Zbornik 27. mednarodne multikonference

INFORMACIJSKA DRUŽBA – IS 2024

Zvezek E





Proceedings of the 27th International Multiconference

INFORMATION SOCIETY – IS 2024

Volume E





17. Mednarodna konferenca o prenosu tehnologij

17th International Technology Transfer Conference





Uredniki / Editors



Urška Florjančič, Robert Blatnik, Špela Stres





http://is.ijs.si





9. oktober 2024 / 9 October 2024

Ljubljana, Slovenia



Uredniki:





Urška Florjančič

Služba za vsebinsko podporo projektom, prenos tehnologij in inovacije, Institut »Jožef Stefan«, Ljubljana Robert Blatnik

Služba za vsebinsko podporo projektom, prenos tehnologij in inovacije, Institut »Jožef Stefan«, Ljubljana Špela Stres





Založnik: Institut »Jožef Stefan«, Ljubljana

Priprava zbornika: Mitja Lasič, Vesna Lasič, Lana Zemljak

Oblikovanje naslovnice: Vesna Lasič





Dostop do e-publikacije:

http://library.ijs.si/Stacks/Proceedings/InformationSociety





Ljubljana, oktober 2024





Informacijska družba

ISSN 2630-371X



Kataložni zapis o publikaciji (CIP) pripravili v Narodni in univerzitetni knjižnici v Ljubljani

COBISS.SI-ID 214450179

ISBN 978-961-264-303-4 (PDF)





PREDGOVOR MULTIKONFERENCI

INFORMACIJSKA DRUŽBA 2024

Leto 2024 je hkrati udarno in tradicionalno. Že sedaj, še bolj pa v prihodnosti bosta računalništvo, informatika (RI) in umetna inteligenca (UI) igrali ključno vlogo pri oblikovanju napredne in trajnostne družbe. Smo na pragu nove dobe, v kateri generativna umetna inteligenca, kot je ChatGPT, in drugi inovativni pristopi utirajo pot k superinteligenci in singularnosti, ključnim elementom, ki bodo definirali razcvet človeške civilizacije.

Naša konferenca je zato hkrati tradicionalna znanstvena, pa tudi povsem akademsko odprta za nove pogumne ideje, inkubator novih pogledov in idej.

Letošnja konferenca ne le da analizira področja RI, temveč prinaša tudi osrednje razprave o perečih temah današnjega časa – ohranjanje okolja, demografski izzivi, zdravstvo in preobrazba družbenih struktur. Razvoj UI ponuja rešitve za skoraj vse izzive, s katerimi se soočamo, kar poudarja pomen sodelovanja med strokovnjaki, raziskovalci in odločevalci, da bi skupaj oblikovali strategije za prihodnost. Zavedamo se, da živimo v času velikih sprememb, kjer je ključno, da s poglobljenim znanjem in inovativnimi pristopi oblikujemo informacijsko družbo, ki bo varna, vključujoča in trajnostna.

Letos smo ponosni, da smo v okviru multikonference združili dvanajst izjemnih konferenc, ki odražajo širino in globino informacijskih ved: CHATMED v zdravstvu, Demografske in družinske analize, Digitalna preobrazba zdravstvene nege, Digitalna vključenost v informacijski družbi – DIGIN 2024, Kognitivna znanost, Konferenca o zdravi dolgoživosti, Legende računalništva in informatike, Mednarodna konferenca o prenosu tehnologij, Miti in resnice o varovanju okolja, Odkrivanje znanja in podatkovna skladišča – SIKDD

2024, Slovenska konferenca o umetni inteligenci, Vzgoja in izobraževanje v RI.

Poleg referatov bodo razprave na okroglih mizah in delavnicah omogočile poglobljeno izmenjavo mnenj, ki bo oblikovala prihodnjo informacijsko družbo. “Legende računalništva in informatike” predstavljajo slovenski “Hall of Fame” za odlične posameznike s tega področja, razširjeni referati, objavljeni v reviji Informatica z 48-letno tradicijo odličnosti, in sodelovanje s številnimi akademskimi institucijami in združenji, kot so ACM Slovenija, SLAIS in Inženirska akademija Slovenije, bodo še naprej spodbujali razvoj informacijske družbe. Skupaj bomo gradili temelje za prihodnost, ki bo oblikovana s tehnologijami, osredotočena na človeka in njegove potrebe.

S podelitvijo nagrad, še posebej z nagrado Michie-Turing, se avtonomna RI stroka vsakoletno opredeli do najbolj izstopajočih dosežkov. Nagrado Michie-Turing za izjemen življenjski prispevek k razvoju in promociji informacijske družbe je prejel prof. dr. Borut Žalik. Priznanje za dosežek leta pripada prof. dr. Sašu Džeroskemu za izjemne raziskovalne dosežke. »Informacijsko limono« za najmanj primerno informacijsko tematiko je prejela nabava in razdeljevanjem osebnih računalnikov ministrstva, »informacijsko jagodo« kot najboljšo potezo pa so sprejeli organizatorji tekmovanja ACM Slovenija. Čestitke nagrajencem!

Naša vizija je jasna: prepoznati, izkoristiti in oblikovati priložnosti, ki jih prinaša digitalna preobrazba, ter ustvariti informacijsko družbo, ki bo koristila vsem njenim članom. Vsem sodelujočim se zahvaljujemo za njihov prispevek k tej viziji in se veselimo prihodnjih dosežkov, ki jih bo oblikovala ta konferenca.



Mojca Ciglarič, predsednica programskega odbora

Matjaž Gams, predsednik organizacijskega odbora





i

PREFACE TO THE MULTICONFERENCE

INFORMATION SOCIETY 2024

The year 2024 is both ground-breaking and traditional. Now, and even more so in the future, computer science, informatics (CS/I), and artificial intelligence (AI) will play a crucial role in shaping an advanced and sustainable society. We are on the brink of a new era where generative artificial intelligence, such as ChatGPT, and other innovative approaches are paving the way for superintelligence and singularity—key elements that will define the flourishing of human civilization. Our conference is therefore both a traditional scientific gathering and an academically open incubator for bold new ideas and perspectives.

This year's conference analyzes key CS/I areas and brings forward central discussions on pressing contemporary issues—environmental preservation, demographic challenges, healthcare, and the transformation of social structures. AI development offers solutions to nearly all challenges we face, emphasizing the importance of collaboration between experts, researchers, and policymakers to shape future strategies collectively. We recognize that we live in times of significant change, where it is crucial to build an information society that is safe, inclusive, and sustainable, through deep knowledge and innovative approaches.

This year, we are proud to have brought together twelve exceptional conferences within the multiconference framework, reflecting the breadth and depth of information sciences:

• CHATMED in Healthcare

• Demographic and Family Analyses

• Digital Transformation of Healthcare Nursing

• Digital Inclusion in the Information Society – DIGIN 2024

• Cognitive Science

• Conference on Healthy Longevity

• Legends of Computer Science and Informatics

• International Conference on Technology Transfer

• Myths and Facts on Environmental Protection

• Data Mining and Data Warehouses – SIKDD 2024

• Slovenian Conference on Artificial Intelligence

• Education and Training in CS/IS.

In addition to papers, roundtable discussions and workshops will facilitate in-depth exchanges that will help shape the future information society. The “Legends of Computer Science and Informatics” represents Slovenia’s “Hall of Fame” for outstanding individuals in this field. At the same time, extended papers published in the Informatica journal, with over 48 years of excellence, and collaboration with numerous academic institutions and associations, such as ACM Slovenia, SLAIS, and the Slovenian Academy of Engineering, will continue to foster the development of the information society. Together, we will build the foundation for a future shaped by technology, yet focused on human needs.

The autonomous CS/IS community annually recognizes the most outstanding achievements through the awards ceremony. The Michie-Turing Award for an exceptional lifetime contribution to the development and promotion of the information society was awarded to Prof. Dr. Borut Žalik. The Achievement of the Year Award goes to Prof. Dr. Sašo Džeroski. The "Information Lemon" for the least appropriate information topic was given to the ministry's procurement and distribution of personal computers. At the same time, the

"Information Strawberry" for the best initiative was awarded to the organizers of the ACM Slovenia competition. Congratulations to all the award winners!

Our vision is clear: to recognize, seize, and shape the opportunities brought by digital transformation and create an information society that benefits all its members. We thank all participants for their contributions and look forward to this conference's future achievements.



