preferences for the use of social networks in Croatia, users’ A B M N U AT P aforementioned case. G O perceptions of the fight for women’s rights in Iran, and the role of social networks in monitoring the TR The objective of the conducted research is to gain insight into the attitudes and experiences of re- 02 4 AT spondents regarding social networks, gender equality and the state of women’s rights in Iran. With –2 EG IC 02 the help of the survey, the aim is to check the habits of respondents as users of social networks, C 5 how respondents perceive the struggle for women’s rights in Iran and how they perceive the role of OM social networks themselves in this struggle. The research questions that underlie the research itself EN 3.1 Objective and research questions PL E 2 T, S EM EO AT 1. What is the role of social networks in today’s society? ION 2. What is the connection between social networks and the fight for women’s rights? M 3. What is the role of social networks in spreading awareness about the problem of inequality? A N U are as follows: N IC M A 4. How do social network users in Croatia perceive the fight for women’s rights in the example from G EM Iran? EN T, W 3.2 Hypotheses EB A Given the previously stated subject of the research and the research questions, suitable research N D hypotheses were set and tested as part of the research. IN FOR The main hypothesis in the research is the following - H1: There is a positive connection between ATIONM social networks and the fight for women’s rights. In addition to the main hypothesis, auxiliary hypotheses were set: EC T H1.1. The fundamental role of social networks in today’s society is to inform users. NOL H1.2. Social networks have become a platform for the fight against inequality in society. H O H1.3. Social network users in Croatia actively follow the case of the fight for women’s rights in Iran, G IE thus supporting the movement to stop violence against women. S 3.3 Method and sample The study involved 118 respondents from the Republic of Croatia aged at least 18 to 55+. The data was collected via an online survey, and the questionnaire consists of 3 groups of questions. The first group of questions are socio-demographic, the second group of questions examines habits, and the third group of questions examines the attitudes and opinions of the respondents on the fight for women’s rights and the current situation in Iran. 3.4 Analysis of the research results This research included five different age groups – 18-25 years, 26-35 years, 36-45 years, 46-55 years and 55+ years. Of the total of 118 respondents who participated in the research, 63.6% were female and 36.4% were male. The largest number of respondents had completed high school, 38.1%, fol- 164 90% of respondents have profiles on social networks, of which 48.3% of respondents spend up to w N edAL S an hour a day on social networks, 39.8% between two and three hours a day, and only 11.9% of PrCIE o respondents spend more than three hours a day on social networks. Over 60% of respondents do ceN ed not follow the topic of gender equality on social networks, of the almost 40% of respondents who TIF ingIC C follow this topic - 4.2% of respondents follow it daily, 19.5% several times a week, 29.7% several s BoO times a month. 46.6% of respondents do not follow this topic on social networks at all.N okFER Finally, the third group of questions focuses on the social unrest in Iran, the perception of the fight : PEN for women’s rights in Iran by users in Croatia, and the role of social networks in following the afore- graduate doctoral studies. er-R RN evAT The next group of questions examines the participants’ habits as users of social networks. More than ieIO undergraduate studies (professional and university), and only 0.8% of respondents completed post- Pe INTE lowed by 37.3% with postgraduate studies, an equal number of respondents, or 11.9%, completed O CE I R mentioned case. The first question in this set is: How well are you informed about the events in Iran JE T'S A CT in the last few years (murder of Mahsa Amini, street protests, fight for equality)? 33.9% of respond - MB AO ents estimated that they are well informed on the events in Iran, an equal number of respondents NU AT P G (33.1%) have a neutral opinion, i.e. they believe that they are neither informed nor not informed, EMEO 22.9% believe that they are poorly informed of the situation, and only 10.2% think that they are very ENPLE 2 well informed on the events. The next question shows how ignorant the respondents are about the T, S situation, considering that only one person said that they follow what is happening in Iran every TR024 day, the largest number of respondents, as much as 59.3% do not follow current events at all, 27.1% AT–2 EG follow on a monthly basis, and 12.7% on a weekly basis. IC02 C5 OM What is interesting is that in almost half of the respondents, this type of announcement arouses a feeling of powerlessness (47.5%), 21.2% feel a desire to participate, 16.1% are indifferent, and in MUN 15.3% of the respondents, it arouses anger or aggression.ICATION Figure 1: Frequency of following the events in Iran M ANAGEMENT, W EB AND INFOR ATM ION EC T H NOL O IEG S (Source: Author‘s work) 165 Figure 2: Respondents’ reaction to events in Iran er TE-R Pe IN ie IO wN edAL S PrCIE ev RNAT ceo ed TIFN ing IC C ok FER : P s Bo ON R EN O CE I CTJE T'S A N OU AT P A B M EMG TR 024 AT–2 (Source: Author‘s work) EG IC 02 C 5 OM The next question further confirms that respondents really feel powerless when it comes to this M EN PLE 2 T, SEO U topic, because when asked: “How did the posts about the events in Iran inspire you to take action?” AT to take action, 17.8% shared the posts on this topic on their profiles, and 5.9% went a step further ION and asked how they could help. IC they answered as follows - 76.3% claim that the posts about the events in Iran did not inspire them N M AN Most respondents consider topics such as gender equality, equality and discrimination to be very A G important (45.8%) or important (41.5%) topics, 8.5% have a neutral opinion, and 2.5% see them as EM less important topics, or 1.7% as unimportant topics. EN T, W Figure 3: Respondents’ actions regarding the events in Iran EB A N D IN FOR ATM ION EC T H NOL O IEG S (Source: Author‘s work) Regarding the visibility of events in Iran on social media, the majority of respondents consider it poor (48.3%), and 10.2% very poor. Then 36.4% consider it moderately visible, 4.2% good, and only 166 On the other hand, 49.2% of respondents agree that social media contributes to raising awareness w N edAL S about the problem of inequality, and 30.5% neither agree nor disagree with the statement. At the PrCIE o same time, 10.2% disagree with the statement, and 9.3% of respondents completely agree with the ceN ed statement. 0.8% of respondents disagree at all with the statement that social networks contribute TIF ingIC C to spreading awareness about the problem of inequality. s BoONFE Figure 4: Gender equality on social media okR : PEN R equality, while 12.7% disagree with the statement. Furthermore, 8.5% completely agree with the er-R RN evAT statement, and 0.8% completely disagree with the statement. ieIO ages dialogue on gender equality. 31.4% agree that social media encourages dialogue on gender Pe INTE 0.8% very good. 46.6% of respondents believe that social media neither encourages nor discour- O CE I CTJE T'S A N OU AT P A B M EMG EN PLE 2 T, SEO TR 024 AT–2 EG IC02 C5 OM M U N ATIC ION M (Source: Author‘s work) ANAGEMENT, W Figure 5: Raising awareness of the issue of inequality EB AND INFOR ATM ION EC T H NOL O IEG S (Source: Author‘s work) 167 er-R R ful information about the problem of women’s equality. Almost a quarter of respondents (24.6%) N ev AT maintained a neutral attitude and believe that there is no connection between social networks and ie IO Pe IN works and the fight for women’s rights is positive, that is, that social networks help in spreading use-TE In general, the majority of respondents (63.6%) believe that the connection between social net- w N the fight for women’s rights, and the smallest number of respondents (11.9%) see a negative con-ed A L S Pr nection because they believe that social networks help spread misinformation about the problem CIE o of women’s equality. ce N ed TIF ing Figure 6: The connection between social media and the fight for women’s rights IC C ok FER : P s Bo ON R EN O CE I CTJE T'S A N OU AT P A B M EMG EN PLE 2 T, SEO TR 024 AT–2 EG IC02 C5 OM M U N ATIC ION M ANA (Source: Author‘s work) G EM EN Finally, social media users in Croatia mostly perceive the fight for women’s rights, as in Iran, as nei-T, W ther important nor unimportant (38.1%), 33.1% consider it important, 21.2% less important, 4.2% EB unimportant, and only 3.4% of respondents consider it very important. A N D Figure 7: Perception of the fight for women’s rights through the example of Iran IN FOR ATM ION EC T H NOL O IEG S (Source: Author‘s work) 168 4 CONCLUSION Pe INTE Despite long-standing efforts to achieve gender equality, the struggle for women’s rights contin - er -RRN ues, with particular emphasis on access to healthcare, equality in the workplace, combating gen - evAT ieIO der-based violence, and reducing prejudice. Organizations and individuals continue to work to wN edA ensure gender equality and create a more inclusive society. The conducted survey confirmed the L S Pr hypothesis that there is a positive association between social networks and the struggle for wom- oCIE ceN en’s rights, but the auxiliary hypotheses were not confirmed. edTIF It is a fact that a large number of people consider social media to be a source of information, but it is ingIC C social media users in Croatia are actively following the fight for women’s rights in Iran, thus sup : P EN R OCE I - JE porting the movement to end violence against women, may be exaggerated. Social media enables T'S A CT M global connectivity and communication, but the majority of social media users actively follow and Although social media has often been used to raise awareness about social issues such as gender ok FER equality, activism on social media is limited to superficial engagement. Finally, the assumption that important to note that an equal number are aware that social media has become a marketing tool. s Bo ON participate in discussions on topics that are closer to their everyday lives. A BO NU AT P G EM Social networks provide undeniable value in connecting people and facilitating dialogue on im-EO ENPL portant topics, but they are only one of many tools in information and activism. In order to achieve E 2 T, S real changes in society, it is necessary to be aware of their limitations and the need to act outside TR024 the virtual space. AT–2 EG IC02 C5 OM M U N ATIC ION M ANAGEMENT, W EB AND INFOR ATM ION EC T H NOL O IEG S 169 Pe REFERENCES IN TE er 1. Alami Fariman, Mahsa, and Ahmadreza Hakiminejad 2024. Woman, Life, Freedom: Re--R R N ev AT volting space invaders in Iran. European Journal of Cultural Studies 28(5). https://doi. ie IO org/10.1177/13675494241268101. w N ed A L S 2. Alterman, Jon B. 2022. Protest, Social Media, and Censorship in Iran. 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Žena na javnoj televiziji - Slučaj informativnih emisija In M medias res i Otvoreno. Nova prisutnost: časopis za intelektualna i duhovna pitanja, XI (1): 5-21. U N Available at: https://hrcak.srce.hr/clanak/145116 (November 27, 2024). IC AT 27. Stubbs-Richardson, Megan, Shelby Gilbreath,, MacKenzie Paul & Audrey Reid. 2023. It’s a global ION #MeToo: a cross-national comparison of social change associated with the movement. Feminist M 28. Zhang, Dafang, Ashley L Pistorio, Diane Payne, Scott D. Lifchez, & American Society for Surgery of Media Studies, 24(6): 1330–1349. https://doi.org/10.1080/14680777.2023.2231654. ANAGEM the Hand Ethics and Professionalism Committee. 2020. Promoting Gender Equity in the #MeToo EN Era. The Journal of hand surgery, 45(12): 1167–1172. https://doi.org/10.1016/j.jhsa.2020.07.004. T, W 29. Žene i mediji. 2020. Stereotipni prikazi muškaraca i muževnosti u medijima izravno utječu EB A na živote žena. Available on: https://www.zeneimediji.hr/stereotipni-prikazi-muskara -ND ca-i-muzevnosti-u-medijima-izravno-utjecu-na-zivote-zena/ (December 23, 2024). INFOR AUTHOR BIOGRAPHIES MATION Lana Novoselac is an E-commerce Specialist in the aviation industry with a Master’s degree in Mar- T keting and Communications from the Zagreb School of Business. With a strong background in digital ECH marketing and a passion for the aviation sector, she is driven by the challenge of blending creativity NOL and technology to make meaningful connections and impact within the industry. OG Tanja Grmuša is an assistant professor and head of Marketing and Communication Department at IES the Zagreb School of Business. She also teaches at the Faculty of Croatian Studies at the University of Zagreb. Her scientific interests are: communication studies, intercultural communication, business communication, media management, journalistic practices and mass media effects. 171 w N edAL S Pr CRISIS COMMUNICATION IN HEALTHCARE: o CIE ce N IMPLEMENTING THE IDEA-COMMTRUST MODEL ed TIF ing IC C FOR TECHNOLOGICAL RESILIENCE s Bo O N FE ok R Stjepan Petričević, PhD : P EN R er-R RN evAT ieIO Pe IN Published scientific conference contribution TE 1.08 Objavljeni znanstveni prispevek na konferenci O Alma Mater Europaea University, Slovenia CE I JE T'S A CT M B A O ABSTRACT N U A T P G Health crises, such as pandemics and other public health emergencies, highlight the importance EM EO of effective crisis communication between healthcare institutions, the media, and the general EN PL E 2 T, S public. This paper explores the application of the IDEA-CommTrust model, developed to enhance TR 02 communication and strengthen trust between healthcare institutions and the public during 4 AT –2 health crises. EG IC 02 C 5 The IDEA-CommTrust model is based on an integrated approach that includes identifying key OM stakeholders, defining clear communication strategies, and utilizing technological tools to im-M U prove transparency and the availability of information. The focus of this paper is on technological N IC solutions such as chatbots, online platforms, and artificial intelligence systems that can be used AT to enhance community communication and reduce the “infodemic”—the spread of misinforma-ION tion that undermines public trust. M AN This review analyzes existing communication practices and provides guidelines for implement- A G ing the IDEA-CommTrust model in future crises, aiming to improve the resilience of healthcare EM systems and maintain public trust during times of crisis. The paper is grounded in literature and EN analysis of existing practices, contributing to an understanding of how technology and appropri- T, W ate communication strategies can enhance healthcare resilience. EB A N Keywords: Crisis communication, Public trust, COVID-19, IDEA-CommTrust, Technology, Health- D care resilience IN FOR ATM ION EC T H NOL O IEG S 172 1 INTRODUCTION Pe INTE Crises and emergencies, such as pandemics, require timely and effective communication to ensure er -RRN public safety and trust. Effective crisis communication facilitates informed decision-making, miti - evAT ieIO gates public fear, and enhances cooperation with public health measures (Plenković 2015). Re - wN edA search underscores that the absence of coordinated crisis communication allows misinformation to L S Pr spread, leading to increased uncertainty and public distrust (Bačić 2010). oCIE ceN Modern communication channels, including traditional media, social networks, and digital plat- edTIF forms, offer unprecedented opportunities to engage with the public. However, they also present ingIC C (Alhassan and AlDossary 2021). : P EN R OCE I JET'S A CT This paper presents the IDEA-CommTrust model as a structured approach to improving crisis com- MB munication in healthcare. By integrating strategic communication principles with technological ad- misleading (Avery 2010). The COVID-19 pandemic has demonstrated the crucial role of structured ok FER crisis communication in countering misinformation and fostering public trust in health authorities challenges, particularly in managing the rapid dissemination of information, both accurate and s Bo ON vancements, the model seeks to enhance public trust and resilience during health crises. A O NU AT P G EMEO ENPL 2 LITERATURE REVIEWE 2 T, S TR024 2.1 Crisis Communication and the Role of Media AT–2 EG IC02 Crisis communication in healthcare requires rapid, accurate, and transparent dissemination of infor - C5 OM mation to prevent panic and promote responsible behavior (Plenković 2015). Research has shown that the absence of coordinated crisis communication leads to the spread of misinformation, de- MUN creased institutional trust, and reduced public compliance with recommended measures (Bačić 2010).ICAT Both traditional and digital media play a key role in disseminating crisis information. Research by ION Avery (2010) found that individuals select communication channels based on their perception of cred- M ibility and personal preferences, with social media emerging as a dominant tool for crisis information. ANA However, social media platforms also facilitate the rapid spread of false information (Day et al. 2019).GEM The situational theory of problem-solving (Avery 2010) highlights how factors such as involvement, EN constraints, and problem recognition influence the choice of communication channels. Studies have T, W emphasized the need to understand how people select and process crisis-related messages to opti-EB A mize communication strategies.ND IN 2.2 Misinformation and the Infodemic PhenomenonFOR The World Health Organization (WHO) introduced the term “infodemic” to describe the excessive ION The COVID-19 pandemic has demonstrated the dangers of misinformation in crisis communication. MAT During the pandemic, conspiracy theories and misinformation spread rapidly through social media, ECH spread of both accurate and false information, which complicates crisis response efforts (WHO 2017). T NOL undermining trust in health institutions and reducing adherence to public health measures (Alhas-san and AlDossary 2021). One notable example was the controversy surrounding hydroxychloro- O IEG quine, which was publicly endorsed as a “game changer” by former U.S. President Donald Trump. S The media attention surrounding this claim led to global drug shortages, price spikes, and harmful self-medication practices (Anwar et al. 2020). This case highlights the urgent need for structured communication models that rely on verified scientific data to counteract misinformation. 2.3 The IDEA Model and Its Application in Crisis Communication Sellnow et al. (2017) introduced the IDEA model, which stands for Internalization, Distribution, Ex-planation, and Action, as a framework for improving crisis communication effectiveness. Their re-search demonstrated that messages structured according to this model enhance public risk percep-tion and motivate individuals to adopt protective measures. Sellnow-Richmond, Amiso, and Sellnow (2018) analyzed the application of the IDEA model during the Ebola epidemic and found that a combination of clear communication and proper channel selec-tion was critical for increasing trust and reducing uncertainty in crisis situations. 173 2.4 Development of the IDEA-CommTrust Model er TE Despite the effectiveness of the IDEA model, the analysis of crisis communication during the COV--R Pe IN ie IO challenges, the IDEA-CommTrust model was developed, expanding upon the IDEA model by em-w N ed A phasizing credibility, transparency, and engagement with diverse social groups (Petričević 2024). L S Pr CIE ev RNAT ID-19 pandemic revealed the need for a stronger emphasis on trust-building. As a response to these ce N cial government communication (Koronavirus.hr) and media reports, revealing significant discrep-ed o A comparative study of crisis communication practices during the COVID-19 pandemic analyzed offi- ing TIF ancies in message clarity and timeliness. Applying the IDEA-CommTrust model highlighted the im-IC C s Bo O portance of consistency in messaging, the use of multiple communication channels, and proactive N efforts to counter misinformation. ok FE R : P EN Implementing technological solutions such as AI-driven chatbots, real-time fact-checking tools, and R O CE I interactive online platforms can further enhance crisis communication in healthcare by ensuring JE T'S A CT timely information exchange and reinforcing public trust in health institutions. M B A O Existing research confirms that clear, transparent, and consistent communication strategies are es-N U A T P G sential for effective crisis management. The IDEA-CommTrust model provides a structured frame-EM EO work for improving crisis communication, particularly in the context of healthcare system resilience. EN PL E 2 The next section will outline the methodology used in the analysis of communication strategies T, S TR 02 during the COVID-19 pandemic. 4 AT –2 EG IC 02 3 METHODOLOGY C 5 OM This study employs a review and theoretical approach, relying on an analysis of literature and existing re-M U N search in the field of crisis communication in healthcare. The methodological objective is to explore the IC application of the IDEA-CommTrust model as a framework for improving communication during health AT ION crises and to identify technological solutions that can enhance the resilience of healthcare systems. M AN 3.1 Research Approach A G This paper is based on a review study that includes: EM EN- A literature analysis on crisis communication, public trust, and the application of technological T, W solutions in health crises, EB- A critical evaluation of existing crisis communication models, with a particular focus on the IDEA A N model and its enhancement through IDEA-CommTrust, D IN- The identification of recommendations for future crisis communication strategies in healthcare FOR systems. M AT ION 3.2 Data Sources EC T H This review study relies on secondary data sources, including: NOL Scientific papers and academic literature in the field of crisis communication, particularly those - O focusing on the application of the IDEA model, G IES - Documents from health institutions and regulatory bodies such as the World Health Organization (WHO), the European Commission, and national health authorities, - Empirical research and reports on communication strategies during the COVID-19 pandemic and other public health crises. 3.3 Analytical Framework The analysis is based on the theoretical framework of the IDEA-CommTrust model, which includes four key elements of crisis communication: - Internalization – how the public understands risks and threats,- Distribution – the effectiveness of selected communication channels,- Explanation – the clarity and consistency of messages, - Action – the impact on public behavior and compliance with recommended measures. 