Mojca Ciglarič, Chair of the Program Committee

Matjaž Gams, Chair of the Organizing Committee



ii





KONFERENČNI ODBORI

CONFERENCE COMMITTEES



International Programme Committee

Organizing Committee

Vladimir Bajic, South Africa

Matjaž Gams, chair

Heiner Benking, Germany

Mitja Luštrek

Se Woo Cheon, South Korea

Lana Zemljak

Howie Firth, UK

Vesna Koricki

Olga Fomichova, Russia

Mitja Lasič

Vladimir Fomichov, Russia

Blaž Mahnič

Vesna Hljuz Dobric, Croatia



Alfred Inselberg, Israel

Jay Liebowitz, USA

Huan Liu, Singapore

Henz Martin, Germany

Marcin Paprzycki, USA

Claude Sammut, Australia

Jiri Wiedermann, Czech Republic

Xindong Wu, USA

Yiming Ye, USA

Ning Zhong, USA

Wray Buntine, Australia

Bezalel Gavish, USA

Gal A. Kaminka, Israel

Mike Bain, Australia

Michela Milano, Italy

Derong Liu, Chicago, USA

Toby Walsh, Australia

Sergio Campos-Cordobes, Spain

Shabnam Farahmand, Finland

Sergio Crovella, Italy





Programme Committee

Mojca Ciglarič, chair

Marjan Heričko

Baldomir Zajc

Bojan Orel

Borka Jerman Blažič Džonova

Blaž Zupan

Franc Solina

Gorazd Kandus

Boris Žemva

Viljan Mahnič

Urban Kordeš

Leon Žlajpah

Cene Bavec

Marjan Krisper

Niko Zimic

Tomaž Kalin

Andrej Kuščer

Rok Piltaver

Jozsef Györkös

Jadran Lenarčič

Toma Strle

Tadej Bajd

Borut Likar

Tine Kolenik

Jaroslav Berce

Janez Malačič

Franci Pivec

Mojca Bernik

Olga Markič

Uroš Rajkovič

Marko Bohanec

Dunja Mladenič

Borut Batagelj

Ivan Bratko

Franc Novak

Tomaž Ogrin

Andrej Brodnik

Vladislav Rajkovič

Aleš Ude

Dušan Caf

Grega Repovš

Bojan Blažica

Saša Divjak

Ivan Rozman

Matjaž Kljun

Tomaž Erjavec

Niko Schlamberger

Robert Blatnik

Bogdan Filipič

Stanko Strmčnik

Erik Dovgan

Andrej Gams

Jurij Šilc

Špela Stres

Matjaž Gams

Jurij Tasič

Anton Gradišek

Mitja Luštrek

Denis Trček

Marko Grobelnik

Andrej Ule

Nikola Guid

Boštjan Vilfan

iii





iv





KAZALO / TABLE OF CONTENTS



17. Mednarodna konferenca o prenosu tehnologij / 17th International Technology Transfer Conference

................................................................................................................................................................... 1

PREDGOVOR / FOREWORD ............................................................................................................................... 3

PROGRAMSKI ODBORI / PROGRAMME COMMITTEES ............................................................................... 5

Intellectual Property as a Success Factor for Startups: Systematic Literature Review / Fortun Novak Maja ........ 7

The Reversed European Paradox: do European Patents have a High Market Value but Low Impact? / Hafner

Ana ................................................................................................................................................................... 10

The Importance of Technology Transfer Offices in University Industry Collaboration: KTÜ TTM Example /

İskender Balaban Dilek, Değermenci Beril, Yüksel Harun, Yilmaz Eren, Kalyoncu Sedanur, Ayvaz Emrah,

Yildiz Oktay, Aykut Yalçın, Yildiz İslam, Sağlam Gözde, Ünver Müslüm Serhat, Sabir Hülya, Sönmez

Kerim, Gültekin Güler Tuğba, Aydin Aleyna .................................................................................................. 14

The Impact of International Networks on Grants, R&D, Knowledge and Technology Transfer – Case of COST

Network and KTU / Kalyoncu Sedanur, Yildiz İslam, Ayvaz Emrah, Sağlam Gözde, Ünver Müslüm Serhat,

Yildiz Oktay, Gültekin Güler Tuğba, Yilmaz Eren, Sönmez Kerim, Sabir Hülya, Değermenci Beril, Aykut

Yalçın, Koç Ayhan, İskender Balaban Dilek, Aydin Aleyna, Baş Seda .......................................................... 18

The Effect of Evaluating Graduate Thesis Topics as Invention Notification Form on Industrial and Intellectual

Property Applications: The Case of Karadeniz Technical University / Sönmez Kerim, Ayvaz Emrah, Sabir

Hülya, Değermenci Beril, Kalyoncu Sedanur, Yildiz İslam, Ünver Müslüm Serhat, Aykut Yalçın, Sağlam

Gözde, Yilmaz Eren, Aydin Aleyna, İskender Balaban Dilek, Gültekin Güler Tuğba, Koç Ayhan, Yildiz

Oktay ................................................................................................................................................................ 22

Using Open-Access Resources and Platforms to Create a Technology Transfer Ecosystem / Britchkovski

Viatcheslav ....................................................................................................................................................... 26

Fostering Open Innovation and Technology Transfer: Insights from the Euro-Mediterranean Innovation Camp

(EMIC) / El-Zoheiry Abdelhamid, Gladović Karen ........................................................................................ 30

Research Organisation-Industry Cooperation and State Aid Rules in Slovenia and Europe / Lutman Tomaž,

Florjančič Urška, Fric Urška ............................................................................................................................ 35

Feasibility Analysis for the New Mechanism of Knowledge Transfer within the INDUSAC Project / Odić

Duško, Mrgole Urška, Trobec Marjeta ............................................................................................................ 39

Aproaches to Monitoring and Impact Assessment in Reseach Infrastructures / Plaskan Jure, N. Brečko Barbara

.......................................................................................................................................................................... 43

Intellectual Property Valuation in the Cyber Security Sector / E. Wachowicz Marta .......................................... 48

The Challenge of Licensing Artificial Intelligence Technology for Cybersecurity Applications / Rotnicki

Michał .............................................................................................................................................................. 52

Technology Transfer: Revenues Estimation in the Cyber Security Sector / Falkowski Michal J., Kaminski

Jaroslaw, Wachowicz Marta............................................................................................................................. 56

Prospects for the Use of AI Tools in the Republican Center for Technology Transfer Network / Uspenskiy

Alexander, Uspenski Aliaksei, Prybylski Maxim ............................................................................................ 60

Indeks avtorjev / Author index ................................................................................................................... 65





v





vi



Zbornik 27. mednarodne multikonference

INFORMACIJSKA DRUŽBA – IS 2024

Zvezek E





Proceedings of the 27th International Multiconference

INFORMATION SOCIETY – IS 2024

Volume E





17. Mednarodna konferenca o prenosu tehnologij

17th International Technology Transfer Conference





Uredniki / Editors



Urška Florjančič, Robert Blatnik, Špela Stres





http://is.ijs.si





9. oktober 2024 / 9 October 2024

Ljubljana, Slovenia

1





2

FOREWORD / PREDGOVOR



Dear guests, experts, panelists, and participants,

Welcome to the 17th International Technology Transfer Conference (17ITTC). Since its inception, the Jožef Stefan Institute has proudly served as the initiator and main organizer of this esteemed event, advancing innovation and knowledge transfer in Slovenia. This year, we are honored to host the conference in collaboration with 13 public research organizations, representing two national consortia of knowledge transfer offices (KTOs). The event is co-financed and supported by the Ministry of Higher Education, Science, and Innovation, as part of the "Mesec znanosti" campaign.



The ITTC has established itself as a crucial platform for exchanging ideas and fostering collaboration between domestic and international stakeholders, significantly contributing to the development of Slovenia’s national innovation ecosystem. The conference has been instrumental in helping Slovenian public research organizations address challenges such as securing funding for spin-outs, updating national legislation on research and innovation, and building robust consortia for KTOs.



Collaboration among KTOs, both within and across the two consortia continues through joint activities aimed at promoting KTO initiatives, raising awareness, and encouraging networking and the exchange of best practices. These efforts focus on enhancing the skills and capabilities of all stakeholders—from KTO employees and researchers to students—while improving the implementation of intellectual property (IP) marketing and protection. Additionally, coordinated efforts will establish common metrics and indicators, enabling effective monitoring and evaluation of knowledge valorization processes at public research organizations, ensuring long-term success.



This year’s conference theme, “Self-Evaluation of Research Organizations to Support the Development and Strengthening of Knowledge Transfer,” aligns with our goal of bolstering the role of KTOs and improving the commercialization of intellectual property, as well as to promote the wider social relevance of knowledge transfer and the outputs and impacts of KTO work on the well-being of society as a whole. The theme is being explored in a keynote address focuses on the role of institutional self-evaluation within the Framework of proposed amendments to the General Acts of the Slovenian Research and Innovation Agency (ARIS), followed by a round table discussion. The panel will feature representatives from the Ministry of Higher Education, Science, and Innovation, ARIS, the Slovenian Rectors' Conference, KOsRIS, Leiden University, the Institute for Economic Research, and the University of Colorado Boulder.



We present several prestigious awards during the conference, including the Conference Prize for the Best Innovation in 2024, which aims to promote the commercialization of innovative technologies developed at public research organizations. The WIPO National Award for Enterprises is awarded to a Slovenian enterprise that has successfully developed a strategy for commercializing university-based innovations. In addition, the WIPO National Award for Inventors honors an individual researcher or a team of researchers from a Slovenian public research institute whose patented invention has significantly contributed to Slovenia’s economic and technological development.



The conference also features sessions on Opportunities Arising from Publicly Funded Research Projects, where researchers and KTO experts showcase successful scientific projects 3

funded by the Slovenian Research Agency, highlighting their potential for innovation and commercialization. In the session on Connecting the Educational System with the Academic Sphere, presentations of selected research topics and collaboration proposals emphasize the importance of bridging the gap between academia and education, fostering greater cooperation and engagement.



We are especially excited about the ongoing growth of the conference, which, for the fifth consecutive year, includes peer-reviewed contributions from researchers specializing in knowledge and technology transfer. Since 2009, the entrepreneurial pitch competition for research teams and their inventions, evaluated by international teams of commercialization and investment experts, has remained a key feature, supporting over 100 research teams in developing business models, with more than 30 winners recognized to date.

Together, we look forward to exploring new opportunities, including collaborations with the Vesna DeepTech Fund, which plays a vital role in providing early-stage funding to spin-out companies emerging from public research organizations. Established by the EIF in partnership with Slovenian and Croatian development banks, the fund bridges the gap between research and commercialization, offering financial backing to help transform cutting-edge innovations into successful ventures. This collaboration fosters stronger partnerships between research institutions and industry, further boosting the commercialization of scientific discoveries.

Thank you for being part of this journey, and we look forward to an inspiring exchange of ideas at the 17ITTC.



Programme Committee of the 17ITTC





ACKNOWLEDGEMENTS



We would like to acknowledge the valuable contributions of the scientific programme committee to the scientific programme, review of the scientific papers on technology transfer and intellectual property, and selection of publications in the conference proceedings, and the efforts of the conference programme and organising committees for successful implementation of the 17th International Technology Transfer Conference.





4

SCIENTIFIC PROGRAMME COMMITTEE



Niko Schlamberger, past President of Slovenian Society INFORMATIKA Tamara Besednjak Valič, Faculty of Information Studies in Novo Mesto Dolores Modic, Nord University Business School

Jana Hojnik, University of Primorska

Urška Fric, Faculty of Information Studies in Novo mesto





CONFERENCE PROGRAMME COMMITTEE



Robert Blatnik, Jožef Stefan Institute

Špela Stres

Peter Alešnik, University of Ljubljana

Simona Kustec, University of Primorska

Jana Hojnik, University of Primorska





ORGANISING COMMITTEE



Robert Blatnik, Jožef Stefan Institute

Marjeta Trobec, Jožef Stefan Institute

Doroteja Novak, University of Maribor

Maša Stošič, University of Maribor

Matej Draksler, Geological Survey of Slovenia

Urška Fric, Faculty of Information Studies in Novo mesto

Ana Hafner, Rudolfovo – Science and Technology Centre Novo mesto

Mateja Košir, Slovenian National Building and Civil Engineering Institute 5



6





Intellectual Property as a Success Factor for Startups: Systematic Literature Review

Maja Fortun Novak

Faculty of information studies

Novo mesto, Slovenia

majafortunnovak@gmail.com



ABSTRACT

Globally, the number of new companies, known as startups, is

This paper presents a systematic literature review on the impact

rapidly increasing daily [18]. Such companies, especially

of intellectual property on startup success. By reviewing 21

innovative startups, often lack historical financial data or a track relevant articles published in the last five years, sourced from

record, making it more difficult to establish a market reputation.

Google Scholar, it analyses the influence of intellectual property Their innovative products or business processes also lack prior

on key business factors such as financing, growth,

experience or comparative standards [2]. This presents

competitiveness, and innovation. The findings show that

challenges that can lead to the failure of companies due to

intellectual property plays a significant role in startup success, inadequate or non-existent business models, and insufficient

though results vary regarding formal (patents) and informal

business growth [4].

(market advantage, trade secrets) protection methods. A

balanced approach to intellectual property management, tailored

Díaz-Santamaría and Bulchand-Gidumal identify several factors

to startups' needs and developmental stages, is recommended.

that can influence the success of startups [6]. The results of their The article emphasizes the need for further research on different

research indicate that the success of a startup can be measured in forms of intellectual property, considering regional contexts and

two ways: the startup achieves significant revenue, and the

long-term effects. Its value lies in offering both theoretical

startup receives funding. In the following sections, we also

insights and practical recommendations, particularly for

highlight other indicators for measuring the business success of

policymakers, investors, and startup owners seeking to promote

a startup.

innovation and growth through effective intellectual property

management.

Despite numerous studies in recent years on the impact of

innovative practices on the business development and success of

KEYWORDS

startup companies, no comprehensive and systematic analysis of

scientific literature has yet been conducted that specifically

Intellectual property, startup, trademark, patent, innovation,

focuses on the influence of IP rights on the business success of

growth, business success

startups. This gap in scientific research indicates the need for an in-depth review of existing scientific sources that would enable

a holistic understanding of the impact of IP on the business

1 INTRODUCTION

success of startups.

The purpose of our research is to systematically review the

The research question is, how are a startup's IP and business

literature on the impact of intellectual property (hereinafter

success connected, i.e., does IP affect business success, and how?

referred to as IP) on the business success of startup companies.

In this way, we can better understand how IP contributes to the

Through an analysis of existing research results, we aim to

competitiveness and long-term success of startups.

explore how IP contributes to achieving these success criteria.

Our objective is to determine whether, and how, IP influences

2 METHOD

the business success of startups, which is crucial for

understanding their growth in a dynamic business environment.

For this research, we used the systematic literature review

method, conducted between January and April 2024. During this

In the modern economy, there is a notable impact that new

period, we reviewed foreign literature, focusing on the impact of

companies have on innovation [9, 15], and the economy as a

IP on the success of startup companies. We examined

whole [4, 10]. In particular, startups drive innovation, create new professional, scientific, and research publications published in

jobs and introduce competitiveness into the business world [17].

the last five years to ensure the most up-to-date data and

The influence of IP is particularly interesting, as it can be crucial discussions in this field. We used the international bibliographic for their success.

database Google Scholar to collect information, which allows for



the search of scientific literature and the ranking of documents in Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or a manner used by researchers. To identify relevant sources, we

distributed for profit or commercial advantage and that copies bear this notice and used the following set of keywords: "Intellectual Property,"

the full citation on the first page. Copyrights for third-party components of this work

"Startups," "Start-ups," "Patents," and "Trademark." In total, we must be honored. For all other uses, contact the owner/author(s).

obtained 30 relevant articles. After excluding 9 duplicates, we

Information Society 2024, 7–11 October 2024, Ljubljana, Slovenia

© 2024 Copyright held by the owner/author(s).

retained 21 suitable articles for further analysis. The four data

collection strategies were used to ensure a thorough and



comprehensive review of the relevant literature, tailored to the

7



research question. Each strategy contributed to refining the

Schaberg explores various forms of IP protection and finds

search and eliminating irrelevant sources.

that startups with a diverse portfolio of protected rights grow and innovate more easily [19]. Various forms of protection, such as

patents, trademarks and copyrights, provide comprehensive

protection, increase investor confidence, and facilitate access to capital, which encourages further innovation. Ljungqvist, Hegde,

and Raj add that the rapid granting of patents stimulates

innovation and facilitates the acquisition of capital, while delays in patent granting negatively impact startups' growth [13].

Despite the numerous positive impacts of IP on startup

companies, some research shows mixed results. Power and Reid

caution that patents can negatively affect the success of startups, while trademarks and licensing have a positive impact [16].

Teixeira and Ferreira, as well as YunQi and Lin, find that formal

methods such as patents often reduce companies'

competitiveness, while informal mechanisms such as market

advantage and trade secrets can improve competitiveness [22,

24]. Some studies recommend a balanced approach to IP

management. Silva Júnior, Siluk, Neuenfeldt Júnior, Rosa, and

Michelin believe that a combination of formal and informal



protection mechanisms, such as patents, trademarks, and

copyrights, is crucial for protecting innovations and enhancing

Figure 1: Diagram of the Results of the Systematic

competitive advantage [21]. Audretsch, Colombelli, Grilli,

Literature Review

Minola, and Rasmussen emphasise that policies for innovation

and IP protection must be tailored to the specific needs and stages of startups' development [1]. Chou adds that patents help in

3 RESULTS AND DISCUSSION

securing funding, but startups often face patent litigation, which reduces their productivity [5]. The solution lies in

Most research confirms that IP significantly influences the

commercialisation patents, which would reduce the negative

success of startup companies. Researchers have examined how

impacts of disputes and enable better protection and marketing

IP affects various aspects of startups' operations, such as

of innovations.

financing, growth, competitiveness, and innovation

Research by EPO-EUIPO, Krauss, Breitenbach-Koller, and

performance. Below, we summarise the key findings of these

Kuttenkeuler, Brandt, Laibach, Kamrath, and Bröring, Schaberg

studies.

and Ljungqvist, Hegde and Raj emphasise the importance of

Hellström, Nilsson, Andersson, and Hakanson found that a

effective IP management for startup success [7, 11, 3, 19, 13].

combination of patents and secrecy positively influences the

However, these studies primarily focus on specific sectors or

protection of innovations and market opportunities, thereby

particular cases and only certain forms of IP, which can lead to a increasing companies' competitiveness [8]. Similarly, research

limited understanding of the overall picture and strategies that

by EPO-EUIPO reports that 29% of European startups invest in

would be beneficial for startups across different fields.

IP, which increases their chances of securing funding [7]. Krauss, Some studies focus on specific countries or geographical

Breitenbach-Koller, and Kut enkeuler emphasise that IP is

areas, such as EPO-EUIPO on European startups or Li, Gan, and

crucial for the success of biotech startups, as it enhances their

Zhang on Chinese startups [7, 12]. These studies highlight

value and attractiveness to investors [11].

regional particularities in the use of IP, which can affect the

The role of IP is particularly pronounced in international

innovation and competitiveness of companies in specific

markets, where the protection of innovations is essential for the

geographical environments.

survival and growth of companies. Tula, Ofodile, Okoye, Nifise,

University startups, as discussed by Shahidan, Latiff, and

and Odeyemi highlight that IP plays a key role in ensuring the

Wahab, represent a special category where innovation

business success of startups in a global context, as it prevents the intertwines with academic knowledge [20]. These startups often

copying and exploitation of innovations by competitors, with

face specific challenges in commercialising technologies, which

registered patents and trademarks serving as signals to investors

can hinder the value creation process. Successful university

of startups' innovation and credibility [23].

startups must identify market opportunities, ensure

Brandt, Laibach, Kamrath, and Bröring also point out that IP

entrepreneurial commitment, and continuously develop their

increases the value of companies and attracts investors, which is

technologies to meet market demands.

crucial for success in corporate investments. Startups with well-

The inclusion of perspectives such as that proposed by

protected IP find it easier to attract investors, as they perceive Panagopoulos and Park, where patents serve as negotiation tools,

protected technology as a lower-risk investment with greater

highlights the potential for strategic use of IP in corporate

potential for profitability [3]. Additionally, IP enables startups to negotiations, not just as a defensive mechanism [14].

collaborate more easily with larger corporations, further

Effective IP management generally has a positive impact on

strengthening their financial and strategic positions.

the success of startups, but some results indicate the need for a

8

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9





The Reversed European Paradox: do European Patents have a High Market Value but Low Impact?