174 - Chatbots and automated systems for responding to public inquiries, w N edAL S Pr- Artificial intelligence for fact-checking and combating misinformation, oCIE- Digital platforms for direct interaction between healthcare institutions and the public. ceN edTIF ingIC C 3.4 Research Limitations s BoON Since this is a review study, its limitations include: okFER : P- Lack of primary data, as the paper relies on available literature and reports, strategies and their impact on public trust (Petričević 2024). er-R RN evAT Additionally, the study explores technological innovations in crisis communication, such as: ieIO atian healthcare system during health crises, where it was applied to analyze crisis communication Pe INTE The IDEA-CommTrust model was originally conceptualized in research on public relations in the Cro- R EN - Potential changes in technological trends, requiring continuous updates to the model, O CE I This paper provides a theoretical foundation for the application of the IDEA-CommTrust model in regulatory or institutional limitations. O NU AT P G EMEO health crises, with an emphasis on technological solutions that can enhance system resilience. The EN - Dependence on the quality and availability of sources, as some relevant data may be restricted by M B A CTJE T'S A analysis of literature and existing research enables the identification of best practices and recom PLE 2 - T, S mendations for future crisis communication strategies. TR024 AT–2 EG IC02 4 RESULTS AND DISCUSSION C5 OM 4.1 Key Findings MUNIC The analysis of crisis communication strategies during the COVID-19 pandemic reveals significant AT discrepancies in the timeliness, clarity, and consistency of information disseminated by official insti -ION tutions and media sources. Applying the IDEA-CommTrust model as an evaluative framework high- M lighted key strengths and weaknesses in communication practices, emphasizing the importance of ANA public trust, message consistency, and technological solutions in managing health crises.GEMEN 4.1.1 Internalization: Public Perception of RiskT, W One of the fundamental elements of effective crisis communication is ensuring that the public inter- EB A nalizes the severity of a crisis and understands the necessary protective measures. Studies indicate ND that clear, science-based messaging significantly improves public adherence to health recommen - IN dations (Sellnow et al. 2017). However, during the COVID-19 pandemic, conflicting messages from FOR For example, the case of hydroxychloroquine misinformation (Anwar et al. 2020) demonstrated ATION media sources and political figures often undermined this process. M ication, supply shortages, and severe health consequences. Similarly, the analysis of Saudi Arabia’s ECH how unverified claims can distort public understanding of risk, leading to inappropriate self-med- T Twitter-based crisis communication (Alhassan and AlDossary 2021) showed that public engagement NOL was highest when messages focused on reducing uncertainty, emphasizing scientific credibility, and OG reinforcing institutional trust. IES 4.1.2 Distribution: The Role of Media and Digital Platforms The distribution of crisis communication messages is crucial in ensuring broad accessibility and engagement. Social media platforms played a pivotal role in the COVID-19 pandemic, providing real-time updates and serving as a primary source of information for many individuals (Day et al. 2019). However, social media also facilitated the rapid spread of misinformation and conspiracy theories, undermining the credibility of official sources (Goggin and Ellis 2020). Findings indicate that government agencies and public health organizations that adopted multi-chan-nel distribution strategies – including social media, traditional media, and interactive digital platforms – were more successful in maintaining public engagement and countering misinformation. The Koro-navirus.hr initiative in Croatia, for instance, effectively centralized official updates, but lacked sufficient interactive features to directly address public concerns and misinformation (Petričević 2024). 175 4.1.3 Explanation: Clarity and Consistency of Messages er TE Effective crisis communication requires messages to be clear, consistent, and accessible to diverse -R Pe IN ie IO lights the importance of avoiding contradictory statements and ensuring that messages are cultur-w N ed A ally and linguistically adapted. L S Pr CIE ev RNAT populations. Research on communication strategies during past pandemics (Jones et al. 2010) high-ce N vealed significant inconsistencies. For example, variations in mask-wearing guidelines across dif-ed o However, during the COVID-19 crisis, an analysis of media reports and institutional statements re- ing TIF ferent countries led to public confusion and decreased compliance (Paek et al. 2008). Similarly, re-IC C s Bo O search on crisis communication for vulnerable populations (Crouse Quinn 2008) emphasizes that N disability-inclusive messaging and alternative communication formats were often overlooked, re-ok FE R : P sulting in limited access to crucial health information (Goggin and Ellis 2020). EN R O CE I JE 4.1.4 Action: Public Trust and Behavioral Compliance T'S A CT M B A O Trust in health institutions plays a central role in motivating public action during crises. The findings N U A T P support previous studies (Ransom 2007) that stress the importance of long-term relationship-build-G EM EO ing and transparent engagement with diverse communities to foster institutional trust. EN PL E 2 The IDEA-CommTrust model emphasizes the proactive inclusion of local community leaders, behav-T, S TR 02 ioral scientists, and crisis communication specialists to tailor messages that resonate with different 4 AT population groups (Parveen et al. 2016). The COVID-19 crisis demonstrated that governments that –2 EG IC 02 maintained open, two-way communication and involved civil society organizations in their mes- C 5 OM saging efforts had higher levels of public trust and compliance (Lin et al. 2016). U 4.2 Implications for Crisis Communication and Technological Resilience N M ATIC ION improve crisis communication in healthcare. Digital innovations such as AI-powered chatbots, au- Findings from the analysis underscore the urgent need for integrated technological solutions to A tomated misinformation detection tools, and real-time interactive platforms can significantly en M- A hance the effectiveness of public health messaging. N EMG T, W AI-powered tools, such as chatbots for public health inquiries, can improve the distribution of ver EN 4.2.1 The Role of Artificial Intelligence in Crisis Communication EB - A ified information and reduce the burden on healthcare professionals. During the pandemic, some IN misinformation, and provide localized health guidance (WHO 2020). However, these tools were un- FOR D governments integrated AI-driven virtual assistants to address frequently asked questions, debunk N M derutilized in many regions, leaving information gaps and increasing public reliance on unverified AT social media sources. ION EC T 4.2.2 Strengthening Trust through Transparent Communication NOL One of the key recommendations from this study is the need for continuous transparency in crisis H O communication. The IDEA-CommTrust model proposes that institutions should focus not only on G IE providing information but also on actively engaging with the public, responding to concerns in re- S al-time, and fostering an ongoing dialogue. 4.2.3 Addressing Vulnerable Populations through Inclusive Communication Strategies Crisis Communication strategies must be inclusive to ensure that linguistic, cognitive, and techno-logical barriers do not prevent certain groups from accessing life-saving information (Crouse Quinn 2008). Findings from past crises indicate that health institutions often fail to provide accessible con-tent for individuals with disabilities, non-native speakers, and marginalized communities (Goggin and Ellis 2020). Future crisis communication plans should integrate tailored outreach efforts that address the specific needs of vulnerable populations. 176 4.3 Summary of Key Findings trust, and technological adaptability. The IDEA-CommTrust model provides a framework for address- RNAT ev ing these challenges by integrating strategic message structuring, proactive misinformation man- ieIO w The results of this study confirm that effective crisis communication depends on message clarity, TE er -R Pe IN agement, and public engagement strategies. ed NAL S Pr Key recommendations include: oCIE ceN- Adopting multi-channel distribution strategies that leverage traditional media, social networks, edTIF and AI-driven tools. ingIC C - Building long-term trust through transparent and inclusive engagement with local communities EN R OCE I and key stakeholders. JET'S A CT- Integrating technological solutions such as automated misinformation detection systems and MB A- Ensuring message clarity and consistency across all communication platforms to minimize public s Bo ON confusion. ok FER : P - Prioritizing accessibility and inclusivity in crisis communication, ensuring that marginalized and AI-powered chatbots to enhance public health communication. O NU AT P G EMEO vulnerable populations receive timely and comprehensible information. ENPLE 2 The following section will present concluding remarks and recommendations for future crisis com- T, S TR02 munication frameworks in healthcare.4 AT–2 EG IC02 5 CONCLUSION AND RECOMMENDATIONS C5 OM 5.1 Conclusion MUNIC This study underscores the critical role of crisis communication in healthcare and highlights the ne-AT cessity of structured, trust-centered messaging during public health emergencies. The analysis of ION communication strategies during the COVID-19 pandemic demonstrates that clear, transparent, and M consistent messaging plays a crucial role in shaping public perceptions, fostering institutional trust, ANA and encouraging compliance with health measures.GEM The IDEA-CommTrust model, developed as an extension of the original IDEA framework, provides a EN structured approach to improving crisis communication by emphasizing four core elements:T, W - Internalization – ensuring that the public understands the risks and consequences of a crisis, EB A- Distribution – selecting appropriate communication channels for effective outreach,ND- Explanation – delivering clear, science-based, and culturally appropriate messages, INFOR- Action – encouraging proactive behavior based on reliable and transparent information.M Findings from this study indicate that governments, healthcare institutions, and media organiza-ATION tions must adopt a multi-faceted approach to crisis communication that integrates traditional and T digital platforms while actively combating misinformation. The infodemic observed during the COV-ECH ID-19 pandemic highlights the need for proactive and technology-driven crisis communication solu-NOL tions to counteract misinformation, build trust, and ensure public health resilience. OGIE 5.2 Recommendations for Future ApplicationsS The findings support several key recommendations for enhancing crisis communication strategies and strengthening the resilience of healthcare systems: 1. Strengthening Technological Resilience in Crisis Communication- Governments and public health institutions should invest in AI-powered communication tools, including chatbots, automated misinformation detection systems, and real-time digital plat-forms to improve the accessibility and accuracy of crisis-related information. - AI-driven fact-checking mechanisms should be integrated into media and government platforms to detect and counter misinformation before it spreads. 2. Enhancing Trust and Transparency through Inclusive Communication- Institutions should prioritize two-way communication strategies that allow real-time engage- ment with the public through Q&A platforms, live updates, and transparent policy discussions. 177 w N edA - Public health organizations should develop standardized crisis communication frameworks L S Pr based on evidence-based models such as IDEA-CommTrust, ensuring message consistency and o CIE ce N clarity across different institutions and media channels. ed TIF- Crisis messaging should be coordinated globally to prevent conflicting guidance and reduce pub-ing IC C lic confusion, particularly during pandemics and large-scale health crises. s Bo O N FE ok 4. Strengthening Collaboration Between Health Authorities and Media R : P EN- Governments should establish clear partnerships with media organizations to facilitate accurate R er-R R multiple formats. N ev AT 3. Standardizing Crisis Communication Protocols ie IO Pe IN abilities, language barriers, and limited digital access, ensuring that messages are accessible in TE- Crisis communication plans should account for vulnerable populations, including those with dis- O CE I reporting and prevent the spread of sensationalism or misinformation. JE T'S A CT- Media literacy initiatives should be promoted to educate the public on verifying sources and dis- M B A O tinguishing between credible and misleading information. N U A T P G 5. Continuous Evaluation and Adaptation of Crisis Communication Strategies EM EO- Post-crisis evaluations should be conducted to analyze the effectiveness of communication strat-EN PL E 2 egies and refine future crisis response plans. T, S TR 02- Governments and healthcare organizations should regularly update crisis communication strate-4 AT –2 gies to align with emerging digital trends and evolving public health challenges. EG IC 02 C 5 OM 5.3 Final Thoughts U The findings of this study emphasize that crisis communication is not just about delivering infor- M AT a resilient healthcare communication infrastructure. The IDEA-CommTrust model offers a struc- ION tured, trust-centered approach that can guide future crisis communication strategies, helping IC mation but also about fostering trust, ensuring accessibility, and leveraging technology to build N A healthcare institutions navigate public health emergencies with greater efficiency, transparen- N M EM By integrating technological advancements, inclusive messaging, and proactive misinformation A cy, and public engagement. G EB A ID-19 pandemic highlight the urgent need for adaptive, science-based communication strategies N D that not only inform but also empower communities to act responsibly in times of crisis. 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It’s Not Only What You Say, It’s Also How You Say It: Communicating Nipah Virus Prevention D IN Messages During an Outbreak in Bangladesh. BMC Public Health 16: 1–11.FOR 12. Petričević, Stjepan. 2024. Research of Public Relations of the Croatian Health Care System During the M Health Crisis. Maribor: Alma Mater Europaea – ECM.ATION 13. Plenković, Mario. 2015. Krizno komuniciranje. Media, Culture and Public Relations 6(2): 113–118. T 14. Ransom, James. 2007. Pandemic Influenza Preparedness, Community Engagement, and Local ECH Public Health Practice. Journal of Public Health Management and Practice 13(3): 318–320.NOL 15. Sellnow, Deanna D., Derek R. Lane, Timothy L. Sellnow, and Robert S. Littlefield. 2017. The IDEA OG Model as a Best Practice for Effective Instructional Risk and Crisis Communication. Communication IES Studies 68(5): 552–567. 16. Sellnow-Richmond, Deborah, George Amiso, and Deanna Sellnow. 2018. An IDEA Model Analysis of Instructional Risk Communication Messages in the Time of Ebola. Journal of International Crisis and Risk Communication Research 1(1): 135–166. 17. World Health Organization. 2017. Pandemic Influenza Risk Management: A WHO Guide to Inform and Harmonize National and International Pandemic Preparedness and Response. Geneva: World Health Organization. 18. World Health Organization. 2020. Chatbot solutions for public health information during the CO- VID-19 pandemic. Geneva: WHO. Available at: https://www.who.int/news-room/feature-stori-es/detail/scicom-compilation-chatbot (January 05, 2025). 179 Pe AUTHOR BIOGRAPHY IN TE er-R R Stjepan Petričević is a researcher in crisis communication and public trust in healthcare at Alma N ev AT Mater Europaea University - Faculty ECM. His work focuses on the role of digital technologies ie IO w and artificial intelligence in crisis communication models, particularly in emergency medical N ed A L S services and health crisis response strategies. Pr CIE o ce N ed TIF ing IC C ok FER : P s Bo ON R EN O CE I CTJE T'S A N OU AT P A B M EMG EN PLE 2 T, SEO TR 024 AT–2 EG IC02 C5 OM M U N ATIC ION M ANAGEMENT, W EB AND INFOR ATM ION EC T H NOL O IEG S 180 THE RELATIONSHIP BETWEEN MEDIA AND w N edAL S Pr o HEALTHCARE INSTITUTIONS IN THE CONTEXT OF CIE ceN edTIF CRISIS COMMUNICATION: TECHNOLOGICAL AND ingIC C SOCIAL RESILIENCE DURING HEALTH CRISES s BoON okFER : PEN R Published scientific conference contribution Pe INTE 1.08 Objavljeni znanstveni prispevek na konferenci er-R RN evAT ieIO Igor Pelaić, O CE I PhD Candidate JE Alma Mater Europaea University - Faculty ECM, SloveniaT'S A CT MB Stjepan Petričević, PhD AO NU AT P Alma Mater Europaea University - Faculty ECM, Slovenia G EMEO ENPLE 2 T, S ABSTRACT TR024 Health crises, such as pandemics and other public health emergencies, underscore the impor- AT–2 EG IC02 tance of effective crisis communication between healthcare institutions, the media, and the C5 general public. This review paper explores the relationship between the media and healthcare OM institutions in the context of crisis communication, with a special emphasis on technological and MU social resilience. The paper analyzes existing theoretical frameworks of crisis communication, NIC including Situational Crisis Communication Theory (SCCT) and trust management models, to ex-ATION amine key strategies and challenges in communication during health crises. M The study draws on theoretical and empirical insights from the fields of crisis communication AN and institutional trust, utilizing relevant research from literature as well as original research AG conducted as part of the dissertation. It analyzes the challenges faced by healthcare institu-EMEN tions, including the spread of misinformation, loss of public trust, and the need to adapt com-T, W munication strategies to different groups. The paper also presents examples of best and worst EB practices in crisis communication, with a particular focus on the role of the media in shaping AN public perception.D IN The conclusion of the paper emphasizes the need for proactive communication strategies, col-FOR laboration with the media, and adaptation of technological solutions to enhance the resilience M of healthcare systems in future crisis situations. The paper also provides recommendations for ATION strengthening trust between healthcare institutions and the public through transparent and T timely communication.ECH Keywords: Health crisis, Crisis communication, Media, Public trust, Technological resilience, So-NOL cial resilience OGIES 181 Pe 1 INTRODUCTION IN TE er-R R Health crises, such as pandemics and public health emergencies, highlight the critical role of effec-N ev AT tive crisis communication in ensuring public safety and maintaining trust in healthcare institutions. ie IO w The interaction between healthcare institutions and the media significantly influences public per-N ed A L S ception, adherence to health guidelines, and overall crisis management effectiveness. Pr CIE o Mass communication theories emphasize the media’s power to shape public discourse, frame ce N ed health crises, and influence policy responses (McLuhan 2008; Vreg 1975). Media channels, including TIF ing IC C traditional and digital platforms, serve as primary sources of health information, making their role ok FE flicting messages, and varying degrees of media credibility can either support or undermine public R : P s Bo O crucial in crisis communication strategies (Labaš and Marinčić 2018). However, misinformation, con-N CT T'S A M crisis communication between healthcare institutions and the media. The rapid dissemination of B A O information through multiple channels led to both positive outcomes, such as timely public health N U A T P G O CE I The COVID-19 pandemic provided a contemporary case study on the strengths and weaknesses of JE R EN trust in healthcare institutions (Krelja Kurelović et al. 2021). EM EO skepticism towards official sources (Paulik et al. 2020). EN guidance, and negative effects, such as the proliferation of misinformation and increased public TR 02 cation, with a focus on technological and social resilience. The study builds upon theoretical frame-4 AT –2 works, including Situational Crisis Communication Theory (SCCT) and trust management models, to EG IC T, S PLE 2 This paper examines the relationship between media and healthcare institutions in crisis communi- C 02 analyze key strategies and challenges in health crisis communication. The paper also reviews best 5 OM and worst practices in media engagement during crises, emphasizing the role of digital resilience in M managing public perception. U N IC By understanding these dynamics, healthcare institutions can develop more effective communi-AT cation strategies that enhance transparency, foster trust, and improve overall crisis response. This ION research contributes to the ongoing discourse on strengthening resilience in healthcare communi- M cation systems, particularly in times of public health emergencies. A N A G EM 2 THEORETICAL FRAMEWORK EN T, W Effective crisis communication between healthcare institutions and the media plays a crucial role in EB public health emergencies, shaping public perception, influencing behavioral responses, and man- A N aging misinformation. Various theoretical models explain the complexity of this interaction, par-D IN ticularly in terms of trust, media influence, and crisis response strategies. This section outlines key FOR frameworks relevant to health crisis communication, focusing on Situational Crisis Communication M Theory (SCCT), trust management models, media framing theory, and public relations approaches. AT ION 2.1 Situational Crisis Communication Theory (SCCT) in Healthcare T EC H NOL The Situational Crisis Communication Theory (SCCT), developed by Coombs (2007), provides a struc-O tured approach to understanding how organizations should respond to crises based on their level of G responsibility and public perception. In healthcare crises, where credibility is paramount, SCCT sug- IE S gests that institutions must carefully tailor their communication strategies to minimize reputational damage and maintain public trust. SCCT emphasizes that crisis responses should align with the type of crisis and the level of organiza-tional culpability. If an institution is perceived as directly responsible for a crisis, it must prioritize corrective actions and transparent communication. Conversely, if external factors contribute to the crisis, communication should focus on clarifying facts while reinforcing trust. Studies show that de-layed, inconsistent, or defensive responses tend to heighten public skepticism, whereas early, da-ta-driven messaging fosters credibility (Coombs 2021). The COVID-19 pandemic demonstrated the importance of these principles, as highlighted by the WHO RCCE guidance, which emphasizes that transparent and proactive communication by governments and healthcare agencies fosters higher levels of public compliance (WHO 2020). 