Ana Hafner

Centre for Technology Transfer and Intellectual Property Rights

Rudolfovo - Science and Technology Centre Novo mesto

Novo mesto, Slovenia

ana.hafner@rudolfovo.eu

ABSTRACT

perceived to lag behind the U.S. in converting its academic

results into economic outcomes” [4]. This lag may affect the

The U.S. research institutions often serve as role models for

economic growth of European countries and also their global

European research institutions in knowledge and technology

competitiveness in industries that rely on technological

transfer. This paper investigates the widely held belief that

innovation.

European technology transfer performance is inferior to that of



the U.S. To explore this, an analysis of the quality of patents

The aim of this study is to contribute to existing studies which

from leading U.S. and European universities and research

deal with different aspects of KTT in Europe, especially in

institutes was done. The methodological approach involves a

comparison to the U.S. For example, Crespi et al. [1] focused on

comparative analysis of key patent quality indicators: number

a comparison of European and U.S. academic patenting systems

of patent family members, forward citations, backward

and discovered that there is a difference between PRO-owned

citations, and claims. Results indicate that the dominance of

and PRO-invented patents (inventions). They discovered that EU

U.S. organizations is not as clear as commonly perceived. The

PROs lag behind the U.S. because 80% of patents with academic

study adds value by providing an additional understanding of

inventors are in the EU owned by private firms rather than PROs,

the technology transfer landscape, challenging the assumption

and they are statistically not recognized as PRO patents.

of U.S. superiority.

On the contrary, this study is not focused on the quantity of the

KEYWORDS

patents, such as Crespi’s et al. [1], but on their quality. The top European and U.S. PROs will be compared according to the

Patents, patent quality, patent valuation, public research

value of their patents by indicators of patent value.

organizations, research institutes, universities, Europe-U.S.



comparison, number of patent family members, forward

The research question is: If we compare the patents of the top

citations.

European and U.S. PROs by indicators of patent value, such as

the number of patent family members and forward citations, are

1 INTRODUCTION

there any differences between Europe and the U.S.?



The European paradox is a term coined to describe that Europe

Understanding this research problem is important because the

is strong in basic science but lags behind some other developed

effective commercialization of scientific knowledge directly

countries in technological applications in world markets [1],

impacts economic growth and innovation. If European PROs can

specifically in the commercialisation of scientific findings or

enhance their KTT performance, it could lead to increased

what we call knowledge and technology transfer (KTT).

competitiveness in global markets. By focusing on patent quality



rather than quantity, this study aims to provide some insights into Many scholars have studied why some public research

how Europe might overcome the perceived lag behind the U.S.

organisations (PROs) – which include universities and research

institutes – are more successful in commercializing knowledge.

Most of the research on university knowledge commercialization

2 INDICATORS OF PATENT VALUE

has been conducted in the U.S., often identified as pioneers in

Methods for patent valuation can be qualitative or quantitative

this area [2].

[5]. We will focus only on quantitative and non-monetary



methods, i.e., patent indicators [5]. Typical indicators are legal In Europe, most university or PROs’ technology transfer offices

status, international and technological scope, number of forward

are still young, with half of them being established after 2000 [3].

citations and the existence of opposition and litigation [5]. Such However, this is probably not the only reason why “Europe is

valuation has many advantages: the method is fast, objective and

∗Article Title Footnote needs to be captured as Title Note

inexpensive and can be fully automated once the valuation

†Author Footnote to be captured as Author Note

system is set up [5]. International scope (size of patent family)



and forward citations (citations received from patents applied

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed later) are probably the most frequent measures for assessing

for profit or commercial advantage and that copies bear this notice and the full patent value. Patent valuation using forward citations has been

citation on the first page. Copyrights for third-party components of this work must increasingly used by practitioners when a patent’s value has not

be honored. For all other uses, contact the owner/author(s).

been otherwise established [6].

Information Society 2024, 7–11 October 2024, Ljubljana, Slovenia

© 2024 Copyright held by the owner/author(s).





10

Og et al. [7] divide patent value indicators into ex-ante indicators 3 METHOD

(family size, backward citations, backward references to non-

patent literature, number of claims, and number of inventors) and

For this study, the first methodological question was, how to

ex-post indicators (forward citations).

determine the most important or innovative European and U.S.



PROs.

We will consider the following indicators:



•

Number of claims

For the U.S., the Heartland Forward’s report (2022) was used

•

Number of patent family members

[12]. From this report, five top PROs were chosen:

•

Number of backward citations

•

Carnegie Mellon University

•

Number of forward citations

•

University of Florida



•

Columbia University

According to Squicciarini et al. [8], claims define the extent of

•

Stanford University

the exclusive rights granted to a patent holder, as only the

•

Harvard University

technologies or elements specified within these claims receive



legal protection and can be enforced. Consequently, the scope of

For Europe, the European Research Ranking list (2020) was used

a patent's protection is determined by the number and specifics

[13]. From this list, five top PROs were chosen:

of its claims. Additionally, since patent fees typically depend on

• Centre National de la Recherche Scientifique

the number of claims included, having numerous claims can

• Fraunhofer Gesellschaft zur Foerderung der Angewandten

result in higher costs. Therefore, the number of claims in a patent Forschung E V

can indicate not just its technological scope but also its

• Commissariat a L'energie Atomique

anticipated market value: more claims often suggest a higher

• Eidgenoessische Technische Hochschule Zuerich (ETH)

expected value for the patent [8].

• University Of Copenhagen





Patent family size – the number of countries in which the same

Additionally, two not listed here PROs from Reuters' Top 100

invention is patented – is a very important indicator of patent

report (2019) were selected [14].

quality [9]. Due to the expenses associated with obtaining patents in various regions, patent holders typically choose to protect their For the U.S.:

most valuable inventions internationally. Besides considering

• Massachusetts Institute of Technology (MIT) which was

raw family size, such as in this case, one variation of this method ranked at the world’s second place in this report.

is to look at triadic patents, which cover an invention in the three For Europe:

principal markets: the U.S., Japan, and the European Patent

• KU Leuven (which was the top rank in Europe and took

Office (EPO). Alternatively, transnational patents, defined as

seventh place on the Reuters' Top 100 report).

patent families with at least one filing with the EPO or under the Patent Cooperation Treaty (PCT), can be considered [10].

To access indicators of patent value for these selected PROs the



Orbis Intellectual Property database (Orbis IP) was used. Orbis

Backward citations reveal the prior art or existing knowledge that IP contains over 145 million patents linked to detailed company

a new patent builds upon. They are added by patent applicants,

information and ownership structures [15].

examiners, and also by third parties (e.g. during opposition



proceedings), and are often used as measures of knowledge

Excel was used to sort the data and draw the chart, and the open-

transfer [11]. A patent with numerous and relevant backward

source program JASP was used for statistical analysis. We used

citations indicates that the patent applicants or inventors or

the Student’s t-test (also called T-test) to compare the means

attorneys and examiners conducted a comprehensive search of

between two groups [16], in the presented case, Europe and the

prior art. Such patents may also be less vulnerable to legal

U.S.

challenges and can be protected from being invalidated due to

overlooked prior art. Additionally, if a patent references

foundational and high-impact prior patents, it suggests that the

4 RESULTS

patented invention is building on well-established and important

technology, potentially indicating a higher-quality patent.

From the selected institutions, we can first notice that in Europe, there are three research institutes listed and three universities, Forward citations are commonly used to measure the

while in the U.S., there are five universities and only one research technological impact of innovation [11]. We can say that this

institute.

indicator is the most understandable to us, as we are already



familiar with it from scientific articles: when later patents quote Figure 1 below shows that selected European PROs outnumber

an earlier one, it suggests that the earlier patent has contributed the U.S. PROs in patents in the last at least 65 years. However,

to new developments in the field. The more forward citations a

since there are no reliable and comparable data about these

patent receives, the more significant its impact on subsequent

organisations' date of establishment, size and income (which can

technological improvements.

all affect the presented number of patents), it is not possible to make any comparisons or conclusions.

Among these four indicators, the two most important can be



considered: 1) patent family size for reflecting the potential

commercial success of an invention and 2) forward citations,

which indicate the technological/scientific impact of the

invention.

11



Group

N

Mean

SD

SE Coefficient

of variation

Number of patents from 1940

Number of Europe 112918 10.099 18.835 0.056

1.865

on

family

members

U.S.

49752 8.610 10.977 0.049

1.275

16000



14000

Number of Europe 112918 3.027 9.733 0.029

3.215

backward

12000

citations

10000

U.S.

49752 6.789 27.966 0.125

4.120



8000

Number of Europe 112918 0.806 3.649 0.011

4.526

6000

forward

4000

citations

U.S.