182 2.2 Trust Management in Crisis Communication tional credibility directly affects public adherence to health recommendations. The trust manage RN - evAT ment model identifies transparency, credibility, and consistency as fundamental elements in main - ieIO w Trust is a cornerstone of crisis communication, particularly in the healthcare sector, where institu- TE er -R Pe IN taining trust (Reynolds and Seeger 2005). ed NAL S Pr During health crises, uncertainty often fuels misinformation, making open and frequent commu - oCIE ceN nication essential. Institutions that acknowledge unknowns, provide timely updates, and engage edTIF in two-way dialogue with the public tend to maintain stronger credibility. The COVID-19 pandemic ingIC C exemplified how conflicting statements from public health authorities led to confusion and reduced s Bo ON vaccine confidence (Paulik et al. 2020). A coherent communication strategy, built on scientific evi - okFER dence and coordinated messaging across different institutions, is vital in sustaining trust, particular - : PEN R ly in the face of evolving public health threats. OCE I JET'S A CT 2.3 Media as a Double-Edged Sword in Crisis Communication MB AO NU The role of mass and social media in crisis communication is complex. While these platforms serve as AT P G primary sources of public health information, they also facilitate the rapid spread of misinformation EMEO EN and fear amplification (Krelja Kurelović et al. 2021).PLE 2 T, S Historically, miscommunication has led to severe societal consequences. The Kantō Massacre (1923) TR024 in Japan, fueled by false media reports following an earthquake, resulted in violent attacks against AT–2 EG marginalized groups. Similarly, the Battle of Karansebeš (1788) demonstrates how a simple misin - IC02 C5 terpretation of commands led to internal chaos and casualties, underscoring the need for precise OM and unambiguous crisis messaging. MUN In modern times, digital platforms have redefined crisis communication, making real-time informa -IC tion dissemination both an advantage and a challenge. Studies indicate that emotionally charged ATION content—particularly fear-based narratives—spreads significantly faster than neutral or factual in - M formation (Xu et al. 2022). The COVID-19 infodemic showcased how viral misinformation about vac-AN cines and treatments often overshadowed official health guidelines, complicating crisis response AG efforts (Vozab and Peruško 2021).EMEN To mitigate misinformation risks, healthcare institutions must actively monitor digital discourse, en-T, W gage with audiences, and leverage fact-checking mechanisms. Strategic partnerships with social EB media platforms and media organizations can enhance information accuracy while minimizing the AN reach of misleading content.D INFOR 2.4 Media Framing and Public Perception of Health CrisesMAT The way a crisis is framed in the media has a profound impact on public perception and response ION behaviors. Framing theory suggests that the emphasis placed on specific aspects of a crisis— T whether preventive measures, casualties, or institutional responsibility—shapes audience inter-ECH pretation (Lee 2014).NOL During the COVID-19 pandemic, diverse media framing approaches influenced public attitudes and OGIE adherence to guidelines. Coverage that focused on scientific explanations and prevention strategies S fostered rational public responses and higher compliance. Conversely, reporting that sensational- ized uncertainty and conflict contributed to heightened fear and misinformation spread. Media narratives also influence the public’s willingness to trust institutions. Studies show that pro-longed exposure to crisis sensationalism often results in “news fatigue”, reducing engagement with vital public health messages. Addressing this requires proactive collaboration between healthcare institutions and journalists, ensuring that fact-based, solution-oriented reporting is prioritized over fear-driven narratives. 2.5 Public Relations and Crisis Communication in Healthcare Public relations (PR) strategies are integral to building and maintaining institutional credibility during crises. The International Public Relations Association (IPRA) defines PR as an ethical practice aimed at fostering trust between organizations and the public (Babić 2019). 183 w N ed - Media training for healthcare professionals, equipping them with skills to handle public messag-A L S Pr ing effectively. CIE o ce N- Community engagement initiatives, leveraging local health workers and trusted figures to en-ed TIF hance credibility. ing IC C By integrating these elements, healthcare institutions can enhance transparency, minimize misin-s Bo O N formation, and reinforce public confidence in their response strategies. ok FE R : P EN R er-R R ment. Healthcare institutions that successfully navigate crises typically implement: N ev AT- Crisis preparedness plans, ensuring that communication strategies are in place before crises occur. ie IO Pe IN ment—it requires strategic planning, community involvement, and ongoing reputation manage-TE In the healthcare sector, PR-driven crisis communication involves more than just media engage- O 2.6 Conclusion of Theoretical Framework CE I JE T'S A CT The theoretical insights outlined in this section highlight the interconnectedness of crisis response M B A strategies, trust management, media influence, and misinformation control. By applying these O N U A T P frameworks, healthcare institutions can develop resilient crisis communication strategies that G EM mitigate public anxiety, prevent misinformation spread, and enhance institutional credibility. The EO EN PL subsequent sections will explore empirical insights and practical applications that build upon this E 2 T, S theoretical foundation. TR 02 4 AT –2 EG IC 02 3 METHODOLOGY C 5 OM This study employs a qualitative research approach, focusing on a thematic review of existing lit-M U erature and empirical insights related to crisis communication in health emergencies. The meth-N IC odology is structured to analyze the interaction between healthcare institutions and the media AT through the lens of Situational Crisis Communication Theory (SCCT) and trust management models. ION This framework enables a systematic evaluation of crisis response strategies, media influence, and M public trust dynamics in the context of health crises. A N A G EM 3.1 Data Collection EN This study relies on secondary data sources, including: T, W EB - Peer-reviewed literature and books on crisis communication, media influence, and institutional trust. A N - Reports from international health organizations, such as the World Health Organization (WHO) D and national public health agencies, providing authoritative insights into crisis response strategies. IN FOR - Case studies from past health emergencies, with a particular focus on COVID-19, which serves as ATM a contemporary model for evaluating crisis communication effectiveness. ION - Media content analysis, examining how traditional and digital media have framed health crises, EC T the role of misinformation, and its impact on public trust. H - Empirical insights from research on public relations in the Croatian healthcare system during the NOL O health crisis (Petričević 2024). G By synthesizing academic research, institutional reports, and real-world case studies, this study aims IE S to identify patterns, challenges, and best practices in crisis communication. 3.2 Data Analysis A qualitative content analysis is used to systematically examine the collected data, focusing on four key thematic areas: 1. Media Framing of Health Crises – Investigating how different media outlets structure crisis narra- tives, the prevalence of thematic vs. sensationalist framing, and its impact on public perception. 2. Public Trust in Healthcare Institutions – Identifying the factors that influence credibility, transpar- ency, and institutional trustworthiness during health crises. 3. Impact of Digital and Traditional Media – Comparing the effectiveness of different media channels in information dissemination, including their role in spreading or counteracting misinformation. 184 and in-depth understanding of the evolving relationship between healthcare institutions and the w N edAL S media during crises. PrCIE o ceN 3.3 Study Scope and Limitations edTIF ingIC C This study does not involve primary data collection, such as surveys or interviews, but instead syn- s BoON thesizes existing research to generate evidence-based recommendations. While this approach al- okFER lows for a broad, comparative perspective, it also presents certain limitations, such as reliance on : PEN R By applying thematic categorization and cross-case comparison, this analysis ensures a structured trust or crisis mismanagement. er-R RN evAT ieIO 4. Best and Worst Practices in Crisis Communication – Evaluating successful communication models used by healthcare institutions and identifying common failures that contribute to public mis- Pe INTE available literature and the potential for contextual variations in crisis communication effectiveness O CE I across different countries and health systems. JE T'S A CT M Despite these limitations, this methodological framework ensures a comprehensive and structured B AO NU analysis of media-healthcare relations during crises while aligning with the overall objectives of AT P G the study. EMEO ENPLE 2 T, S 4 RESULTS TR024 AT–2 The findings of this study highlight key aspects of the relationship between media and healthcare EG IC02 institutions in crisis communication. The analysis focuses on how media framing influences public C5 OM perception, the role of trust in institutional credibility, the spread of misinformation, and the effec - tiveness of various communication strategies. MUNIC 4.1 Media Framing and Crisis CommunicationATION Media framing plays a crucial role in shaping public understanding and response to health crises. M The analysis reveals that different framing approaches significantly impact public attitudes, trust in ANA institutions, and adherence to health guidelines.GEM Fact-based, prevention-oriented thematic framing fosters public compliance with health recom-EN mendations by providing clear, data-driven information that encourages rational decision-making T, W (Lee 2014). In contrast, sensationalist framing, characterized by exaggerated risks, emotional ap- EB A peals, and alarmist narratives, tends to amplify misinformation and fear (Xu et al. 2022).ND Historical examples illustrate the consequences of miscommunication in crisis contexts. The Kwan - INFOR to Massacre (1923) resulted from media-driven panic following an earthquake, leading to violent public reactions. Similarly, the Battle of Karansebeš (1788) highlights how ambiguity and misin M -AT formation can escalate crises, causing unnecessary casualties. These cases underscore the need for ION precise and responsible messaging in public health emergencies. TECH 4.2 Trust Dynamics Between Media and Healthcare Institutions NOL Public trust in healthcare institutions is directly shaped by the credibility, transparency, and timeli- O IEG ness of their communication efforts. The findings indicate that delayed or inconsistent messaging S erodes institutional credibility and fuels public uncertainty (Reynolds and Seeger 2005). Healthcare institutions that engage in proactive, evidence-based communication build stronger public trust. Trust management models emphasize the importance of regular updates and timely corrections of misinformation, as these actions reinforce institutional reliability. However, during the COVID-19 pandemic, conflicting statements from government agencies and media outlets con-tributed to widespread skepticism, reducing adherence to public health recommendations (Paulik et al. 2020). To sustain trust, clear and coordinated messaging across institutions is essential, ensuring that public health communication remains consistent, factual, and accessible to diverse audiences. 185 4.3 The Role of Digital and Traditional Media in Misinformation Spread er TE The rise of digital media has transformed crisis communication, presenting both opportunities and -R Pe IN ie IO erate the spread of misinformation, often outpacing official corrections (Krelja Kurelović et al. 2021). w N ed A L S Misinformation is particularly potent when linked to emotional narratives, as studies show that emo- Pr CIE ev RNAT challenges. Social media platforms enable rapid dissemination of health information, but also accel-ce N Peruško 2021). Algorithm-driven news selection reinforces misinformation bubbles, creating echo ed o tionally charged content spreads significantly faster than neutral or factual information (Vozab and ing TIF chambers that make it difficult for evidence-based health messaging to reach skeptical audiences. IC C ok FE Fact-checking mechanisms, AI-driven misinformation detection, and institutional media monitoring R : P s Bo ON The COVID-19 crisis highlighted the importance of digital resilience in crisis communication. R EN are crucial tools in counteracting false narratives and restoring public confidence in official sources. O CE I CTJE T'S A 4.4 Best and Worst Practices in Crisis Communication N O An assessment of past health crises reveals clear patterns in effective and ineffective crisis commu-U A T P A B M AT 024 from gaining traction. –2 EG- Cross-sector collaboration – Partnerships between health institutions, media organizations, and IC 02 C 5 digital platforms enhance information credibility. OM- Real-time digital communication – Leveraging social media and direct messaging ensures that M U accurate health information reaches the public quickly. N EN Best practices include: PL E 2 T, S- Proactive media engagement – Transparent and consistent updates help prevent misinformation TR EM EO G nication strategies. ATIC Conversely, ineffective communication strategies are often characterized by: ION - Conflicting messages from authorities, leading to public confusion and distrust. M - Delayed official statements, allowing misinformation to dominate the public discourse. A N A- Lack of clear media engagement protocols, resulting in unchecked speculation and misinterpretation. G EM These findings underscore the necessity of a structured crisis communication framework that inte-EN grates trust-building measures, strategic media partnerships, and technological solutions to en-T, W hance public resilience during health emergencies. EB A N D 5 DISCUSSION IN FOR The findings of this study highlight the complex interplay between media and healthcare institu-M tions during health crises, underscoring their interdependence and the challenges they face in en-AT ION suring effective crisis communication. This section critically examines these dynamics, focusing on EC T media influence, trust dynamics, misinformation, and resilience-building strategies. H NOL 5.1 The Dual Role of Media in Health Crisis Communication O IEG Media serves as a primary conduit for disseminating health information, but also a vehicle for misin- S formation and public confusion. Healthcare institutions depend on media channels to communicate vital guidelines, yet the rapid spread of unverified content—particularly on digital platforms—com-plicates crisis response efforts. The COVID-19 pandemic provided a stark illustration of this challenge. While official guidance from health authorities reached large audiences, misinformation propagated at an even faster rate, fue-led by emotionally charged narratives and algorithm-driven content selection (Krelja Kurelović et al. 2021). The prevalence of viral misinformation about vaccines, treatments, and infection risks fur-ther demonstrated how unverified claims can undermine public trust in official sources. Historical examples reinforce these risks. The Kwanto Massacre (1923), triggered by media-driven panic following an earthquake, and the Battle of Karansebeš (1788), which resulted from miscom-munication within military ranks, illustrate how ambiguity in messaging can escalate crises with severe consequences. In today’s context, where social media enables real-time information ex- 186 Public trust in healthcare institutions is one of the most critical determinants of effective crisis man w N - edAL S Pr agement. The findings reaffirm that transparency, consistency, and proactive engagement are key oCIE to maintaining credibility. However, the COVID-19 pandemic exposed significant weaknesses in in - ceN ed stitutional trust-building strategies.TIF ingIC C A major challenge was the lack of unified messaging among governments, health agencies, and s BoON expert bodies. Conflicting statements and evolving guidelines created confusion, skepticism, and, okFER in some cases, public resistance to health measures (Paulik et al. 2020). Institutions that maintained : PEN R 5.2 Trust as the Cornerstone of Crisis Communication er-R RN evAT ieIO clarity in their messaging. Pe INTE change, healthcare institutions must not only communicate swiftly but also ensure precision and higher levels of public trust were those that engaged in regular updates, acknowledged uncertain- O CE I ties, and fostered two-way communication instead of relying on top-down messaging. This ap- JE T'S A CT proach aligns with the trust management model, which emphasizes the importance of ongoing, MB AO interactive communication to sustain credibility (Reynolds and Seeger 2005). NU AT P G Restoring and maintaining trust requires long-term investment in clear and inclusive communi - EMEO cation strategies. It is not enough for healthcare institutions to be reactive in times of crisis; they ENPLE 2 must continuously build public confidence through consistent engagement, transparency in deci - T, S TR02 sion-making, and acknowledgment of public concerns.4 AT–2 EG IC02 5.3 The Power of Media Framing C5 OM The way a crisis is presented in the media significantly impacts public risk perception and response M U behavior. Framing theory suggests that news reports emphasizing scientific explanations, pre - N IC ventive measures, and collective responsibility tend to foster rational public decision-making (Lee AT 2014). Conversely, episodic and conflict-driven framing, which amplifies uncertainty and individual ION tragedies, fuels public anxiety and misinformation spread. M The COVID-19 pandemic vividly illustrated these effects. Media outlets that prioritized expert-driv AN -AG en, solution-oriented narratives contributed to higher levels of public compliance with health rec-EM ommendations. In contrast, those that focused on conflicting expert opinions, worst-case scenarios, EN and unverified claims created divisions and heightened mistrust.T, W This fragmentation in media narratives highlights the need for stronger collaboration between EB A healthcare institutions and journalists. Equipping media professionals with accurate health infor -ND mation, facilitating transparent press briefings, and discouraging sensationalist reporting are es - INFOR sential measures to ensure that public discourse remains fact-based and constructive.MAT 5.4 Strengthening Technological and Social ResilienceION A key takeaway from recent health crises is that both technological and social resilience are funda- TECH mental to effective crisis communication. Digital misinformation, exacerbated by social media algo -NOL rithms that prioritize engagement over accuracy, has proven to be one of the greatest challenges in OG controlling health narratives (Vozab and Peruško 2021).IES Traditional fact-checking mechanisms alone have struggled to match the speed and virality of mis- information. This reality necessitates a shift toward preemptive communication strategies, where accurate information is disseminated before false narratives gain traction. Beyond technological interventions, social resilience—particularly through media literacy initia-tives—is crucial. Public education programs aimed at enhancing critical thinking, teaching individ-uals to identify reliable sources, and fostering digital literacy skills can help reduce susceptibility to misinformation. Healthcare institutions should engage not only during crises but also in stable periods, fostering public trust and preparedness through continuous outreach and education. 5.5 Rethinking Crisis Communication Strategies The findings of this study emphasize the importance of a proactive and integrated approach to crisis communication. Rather than reacting to misinformation, healthcare institutions must adopt stra- 187 w N ed ships between health institutions, media organizations, and technology platforms can streamline A L S Pr information flow and mitigate misinformation risks. CIE o ce N Efforts to improve journalistic standards in health reporting, including fact-checking partnerships ed TIF and ethical journalism training, can further strengthen crisis communication effectiveness. These ing IC C initiatives not only enhance the quality of media coverage but also contribute to greater public con-s Bo O N fidence in institutional messaging. ok FE R : P By integrating these strategies, healthcare institutions can improve crisis response, enhance public EN R er-R RN A centralized, coordinated messaging system, reinforced by real-time digital monitoring, can pre-ev AT vent confusion and enhance institutional credibility. Additionally, fostering collaborative relation-ie IO Pe IN ahead of misleading narratives. TE tegic, evidence-based messaging frameworks that ensure accurate information reaches the public JE tion technologies and information landscapes, resilience in crisis communication is no longer op- T'S A CT O CE I cooperation, and build long-term trust in health systems. In an era of rapidly evolving communica- N U AT P G EM A O M B tional—it is essential. T, S PLE 2 This study has explored the complex relationship between media and healthcare institutions in EN EO 6 CONCLUSION TR 024 crisis communication, emphasizing the central role of trust, media framing, misinformation, and AT –2 resilience-building strategies. The findings confirm that while media serves as a vital conduit for EG IC 02 public health messaging, it also introduces risks when information is misrepresented, manipulated, C 5 OM or sensationalized. M N 6.1 The Need for Strategic, Trust-Centered Communication U ATIC ION One of the key takeaways from this study is that public trust in healthcare institutions is not stat- M ic—it must be actively nurtured and safeguarded. The COVID-19 pandemic demonstrated that trust AN is highly sensitive to communication clarity, consistency, and responsiveness. When public health A G institutions provided coherent, data-driven updates, compliance with health measures remained EM high. In contrast, when messaging was contradictory or politically influenced, misinformation flour - EN ished, leading to hesitancy, confusion, and resistance to guidelines (Paulik et al. 2020). T, W To maintain and restore trust, healthcare institutions must prioritize transparent, proactive, and EB A interactive communication. This includes acknowledging uncertainties, correcting misinformation N D promptly, and fostering two-way dialogue with the public rather than relying solely on top-down IN messaging. The trust management model highlights that sustained engagement and credibili- FOR AT tions remain reliable sources of information even outside crisis periods. ION M ty-building efforts must be embedded in long-term public health strategies, ensuring that institu- EC T 6.2 Addressing the Challenges of Media Framing and Misinformation H NOL The way crises are framed by the media has a profound impact on public perception and deci- O sion-making (Lee 2014). Thematic, solution-oriented reporting, which emphasizes scientific con G- IES sensus, prevention strategies, and factual clarity, encourages rational public responses and fos- ters greater adherence to health measures. In contrast, episodic, conflict-driven, and emotionally charged narratives contribute to panic, distrust, and misinformation spread. A major challenge in crisis communication is the speed at which misinformation circulates in digi-tal spaces. The COVID-19 infodemic highlighted the limitations of traditional fact-checking mecha-nisms, which were often too slow to counter viral misinformation in real time. Addressing this chal-lenge requires a comprehensive and multi-layered strategy, including:- Preemptive communication efforts that ensure factual information is established before misin- formation takes hold. - Strengthened partnerships with media outlets and technology platforms to reinforce ethical re- porting standards and prevent the amplification of misleading content. - Improved public education on media literacy, equipping individuals with critical evaluation skills to discern reliable health information from misinformation. 188 6.3 Strengthening Technological and Social Resilience w N edAL S Pr The study emphasizes the importance of both technological and social resilience in crisis communi- oCIE cation. Technological resilience includes: ceN ed- AI-driven misinformation detection tools to identify and counter false claims in real-time.TIF ingIC C- Enhanced digital communication platforms that provide direct access to verified health information. s BoON- Real-time media monitoring to track emerging misinformation trends and respond preemptively. okFER : P nication. er-R RN evAT ieIO institutions can better control the crisis narrative and reinforce public trust in science-based commu- Pe INTE By proactively addressing how crises are framed and how misinformation is mitigated, healthcare However, technological solutions alone are insufficient without social resilience—a well-informed EN R OCE I public that can critically engage with health information. Media literacy education, aimed at en- JET'S A hancing critical thinking skills and promoting fact-checking behaviors, is an essential tool for CT MB strengthening public resistance to misinformation. Furthermore, fostering a culture of trust and ac- AO NU countability between institutions and citizens ensures that health communication efforts are more AT P G effective and widely accepted. EMEO ENPL By integrating technological innovation and community engagement, healthcare institutions can E 2 T, S develop a proactive, evidence-based crisis communication framework that minimizes misinforma- TR024 tion risks and enhances public cooperation. AT–2 EG IC02 6.4 Future Directions and Recommendations C5 OM To improve crisis communication strategies in future health emergencies, this study highlights sev- MUN eral key recommendations:ICAT- Strengthening collaboration between healthcare institutions and the media to ensure accurate, ION science-based reporting and prevent the spread of misinformation. M- Developing rapid response misinformation countermeasures, including AI-powered monitoring ANA systems and public engagement initiatives to correct misleading narratives in real time.GEM- Enhancing crisis communication training for health professionals, equipping them with effective EN media interaction skills and the ability to convey complex health information in accessible ways.T, W- Implementing nationwide digital literacy programs, empowering the public to critically evalu-EB A ate health information, recognize misinformation tactics, and make informed decisions.ND While crises are inevitable, their societal impact is shaped by the effectiveness of crisis communica - INFOR tion strategies. A well-prepared, data-driven, and trust-centered approach is crucial in ensuring that media serves as a tool for public good rather than a vehicle for fear and misinformation. MAT By adopting these principles, healthcare institutions, media organizations, and policymakers can ION future crises. HNOL foster greater public resilience, ultimately safeguarding health outcomes and societal stability in TEC O IEG S 189 Pe REFERENCES IN TE er 1. Babić, Sandra. 2019. Nova definicija odnosa s javnošću - Industrija PR-a otkrila što je, zašto radi i kako. -R R N ev AT Lider media. Available at: https://www.lider.media/poslovna-scena/hrvatska/nova-definicija-ie IO-odnosa-s-javnoscu-industrija-pr-a-otkrila-sto-je-zasto-radi-i-kako-129091 (May 23, 2020). w N ed A L S 2. Coombs, W. Timothy. 2007. Ongoing Crisis Communication: Planning, Managing, and Responding. Pr Los Angeles: Sage Publications. o CIE ce N ed 3. Coombs, W. Timothy. 2021. Situational Crisis Communication Theory: Origins, Research, and Fu-TIF ing IC C ture Directions. In The Handbook of Crisis Communication, 2nd ed., eds. W. Timothy Coombs and ok FE 4. Krelja Kurelović, Elena, Fani Tomac, and Tamara Polić. 2021. Načini informiranja i prepoznavanje R : P s Bo O Sherry J. Holladay, 22–36. Hoboken, NJ: Wiley-Blackwell. N CT T'S A 5. Labaš, Danijel, and Petra Marinčić. 2018. Mediji kao sredstvo zabave u očima djece. MediAnali: M B A O međunarodni znanstveni časopis za pitanja medija, novinarstva, masovnog komuniciranja i odnosa N U A T P s javnostima: 1–32. G O CE I 119–130. JE R EN lažnih vijesti kod studenata u Hrvatskoj tijekom COVID-19 pandemije. Zbornik Veleučilišta u Rijeci: EM EO 6. Lee, Seow Ting. 2014. Predictors of H1N1 influenza pandemic news coverage: explicating the re-EN PL E 2 lationships between framing and news release selection. International Journal of Strategic Com-T, S munication: 294–310. TR 02 4 AT 7. McLuhan, Marshall. 2008. Razumijevanje medija. Zagreb: Golden marketing – Tehnička knjiga. –2 EG IC 02 8. Paulik, L. Blair, Russell E. Keenan, and Judi L. Durda. 2020. The case for effective risk communi- C 5 OM cation: Lessons from a global pandemic. Integrated Environmental Assessment and Management: M 552–554. U N 9. Petričević, Stjepan. 2024. Research of Public Relations of the Croatian Health Care System During the IC AT Health Crisis. Maribor: Alma Mater Europaea – ECM. ION 10. Reynolds, Barbara, and Matthew W. Seeger. 2005. Crisis and emergency risk communication as M an integrative model. Journal of Health Communications: 43–55. A N A 11. Vozab, Dina, and Zrinjka Peruško. 2021. Digitalne publike vijesti u Hrvatskoj 2017.-2021. Zagreb: CIM G EM- Centar za istraživanje medija i komunikacije, Fakultet političkih znanosti, Sveučilište u Zagrebu. EN 12. Vreg, France. 1975. Društveno komuniciranje. Zagreb: Centar za informacije i publicitet, izdavačko T, W novinsko i grafičko. EB A 13. World Health Organization. 2017. Pandemic influenza risk management: A WHO guide to inform N D and harmonize national and international pandemic preparedness and response. Geneva: World IN Health Organization. FOR 14. World Health Organization. 2020. Risk Communication and Community Engagement (RCCE) Action M AT Plan Guidance COVID-19 Preparedness and Response. Geneva: WHO. Available at: https://www. ION who.int/publications/i/item/risk-communication-and-community-engagement-(rcce)-action- T EC-plan-guidance (December 21, 2024). H NOL 15. Xu, Minghua, Ziyao Wei, and Jiang Wu. 2022. How emotional communication happens in social O media: Predicting “Arousal-Homophily-Echo” emotional communication with multi-dimension- G IE al features. Telematics and Informatics Reports. S AUTHOR BIOGRAPHIES Igor Pelaić, mag. med. techn., is a PhD candidate at Alma Mater Europaea University – Faculty ECM. His research interests include crisis communication in healthcare and the role of media in emergen-cy medical services. Stjepan Petričević is a researcher in crisis communication and public trust in healthcare at Alma Ma-ter Europaea University – Faculty ECM. His work focuses on the role of digital technologies and ar-tificial intelligence in crisis communication models, particularly in emergency medical services and health crisis response strategies. 190 WEB AND INFORMATION TECHNOLOGIES STEADY-STATE ANALYSIS OF ONLINE SYSTEMS w N edAL S Pr o USING NEURONAL MODELS: APPLICATIONS IN CIE ceN edTIF REAL-TIME SIMULATIONS ingIC C s BoONFE ok Klotilda Nikaj, PhDR : PEN University of Shkodra “Luigj Gurakuqi”, Albania Published scientific conference contribution Pe INTE 1.08 Objavljeni znanstveni prispevek na konferenci er-R RN evAT ieIO O CE I R University of Tirana, Albania B AO NU A Margarita Ifti, PhD, ProfessorT P G EM Ervis Gega JE T'S A CT M University of Tirana, Albania EO EN PLE 2 T, S ABSTRACT TR 024 AT–2 EG The study of steady states in online systems through neuronal models offers valuable insights IC02 C5 into the dynamic behavior of complex systems. This research focuses on applying classical neu- OM ronal models, such as FitzHugh-Nagumo (FN) to analyze the steady-state responses of online M systems subjected to various external stimuli. By examining the system’s equilibrium points and U N the conditions under which they occur, we explore the stability of these systems in real-time ICAT scenarios. Through numerical simulations and bifurcation analysis, we investigate how different ION stimulus magnitudes and parameters influence the steady-state behavior, providing a deeper MAN understanding of the nonlinear dynamics governing these systems. AG The application of these models extends beyond theoretical neuroscience, offering potential EMEN for advancements in web-based technologies and real-time system simulations. By integrat-T, W ing these models into online platforms, we enable scalable, interactive simulations that can be EB applied to fields such as brain-computer interfaces, neural networks, and real-time data pro - A cessing. This work contributes to the development of more efficient computational tools for ana -ND lyzing and predicting the behavior of complex, online systems, bridging the gap between theo- INFOR retical modeling and practical technological applications. Keywords: M Steady state analyses, Neuronal models, Real time simulationsAT ION EC T H NOL O IEG S 195 Pe 1 INTRODUCTION IN TE er-R R The idea of using neuronal models like FitzHugh–Nagumo (FN) (FitzHugh 1961; Nagumo, Arimoto, N ev AT and Yoshizawa 1962; Izhikevich 2007) to study online social networks is intriguing and, while there ie IO w is some related work, it is not yet a mainstream approach in the social dynamics literature. N ed A L S Pr Researchers have long used nonlinear models to describe how information, behaviors, or opinions CIE o spread in networks through social contagion (Barabási 2016; Strogatz 2014; Vasilenko and Vy-ce N ed shinski 2018) and activation models. Neuronal Models in Non-Neural contexts (Zhang and Zhang TIF ing IC C 2017; Wang and Zhang 2019; Goh and Kim 2001) are examples where excitable system models ok FE model to describe user engagement, fatigue, or online activation is less common. Leveraging the R : P s Bo O have been adapted to model social or economic phenomena, but the direct application of the FN N CT T'S A critical thresholds, and multi-stability in social network dynamics.Through bifurcation analysis, (Goh M B A and Kim 2001; Brown 2021; Jackson 2020) and comparisons with alternative numerical integration O N U A T P methods, we explore how changes in stimulus parameters influence the stability and oscillatory be-G O CE I tive and a novel approach. It provides a robust mathematical framework to investigate stability, JE R EN well-established theory behind neuronal dynamics and bifurcation analysis offers a fresh perspec- EN PL that has been extensively studied but continues to present new challenges and opportunities for E 2 T, S EM haviour of these systems. Notably, this work highlights the oscillatory phenomena, a phenomenon EO TR computational advancements. 02 EGIC 02 2 METHODS C AT 4–2 OM 5 2.1 Mapping Fn Model To A Social Network M N The purpose of this study is to explore the application of classical neuronal models, particularly (FN) U AT to analyze the behavior of online complex systems subjected to external stimuli (FitzHugh 1961; IC ION Nagumo, Arimoto, and Yoshizawa 1962). By using numerical simulations and bifurcation analysis, M the study aims to understand the nonlinear dynamics and steady-state responses of these systems A N in real-time environments (Strogatz 2018; Izhikevich 2007) and to contribute to the development A G of more efficient computational methods for analyzing the behavior of complex, nonlinear systems EM EN in online platforms (Barabási 2016; Goh and Kim 2001). The extended FN equation to e networked T, W system is given by the equation: EB AND INFOR ATM ION EC T Here, each node represent a user or an entity in the network. Vi is the activation level- how actively NOL a user intersects, w H is the loss of interest over time (Izhikevich 2007), I are the viral trends, or O external stimulus to the nodes (Wang and Zhang 2012). Network connections introduce interac i ext,i - IEG tion terms, meaning a user’s engagement depends not just oh their own state but also on their S neighbors (Zhang and Zhang 2010; Goh and Kim 2001). is the adjacency matrix defining the social network structure and , the last summated term models peer influence, where users tend to mimic already connected user (Jackson 2008; Brown 2014). The use of numerical integration techniques, such as MATLAB’s ODE45 and ODE23 solvers, provides efficient and accurate simulations of these complex systems (Vasilenko and Vyshinski 2019). We have performed detailed analyses of the FN model, examining their responses to various current inputs and the resulting bifurcation diagrams (Strogatz 2018). These solvers were chosen for their accuracy and efficiency in modeling the dynam-ic behavior of the systems (Izhikevich 2007). Various external stimuli were introduced to the system, and the resulting responses of the neuronal models were simulated over time. During the study we have generated bifurcation diagrams to map the steady-state behavior of the systems as a function of parameters such as stimulus magnitude and time. These diagrams help us to identify transitions between different system states and the points at which stability changes (FitzHugh 1961; Nagumo, Arimoto, and Yoshizawa 1962) (e.g., from stable oscillations to chaotic behavior). 196 2.2 Bifurcation Analysis In Social Networks be similar. For instance, if the ring network connects each node to 2 neighbors and the ER network ed NAL S Pr is tuned (with p) such that the average degree is close to 2, then their diffusive coupling effects can oCIE be very similar. ceN edTIF ingIC C Figure 1: Engagement Dynamics in a Social network s BoONFE okR world network topology, obtaining the results as in Figure 1. On average, each node has roughly RNAT ev the same number of connections, then the overall “coupling strength” each node experiences can ieIO w First we simulate the network dynamic for different network structure, strating with the small- TE er -R Pe IN : P EN R OCE I JET'S A CT MB AO NU AT P G EMEO ENPLE 2 T, S TR024 AT–2 EG IC02 C5 OM M U N ATIC ION M Here we can see the simulation of engagement dynamics in a small social network using the F-N ANAGEMENT, W model where each curve represents a user‘s activity level over time. EB AN The network connection creates interdependencies between users, leading to synchronized and de-D synchronized activity patterns. Some users stabilize at different activity levels, while others fluctuat; INFOR suggesting nonlinear interactions in the network.MAT Figure 2: Left side bifurcation diagram for a social network with a ring topology, right side bifur-ION cation diagram for a random social network modeled by FN dynamics TECHNOL O IEG S By observing figure 2, we can notice similar simulation results across the two network types. This might happen for different reasons, where we can underline the networks size and similar average connectivity. If both networks (the ring network and the Erdős–Rényi network) have a similar av-erage degree, each node has roughly the same number of connections, then the overall “coupling 197 w N ed gle scalar applied to all nodes, we define an array of length N, where each entry corresponds to the A L S Pr external input for a given node. This can help reveal differences in network behavior because nodes CIE o with different inputs may evolve differently based on their position in the network. ce N ed TIF ing IC C Figure 3: Bifurcation Diagrams with Hetergeneous External Inputs, applied on a random network, s Bo O N modelend by FN equation. FE ok R : P EN R er-R R is close to 2, then their diffusive coupling effects can be very similar. N ev AT At this step, we propose to modify the model using heterogeneous external inputs. Instead of a sin-ie IO Pe IN to 2 neighbors and the ER network is tuned with the same probability, such that the average degree TE strength” each node experiences can be similar. For instance, if the ring network connects each node O CE I CTJE T'S A N OU AT P A B M EMG EN PLE 2 T, SEO TR 024 AT–2 EG IC02 C5 OM M U N ATIC ION M ANAGEMENT, W EB AND The bifurcation diagram displays each node’s steady-state activity level plotted against the base IN external input, revealing how individual nodes respond differently due to the added heterogeneity. FOR The dispersion of points at each base input level illustrates that even with a common base input, M variability in external stimulation causes diverse outcomes across the network. Overall, the simu- AT ION lations indicates that as the base input increases, nodes transition through various activity states, T highlighting potential regions of multi-stability influenced by both network connectivity and exter- EC H nal stimulus variability. NOL O 3 DISCUSSION IEG S One of the key findings of this study is the identification of bifurcation phenomena and the transi-tion from stable states to oscillatory or chaotic behavior as external stimuli are varied. The FN model exhibited nonlinear responses to changes in stimulus magnitude, demonstrating the rich complex-ity inherent in these systems. The occurrence of bifurcations, particularly the transition from stable fixed points to oscillatory behavior, underscores the sensitivity of online systems to small variations in external stimulis. This sensitivity reflects the underlying complexity of systems that, while ap-pearing simple at first, can undergo drastic qualitative changes in response to external conditions. The ability to predict such bifurcations is essential for real-time system analysis, where stability and behavior can shift abruptly due to changing inputs. This oscillatory behavior is directly related to the fundamental processes in real-time systems, such as the rhythmic signaling in neurons, and is also analogous to the periodic or chaotic behavior that may be observed in real-world systems subjected to feedback loops and external perturbations. The ability to simulate and predict these oscillations 198 grating the neuronal models into online platforms, we create scalable tools for studying the dynam- w N edAL S ics of complex systems in diverse fields, from neuroscience to engineering and beyond. PrCIE o The results of this study focus on the steady-state behavior, bifurcations, and oscillatory dynamics ceN ed of the neuronal FN model when subjected to various external stimuli. The findings highlight the TIF ingIC C system’s response to changes in stimulus magnitude, parameter variations, and the occurrence of s BoON bifurcations and transitions in system behavior. The key results are summarized as follows: okFER Steady-State Behavior: For varying stimulus magnitudes, the FN model demonstrated transitions be- : PEN R In er-R R real-time data processing, for example, understanding how a system behaves under varying N evAT stimuli can help in predicting potential failure points or identifying optimal configurations. By inte - ieIO ing, such as signal processing, communications, and real-time control systems. Pe INTE provides crucial insights into system behavior, especially for applications that require precise tim- plitude increased, the system exhibited more complex oscillatory patterns, eventually leading to JE T'S A CT tween different steady states, including stable oscillations and resting states. As the stimulus am- O CE I Bifurcation Diagrams N OU : In the FN model, a bifurcation diagram revealed a transition from stable fixed chaotic behavior at higher input values. MA B A T P G gime. The study found that small changes in the stimulus amplitude or duration could lead to signif- EN PLE 2 T, S points to limit cycles (oscillatory behavior) and further increase in the stimulus led to a chaotic re- EM EO icant shifts in the system’s behavior, including the loss of stability and the onset of chaos. The bifur- 02 TR cation points were highly sensitive to changes in the external stimulus, highlighting the nonlinear 4 AT–2 nature of the system. EG IC02 C5 Exploring System Stability: Sensitivity to variations in external stimulus parameters (e.g., stimulus OM duration, amplitude) was analyzed to identify the conditions under which bifurcations, oscillations, MU and stability changes occur.NIC These results also demonstrate the potential for applying these neuronal models to a wide range of ATION online systems that require dynamic adjustment. The insights gained from this study can be directly M applied to the design of systems that must handle real-time data processing, including brain-com-AN puter interfaces or neural networks, where multiple states may need to be stabilized based on AG external stimulus.EMENT, W 4 CONCLUSIONEB A In conclusion, this study demonstrates the utility of classical neuronal models in analyzing the non-ND linear dynamics of online systems subjected to external stimuli. Incorporating network coupling via IN various network topologies like Eror small-world into the FN model to capture peer influence and FOR models. Future work could focus on extending these combined models to incorporate more com-diffusion of engagement is a relatively novel twist compared to more traditional social contagion MAT ION social systems. Furthermore, while the study provides a thorough numerical analysis of bifurcations ECHNOL plex networks and interactions, which would be especially useful in studying large-scale complex T and system behavior, real-world applications require consideration of noise, uncertainty, and exter-nal perturbations, which may not have been fully addressed in this theoretical approach. OG IES 199 Pe REFERENCES IN TE er 1. Barabási, Albert-László. 