49752 2.960 11.729 0.053

3.962



2000



0

A closer look at individual PROs' patents reveals considerable

differences between them. In the number of claims, MIT is the

1940

1946

1952

1958

1964

1970

1976

1982

1988

1994

2000

2006

2012

2018

leading PRO with an average of 28 claims. In the number of

EU

US

family members (Table 3), Fraunhofer is the leader (with a mean



of more than 17 family members), followed by KU Leuven (with

more than 11 family members). PRO with the highest number of

Figure 1: Comparison of no. of patents of current top PROs

backward citations is MIT again, but the leading PRO in the

from 1940 on

number of forward citations (Table 4) is Carnegie Mellon

University, with a mean of 4,18. The best European PRO in the

Moreover, for the answer to the presented research question the

number of forward citations is ETH, with a mean of 2,42.

past is not so important as in the current situation. Therefore,



patents from these organisations only from the last ten years were Table 3: Descriptive statistics - Number of family

selected, i.e., from 2014 on.



members

In Table 1 below, we can see the results of the T-test. All the Atomiqu Carnegie Center Columbi Copenha ETH Florida FraunhofHarvard Leuven MIT Stanford e

National a

gen

er

differences in means are statistically significant (p < 0,05).

Descriptive statistics in Table 2 show us that U.S. PROs are

Valid

35282

2860

34168

8196

1427

26

10191

37257

236

4758

15640

12629



better than European in the number of claims and backward and

forward citations. However, European PROs are better than the

Mean

5,035

4,144

7,328

8,590

8,473

9,846

6,076

17,335

11,169

11,387

9,539

10,481



U.S. regarding the number of family members.

Std.

deviation 3,680

4,733

7,298

10,217

9,001

7,412

6,777

29,953

11,778

15,114

13,095

11,641



Table 1: Comparison of European and U.S. PROs (patents

Minimum 1,000

1,000

1,000

1,000

1,000

1,000

1,000

1,000

1,000

1,000

1,000

1,000



from 2014-2024)

Maximu

m

48,000

29,000

147,000 130,000 44,000

22,000

52,000

300,000 93,000

74,000

106,000 78,000



Independent Samples T-test





t

df

p



Table 4: Descriptive statistics - Number of forward

Number of claims

-91,101 162668 < ,001



citations

Number of family members 16,447 162668 < ,001

Atomiqu

Center Columbi Copenha

Fraunhof

Number of backward citations -40,025 162668 < ,001



e

Carnegie National a

gen

ETH

Florida er

Harvard Leuven MIT

Stanford

Number of forward citations -55,886 162668 < ,001

Valid

35282

2860

34168

8196

1427

26

10191

37257

236

4758

15640

12629

Mean

0,849

4,180

0,629

2,319

0,800

2,423

1,947

0,871

0,915

1,251

4,102

2,543



Std.

deviation 3,246

11,998

2,583

9,115

3,238

8,339

6,242

3,593

8,873

9,209

16,149

9,815



Minimum 0,000

0,000

0,000

0,000

0,000

0,000

0,000

0,000

0,000

0,000

0,000

0,000



Maximu

m

162,000 260,000 117,000 232,000 53,000

41,000

181,000 126,000 130,000 396,000 410,000 259,000

Table 2: Group descriptives (patents from 2014-2024)

5 DISCUSSION AND CONCLUSION



Group

N

Mean

SD

SE Coefficient

Results of this study show something quite the opposite of the

of variation

European paradox, which suggests that while European scientific

Number of Europe 112918 14.082 13.774 0.041

0.978

performance is on par with its main international competitors,

claims

Europe lags behind in converting research results into



U.S.

49752 23.823 29.331 0.131

1.231

innovations and gaining a competitive advantage [17]. European

12

paradox is a term that describes Europe's strength in basic science gap with Europe by filing and enforcing its patents in more

but its perceived lag in technological applications in the global

countries.

market (for example, compared to the U.S.).





In this study, the top European and U.S. PROs were compared.

Results show that the U.S. top PROs are much stronger in the

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impactful patents that include more claims and are more

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https://doi.org/10.1080/00036846.2019.1624914



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between European and U.S. PROs in terms of patent

World patent information, 53, 39-44.

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studies of successful collaborations could provide deeper

https://www.applytosupply.digitalmarketplace.service.gov.uk/g-

cloud/services/762715914988187 (assessed: 17.08.2024).

insights into the mechanisms that drive patent performance.

[16] Mishra, P., Singh, U., Pandey, C. M., Mishra, P., & Pandey, G. (2019).

Additionally, exploring policy interventions and strategies to

Application of student's t-test, analysis of variance, and covariance.

strengthen technology transfer offices and foster innovation

Annals of cardiac anaesthesia, 22(4), 407-411.

ecosystems in Europe could offer actionable solutions to close

[17] Nagar, J. P., Breschi, S., & Fosfuri, A. (2024). ERC science and invention: Does ERC break free from the EU Paradox?. Research Policy, 53(8),

the gap with the U.S. The U.S., on the other hand, may close the

105038.





13





The Importance of Technology Transfer Offices in University Industry Collaboration: KTÜ TTM Example



Dilek İSKENDER BALABAN*

Beril DEĞERMENCİ

Harun YÜKSEL

Technology Transfer ARC

Technology Transfer ARC

Finance Department

Karadeniz Technical University

Karadeniz Technical University

Avrasya University

Trabzon, Türkiye

Trabzon, Türkiye

Trabzon, Türkiye

dilekiskender@ktu.edu.tr

berildegermenci@ktu.edu.tr

harun.yuksel@avrasya.edu.tr

Eren YILMAZ

Sedanur KALYONCU

Emrah AYVAZ

Technology Transfer ARC

Technology Transfer ARC

Technology Transfer ARC

Karadeniz Technical University

Karadeniz Technical University

Karadeniz Technical University

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

erenyilmaz@ktu.edu.tr

sedanursaglam@ktu.edu.tr

emrahayvaz@ktu.edu.tr

Oktay YILDIZ

Yalçın AYKUT

İslam YILDIZ

Technology Transfer ARC

Technology Transfer ARC

Technology Transfer ARC

Karadeniz Technical University

Karadeniz Technical University

Karadeniz Technical University

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

oktayyildiz@ktu.edu.tr

yalcin.aykut@ktu.edu.tr

islamyildiz@ktu.edu.tr

Gözde SAĞLAM

Müslüm Serhat ÜNVER

Hülya SABIR

Technology Transfer ARC

Technology Transfer ARC

Technology Transfer ARC

Karadeniz Technical University

Karadeniz Technical University

Karadeniz Technical University

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

gozdesaglam@ktu.edu.tr

serhatunver@ktu.edu.tr

hulyahacisalihoglu@ktu.edu.tr

Kerim SÖNMEZ

Güler Tuğba GÜLTEKİN

Aleyna AYDIN

Technology Transfer ARC

Technology Transfer ARC

Technology Transfer ARC

Karadeniz Technical University

Karadeniz Technical University

Karadeniz Technical University

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

kerimsonmez@ktu.edu.tr

gulertugbagultekin@ktu.edu.tr

aleynaaydin@ktu.edu.tr





ABSTRACT

1.INTRODUCTION

Technology Transfer Offices (TTOs) are organizational

Within the scope of the research, interviews were conducted with

structures that play a role in directing academic research towards the participants on the subject in order to answer the question national and international research projects, facilitating its

“What is the place of technology transfer offices within the transfer to industry, and commercializing it. In general, TTOs framework of university-industry collaboration?” This study

located within universities act as intermediaries between

evaluated the place of Karadeniz Technical University

universities, research institutes, students, investors, and

Technology Transfer Application and Research Center (KTÜ

companies. They engage in activities such as establishing

TTM) within the framework of university-industry collaboration.

connections and making matchings according to the necessary

In the study, qualitative research technique was used and

needs.

“phenomenology” was used as the research design. The data in

In Türkiye, TTOs provide consultancy and support to all

this research was examined with the descriptive content analysis

stakeholders throughout the entire process, from transforming method. Analysis was conducted in RStudio in order to analyze

knowledge into products, selecting industrial partners,

the collected qualitative data and determine emotional tendencies.

identifying appropriate funding sources, project development

According to the analysis results; It was seen that KTÜ TTM

activities, intellectual property and industrial property rights made significant contributions to raising the bar of success by

applications, to commercialization and/or the establishment of using the potential of the university and had a positive effect in academic-based firms [10].

general. When similar studies in the literature are examined, it is As intermediary organizations, TTOs operate according to

seen that TTOs play an important role in university-industry various strategies based on the past experiences of academic and

collaboration. This study supports the theoretical discussions in

industrial actors and the quality of the information conveyed in

the literature with a practical example. Since the study provides

the university-industry collaboration process. TTOs particularly

an evaluation specific to KTÜ TTM, it makes a local and specific

focus on enhancing cognitive and organizational domains. They

contribution to the literature by examining the effects of TTOs in play a crucial role in bringing together actors with different a different university and geographical region. This could fill the visions, ways of interpreting life, and perspectives on the world

gap in the literature on the functioning of TTOs across different

[11].

institutions and regions.

The collaboration between two distinct entities, universities and



industry, can contribute to national development; however, this

KEYWORDS

is achievable only if the process is managed with sound and Technology, technology transfer office, university industry

appropriate strategies. Nowadays, while collaborations between

cooperation, KTÜ TTM

universities and industry can occur through various

*Dilek İSKENDER BALABAN is corresponding author of the ARC for Technology Transfer Karadeniz Technical University in Trabzon, Türkiye.

14

communication channels apart from the support of technology university-industry collaboration. Firms are prioritized and

transfer offices, the outcomes of these collaborations are often

analyzed, and guidance is provided based on current calls for quite weak [7].

proposals. Information on academicians' research that can be A review of the literature reveals that technology transfer offices applicable in the industry or discussions on potential

(TTOs) play a significant role in enhancing and sustaining collaborations with industrial organizations are conducted.

university-industry collaboration.