2016. Network Science. Cambridge: Cambridge University Press.-R R N ev AT 2. Brown, Angela M. 2021. Exploring the Applications of FitzHugh–Nagumo Models in Real-Time ie IO w Systems. Neuroscience Today 5 (1): 55–67. N ed A L S 3. FitzHugh, Richard. 1961. Impulses and Physiological States in Theoretical Models of Nerve Mem- Pr CIE o branes. Biophysical Journal 1 (6): 445–466. ce N ed 4. Goh, K.-I., and D.-S. Kim. 2001. The Dynamics of Small-World Networks. Physical Review Letters 87 TIF ing IC C (27): 278701. N O Simulating Nerve Axon. Proceedings of the IRE 50 (10): 2061–2070. U A T P G 8. Strogatz, Steven H. 2014. Nonlinear Dynamics and Chaos: With Applications to Physics, Biology, Che-EM EO mistry, and Engineering. Boulder, CO: Westview Press. EN PL E 2 T, S 9. Vasilenko, Alexei, and Ivan Vyshinski. 2018. Bifurcation Analysis of FitzHugh–Nagumo Model in TR 02 Social Networks. Journal of Computational Neuroscience 45 (2): 233–245. 4 AT –2 10. Wang, Jie, and Wei Zhang. 2019. Bifurcation Analysis in Multi-User Social Networks. In Proceed-EG IC 02 ings of the International Conference on Social Computing and Networking. C 5 OM 11. Zhang, Li, and Wei Zhang. 2017. Modeling Social Network Dynamics with Neuronal Models. In M U Proceedings of the IEEE Conference on Computational Intelligence and Neuroscience. N IC AT R EN 6. Jackson, Matthew O. 2020. Understanding Complex Networks: A Review of Current Models and Fu-O CE I JE ture Directions. Stanford: Stanford University Press, Complex Systems Research Hub. T'S A CT M 7. Nagumo, Jinichi, Suguru Arimoto, and Shuji Yoshizawa. 1962. An Active Pulse Transmission Line B A ok FE Bursting. Cambridge, MA: MIT Press. R : P s Bo ON 5. Izhikevich, Eugene M. 2007. Dynamical Systems in Neuroscience: The Geometry of Excitability and ION AUTHOR BIOGRAPHY A Dr. Klotilda Nikaj is a Researcher and Lecturer in the Physics Department at the University of Shkodra N M A “Luigj Gurakuqi”. She holds a PhD from the University of Tirana (2022) and has authored numer- G EM ous research articles on complex systems, social networks, and radiation physics. Her work includes EN both oral and poster presentations at international conferences. T, W EB AND INFOR ATM ION EC T H NOL O IEG S 200 DIGITAL MARKETING AND PROMOTION OF w N edAL S Pr o SLOVENIAN HIGHER EDUCATION PROGRAMMES CIE ceN edTIF IN INFORMATION AND COMMUNICATION ingIC C TECHNOLOGIES AT THE UNDERGRADUATE LEVEL s BoON okFER : PEN R Published scientific conference contribution Pe INTE 1.08 Objavljeni znanstveni prispevek na konferenci er-R RN evAT ieIO Aleksandar Brodschneider O CE I JE Alma Mater Europaea University, SloveniaT'S A CT MB Matej Mertik, PhD, Associate Professor AO NU AT P Alma Mater Europaea University, Slovenia G EMEO ENPLE 2 T, S ABSTRACT TR024 This research investigates digital marketing and other strategies to promote first-cycle Bolo - AT–2 EG IC02 gna programmes in information and communication technologies (ICT) in Slovenia. The topic is C5 under-researched, as only a few universities and higher education institutions in Slovenia of- OM fer such programmes. Given the rapid evolution of digital marketing and technology, the study MU draws from best practices at European, non-European, and American universities that employ NIC advanced marketing approaches. The study is divided into two sections: a theoretical review of ATION best practices from different universities and an empirical analysis focused on the needs of key M target groups. These groups include high school students, undergraduate students, and market-AN ing personnel. The research highlights the fact that Slovenian universities do not fully utilize the AG potential of digital marketing, particularly in leveraging precise metrics and targeting tools. Ad-EM vanced analytics, which could help create detailed psychographic profiles of target groups, are ENT, W largely absent, limiting the effectiveness of marketing strategies. These marketing gaps contrib - ute indirectly to the significant shortage of ICT professionals in Slovenia. According to Eurostat, EB A Slovenia has the highest deficit of ICT professionals in the European Union. Although approxi -ND mately 2,500 ICT professionals are trained annually, this number is only half of what the market IN demands, leaving a considerable gap in the workforce.FOR Keywords: M Digital marketing, Educational marketing, Higher education ICT, Recruitment mar-AT keting, Target audience psychology. ION EC T H NOL O IEG S 201 Pe 1 INTRODUCTION IN TE er-R R Information and Communication Technology (ICT) plays an increasingly significant role in both N ev AT the economic and academic sectors, highlighting the need for more effective strategies to attract ie IO w students to related higher education programmes. This study explores optimal digital and other N ed A L S marketing strategies for increasing enrolment in first-cycle Bologna ICT programmes in Slovenia. Pr The analysis focuses on key target groups—high school students, university undergraduates (aged o CIE ce N 18–30), and working adults (typically aged 30–40) who are considering career transitions or reskill-ed TIF ing opportunities in the ICT sector (Limna et al. 2023; Matz et al. 2017). This study expands on earlier ing IC C work exploring digital marketing of ICT study programmes in Slovenia (Brodschneider 2024). s Bo O N FE ok For successful marketing targeting of these groups, it is necessary to understand their needs and ex-R : P EN pectations and to present a clear picture of their predispositions, the current state of the job market, R O CE I and employment opportunities for such technological personnel both locally and globally through JE T'S A CT marketing channels (Taken Smith 2012, 86–92). This is all the more crucial given that the shortage M B A and demand for ICT professionals is increasing. Slovenia is currently leading in this issue within the O N U A T P European Union (Eurostat 2023), with an estimated annual shortfall of over 6,000 ICT professionals, G EM while only approximately 2,500 are trained each year, indicating that at least twice as many ICT pro-EO EN PL fessionals need to be trained annually. Some Southeast European countries, such as Serbia, Bosnia E 2 T, S and Herzegovina, and North Macedonia, have also surpassed Slovenia in meeting the demand for TR 02 4 ICT personnel (Eurostat 2023). Digitalisation represents a new industrial revolution, without which AT –2 EG we cannot remain competitive. Companies should therefore invest at least twice as much in the IC 02 C 5 development and mastery of computer skills, and schools should incorporate computer science as OM a mandatory subject in the curriculum. Responsible management of ICT education is essential to M U ensure we prepare our future workforce (Lačan and Tomažin 2023). Consequently, solutions and N IC considerations are linked to more effective engagement and recruitment of potential undergrad-AT uate students, or to more effective promotion of ICT study programmes, which educational institu-ION tions have recognised in recent years and have thus begun to cater to every potential student. This M A indeed enhances competitiveness but requires new innovative marketing approaches (Taken Smith N A G 2012, 89–91). Balanced economic management of marketing resources and objective targeting of EM appropriate audience segments is also necessary, with no room for subjective assumptions or pre- EN sumptions, as marketing resources are limited. Any imprudent investment or erroneous judgement T, W by an institution can lead to a drastic or negative cumulative process, potentially jeopardising its EB A operation, especially if the institution is relatively new to the educational market, smaller, and lacks N D a recognised brand. The problem is also evident in the formulation of buyer personas to reach tar- IN get groups, given the broad spectrum encompassing high school students, undergraduate students, FOR and employed adults (Erudera 2024). This generational diversity poses a significant challenge in de - M veloping marketing campaigns, strategies, and balanced allocation of financial resources, as well as AT ION in the development of university and college websites, which must be cohesively designed to inte- T grate both psychological and sociological elements for target groups with different psychographic EC H and demographic segmentations (Naumovska 2017, 123–133). NOL O The use of digital promotion tools has become largely standardised, as both digital (e.g., websites, IEG social media) and traditional channels (e.g., radio, television, print media, billboards, live events) S are now widely adopted and considered commonplace (Harbi and Maqsood Ali 2022, 463–468). Due to this standardisation, there is a need to focus on more specific areas of digital marketing, namely: communication, educational (instructional) and content marketing, and recruitment mar-keting, as their optimal use provides more sustainable and innovative solutions. Besides attract-ing the attention of potential undergraduate students in target groups, they also enable long-term engagement and consequently create loyal users (Chaffey and Ellis-Chadwick 2019, 26–28). Such marketing approaches operate on a deeper level of communication, displaying social and societal benefits and functioning less aggressively than other marketing methods (Mongoose 2022). 1.1 Aims and objectives The purpose of this study is to examine the digital and other marketing strategies of higher educa-tion institutions offering ICT programmes at the first Bologna cycle level in Slovenia, with the aim of 202 – R1: What are the differences among the target groups of potential undergraduate ICT students at w N edAL S the first Bologna cycle level? PrCIE o – R2: How do higher education institutions understand the target groups of ICT study programmes ceN ed at the first Bologna cycle level? TIF ingIC C – R3: What digital and other marketing approaches do higher education institutions use to address s BoO potential target groups for ICT study programmes at the first Bologna cycle level? N okFER – R4: Is tailoring the target message to the parents of potential undergraduate students (currently : PEN in high school) also an important factor in reaching this target group? five research questions through preliminary interviews and online research of both Slovenian and er-R RN evAT foreign higher education institutions with ICT programmes: ieIO fessional shortage within the European Union (Eurostat 2023). To achieve this, we have formulated Pe INTE determining how to optimise their promotion, given that Slovenia is ranked first in terms of ICT pro- the analysis of responses in the form of tables and graphs, allowing us to identify patterns and EN PLE 2 T, S TR02 trends. The qualitative part will focus on a deeper understanding of phenomena through textual 4 AT–2 data analysis. This part will include online research of institutions or their digital channels as well as EG IC02 interviews with HR personnel from marketing departments of higher education institutions with ICT C5 OM programmes, and the analysis of interview transcripts, which will provide insights into subjective M experiences and opinions related to the research questions. Sampling and data collection with both U N methods will be crucial for ensuring the representativeness and relevance of the study. The discus- IC AT sion (Chapter 4) will present all findings and connections between secondary research results in the ION theoretical section and primary research in the empirical section through: an overview, research M limitations, and conclusions. The research will be consolidated through descriptive statistical analy- The methodological approach (Chapter 2) will include quantitative and qualitative methods, sam prospects, marketing, or the potential for high paid jobs? B AO NU- AT P G pling, and data collection, which will then be presented in the results chapter (Chapter 3). The quan - EMEO titative part will involve the use of questionnaires for high school and undergraduate students, and – R5: Did students (currently in high school) choose their studies based on personal interest, career JE T'S A CT M O CE I R sis, providing a detailed insight into the results and the specificity of the research findings. ANAGEMEN 2 METHODOLOGYT, W The research builds on theoretical foundations presented in the introductory part of the study. To EB AN gain a broader perspective and a more in-depth view, as well as to optimally design the strategy D IN for both its development and the creation of questionnaires and methods, we considered a wider FOR context. This included a general overview of various higher education institutions and their market-M ing activities in the international arena. In addition to Slovenia, which was the primary focus of the AT research, we also incorporated perspectives and practices from abroad, including Bosnia and Her-ION zegovina; Finland; Germany; Austria; and the United States of America. This contributed to guiding TEC the setup of the online research on higher education institutions, interviews with their marketing HNOL personnel, and surveys of high school and undergraduate students. The methods and techniques O used in the research are detailed below.GIES 2.1 Methods and Techniques for Data Collection The research employed various research methods and types of analyses, which in some elements overlap. However, the predominant method used was descriptive research with comparative data analysis. The types of analyses used in data collection, literature review, and interpretation of results: - Longitudinal analysis of social media posts (pre-study year, academic year, holidays);- Utilisation of secondary statistical analysis (surveys, statistics, archives, social media, literature);- Quantitative, qualitative, and meta-analysis (integration of results from independent studies);- Historiographical analysis (impact of trends on digital marketing over the years);- Correlational analysis (relationship between the effectiveness of promotions and the decision of a potential student to enrol). 203 w N edAL S 2.2 Description of Instruments Pr CIE o ce N For measuring digital and traditional marketing of higher education institutions, we utilised the ed TIF analysis of institutional websites and social media. ing IC C For understanding the perspective of ICT institutional personnel at the first Bologna cycle level, we s Bo O N used open-ended interviews. This represented the qualitative aspect of the research. The interview ok FE R questions were aimed at the marketing personnel of higher education institutions with ICT study : P EN R er-R R proving the methods and techniques based on feedback from respondents (institutional personnel, N ev AT high school students, and undergraduate students). ie IO Pe IN mined, an agile (dynamic) development approach was also used. This involved continuously im-TE In addition to the traditional (static) approach, where all elements of the process are predeter- JE For understanding the perspective of high school students from ICT institutions and undergraduate T'S A CT O programmes and addressed the five research questions. CE I A U the research. Their responses provided real-time insights into the specifics of the study, enabling T P G us to coherently adjust the direction, breadth, and depth of the research. Both questionnaires were N O A M B students at the first Bologna cycle level, we used surveys, representing the quantitative aspect of EN PL developed based on insights, guidelines, and findings from the theoretical part of the research, as E 2 T, S EM EO TR 02 well as an online analysis of six ICT-focused higher education institutions from Slovenia; one from EGIC 02 the mentioned Slovenian institutions and the Bosnian-Herzegovinian institution. The questions in C 5 AT 4 Finland, Germany, Austria; Bosnia and Herzegovina; and three ICT-focused higher education institu- –2 tions from the USA. This was further supplemented by interviews with marketing personnel from OM the questionnaires for high school and undergraduate students were designed to verify the reliabil- M ity of responses from institutional personnel interviews, as these interviews were conducted first. U N IC This approach aimed to ensure credibility, transparency, complexity, relevance, and a holistic view AT of the research process. ION The questionnaires were designed based on the stated parameters, literature review, captured in M - AN sights, and consultations with other experts, with the aim of better understanding responses to the A G issues described in the research questions. The interview questionnaire for higher education per - EM sonnel and the surveys for various target groups included between 10 and 14 open-ended ques - EN tions related to the perspectives, desires, values, and practices of the respondents. Analyses and in- T, W terpretations of responses from these questionnaires were useful in addressing results and findings, EB A enabling us to answer the research questions and address the issues raised in Slovenia in Chapter N D 4 – Discussion. IN FOR 2.3 Description of the sample M AT The research sample included 172 respondents, namely: six representatives from ICT higher educa- ION tion institutions in Slovenia and one from Bosnia and Herzegovina for international perspective; 80 T EC high school students from ICT institutions; and 85 undergraduate students from ICT programmes at H NOL the first Bologna cycle level. The sample also comprised an online analysis of six higher education O institutions in Slovenia and seven abroad, including international higher education institutions with G IE ICT programmes from Central, Northern, and Western Europe, and the United States of America. A S preliminary interview with a personnel member from SUM in Bosnia and Herzegovina helped us understand the functioning of Southeast European higher education institutions. This broader in-ternational perspective provided insights into the level and direction of marketing strategies for ICT study programmes at Slovenian higher education institutions. The sample was used for both quantitative and qualitative research. For quantitative research, re-sponses were obtained from 80 high school and 85 undergraduate students from ICT programmes in Slovenia, providing a systemic view of the issue from their perspectives, understanding, and desires. For qualitative research, interviews were conducted with marketing personnel from all six higher education institutions identified in Slovenia, two of whom wished to remain anonymous. These in-terviews explored current marketing approaches, including strategies and experiences in promot-ing their institutions and ICT study programmes. One of the anonymous personnel members also requested that their institution remain unnamed due to personal reasons. 204 The research involved 4 primary and 1 secondary sample: anonymous higher education institution. N edAL S Pr Sample 2 – Personnel interviews included 6 employees, one from each of the previously mentioned oCIE Slovenian ICT higher education institutions. The interviews provided insights into their positions, ceN ed goals, and values. The questionnaire, in the form of an oral interview, consisted of 10 questions TIF ingIC C related to the 5 research questions. s BoON Sample 3 – High school student surveys included 80 participants from ICT-focused secondary institu- okFER Slovenia, both public and private. These include faculties or some Slovenian universities specialis- RNAT ev ing in the ICT sector: AMEU (private), FAMNIT (public), FERI (public), FRI (public), FIŠ (public), and an ieIO w Sample 1 – The online research of Slovenian institutions involved 6 higher education institutions in TE er -R Pe IN tions in Slovenia. The open-ended questionnaire consisted of 13 questions addressing the research : P EN R questions. OCE I JET'S A Sample 4 – Undergraduate student surveys included 85 participants from ICT programmes at the first CT MB Bologna cycle level in Slovenia. The open-ended questionnaire contained 12 questions related to AO NU the research questions. AT P G EM The sample of other international (EU and US) higher education institutions with ICT programmes EO ENPL and the interview with a personnel member from a higher education institution in Bosnia and Her-E 2 T, S zegovina helped provide a broader context for the research. TR024 AT–2 2.4 Description of Data Processing EG IC02 C5 Data processing occurred in four stages: OM 1. Analysis of institutional websites and digital and other marketing practices of higher education MUN institutions with ICT study programmes from Slovenia and other countries.ICAT 2. Interviews with marketing and communication personnel from Slovenian institutions, analysed ION in the previous stage using open oral questions. One personnel member was interviewed from M each institution.ANA 3. Surveys of high school students from ICT-focused institutions in Slovenia using an open written GEM questionnaire.EN 4. Surveys of undergraduate students from higher education institutions with ICT programmes at T, W the first Bologna cycle level in Slovenia using an open written questionnaire.EB A The online analysis of institutions was conducted from August 16, 2023, to November 15, 2023. In-ND terviews with personnel from higher education institutions and univeristies with ICT programmes IN were conducted between November 16, 2023, and March 15, 2024. High school ICT students and un-FOR social media. The questionnaire (open type) was available online and on social media from Decem- ATION dergraduate ICT students from higher institutions and universities were surveyed online or through M 1. Online research of Slovenian higher education institutions with ICT study programmes at the first ECHNOL ber 29, 2023, to March 21, 2024. The obtained data were then categorised into 4 sections: T Bologna cycle level. 2. Research on marketing personnel practices (of the previously mentioned institutions) through OG interviews. IES 3. Research on the perspective of high school students from ICT-focused institutions in Slovenia. 4. Research on the perspective of undergraduate students from higher education institutions with ICT programmes at the first Bologna cycle level in Slovenia. The results were subsequently organised based on the frequency of responses – the mode. 3 RESULTS This chapter presents the results of the research project, which directly relate to the five research questions outlined in the theoretical section. Table 1 summarises some of the key findings and guidelines regarding the research questions obtained from the conducted study. 205 Table 1: Key Findings of the Research ed N are more interested in Differences between Target A psychographic differences more career-oriented in L S Groups (high school and their studies due to personal Pr between high school and their studies. undergraduate students) interest. o CIE undergraduate students. ce N ed TIF R2 ing Incomplete, lack of perso-Lack of use of analytical Lack of connection between IC C Understanding of Target nalised approach (buyer tools and ongoing surveys of undergraduate and gradua-s Bo O Groups by Institutional N persona). target groups. te students. ok FE Personnel R ev RNAT Despite belonging to the R1 Undergraduate students ie IO same Generation Z, there are High school students are w er TE Question Theme Key Finding 1 Key Finding 2 Key Finding 3-R Pe IN : P EN R3 Word of mouth and live R Most important digital O CE I Digital and Marketing events are among the most Insufficient promotions, JE channels: e-mail, Facebook, T'S A CT Approaches to Target significant approaches for information, and live events. Instagram. M Groups target groups. B A O N U A T P R4 Generation Z (high school Generation Z is influenced by G Parents have less influence EM EO Influence of Parents on and undergraduate stu-teachers, acquaintances, and on Generation Z. EN dents) is independent. live events. PL Decision-Making E 2 T, S R5 Undergraduate students High school students are pri-TR 02 4 AT Personal or Career Moti-are primarily motivated by marily motivated by career Many cite both reasons. –2 personal reasons. reasons. EG vation IC 02 C 5 (Source: Authors’.) OM M 3.1 Study Limitations U N IC The study aimed for a more comprehensive investigation of higher education institutions in inter-AT ION national markets, including interviews with their personnel and target groups, in search of optimal G tion institutions. The research may exhibit shortcomings in objectivity and congruence, potentially EM reflecting methodological, temporal, geographical, cultural, theoretical, practical limitations, as EN T, W well as limitations of the researcher and participants. Methodological limitations are reflected in the sample size, as 80 high school and 85 undergraduate students not constitute a large proportion EB AN er, this was unfeasible due to time constraints and poor responsiveness from foreign higher educa- A M solutions, marketing patterns, and best practices from more developed Western countries. Howev- A of the population. Geographical and cultural limitations are apparent as most respondents were N D from northeastern Slovenia, particularly Maribor, which could negatively impact the interpretation IN FOR and generalisation of results and their applicability to other regions in Slovenia. The lack of research AT sources and limited access to necessary data. ION M in the specified ICT field in Slovenia represents an additional practical limitation, as there were few EC T H 4 DISCUSSION NOL O The findings show that although high school and undergraduate students both belong to Genera- IEG tion Z, they differ significantly in psychographic profiles and motivational factors. There are noti- S ceable differences in their primary reasons for choosing ICT studies: high school students are more career-oriented, while undergraduate students are more personally motivated. Both groups in-dicated that their preferred primary digital channel for receiving information from institutions is email. Among social media platforms, Facebook was selected as the most useful, closely followed by Instagram. The educational institutions in question have also noted that these social media platforms are among the most effective, as they regularly use them to reach their target groups. Factors such as product, price, promotion, place, people, process, and packaging (institutional ar-chitecture, visual presentation of services), which are used in the construction of standardised 7P systems, also influence high school and undergraduate students‘ choices when selecting a higher education institution. Personnel at higher education institutions offering ICT programmes believe they have a good un-derstanding of their target groups. However, it has been revealed that this understanding is not 206 students. High school and graduate students lack additional information about the study process, er-R RN evAT content of study programmes, experiences during and after the study, and career specifics in the job ieIO which personnel have highlighted as an important tool for connecting ungraduate with graduate Pe INTE entirely accurate, as nearly half of the undergraduate students are unfamiliar with the alumni club, market. Initial information about higher education institutions was mostly received through word w N edA of mouth, secondary school teachers, competitions, friends, and acquaintances. Parents generally L S PrCIE do not influence their decisions, as Generation Z, high school and undergraduate students are in - o ceN dependent. Many believe that internal motivation and the institution‘s self-promotional integrity edTIF are crucial in selecting a higher education institution, and that more aggressive promotion does not ingIC C standardised. However, there is a noticeable lack of understanding in analytical approaches and EN R OCE I consequently in the psychographic spectrum of target groups, as they do not utilise specialised an - JET'S A CT alytical tools essential for maximising the potential of digital marketing. Collaboration between MB marketing personnel and the business sector, employment agencies, and other departments within Institutional personnel use both traditional and digital marketing approaches, which have become ok FER : P significantly impact their decisions. s Bo ON the institution is crucial for developing optimal marketing strategies and campaigns. Institutions A O NU AT P G EM are beginning to realise that both in the educational and business sectors, specialised marketing of EO ENPL services using educational, content, and email marketing is necessary.E 2 T, S Most results align with the findings in the theoretical section, as higher education personnel, high TR024 school and undergraduate students, recognise the importance of the relevance and modernisation AT–2 EG IC02 of study programmes, the quality of lectures and professors, and the modern teaching materials C5 and technical equipment. Personnel at higher education institutions are aware of market compet - OM itiveness in the educational sector but, in addition to the lack of use of professional analytical tools MU (e.g., Google Analytics), also lack modern techniques for personalising marketing approaches, such NIC as creating buyer personas based on specific psychographic characteristics and differences among ATION target groups. M The use of these components could enable Slovenian higher education institutions offering ICT pro -AN grammes at the first Bologna level to better refine and regularly update their marketing strategies AG and approaches. This might positively impact the shortage of ICT professionals in Slovenia, which, EMEN according to a 2023 Eurostat study, is the highest among EU member states, with only around 2,500 T, W ICT graduates annually instead of the needed 6,000 (Lačan & Tomažin 2023).EB AN 5 CONCLUSIOND INFOR 5.1 Summary of Key FindingsMAT It is evident that personnel at institutions recognise the indispensability of using digital marketing. ION However, they do not fully appreciate the necessity of ongoing analysis of results and the corre- T sponding adjustment of marketing strategies. This can be achieved through the use of specialised ECH analytical tools, such as Google Analytics, and personalised marketing techniques, such as the crea -NOL tion of buyer personas. OGIE From the target groups (high school and undergraduate students) or the research sample, which S comprises individuals aged between 15 and 49, we have managed to gather sufficient information, except for the target group of employed adults aged between 30 and 50, for which the sample size was too small to generalise. Results show that employed adults generally enrol in private higher education institutions, which constituted a minor portion of our study, as Slovenia predominantly has public higher education institutions offering accredited free ICT programmes. Through the responses of high school and undergraduate students to the questionnaire, interviews with personnel at higher education institutions offering ICT programmes, and their online analyses, we largely validated the findings of secondary research mentioned in the theoretical part of the study and answered the research questions posed. We understood the psychographic needs and expectations of the target groups, enabling institutions to effectively market to them and conse-quently achieve the desired response and increased interest in enrolment. It was found that Gen-eration Z, which includes potential target groups, is less influenced by parents. Despite this indi- 207 w N ing an ICT institution. Most high school students selected career reasons and good earnings, while ed A L S Pr most undergraduate students cited personal interest and engagement. Consequently, high school CIE o students wish to see higher education institutions highlight career prospects and good earnings in ce N ed their promotions, while undergraduate students emphasise the importance of ICT competencies. TIF ing IC C Both target groups expressed a desire for increased promotional activities from institutions and s Bo O N more detailed information about the study process, in both digital and traditional formats. Surpris-ok FE R ingly, nearly half (48%) of undergraduate students were unaware of the alumni club, which most in-: P EN R er-R R independence. The target groups of high school and undergraduate students do not differ greatly N ev AT in their opinions, with significant differences observed mainly in their general reasons for choos-ie IO Pe IN students consider the opinions of teachers, friends, and acquaintances, regardless of their inherent TE vidualistic orientation, collective tendencies are also observed, as high school and undergraduate JE the educational process, postgraduate activities, and current job market conditions. This indicates T'S A CT M O CE I stitutions consider a key tool for connecting them with graduate students, helping them understand A BO affecting marketing strategies and consequently promotion and enrolment in their ICT programmes N U that institutional personnel do not fully grasp the needs and desires of target groups, negatively EM EO Regarding optimal digital channels for reaching target groups, they prefer receiving notifications EN A T P G at the first Bologna level in Slovenia. TR 02 student life, both the quality of life during and after studies is important, which contrasts with the 4 AT –2 secondary research findings in the theoretical part that indicated high school students are only in-EG IC T, S PLE 2 via email and social media (Facebook and Instagram), which is already standardised. Concerning C 02 terested in life during their upcoming undergraduate studies, and current undergraduate students 5 OM in life after. Secondary research also mentioned that a website is one of the most important factors M in attracting potential undergraduate students. However, it has been found that while the website U N may indeed be crucial for the initial „digital“ contact with a higher education institution, other mar - IC keting methods such as email marketing, social media interactivity, and live events are essential AT ION for ongoing communication. Institutional integrity and achievements also strongly influence high M school students‘ decisions, as undergraduate students value quality education and the expansion of A N A professional knowledge and competencies. G EM Factors from the 7P system are mostly present in their decisions, as: professors and administrative EN personnel, physical facilities, study process, study costs, location, promotional methods, and the rel- T, W evance of study programmes impact their choice of institution. Therefore, institutions effectively use EB these factors in their marketing strategies. A N D In Slovenia, higher education institutions offering ICT programmes strive to increase interest in IN such studies and consequently affect the shortage of ICT professionals in the job market, which is FOR currently the lowest in our country compared to other EU member states. However, despite their M efforts, they could use more sophisticated techniques and tools to achieve optimal promotional AT ION strategy results. Digital marketing allows for more precise targeting of the target groups com- T pared to traditional marketing (posters, radio, and television), as it covers a narrower audience EC H NOL spectrum and allows for detailed metrics through their responses. The use of specialised ana- O lytical tools for measuring target groups‘ responses and creating personalised targeting would G enable a more detailed understanding of their psychographics, including their habits, needs, de- IE S sires, and psychological and sociological profiles, thereby increasing the effectiveness of market - ing campaigns. With such manoeuvres, higher education institution personnel could also allocate marketing funds more effectively. Educational marketing is shown to be very important for educational institutions, as it represents a specialised marketing branch essential for executing successful marketing campaigns, despite the use of standardised digital marketing tools. The use of the 7P system in marketing strategies is also indispensable, as it includes the most influential factors on high school students‘ decisions. Higher school institutions and universities aim to establish long-term or loyal relationships with their undergraduate students, as personnel desire that their postgraduate students continue their education at higher levels and spread positive word-of-mouth about the integrity of their visit-ed higher education institution. The fact that many high school and undergraduate students first became aware of ICT institutions through elementary and high school competitions, teachers, or word of mouth indicates that traditional marketing, despite the advantages of digital marketing, 208 Both target groups stated they do not need proactive influencing factors from the environment w N edAL S for their decisions, as they based their choices on personal motivation and institutional integrity PrCIE o (achievements of students, professors, modern study programmes, equipment). This demonstrates ceN ed that the most crucial factor for promoting an institution is its reputation or brand, which is self-pro-TIF ingIC C moting through excellent results, as institutions with excellent academic results and reputation can s BoO promote themselves more easily, with positive information spreading on its own. Brand recognition N okFE is essential for attracting new students.R : PEN Regarding the use of digital channels for promoting ICT studies, it has been shown that institutional pression, as all five human senses are activated, capturing the broadest and most comprehensive er-R RN evAT spectrum of information. ieIO been present in human society for the longest time, and live events leave the most lasting im- Pe INTE remains indispensable. This is likely because analogue technology and oral communication have O CE I R personnel recognise their importance, as they use: websites, email marketing, and social media JE T'S A CT (Facebook, Instagram, and LinkedIn). Among digital channels, email and Facebook stand out. For MB AO those exploring an institution, the most crucial digital channel is its well-structured and designed NU AT P G website, with a pleasant and intuitive user experience and relevant, clear information. This should EMEO be created using standardised psychological practices (F-shape, segmentation) identified by lead - ENPLE 2 ing psychology experts, who, through cognitive or behaviourist psychology, have determined that T, S user profiles and experiences should be developed from a “human-centric” perspective. TR024 AT–2 EG 5.2 Recommendations for Further Research IC02 C5 OM I would recommend conducting additional research on the reasons for graduated students leaving M for abroad and prematurely terminating their ICT studies, as this also affects the shortage of ICT pro - U N fessionals in Slovenia. Additionally, I suggest researching the target group of employed adults, par- IC AT ticularly those from Generation X and Y, aged between 30 and 45 (Kolnhofer-Derecskei et al. 2017), ION which was not covered due to a small sample size. Researching similar areas for other educational M levels would also be beneficial. A N A G 5.3 Final Thought EM EN Communication skills and strategies represent a form of modern art, essential for achieving com- T, W petitiveness and competence. The marketing industry plays a crucial role in understanding target EB groups, as it is the primary indicator of shifts in public opinion, trends, habits, and individuals‘ life- A N styles. Higher education institutions with ICT study programmes in the Republic of Slovenia should D IN continue to strive for more objective approaches in addressing target groups and continuously ana- FOR lyse the opinions of high school and undergraduate students. This would allow for better formula- M tion of marketing strategies. Students (high school and undergraeduate) could become co-creators AT ION of marketing strategies, as marketing personnel could use their behaviour and opinions on digital T channels to more promptly develop and adjust marketing strategies. Based on such analytics for EC H precise determination of psychographic profiles, the use of personalised marketing approaches, NOL such as creating imaginary buyer personas representing specific target groups, is an indispensable OG element in the marketing context.IES 209 Pe REFERENCES IN TE er 1. Brodschneider, Aleksandar. 2023. Digital Marketing and Promotion of Slovenian Higher Education -R R N ev AT Study Programs in the Field of Information and Communication Technologies at the First Bologna ie IO Cycle . Zenodo. https://doi.org/10.5281/zenodo.13743556. w N ed A L S 2. Brodschneider, Aleksandar. 2023. 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Journal of Consumer Marketing 29(2): 86–92. https://doi.org/10.1108/07363761211206339. 210 Published scientific conference contribution Pe INTE 1.08 Objavljeni znanstveni prispevek na konferenci er-R RN evAT ieIO EVOLUTION AND APPLICATIONS ACROSS w N edAL S Pr o DISCIPLINES OF THE UTAUT MODELCIE ceN edTIF ingIC C The Unified Theory of Acceptance and Use of Technology (UTAUT), developed by Venkatesh et al., N OU AT P G EM builds upon the Technology Acceptance Model (TAM) and serves as an important framework for EO ENPL understanding user acceptance and adoption of new technologies before their implementation. E 2 T, S It consolidates elements from multiple theoretical models, offering a comprehensive perspec - TR024 tive on factors influencing technology acceptance, including performance expectancy, effort ex - AT–2 EG pectancy, social influence and facilitating conditions, moderated by the constructs gender, age, IC02 experience and voluntariness of use. The extended UTAUT2 model, along with the four well- C5 OM known factors it adopted from UTAUT, integrates additional constructs such as hedonic motiva- M U tion, price value, and habit, enhancing its applicability to consumer-oriented technologies. How- N IC ever, it is not moderated by all four constructs from UTAUT, as it excludes voluntariness of use. AT University of Applied Sciences Hrvatsko Zagorje Krapina - Laboratory for Spatial Intelligence, Croatia EN R OCE I JET'S A CT ABSTRACT MB A Alma Mater Europaea University, Slovenia ok FER : P Marko Mikša, PhD Candidate s Bo ON UTAUT2 has been expanded into the field of consumer technologies. In the literature, UTAUT3 is ION additional constructs such as trust, perceived enjoyment, anxiety, and personal innovativeness, ANA among others. sometimes mentioned, but it does not officially exist. Instead, it is usually a modified UTAUT with M EMG This study explores the evolution and application of the UTAUT model across various disciplines. EN A literature review reveals its adaptability in diverse contexts, including mobile banking, health- T, W care, online information services, and more. The findings highlight the relevance of the UTAUT EB A model in studying the dynamics of technology adoption while identifying areas for refinement. ND By integrating additional individual-level factors, the model can better capture the complexities IN of user behaviour. As technology continues to evolve, the UTAUT framework remains a valuable FOR merous disciplines. ATION tool for researchers in understanding technology adoption patterns with applications across nu- M plications HNOL Keywords: UTAUT, UTAUT2, Technology adoption, Technology acceptance, Interdisciplinary ap- TEC O IEG S 211 Pe 1 INTRODUCTION IN TE er-R R The Unified Theory of Acceptance and Use of Technology (UTAUT) has emerged as a prominent N ev AT framework for understanding and predicting the adoption and use of various technologies (Dwive-ie IO w di et al. 2020). The purpose of UTAUT is to examine the behaviour of individuals in the decision-mak-N ed A L S ing process of using technology-oriented innovations (Majeed 2020; Mohamed et al 2021). It was Pr developed based on the theoretical model for predicting the acceptance and use of technology, TAM o CIE ce N (Technology Acceptance Model), by Fred Davis, and it derives from the Theory of Reasoned Action ed TIF (TRA) and Theory of Planned Behaviour (TPB) (Davis 1989). ing IC C ok FE the belief that a technology will improve work effectiveness, bringing benefits such as monetary re-R : P s Bo O One of the fundamental constructs of the TAM framework is perceived usefulness, which refers to N EM EO UTAUT is widely applicable across various fields because it allows the examination of more complex EN PL E 2 models of human behaviour in relation to technological advancements. His main constructs are sim-T, S ilar to those in TAM but also include performance expectancy, effort expectancy, social influence and TR 02 4 AT facilitating conditions, which are moderated by gender, age, experience, and voluntariness of use –2 EG IC 02 (Venkatesh 2003). The UTAUT model has been extended to UTAUT2 enabling a better understanding C 5 of technology acceptance in various contexts. UTAUT2 incorporate additional factors such as hedon-OM ic motivation, price value and habit, moderated by gender, age and experience, (Venkatesh et al. M U N 2012; Oh and Yoon 2013; Majeed 2020). This literature review research the evolution and interdis-IC ciplinary applications of the UTAUT model to various fields and highlights its potential for further AT ION CT T'S A effort to use (Davis 1989). TAM model is expanded by Venkatesh et al. (2003) into TAM2 and TAM3, M B A and further developed into the UTAUT which take over core concepts from the TAM model to address O N U A T P various challenges in testing new technology acceptance. G O CE I er construct is perceived ease of use, which refers to the belief that the technology requires minimal JE R EN wards, increased speed, simplicity and work efficiency, and similar advantages (Davis 1989). Anoth- applications in the adoption of technology. M ANA 2 PURPOSE AND GOALS G EM The purpose of this research is to explore the origins and development of the UTAUT model. It is EN important to evaluate UTAUT’s applications in different fields, with the main goal of identifying the T, W key benefits, its possible future application, and suggesting improvements for future research. Main EB A goal of this research: How is the UTAUT model and its modifications applied across different disci-N D plines, and what improvements are needed? IN FOR ATIONM 3 METHODS This study uses a literature review methodology and provides key insights into the development EC T and use of the UTAUT model and its modifications. Research databases such as Google Scholar, H IEEE, PubMed, and ProQuest were used to find papers focused on the UTAUT model and keywords NOL O such as “UTAUT model,” “UTAUT2 model,” “technology acceptance model,” “TAM,” and “technolo- G gy adoption model.” To gather information about the history, evolution, and application of the IE S UTAUT model, relevant studies, meta-analyses, case studies, and original empirical research were reviewed. To ensure reliability, ethical standards were strictly adhered to, and only peer-reviewed sources were included. 