During the application phase of university-industry collaboration



projects, the entire process of project review, preparation, and 1.1 University Industry Collaboration

submission of application documents is carried out. Legal

University industry collaboration ensures that the knowledge matters and contracts are prepared jointly with the university's

gained from research activities conducted at universities is not

legal counsel. Once a project is approved for funding, support

only published but also transformed into practical applications.

such as accounting transactions, completion of documentation,

It is a collaborative method aimed at and implementing the and signature processes are provided to firms and academicians

transfer of technological developments and knowledge to

by the administrative and financial affairs unit established within production stages according to industrial needs [13]. The cultural KTÜ TTM.

differences between universities and industry contribute to the diversification of research approaches [9]. Effective

2. METHODOLOGY

collaboration between industry and academia requires a special

2.1 Research Methodology and Research Design

alignment; understanding mutual interests, setting common

In this study, the role of KTÜ TTM within the framework of goals, and focusing on complementary skills form the basis for

university-industry collaboration was evaluated. A qualitative achieving successful collaboration [6].

research method was employed, and the research design was

As a result of collaboration, industry, whose goal is to increase

based on "phenomenology." The phenomenological design profits and expand its volume, has seen developments that

typically focuses on phenomena that are recognized but not positively impact production through the adaptation of

deeply or thoroughly understood. Phenomenology is a method

technologically evolving and renewing processes to existing

that concentrates on understanding and evaluating lived

systems. The aim of the university in collaborating with industry

experiences [8]. This methodology aims to deeply examine and

is to develop a qualified human resource and support research

comprehend individuals' experiences.

with a strong knowledge base, leading to the transformation of

Although phenomenological data are obtained from the

theoretical work into practical applications and resulting in some experiences of a few individuals, the information gathered from

modifications [5]. Science plays an extremely important role in

these individuals provides detailed insights into the phenomenon.

facilitating university-industry collaborations. It is a process born The fact that the phenomenon is experienced by different

from the mutual supply and demand between the university,

individuals contributes to the provision of information from which produces science, and industry, which converts science various perspectives by the research participants, thereby aiding

into economic benefits [2].

in understanding the phenomenon from a broad viewpoint. In this

University-industry collaboration highlights a partnership that way, the data obtained from the experiences of different

offers significant benefits for both parties. Through these participants support a comprehensive understanding of the

collaborations, universities strive to address global problems phenomenon [3]. For such research, the number of individuals to

using academic knowledge. Industry, on the other hand, benefits

be included in the sample should generally not exceed ten. It is

from universities' research, expertise, and laboratories, leading to normal to limit the sample size in this type of research since the the development of innovative products and improvements to

interviews often require long and sometimes multiple meetings.

existing products. As a result of this partnership, mutual gains

The limited number of individuals who have experienced the are achieved in areas such as employment, education, innovation,

phenomenon under investigation may also sometimes result in a

and economic growth, which significantly impact life. Thus, restricted number of people who can be included in the sample

these partnerships provide mutual benefits to the parties involved

[12].

and contribute to society and the economy. In addition to their

In addition, sentiment analysis was performed using RStudio to

research mission, universities also have educational and societal

automatically detect and classify emotional expressions present

missions. While the educational mission is clear, societal

in the texts. This analysis employs Natural Language Processing

missions have gained increasing importance in recent years. This

(NLP) techniques to determine whether the sentiments in the is reflected in factors such as the role of universities in university-texts are positive, negative, or neutral. During this process, words industry technology transfer [4].

and expressions within the texts are analyzed to identify the



emotional content.

1.2 University Industry Collaboration Activities of

To visually understand the key themes, topics, and word

KTÜ TTM

distribution in the texts, a word cloud was generated in RStudio.

In order to increase R&D and innovation capacity and strengthen Word clouds, commonly used as part of text mining and data university-industry cooperation activities, KTÜ TTM establishes

visualization techniques, provide a quick representation of the contacts with many new companies every year and develops

frequency of words in a text or text corpus, indicating which bilateral cooperation. These efforts are not limited to the region words are used more frequently.

but extend to firms across the country through online and face-



to-face meetings, integrating new companies into the

2.2 Universe and Sample of the Research

collaboration ecosystem. During these meetings, R&D topics The universe of this research consists of approximately 50

and requests are gathered, the needs of the firms are identified,

faculty members working at KTÜ who have been involved in

and numerous firms are matched with academicians from KTÜ

university industry collaboration processes. To align with the for collaborative projects, involving online meetings and

research objectives, the sample group was composed of 8 faculty

discussions.

members who have both participated in university industry

Meetings are also organized with the boards of Organized

collaboration processes and are knowledgeable about the KTÜ

Industrial Zones to discuss activities within the framework of TTM. The academic titles, faculty and department affiliations, 15

and the total number of projects funded by public and/or private 2.4 Research Findings

sector capital for the faculty members included in the sample The findings of the study are summarized as follows:

group are provided in Table 1.

KTÜ TTM has made significant contributions to raising the bar



2.3 Data Collection Processes and Interview Questions

of success by utilizing the potential of the university. Active



TTOs are essential units that every university must have. They

Within the scope of the research, interviews were conducted with

are crucial in presenting the university as professional and relevant participants to answer the question, "What is the role of institutional in industrial collaborations and play a critical role in KTÜ TTM in the context of university-industry collaboration?"

reducing the risks researchers may encounter during the project

Participants were informed that the interviews would be audio

development process.

recorded by the researcher, but their personal data would not be

KTÜ TTM has been highly effective in conducting one-on-one

shared with third parties. It was explained that the audio meetings with firms, matching academics, providing project

recordings would be used for the purpose of data collection and

writing support, analyzing industrial problems, and guiding both

analysis. Initially, a pool of questions presumed to be relevant to parties on the appropriate course of action throughout the the study topic was created. Subsequently, the questions within

process. It has also played a significant role in realizing many of this pool were evaluated with experts deemed relevant to the the university’s recent collaborations. However, it is observed research content, and the most appropriate eight questions for the that KTÜ TTM faces a disadvantage due to its location being far

study were finalized. The interview questions prepared for the

from major industrial areas. It is suggested that the center could participants are presented in Table 2. Before the interview become more effective by organizing events where industry

questions were posed, a conversation with the participants was

professionals and academics can come together and by placing

initiated to foster a mutual trust relationship. After the audio greater emphasis on institutionalization.

recordings were transcribed, with the permission of the

It is noted that KTÜ TTM is preferred as an intermediary because

participants, the next step was the analysis of the data. The it instills confidence in the industrial sector during company collected data was analyzed using descriptive content analysis,

visits and ensures that academics feel secure. Its professional and and additionally, sentiment analysis was conducted, and a word

corporate identity during industry visits, which represents the cloud was generated using the RStudio program.

university, leads to a more positive and moderate view of the Table1: Characteristics of the Study Sample Group

project

development

processes

among

industrialists.



Additionally, KTÜ TTM is favored for its objective approach to

Number of Public

Academic

both academics and industry parties, its facilitation of smooth Faculty/Departments

/Private Sector

Title

process progress, its role as a mediator, and its handling of Supported Projects

accounting tasks.

Forestry Faculty

Professor

10

KTÜ TTM is believed to be doing its best to achieve its goals.

Forestry Industrial Engineering

Additionally, there are expectations for bringing academics

Faculty of Engineering

Professor

6

Mechanical Engineering

along on company visits, conducting matching processes more

Faculty of Engineering

meticulously, collecting project topic requests from academics Professor

2

Mechanical Engineering

based on company activity areas, and matching academics with

Associate

Faculty of Engineering

large-scale companies in the Technopolis where they have their

4

Professor

Industrial Engineering

firms.

Assistant

Faculty of Science

It is generally believed that KTÜ TTM does not have significant

6

Professor

Computer Science

shortcomings. However, suggestions have been made, including

Assistant

Faculty of Science

collecting R&D topic proposals from academics and forwarding

6

Professor

Computer Science

them to companies, grouping companies sectorally to hold

meetings with academics on specific days, providing support Assistant

Vocational School of Health

Services Medical Services and

3

with sample project forms, and facilitating discussions and Professor

Techniques

integration between academic entrepreneurs and companies.

Research

Forestry Faculty

To increase its activity, it is suggested that KTÜ TTM could 2

assistant

Forestry Industrial Engineering

increase its participation in fairs, fix the names of the companies it works with on its website, enhance materials for promoting Table 2: İnterview Questions

TTO's module functions and staff, utilize international resources, No

and raise awareness among companies about TTO activities.



İnterview Questions



It is believed that TTO plays a facilitative role in reviewing and 1

What are your opinions about KTÜ TTM?

preparing contracts between academics and industrialists,

2

How would you define university industry collaboration?

managing financial obligations, handling bureaucratic processes,

3

Do you think KTÜ TTM is effective in the processes of

and establishing balances between the company and the

university industry collaboration?

academic. Additionally, it is noted that TTO helps eliminate 4

Why would you prefer KTÜ TTM to be an intermediary

problems by coordinating the project development processes for

in university industry collaboration processes?

companies that are located far away.

5

What are your expectations regarding KTÜ TTM's

The data obtained from the interviews was converted into a text

university industry collaboration module?

file and sentiment analysis was performed using the RStudio 6

Is there any aspect of KTÜ TTM's university industry

program. The graph showing the sentiment scores obtained from

collaboration processes that you find lacking?

the analysis is presented in Figure 1.

7

In your opinion, how could KTÜ TTM become more

Subsequently, a word cloud was created using the Rstudio

active in the context of university industry collaboration?

program to analyze frequently used words within the text. The

8

Has the solution/process of the problems you experienced

resulting word cloud is presented in Figure 2.

in university-industry collaborations at KTÜ TTM



become easier?





16





Figure 1: Distribution of Sentiment Scores

In the word cloud presented in Figure 2, the words 'industry,'



'university,' and 'TTO' are prominently featured. The frequent occurrence of the word 'industry' indicates a strong focus on how

KTÜ TTM interacts with and supports industrial partners. The

frequent mention of the word 'university' underscores the

importance of the academic side of the collaboration, suggesting

that researchers view the university's role as critical in partnering with industry. The prominent presence of the abbreviation 'TTO'

highlights the central role of KTÜ TTM in facilitating these collaborations. Overall, the word cloud demonstrates the

significant role that KTÜ TTM plays in supporting and

facilitating these interactions.

The current situation of KTÜ TTM has been evaluated, and the

following recommendations have been proposed:



Increasing awareness of the services provided by TTO and



conveying this awareness to the business ecosystem will enhance

Figure 2: Word Cloud

the sustainability of new collaborations. Organizing events that



bring together universities and industry can foster more

communication between them. The strong relationships

established will increase the sense of trust, thereby creating opportunities for further collaboration. Additionally, such efforts will create internship and job opportunities for students trained

at the university for the business world.

In future studies, the place of TTOs can be examined within the

framework of commercialization of inventions within the

university and/or increasing academic entrepreneurship. By

increasing the number of study samples, the subject can be analyzed in depth with different analysis methods and theoretical

frameworks can be tested. In addition, the role and impact of TTOs in different universities, regions and different countries in university-industry collaboration can be examined by conducting



multiple case studies. It will be useful to compare different 3. CONCLUSION AND RECOMMENDATIONS

structures and operations of TTOs in terms of examining the impact of different regional and sectoral dynamics on

In conclusion, it has been observed that the activities carried out collaboration processes.

by the KTÜ TTM within the framework of university industry



collaboration have yielded positive results, as noted by

participants who are familiar with the structure and functioning

REFERENCES

of the TTO and have been involved in the university industry

[1] Abdulai, A. F., Murphy, L., Thomas, A., & Thomas, B. (2022), Technology collaboration processes. Furthermore, it has been concluded that

Transfer Offices and Their Role with Information Mechanisms for Innovation Performance in Firms: The Case of Ghana. Knowledge, 2(4), 719-734.

the TTO has positively influenced its corporate image. The study

[2] Akdoğan, A. (2007), The Functionality of Research and Application Centers

[1] supports this finding, as it concluded that TTOs positively in Universities (s. 85-104). Ankara: Detay Publishing

impact the innovation capacity within firms, with 47% of firms'

[3] Baker, C., Wuest, J. & Stern, P.N. (1992), “ Method Slurring: the Grounded Theory/ Phenomenology Example”. Journal of Advanced Nursing, 17, 1355-innovation capacity being provided by TTOs.

1360.

Upon evaluating the sentiment analysis scores presented in

[4] Blankesteijn, M., Bossink, B., & van der Sijde, P. (2021), Science-based Figure 1, it is observed that a high score corresponds to a positive entrepreneurship education as a means for university-industry technology sentiment. This result indicates that the university-industry transfer. International Entrepreneurship and Management Journal, 17(2), 779-808.

collaborations carried out with KTÜ TTM generally have a

[5] Eryanık, A. (2018), The Impact of University-Industry Collaboration on positive impact. It demonstrates that stakeholders being satisfied Employment: The Case of Uşak. Published Master's Thesis. Afyonkarahisar: with the collaboration and experiencing positive outcomes.

Afyon Kocatepe University.

[6] Fasi, M. A. (2022), An Overview on patenting trends and technology The high level of trust indicates that KTÜ TTM has established

commercialization practices in the university Technology Transfer Offices in a strong trust relationship between university and industry USA and China. World Patent Information, 68, 102097.

stakeholders and is recognized as a reliable partner. The high

[7] Güler, M., & Kırbaşlar, İ. (2020), The Role of Technology Transfer Offices in level of anticipation reflects the high expectations for future University-Industry Collaboration, Iktisad Publishing

[8] Jasper, M. A. (1994), “Issues in Phenomenology for Researchers of Nursing”.

projects and potential opportunities in collaborations with KTÜ

Journal of Advanced Nursing, 19, 309-314.

TTM.

[9] O’Dwyer, M., Filieri, R., & O’Malley, L. (2023), Establishing Successful Based on the sentiment analysis results, we can conclude that University İndustry Collaborations: Barriers And Enablers Deconstructed. The Journal of Technology Transfer, 48(3), 900-931.

KTÜ TTM's role and significance in university industry

[10] Temel, S., Dabić, M., Ar, I. M., Howells, J., Mert, A., & Yesilay, R. B. (2021), collaboration are highly positive. The high levels of positive Exploring The Relationship Between University İnnovation İntermediaries emotions and trust demonstrate that the collaborations are being

And Patenting Performance. Technology in Society, 66, 101665.

conducted successfully and that stakeholders are satisfied, while

[11] Villani, E., Rasmussen, E., & Grimaldi, R. (2017), How İntermediary Organizations Facilitate University–İndustry Technology Transfer: A the low levels of negative emotions suggest that the processes are Proximity Approach. Technological Forecasting And Social Change, 114, 86-running smoothly and are being managed effectively. This

102.

proves that KTÜ TTM is a reliable and effective interface that

[12] Yıldırım, A. & Şimşek, H. (2013), Qualitative Research Methods in Social Sciences (9th Edition). Ankara: Seçkin Publishing.

strengthens the collaboration between the university and

[13] Yücel, İ. H. (1997), Science and Technology Policies and the 21st Century industry.

Society. In Science and Technology Policies and the 21st Century Society (p.

76). Ankara: State Planning Organization.

17





The Impact of International Networks on Grants, R&D, Knowledge and Technology Transfer - Case of COST

Network and KTU

Sedanur KALYONCU

İslam YILDIZ

Emrah AYVAZ

Technology Transfer ARC

Technology Transfer ARC

Technology Transfer ARC

Karadeniz Technical University

Karadeniz Technical University

Karadeniz Technical University

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

sedanursaglam@ktu.edu.tr

islamyildiz@ktu.edu.tr

emrahayvaz@ktu.edu.tr

Gözde SAĞLAM

Müslüm Serhat ÜNVER

Oktay YILDIZ

Technology Transfer ARC

Technology Transfer ARC

Technology Transfer ARC

Karadeniz Technical University

Karadeniz Technical University

Karadeniz Technical University

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

gozdesaglam@ktu.edu.tr

serhatunver@ktu.edu.tr

oktayyildiz@ktu.edu.tr

Güler Tuğba GÜLTEKİN

Eren YILMAZ

Kerim SÖNMEZ

Technology Transfer ARC

Technology Transfer ARC

Technology Transfer ARC

Karadeniz Technical University

Karadeniz Technical University

Karadeniz Technical University

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

gulertugbagultekin@ktu.edu.tr

erenyilmaz@ktu.edu.tr

kerimsonmez@ktu.edu.tr

Hülya SABIR

Beril DEĞERMENCİ

Yalçın AYKUT

Technology Transfer ARC

Technology Transfer ARC

Technology Transfer ARC

Karadeniz Technical University

Karadeniz Technical University

Karadeniz Technical University

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

hulyahacisalihoglu@ktu.edu.tr

berildegermenci@ktu.edu.tr

yalcin.aykut@ktu.edu.tr

Ayhan KOÇ

Aleyna AYDIN



Dilek İSKENDER BALABAN

Technology Transfer ARC

Technology Transfer ARC

Technology Transfer ARC

Karadeniz Technical University

Karadeniz Technical University

Karadeniz Technical University

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

aleynaaydin@ktu.edu.tr

ayhankoc@ktu.edu.tr

dilekiskender@ktu.edu.tr



Seda BAŞ





Technology Transfer ARC





Karadeniz Technical University





Trabzon / TÜRKİYE



sedabas@ktu.edu.tr

ABSTRACT

involved in the COST program from 2019 to 2023 was examined.

Additionally, Türkiye’s performance during this period was

It is essential that researchers collaborate with international analyzed to assess the effectiveness of the developed strategy. As colleagues and adhere to international standards to facilitate the a result of these analyses, in COST Actions in which a limited

transfer of technology resulting from their research. In order to

number of KTU researchers were involved at the beginning of participate in these projects, it is essential for researchers to have 2019, 252 researchers were involved in 528 actions by the end of

2023, becoming the first university in Türkiye in this context.

a broad international network and reliable collaborators to form

international consortia. This study examines the strategy adopted

Thanks to the researchers and activation included in the COST

by Karadeniz Technical University (KTU) in its pursuit of the Programme, a 92.3% increase in the number of international COST (European Cooperation in Science and Technology)

project applications and a 366% increase in the number of project

Programme and the subsequent results that enabled its

acceptances were observed between 2019 and 2023. The

researchers to engage in prestigious international consortia and

findings indicated that these exemplary practices could serve as

access international funding sources. To increase the number of

an effective approach for the internationalisation of higher Karadeniz Technical University (KTU) members in the

education institutions.

Management Committee (MC) and Working Group (WG) of

COST Actions, which have limited slots, each Action was

KEYWORDS

carefully reviewed, and individual meetings were held with

Technology Transfer, R&D, Internationalisation, COST

researchers. Technical and administrative support was provided



to facilitate researchers' participation in the Actions. A statistical analysis was conducted for researchers who participated in



COST Actions over the past five years. The status of countries



18

1 INTRODUCTION

COST provide invaluable opportunities for researchers to

disseminate their knowledge and experience [5].