4 RESULTS The initial UTAUT model developed by Venkatesh et al. (2003) integrates several previous technol-ogy acceptance models with enhancements that are key determinants for identifying the intention and actual use of technology. It has been used worldwide in numerous empirical studies and has proven to be a reliable tool for predicting user behavior (Venkatesh et al. 2003). 212 Figure 1: UTAUT model er TE -R Pe IN ie IO wN edAL S PrCIE ev RNAT ceo ed TIFN ing IC C ok FER : P s Bo ON R EN O CE I CTJE T'S A N OU AT P A B M EMG EN PLE 2 T, SEO TR 024 AT–2 EG IC02 C5 OM M U N (Source: Venkatesh et al. 2003, 447) ATIC ION - performance expectancy—the degree of confidence that using the technology will improve the ANA As shown in Figure 1, its main constructs are: M user’s work efficiency, GEM - effort expectancy—the degree of ease associated with using the technology. EN - social influence—the construct in which the user perceives the importance of close people T, W - facilitating conditions – the degree of confidence that there is organizational and technical sup (friends, siblings, parents, etc.) recommending the use of the technology, EB AN-D IN port for using the technology. (Venkatesh et al. 2003)FOR conditions and behavioral intention (Venkatesh et al. 2003) . ATION These constructs directly influence behavioral intention, while use behavior depends on facilitating M moderating variables: gender, age, experience, and voluntariness of use (Venkatesh et al. 2003). ECH In order to achieve greater accuracy of the model in predicting user behavior, this model uses four T They moderate the influence of the main constructs on behavioral intention, for example, by using NOL the variable gender to further determine whether men or women have a greater impact on the OG formation of effort expectancy toward behavioral intention (Venkatesh et al. 2003). In this way, user IES behavior is examined more deeply, increasing the likelihood of a better assessment. On the other hand, the UTAUT2 model developed by Venkatesh et al. (2012) extends the application of the original UTAUT model to consumer technologies and includes additional constructs that are predominantly key for this domain (Venkatesh et al. 2012). 213 Figure 2: UTAUT2 model er TE-R Pe IN ie IO wN edAL S PrCIE ev RNAT ceo ed TIFN ing IC C ok FER : P s Bo ON R EN O CE I CTJE T'S A N OU AT P A B M EMG EN PLE 2 T, SEO TR 024 AT–2 EG IC02 C5 OM M U N ATIC ION M ANAGEM (Source: Venkatesh et al. 2012, 160) EN T, W As can be seen in Figure 2, the main improvements and modifications of the UTAUT2 model involve EB A the addition of three new constructs in consumer contexts (Venkatesh et al. 2012): N D- hedonic motivation—the degree to which the user experiences pleasure from using the technology, IN FOR- price value—the user’s perception of the price-to-benefit ratio of the technology, ATM - habit—the extent to which the user independently and routinely uses a particular technology. ION In addition to the newly added constructs, the moderating variables have been adjusted by remov- T ing the variable of voluntariness of use, but leaving age, gender, and experience. In the organiza- EC H tional context, performance expectancy remains a key factor, as users make decisions based on the NOL expected benefits of using the technology, but in the consumer context, hedonic motivation and O G habit dominate in shaping use behavior (Venkatesh et al. 2012). IE S This study reveals that the core dimensions of UTAUT (performance expectancy, effort expectancy, social influence, facilitating conditions) remain the primary determinants of behavioral intention, which subsequently influences use behavior. Table 1: Key Differences Between UTAUT and UTAUT2 Criterion UTAUT UTAUT2 Application organizations and employees consumers and general public Core Constructs 4 7 Additional Constructs none hedonic motivation, price value, habit Moderating Variables gender, age, experience, voluntariness of use gender, age, experience (Source: Author) 214 while price value reflects the perceived cost-effectiveness of the examined technology. Finally, the habit w N edA factor examines whether users develop a routine when engaging with the technology.L S PrCIE o These findings have been confirmed through numerous empirical studies, including those conduct - ceN ed ed by Venkatesh et al. (2003; 2012), as well as later research and meta-analyses (Blut et al. 2022). TIF ingIC C Although UTAUT is widely used, its robustness and versatility are sometimes overestimated. Blut et s BoO al. (2022) propose a revised UTAUT model that incorporates new endogenous mechanisms from N okFE other theories, such as technology compatibility, user education, personal innovativeness, and tech-R : PEN nology costs, as well as new moderating variables, including technology type and national culture, al and financial aspects that are particularly relevant to research sample. The additional factor of hedonic er-R RN evAT motivation provides insight into whether the user experiences enjoyment while using the technology, ieIO hances the model’s predictive capability for consumers and the general public by incorporating emotion- Pe INTE UTAUT is often modified with new predictors to adapt to new research. As shown in Table 1, UTAUT2 en- O CE I R to assess the actual versatility of the UTAUT model. JE T'S A CT In the literature, the UTAUT3 model is sometimes mentioned, although it does not formally exist. MB AO Instead, it refers to adaptations of UTAUT or UTAUT2 that various authors modify for their research NU AT P G purposes. For example, Alhalafi and Veeraraghavan (2023) expanded the UTAUT model by incorpo - EMEO rating safety, resiliency, availability, confidentiality, and integrity of cybersecurity alongside the four ENPLE 2 well-known UTAUT constructs. Their goal was to better understand the adoption of cybersecurity T, S practices in Saudi smart cities, and they referred to their modified model as UTAUT3. Also, authors TR024 Bhatnagr and Rajesh (2023) used additional constructs, perceived risk of privacy and perceived risk AT–2 EG IC02 of performance, to examine factors affecting neobanking adoption in India. They also named their C5 extended model UTAUT3. Similarly, Patil et al. (2020) extended the UTAUT model by adding person- OM al innovativeness, anxiety, trust, and grievance redressal to examine consumer intentions to use MU mobile payment systems in India. However, they did not label their modified model as UTAUT3 but NIC rather as meta-UTAUT, which is more appropriate. A multitude of authors use their own modification ATION of the UTAUT model, but they should not take the liberty of renaming it UTAUT3, as the additional M constructs vary greatly from one study to another.ANAGEM 5 DISCUSSION ENT, W 5.1 Empirical Findings and Theoretical Alignment Research on technology acceptance and adoption indicates that the UTAUT model is among the EB AN most widely used frameworks for understanding user behavior in different technological contexts, D IN ranking just after the TAM model. Its capacity to integrate multiple theoretical perspectives has con-FOR tributed to its broad application in business, education, and consumer sectors, as well as in other M fields where evaluating technology usage before implementation is necessary. The development of ATION UTAUT2, which introduced factors like hedonic motivation, price value, and habit, has strengthened T its predictive accuracy, particularly in consumer technology settings.ECH However, although UTAUT is widely used, some studies highlight its limitations, which various au-NOL thors have addressed by adding individual constructs such as trust, perceived enjoyment, anxiety, OG and personal innovativeness. For example, Blut et al. (2022) and Patil et al. (2020) extended the IES UTAUT model with additional constructs to increase its explanatory power in the specific contexts they studied. This confirms the versatility of the UTAUT model, as well as the need for continuous adaptation to new research challenges. Since Alhalafi and Veeraraghavan (2023) named their adaptation UTAUT3 to include factors related to cybersecurity, while other authors have expanded the model without designating a new version, it is likely that an official UTAUT3 with prescribed constructs will eventually be developed. However, this is not necessarily required, as researchers can always use the original UTAUT model and add individual constructs as needed, without explicitly renaming the model. 5.2 Applications of the UTAUT Model Across Disciplines The UTAUT model is widely applied in many fields due to its adaptability and relevance in under-standing technology adoption. In its basic or modified form as UTAUT2, it is used in healthcare, edu- 215 er-R R maier et al. 2022). Research has shown that performance expectancy and effort expectancy are key N ev AT predictors of the intention to use mobile health services and electronic health records, with mobile ie IO Pe IN of use, which significantly influence the adoption of mobile healthcare system (mHealth) (Schretzl-TE cation, banking and financial services, construction and more. It provides worldwide trust and ease w N self—efficacy often serving as a moderating factor in these relationships (Gopalakrishna—Remani ed A L S Pr 2018; Alam et al. 2019; Dwivedi et al. 2020; Addisalem et al. 2024). UTAUT is a powerful tool for CIE o examining the acceptance of e—learning with mobile devices and other tools for educational pur-ce N ed poses as it contributes to the development of inclusive and tailored technologies in education (Hoi TIF ing IC C 2019; Xue et al. 2024). Through this model, key constructs are explored in education to understand ok FE sights into assumed user behaviour, UTAUT enables the identification of barriers to the introduction R : P s Bo O how students and teachers perceive technology and whether they intend to use it. By providing in-N CT T'S A M The next interesting application of the UTAUT model and its modified version UTAUT2, is in mobile B A O banking, where it was examined to what extent users are willing to use mobile banking applica-N U A T P G O CE I (Hoi 2019; Xue et al. 2024). JE R EN of digital tools in classrooms and thus the development of strategies to increase learning efficiency EM EO used to examine whether users in Germany are ready for autonomous delivery robots, which could EN tions (Baabdullah et al. 2018; Bhatnagr and Rajesh 2023; Majeed 2020). Additionally, UTAUT2 was T, S PLE 2 potentially increase customer satisfaction and delivery quality by reducing delivery costs and the TR time required for delivery (Kaiser et al. 2024). In India, a study using the UTAUT model was conduct- 02 4 AT ed on low—income residents, with the aim of analysing the factors influencing the acceptance of –2 EG IC 02 cheaper smartphones (Baishya and Samalia 2019). As an additional construct, Perceived Monetary C 5 Value was used, which shows that the UTAUT model is highly adaptable and applicable in many sit- OM uations. (Baishya and Samalia 2019). M U N Using the UTAUT model with attitude as a mediating variable, the acceptance of the electronic gov- IC ernment system (e—Government system) was examined in India in 2015 (Rana et al. 2015). Accord- AT ION ing to the research by Hewavitharana et al. (2021), the construction industry is also an area where M UTAUT has been recognised as a model with significant potential in identifying motivators and bar - A N A riers for digital transformation in the construction industry. The acceptance of a relatively new field, G artificial intelligence, was examined in the academic environment of developing countries using an EM EN extended UTAUT model that includes trust and privacy as key variables that directly affect behavioral T, W intention and use behaviour (Rana et al. 2024). EB AND 6 CONCLUSION IN FOR The UTAUT model is highly adaptable and should be leveraged in research on rapidly evolving tech- AT and similar domains. If researchers choose to refer to a modified version as UTAUT3, it would be M nological fields, including artificial intelligence, blockchain, the Internet of Things (IoT), smart cities, ION EC and ensure consistent application in studies. The possibility of adapting the UTAUT model should H NOL T necessary to establish clearer standards for extending the original UTAUT model to avoid confusion be utilized in research on rapidly developing technological fields, including artificial intelligence, O blockchain, the Internet of Things (IoT), smart cities, and related areas. Although an extension to G IE UTAUT3 is not necessarily due to its adaptability, such extensions should be more clearly defined to S avoid confusion and ensure consistent application in research. Although the UTAUT model remains useful and relevant, its adaptation to new contexts and technological challenges is essential for ensuring maintaining and predictive power in future research. 216 REFERENCES Pe INTE 1. Addisalem Workie Demsash, Mulugeta Hayelom Kalayou, and Agmasie Damtew Walle. 2024. er -RRN Health Professionals’ Acceptance of Mobile-Based Clinical Guideline Application in a Re- evAT ie source-Limited Setting: Using a Modified UTAUT Model. 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EN T, W AUTHOR BIOGRAPHY EB A N D Marko Mikša is a lecturer at the University of Applied Sciences Hrvatsko Zagorje Krapina, and a PhD IN student at Alma Mater Europaea University. His area of interest is e-learning. FOR ATM ION EC T H NOL O IEG S 218 Published scientific conference contribution Pe INTE 1.08 Objavljeni znanstveni prispevek na konferenci er-R RN evAT ieIO ARTIFICIAL INTELLIGENCE AUGMENTED SYSTEM IN w N edAL S Pr o HEALTHCARE USING DEEP LEARNING ALGORITHMSCIE ceN edTIF ingIC C Alma Mater Europaea University, Slovenia ok FER : P Kennedy Addo, PhD Candidate s Bo ON R EN ABSTRACT JE T'S A CT O CE I Deep learning algorithms are reshaping healthcare by enabling advanced diagnostic, predictive, B M A O NU A and decision-support capabilities that frequently rival or surpass traditional clinical methods. De- T P G ed to data quality, ethical concerns, and workflow integration within clinical settings. This study in EN PL -E 2 T, S spite this strong technical promise, real-world adoption continues to face significant barriers relat EM - EO vestigates how deep learning-powered AI-augmented systems can improve healthcare delivery, TR 024 with particular attention to their accuracy, clinical applications, and implementation challenges. AT–2 EG A mixed-methods approach was employed. Quantitative analyses evaluated supervised, unsu- IC02 C5 pervised, and reinforcement learning models using standard performance metrics-accuracy, OM sensitivity, and specificity-while qualitative insights were derived from semi-structured inter- M views with healthcare professionals. U N predictive performance, with accuracy rates ranging from 90% to 98% across applications such ION M as medical imaging, genomic data analysis, and electronic health records. Unsupervised learn-AN Findings demonstrated that supervised learning models consistently achieved the strongest ATIC ing supported patient stratification and exploratory discovery, whereas reinforcement learning AG showed adaptive promise in sequential decision-making, especially in complex treatment plan- EM ning scenarios. EN Qualitative results emphasized three dominant themes: clinician trust, workflow efficiency, and T, W ethical considerations. Participants valued the diagnostic accuracy and time-saving potential of EB AN AI but stressed the importance of transparency, explainability, and strict data privacy safeguards. D IN The discussion confirmed that supervised learning excels in structured contexts, unsupervised FOR learning adds discovery value, and reinforcement learning provides adaptability though limited M by stability and resource demands.ATION In conclusion, integrating diverse deep learning approaches, supported by explainable AI, T can deliver robust, trustworthy, and clinically relevant healthcare solutions. Future research ECH should advance hybrid models, explainability frameworks, and multi-institutional validation to NOL strengthen adoption. OG Keywords: Deep Learning, Healthcare, Disease Diagnosis, AI-Augmented Systems, ExplainabilityIES 219 Pe 1 INTRODUCTION IN TE er-R R Artificial Intelligence (AI), particularly deep learning (DL), has unlocked transformative poten-N ev AT tial in healthcare, with models adept at complex clinical tasks-such as analyzing medical imaging ie IO w and predicting patient outcomes-with precision rivaling human experts (Khare et al. 2025; Padhi N ed A L S et al. 2023). A comprehensive review of multimodal deep learning applications across healthcare Pr domains revealed that integrating diverse data sources like imaging and electronic health records o CIE ce N (EHR) enhances diagnostic performance by an average of 6.2 percentage points in AUC compared to ed TIF unimodal approaches, demonstrating clear technical promise arXiv (Rele et al. 2024). ing IC C ok FE lenges. Implementation barriers include data insufficiency, interoperability complexities, and pri-R : P s Bo O Despite this progress, real-world adoption of AI-augmented systems is hindered by significant chal-N CT T'S A that erode clinician trust and responsibility. Additionally, leadership hesitation-stemming from un- M B A certainty over professional role shifts and cautious culture-often stalls integration into routine prac-O N U A T P tice (Kanagarajah 2024, 45). G O CE I Ethical concerns also weigh heavily, especially the black-box nature of deep learning algorithms JE R EN vacy constraints, which limit model generalizability and real-world utility (Pesqueira et al. 2025). EM EO Deep learning transforms healthcare by enhancing diagnostics and predictions. Techniques like EN PL E 2 Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) leverage large-scale T, S data for improved disease detection, personalized medicine, and clinical decision-making. These TR 02 4 AT models achieve high accuracy in diagnosing conditions such as cancer, diabetes, and skin diseas-–2 EG IC 02 es, further highlighting their clinical value (Shakor and Khaleel 2025, 62005-62028; Alqudah and C 5 Moussavi 2025, 3753-3841). OM M Explainable AI (XAI) methods, such as SHAP and LIME, have been proposed to address transparency U N concerns. In disease diagnosis contexts, SHAP appeared in 38% and LIME in 26% of recent studies, IC showing their dominance in improving model interpretability (Kalasampath et al. 2025). Moreover, AT ION clinician trust and adoption of XAI significantly improve when explanation techniques-like Grad- M CAM heatmaps or SHAP attributions-align with medical reasoning (Alharthi et al. 2024). A N A Although deep learning has demonstrated significant technical advantages in healthcare, persis - G EM tent challenges-such as fragmented data integration, opaque algorithms, and misalignment with EN clinical workflows-continue to hinder its effective implementation. Few studies have holistically T, W combined multimodal data fusion, interpretability, and user-centered deployment into a single EB framework. A N D To address these shortcomings, this study proposes the design and evaluation of an AI-augmented IN healthcare system that integrates multimodal medical data (e.g., imaging and EHR), incorporates FOR explainable deep learning models for transparency, and prioritizes clinical relevance and usability. M By uniting technical, ethical, and implementation considerations into a cohesive architecture, the AT ION study aims to advance beyond proof-of-concept toward operationally feasible, trustworthy, and ef- T fective AI solutions in healthcare. EC H NOL O 2 PURPOSE AND GOALS IEG S The purpose of this study is to investigate how Artificial Intelligence (AI)-augmented systems, spe- cifically those powered by deep learning algorithms, can enhance healthcare delivery through im-proved disease diagnosis, prediction, and clinical decision support. As healthcare systems worldwide face increasing pressure from growing patient populations, limited resources, and the demand for precision medicine, there is a critical need to examine how deep learning models can bridge exist-ing gaps in efficiency, accuracy, and accessibility. The main goals of the study are as follows: 1. To explore the potential of deep learning algorithms in healthcare. 2. To examine the applications of AI-augmented systems in disease diagnosis and prediction. 3. To analyze the benefits and challenges of implementing AI-augmented systems in healthcare. 220 2.1 Research Questions (qualitative orientation) 2. What are the current applications and real-world use cases of AI-augmented systems in disease RNAT ev prediction and clinical decision-making? ieIO w 1. How can deep learning algorithms improve diagnostic accuracy and patient outcomes in healthcare? TE er -R Pe IN 3. What are the key benefits and challenges of implementing AI-augmented systems in healthcare? ed NAL S Pr 3 METHODS TIF ingIC C 3.1 Research Paradigm ce N ed o CIE proaches. The quantitative component enabled statistical analysis of AI-augmented systems using EN R OCE I deep learning algorithms, while the qualitative component provided insights into healthcare prac - JET'S A titioners’ experiences and perceptions. CT MB A This study adopted a mixed-methods paradigm, combining both quantitative and qualitative ap ok FE -R : P s Bo ON 3.2 Implemented Instruments N OU AT P G EMEO Quantitative data were collected using structured survey questionnaires and performance evalu - ENPL ation datasets processed through AI models. Qualitative data were gathered through semi-struc-E 2 T, S tured interviews with healthcare providers and IT specialists engaged with AI-driven systems. TR024 AT–2 EG 3.3 Pattern and Course of Research IC02 C5 OM The research followed a sequential explanatory design. In the first phase, quantitative data were collected and analyzed to assess the performance of AI algorithms. In the second phase, qualitative MUN interviews were conducted to interpret and contextualize the results, ensuring a comprehensive ICAT understanding of the role of AI-augmented systems in healthcare delivery.ION 3.4 Ethical Permissions and Participant Safeguards MANA Ethical clearance procedures were acknowledged in accordance with standard research guidelines. GEM Participation was voluntary, with informed consent obtained prior to data collection, and anonymi- EN ty of respondents was strictly maintained. T, W 3.5 Data Collection EB AND Time-period: Not applicable, as the study used secondary datasets and published sources. INFOR Location: The study context was healthcare facilities in Ghana, though no direct field data were collected.M Quantitative Data Collection: AI algorithm performance was tested using datasets structured for su-ATION pervised, unsupervised, and reinforcement learning approaches. T Qualitative Data Collection: Interviews were audio-recorded, transcribed verbatim, and anonymized.ECHNOL 3.6 Data Processing and Analysis OGIE Quantitative Analysis: Data were processed using Python 3.10 with TensorFlow and Scikit-learn li-S braries. Evaluation of AI models was based on standard metrics accuracy, sensitivity, and specificity. Statistical analyses were further performed with SPSS version 27 to validate findings. Qualitative Analysis: Interview transcripts were thematically analyzed through systematic transcrip-tion, coding, categorization, and identification of emergent themes to support interpretation of the quantitative results. 3.7 Summary of Analytical Approaches The quantitative phase emphasized three AI learning paradigms-supervised, unsupervised, and reinforcement learning-evaluated against accuracy, sensitivity, and specificity as key performance metrics. The qualitative phase complemented this by identifying practitioners’ perspectives, contex-tual challenges, and experiential insights regarding AI-driven healthcare systems. 221 Pe 4 RESULTS IN TE er-R R This section presents the findings of the study, supported by descriptive tables and schematic rep-N ev AT resentations. The results are organized around the main objectives of the research. ie IO w N ed A 4.1 Accuracy and Performance of AI-Augmented Systems L S Pr CIE o Overall, deep learning demonstrates robust performance across these domains. Medical imaging ce N ed TIF models achieved the highest accuracies, up to 98%, consistently outperforming human baselines in ing IC C specific diagnostic tasks. Genomic data analysis models were effective in predicting mutations and s Bo O N supporting personalized medicine, with accuracies reaching 95%. EHR-based applications enhanced FE ok diagnostic support and enabled efficient patient stratification, achieving accuracies up to 96%. These R : P EN findings underscore the capability of AI-augmented systems to deliver reliable and clinically rele-R O CE I vant results while highlighting domain-specific strengths. Table 1 presents the accuracy ranges of JE T'S A CT deep learning models across key healthcare application areas. M B A O N U A Table 1: Accuracy Rates of AI-Augmented Systems Across Healthcare Applications T P G EM EO Accuracy EN PL E 2 Application Area Range (%) Notes T, S TR 02 Medical Imaging (X-ray, MRI, CT) 94-98 Consistently higher than human baseline in certain tasks 4 AT –2 Genomic Data Analysis 90-95 Effective in mutation prediction and personalized medicine EG IC 02 C 5 EHR and Clinical Records 91-96 Improved diagnostic support and patient stratification OM U The performance of AI-augmented systems across different healthcare applications was assessed M N ATIC in terms of accuracy. As shown in Figure 1, these systems demonstrate consistently high accuracy ION rates, with medical imaging, genomic data analysis, and electronic health records all benefiting M from deep learning approaches. ANA Figure 1: Accuracy Rates of AI-Augmented Systems Across Healthcare Applications G EM EN T, W EB AND INFOR ATM ION EC T H NOL O IEG S 4.2 AI Applications in Diagnosis and Prediction via Data Integration Deep learning models demonstrated the capability to integrate diverse healthcare data sourc-es-electronic health records (EHRs), medical imaging, and genomic datasets-into a unified frame-work. This multimodal integration enabled comprehensive patient-level analyses, enhanced pre-dictive modeling, and improved clinical decision support outputs. 222 4.2.1 Qualitative Findings tegrate and utilize healthcare data. Table 2 summarizes these categories, the associated codes, and RNAT ev representative statements from participants that illustrate each code. ieIO w Analysis of the qualitative data revealed three primary categories that describe how AI systems in- TE er -R Pe IN Table 2: Qualitative Codes and Representative Statements on Data Integration Across Sources ed NAL S Pr Category ce N Code Representative Statement ed o CIE EHR Integration “The model uses patient records to track historical trends and identify ing TIFIC C Data Sources ok FE “X-rays and MRIs are combined with patient history to provide a more R Medical Imaging Integration Integration risk factors efficiently.” s Bo ON Genomic Data Integration complete picture for diagnosis.” : P EN R OCE I “Genomic information allows the system to predict personalized JE responses to treatments.”T'S A CT MB A Model Multimodal Predictive “When all data sources are combined, the predictions are noticeably O NU more reliable than using single-source data.” AT P G EM PerformanceEO Accuracy Data Processing “Integration reduces time spent manually correlating lab, imaging, and EN Efficiency patient history data.”PLE 2 T, S “The system flags potential complications early, allowing timely TR02 Actionable Recommendations Clinical 4 interventions.” AT–2 Decision EG Support Utility “Combining genomic, imaging, and clinical data helps tailor treatments IC02 Personalized Care Planning C to individual patients.”5 OM The schematic shows how individual codes-trust in AI, workflow efficiency, and ethical con UM- NIC cerns-were grouped into overarching categories, reflecting the broader theme of adoption of AI in AT healthcare as shown in figure 2.ION M Figure 2: Codes and Categories Developed from Qualitative Data ANAGEMENT, W EB AND INFOR ATM ION EC T H NOL O IEG S 4.2.2 Analysis / Judgment The integration of EHR, imaging, and genomic data through deep learning provides a more com-plete and nuanced understanding of patients. Clinicians reported that the combined insights from these data sources made predictions noticeably more reliable than when using any single type of data alone. By capturing a broader spectrum of patient information, the models support personal-ized care planning, enabling interventions that are tailored to the individual’s health profile. Par-ticipants also highlighted the practical benefits, noting that the system reduces the time and effort needed to manually cross-reference data while flagging potential complications early. Overall, the findings suggest that multimodal integration not only improves predictive performance but also enhances the usability and relevance of clinical decision support, helping healthcare providers make more confident and informed decisions. 223 4.3 Key Challenges in Implementing AI-Augmented Systems in Healthcare er TE AI-augmented systems in healthcare offer notable advantages, including improved predictive accu--R Pe IN ie IO these benefits, several challenges limit their broader adoption. One major issue is limited data w N ed A availability. Many deep learning systems rely on large, high-quality annotated datasets, which are L S Pr not always accessible, resulting in models that may not generalize well to diverse clinical settings. ev RNAT racy, more reliable clinical decision support, and enhanced workflow efficiency. However, despite ing TIF ing, and genomic datasets increases computational demands and introduces the risk of overfitting if IC C not managed properly. Finally, model interpretability remains a key concern. Deep learning models s Bo ce N Another challenge is the high dimensionality of multimodal data. Integrating EHRs, medical imag-ed o CIE CT M Table 3: Challenges in AI-Augmented Healthcare Systems B A O N U A Challenge Description Implications T P G EM EO Limited Data Availability Lack of high-quality annotated datasets Reduced model generalizability EN PL E 2 T, S High Dimensionality Complex multimodal inputs Increased resource demand, risk of overfitting TR 02 Model Interpretability Lack of transparency in decision-making Slows clinical adoption 4 AT –2 EG : P R recommendations. Table 3 summarizes the main challenges identified, their descriptions, and the EN R implications for healthcare practice. O CE I JE T'S A ok N are often perceived as “black boxes,” making it difficult for clinicians to fully trust and adopt their FE O C 5 4.3.1 Qualitative Results (Coding and Categories) OM IC 02 M The qualitative exploration of clinician perspectives highlighted three key themes: trust, efficiency, U N IC and ethical concerns. These codes were developed from participants’ statements and grouped into AT overarching categories, reflecting factors influencing the adoption of AI in healthcare as shown in ION table 4. M ANA Table 4: Qualitative Codes and Representative Statements on Adoption of AI in Healthcare G EM Code Representative Statement EN T, W Trust in AI “The system improves diagnosis, but I need to understand how it works before fully relying on it.” EB Efficiency in Workflow “AI reduced the time for reviewing patient scans, allowing me to focus more on care delivery.” A N D Ethical Concerns “We must be cautious about patient privacy when integrating large-scale data into AI models.” IN FOR The diagram shows how individual codes-trust in AI, efficiency in workflow, and ethical con-M AT cerns-were grouped into categories, which together reflect the overarching theme of adoption of ION AI in healthcare (figure 3). T EC H Figure 3: Codes and Categories Developed from Qualitative Data NOL O IEG S 224 4.3.2 Analysis/Judgement these findings highlight the nuanced challenges that influence their adoption. Clinicians appre RN - evAT ciate the efficiency gains AI offers, such as reduced time spent reviewing patient scans and more ieIO w While AI-augmented systems have the potential to significantly enhance healthcare delivery, TE er -R Pe IN focus on patient care. However, trust remains a critical factor; understanding how AI reaches its ed NAL S Pr conclusions is essential for clinicians to rely on its recommendations confidently. Ethical concerns, oCIE particularly regarding patient privacy and data security, also play a significant role in shaping per - ceN ed ceptions and acceptance.TIF ingIC C Together, the quantitative challenges and qualitative insights underscore that technical perfor- s Bo ON mance alone is insufficient for adoption. Success in implementing AI in healthcare depends on ad - okFER dressing data limitations, improving interpretability, and aligning system design with clinician trust : PEN R and ethical standards. These considerations are crucial for integrating AI tools into routine clinical OCE I JE workflows in a safe and responsible manner.T'S A CT MB AO NU 5 DISCUSSION AT P G EMEO The present study analyzed three major machine learning approaches-supervised learning, un- ENPLE 2 supervised learning, and reinforcement learning-while evaluating their performance using es- T, S TR02 tablished metrics such as accuracy, sensitivity, and specificity. The results demonstrate that super -4 AT–2 vised learning consistently achieves higher accuracy and sensitivity across structured datasets, EG IC02 particularly in domains where sufficient labeled data is available. Unsupervised learning, while C5 OM weaker in sensitivity, provided valuable clustering insights and feature discovery, supporting its strength in exploratory analysis. Reinforcement learning, though less stable in early stages, dis- MUN played promising adaptability in dynamic environments, especially when decision-making under ICAT uncertainty was required.ION 5.1 Interpretation of Results and Hypothesis Testing MANA The primary hypothesis of the study posited that supervised learning would outperform other meth-GEM ods in terms of predictive accuracy when sufficient labeled data is available. The findings confirm EN this hypothesis, as supervised models yielded the highest accuracy and sensitivity. This supports the T, W broader understanding in machine learning literature that models like decision trees, random for-EB ests, or deep neural networks excel in structured environments with labeled inputs (Eid et al. 2025). AN A secondary hypothesis anticipated that unsupervised learning would be less effective in predictive D IN tasks but could uncover hidden patterns useful for exploratory phases of research. This too was val-FOR idated, as clustering algorithms (e.g., k-means, hierarchical clustering) revealed subgroups within M datasets, which may inform subsequent predictive modeling. Finally, the third hypothesis, suggest -ATION ing that reinforcement learning could provide adaptive solutions in environments with sequential T decision-making, was partially confirmed. While reinforcement learning achieved improvements in ECH specificity over time, its performance was highly dependent on the quality of reward signals and the NOL length of training episodes, highlighting both its strengths and weaknesses. OGIE 5.2 Meaning and Implications of the ResultsS The results underscore the importance of aligning learning approaches with the characteristics of the dataset and the research objective. Supervised learning should be prioritized when the goal is high predictive accuracy and when sufficient labeled training data exists. Unsupervised methods are more suited for exploratory research where data structure and grouping are unknown, while rein-forcement learning should be leveraged in contexts requiring adaptive, real-time decision-making (e.g., robotics, personalized treatment plans in healthcare). The implications are significant: for instance, in healthcare decision support, sensitivity is often prioritized to minimize false negatives (e.g., in cancer detection). Our findings suggest supervised learning methods are particularly well suited in such high-stakes contexts. Conversely, unsuper-vised learning can help in patient stratification or identifying novel risk groups, while reinforcement learning could optimize long-term treatment regimens. 225 5.3 Comparison with Other Research er TE The results align with findings in recent studies. For example, Azizi et al. (2022) and Jogani et al. -R Pe IN ie IO mance in medical imaging, confirming our observed accuracy advantage. Similarly, Behzadidoost w N ed A and Izadkhah (2025, 463) and Gokcekuyu et al. (2024) demonstrated that unsupervised clustering L S Pr uncovers hidden structures in genomic data, consistent with our findings on exploratory strengths. ev RNAT (2025) reported that supervised deep learning models can match or exceed expert-level perfor- ing TIF areas such as autonomous control systems and adaptive healthcare interventions (Yu et al. 2021). IC C However, our results emphasize its instability and resource intensiveness, echoing concerns raised s Bo ce N Reinforcement learning’s adaptability has also been highlighted in recent literature, particularly in ed o CIE ok N by Ndikum and Ndikum (2024). FE O CT T'S A Despite robust findings, the study faced certain limitations. First, the performance evaluation M B metrics-accuracy, sensitivity, and specificity-though useful, do not fully capture nuanced aspects A O N U A such as precision, F1-score, or area under the ROC curve, which might provide a more comprehen- T P G sive performance picture. Second, the data patterns used in the study may not reflect the hetero - EM R 5.4 Limitations O CE I JE : P REN EN PL geneity of real-world datasets, especially those with high noise or imbalance. Third, the progress E 2 T, S EO TR 02 of reinforcement learning was constrained by computational resources and training time, limiting EGIC 02 of the findings. C 5 AT 4 the scope of experiments. Finally, the study’s reliance on simulated or secondary datasets, rather –2 than domain-specific case studies (e.g., live hospital data), limits the immediate generalizability OM M 5.5 Recommendations and Future Research U N IC Based on the outcomes, several recommendations emerge. First, researchers should carefully match AT ION the choice of learning paradigm with the nature of their data and objectives: supervised learning M for prediction, unsupervised learning for discovery, and reinforcement learning for adaptive opti- AN mization. Second, future work should incorporate a wider set of evaluation metrics (e.g., precision, A G ROC-AUC, interpretability measures) to provide a more holistic assessment of performance. Third, EM hybrid approaches combining supervised and unsupervised learning, or reinforcement learning EN with supervised pre-training, should be explored, as they may overcome the limitations observed T, W when each method is applied in isolation. Finally, research should extend into domain-specific case EB A studies, particularly in healthcare, finance, and robotics, to validate the models under real-world N D conditions and enhance the practical impact of findings. IN FOR Prepare a short summary of your key findings, summarize suggestions for cases of good practice AT summary of the whole paper, but the focus is put on the clarification of results (critically position ION M and suggest possibilities of further research of the discussed problem. The conclusion is not a mere EC issues and the presentation of possible solutions. H NOL T your findings and/or solutions from a wider perspective) and the mentioning of potential unsolved O 6 CONCLUSION IEG S This study demonstrates that the application of supervised, unsupervised, and reinforcement learn- ing approaches in healthcare-related prediction tasks yields valuable but distinct outcomes, each shaped by the nature of the input data and the performance metrics applied. The results show that supervised learning achieved the highest accuracy and specificity, reflecting its suitability in well-structured clinical datasets where labeled information is available. Unsupervised learning, al-though less precise, revealed meaningful hidden patterns, thereby proving useful for exploratory analyses such as clustering patient subgroups or identifying unknown risk factors. Reinforcement learning showed promising adaptability, particularly in sequential decision-making scenarios like treatment optimization, though its performance remains highly dependent on the quality of re-ward structures. The critical insight derived from these findings is that no single learning paradigm universally out-performs the others; rather, their integration within healthcare decision support can yield synergis- 226 interpretability are crucial. w N edAL S From a broader perspective, these findings emphasize the need for context-specific model selec - PrCIE o tion. While high accuracy is desirable, sensitivity often carries greater clinical significance, especially ceN ed in early disease detection where missing a true positive may have severe consequences. Similarly, TIF ingIC C specificity plays an equally critical role in minimizing false alarms, which can otherwise overwhelm s BoO healthcare providers and reduce trust in automated systems. Results align with previous studies N okFE that highlight the trade-offs between these metrics, reinforcing the argument that performance R : PEN evaluation must go beyond a single indicator. refine recommendations in real time. This layered approach represents a case of good practice in er-R RNAT applying machine learning to complex clinical environments, where both predictive accuracy and ev ieIO ing models later exploit for improved classification, while reinforcement learning can adaptively Pe INTE tic benefits. For instance, unsupervised learning can reveal latent structures that supervised learn- O CE I R Despite the encouraging outcomes, this study is not without limitations. Data heterogeneity, po- JE T'S A CT tential bias in training sets, and constraints in computational resources may have influenced the MB AO performance of certain models. Additionally, reinforcement learning’s reliance on simulated en- NU AT P G vironments poses challenges for real-world clinical validation. Addressing these issues requires EMEO robust validation frameworks, diverse datasets, and interdisciplinary collaboration between data ENPLE 2 scientists, clinicians, and policymakers. T, S TR02 Future research should explore hybrid approaches that combine the strengths of different learning 4 AT–2 paradigms, such as semi-supervised models that leverage both labeled and unlabeled data. More- EG IC02 over, explainability and transparency must be central to future developments to ensure clinician C5 OM trust and ethical use of AI-driven decision support systems. Finally, cross-institutional studies that validate models across diverse healthcare settings are essential for improving generalizability and MUN practical adoption.ICAT In summary, this work clarifies that machine learning approaches hold transformative potential for ION healthcare, but their success depends on judicious model selection, rigorous evaluation, and sus- M tained efforts to address limitations. By critically situating our findings within existing research and ANA acknowledging current gaps, we provide both practical recommendations and a roadmap for ad-GEM vancing future work in this field.ENT, W EB AND INFOR ATM ION EC T H NOL O IEG S 227 Pe REFERENCES IN TE er 1. 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He is particularly interested in developing AI-augmented systems, im- wN edA proving clinical decision-making, and leveraging ICT to advance healthcare outcomes.L S PrCIE o ceN edTIF ingIC C ok FER : P s Bo ON R EN O CE I CTJE T'S A N OU AT P A B M EMG EN PLE 2 T, SEO TR 024 AT–2 EG IC02 C5 OM M U N ATIC ION M ANAGEMENT, W EB AND INFOR ATM ION EC T H NOL O IEG S 229