The involvement of researchers in internationally funded



projects presents a duality of opportunities and challenges. One



of the most significant challenges encountered during this

2 METHODOLGY

process is the formation of international consortia. Effective In accordance with the internationalisation strategy for KTU to

communication between researchers from different countries and

become more effective in the international arena, activities are disciplines is of great importance, as consortia require such a being undertaken with the objective of enhancing international diverse group to come together [1]. Furthermore, operational collaboration and increasing the quantity and calibre of project

challenges, including the sourcing of funding, the optimal

proposals submitted to international funding programmes. Given

utilisation of resources and the effective management of projects, the crucial role that a broad international network plays in represent significant obstacles in the context of such projects [2].

securing participation in internationally funded projects,

Nevertheless, the intricacy of these procedures and the presence

concerted efforts have been made to direct students towards the

of bureaucratic impediments can act as a deterrent for numerous

COST Programme since late 2019, with ongoing initiatives still

researchers [3]. The existing literature frequently emphasises that in place.

participation in international projects has positive effects on In this context, awareness-raising activities, which commenced

researchers' career development, knowledge sharing and

with information events held at various locations across the innovation [4]. In particular, the formation of international university and its constituent departments, have yielded tangible

consortia hinges on the existence of reliable networks and outcomes through one-to-one interviews with academics. In this

cooperative networks, which are pivotal for the success of the regard, the strategy pursued by KTU Technology Transfer

projects. In this context, the effective utilisation of international Application and Research Center experts to enhance the

cooperation networks facilitates the efficiency and sustainability involvement of researchers in COST Actions is outlined below.

of projects. Due to the inability of KTU researchers to engage in

- Organisation of information events:

sufficient international cooperation, it was observed that the

- Analysing current COST actions: Existing COST actions are university was quantitatively and qualitatively insufficient in analysed and listed with details covering objectives, research international projects, resulting in limited scientific output and areas, participation requirements, duration, etc.

weakened competitiveness at the global level. This deficiency

- Identification of researchers: Researchers with fields of study prevented the university from fully exploiting its potential, compatible with COST actions are identified by analysing their

especially in areas such as access to international funding, academic profiles (research areas, project experiences, etc.).

exchange of knowledge and experience, and development of

-Establishing contact with researchers: The identified innovative solutions. This study presents the internationalisation researchers are contacted and one-to-one interviews (telephone,

strategy of Karadeniz Technical University, which enables

e-mail or desk interviews) are conducted about the opportunities

researchers to participate in qualified international consortia and and benefits of participation in COST actions. It is assessed access international funding sources, as exemplified by the whether the researchers are suitable for the identified actions.

COST programme.

-Providing technical support services: Technical support is The COST (European Cooperation in Science and Technology)

provided to researchers during the application process for COST

programme was established in 1971 with the objective of

actions (filling out the application form, preparation of necessary promoting scientific and technological research in Europe. The

documents, follow-up of the application process, etc.) and the objective of COST is to facilitate the exchange of knowledge and

application evaluation process is followed.

encourage innovation among researchers by fostering

-Guidance to other COST-related support: Researchers are interdisciplinary networks. The principal objective of the

provided with the opportunity to benefit not only from MC/WG

programme is to facilitate international collaboration and enable

assignments in actions, but also from other COST-related

researchers to collectively address global challenges. While support such as Short-Term Scientific Visit (STSM) and ITC

COST does not provide direct support for research and

Conference Support. In addition, referrals were made to the COST 2515 Programme supported by TUBITAK, the COST

development, it plays a significant role in facilitating the National Coordinator in Türkiye, to provide R&D support to formation of international consortia, which allow researchers to

researchers.

collaborate on the advancement of their projects. Researchers The country-based data used in the study were obtained from the

may participate in the Actions in either the capacity of a member

COST Annual Reports and the researcher-based data were

of the Management Committee (MC) or a member of a Working

obtained from the COST website.

Group (WG). In these roles, they are afforded the opportunity to

In order to assess the status of the developed strategy, a mini engage in in-depth strategic planning, project management, and

survey with open-ended questions was conducted with KTU

the exploration of specific research topics. Those engaged in researchers participating in COST Actions. In the survey, the COST Actions enjoy significant advantages, including access to

benefits of the participated actions for the academics were information and resources, opportunities for career development

evaluated with questions such as to what extent they benefited from the action, what kind of effects it had at the academic level, and the strengthening of leadership skills as part of an

what kind of activities they participated in.

internationally recognised network. Such opportunities permit researchers to make significant progress in their careers and to

3 RESULTS

become more prominent figures within the international

scientific community. COST Actions facilitate the formation of

The COST programme facilitates extensive involvement from a

new collaborative relationships and the expansion of existing diverse array of countries, encompassing 41 member countries

networks, thereby enhancing the probability of securing

and cooperation countries. In addition to Europe's leading

additional funding and support for research projects.

countries in science and research, such as Germany, France, Furthermore, meetings, workshops and conferences organised by

Italy, Spain and the United Kingdom, Türkiye, Israel and some

Western Balkan countries are also actively involved in this 19



programme. Table 1 presents detailed data illustrating the status

institutions. In 2021, participation declined as a consequence of

of active participation in the COST programme between 2019

the impact of the pandemic. However, in 2022, there was a and 2023 [6-10].

revival in participation and a success was achieved as in 2020.



This success continued to increase in the following years. As Table 1: Status of Countries in COST Programme

evidenced by the participation statistics provided by the COST



Organisation, Türkiye achieved notable success in 2022 and

Indicator

2019 2020 2021 2022 2023

2023. In 2022, Türkiye achieved the distinction of becoming the

Runnig

COST

third most participating country, with a participation rate of 99%

294

Action



291

289

302

269



in all active actions. Additionally, the country reached a notable New COST action

number of members, with 3,084 individuals participating in

80

launched



45

40

70

70

Working Groups. In the same year, Türkiye was the fifth most



Average number of

successful country in terms of individual participation in COST

COST

Members 30

network activities, with 1,113 participants, and the fourth 30.8

31

33

33

per Action

country with the highest budget allocation of approximately EUR



Average number of

1.5 million. Türkiye was the leading country in terms of

non-COST

participation by young researchers, with a rate of 52.8%. In 2023,

-

countries

per



4.3

6

5

6

Türkiye sustained its efficacy by participating in 99% of all Action

actions, thereby attaining the distinction of being the country Articles

with the highest number of working group members, with 7,096



479

921

1501 1253 -

Percentage of spin-

working group members. Türkiye was the third most successful

country in terms of individual participation in COST network off H2020*

37%

39%

32%

-

-

activities, with 1,849 participants, and the third most budgeted proposals approved

country, with approximately EUR 2.27 million.

Average value of

As a consequence of the activities conducted throughout this spin-off

6M

process, there has been an enhancement in the awareness of projects per Action



5.8M 3.9M 9.5M 5.2M

researchers, as well as an increase in the number of researchers

(€)

who have submitted applications on an individual basis.

*Horizon 2020 was the EU's research and innovation funding Moreover, the support provided by COST was not confined to

programme from 2014-2020

KTU but was also extended to TTO units and researchers at other



universities, thereby contributing to an increase in Türkiye's Türkiye plays a significant role as an active participant in the participation in the COST Programme.

COST programme. Türkiye's involvement in COST Actions

As the number of researchers engaged in the COST Programme

between 2019 and 2023, along with a comprehensive account of

and active in its actions has grown, the graph below illustrates its contributions and accomplishments, is presented in Table 2

the change in the number of international project applications and

[11-15].

acceptances submitted by KTU between 2019 and 2023 (Fig. 1).





Table 2: Türkiye's Position in COST Programme

Indicator

2019

2020

2021

2022

2023

Individual

participation in all

1075

-

20

1113

1849

action activities

Training

1

12

0

4

10

school/hosted

Short-term

scientific

14

103

8

12

23

missions/hosted

Short-term

scientific

Figure 1. Statistics of KTU projects with international funding 72

380

43

90

158

(2019-2023)

missions/participant



Trainess/participant

197

1001

33

219

310

4 DISCUSSION AND CONCLUSION

Trainers/participant

7

58

1

23

48

The formation of international networks plays a pivotal role in

Budget received (€)

the establishment of dependable and collaborative international

0.9M

4.9M

0.3M

1.5M

2.3M

project consortia. This is achieved by the creation of scientific networks comprising researchers and institutions, which

Türkiye demonstrates a notable level of involvement in the subsequently leads to an increase in the number of international

COST programme, exhibiting a discernible increase in

project applications and acceptances.

participation on an annual basis. The number of individual This study examines the strategy employed in the process by participants increased from 1,649 in 2019 to 103 short-term which KTU researchers were directed to the COST Programme,

scientific missions in 2020, with 380 participants being sent to

an international organisation with the objective of uniting these missions. Furthermore, 12 training schools were conducted

scientists who are experts in their respective fields throughout in 2020, with 1,001 individuals undergoing training at these Europe in scientific networks. This strategy facilitates the 20

integration of scientists engaged in national research projects into This, in turn, has resulted in KTU researchers establishing more

the international scientific community.

robust international networks, which has directly influenced the

The strategy pursued has yielded notable results. At the inception number of international project applications and acceptances. In

of 2019, a modest number of KTU researchers were engaged in

conclusion, the findings indicate that these exemplary practices

COST actions. By the conclusion of 2023, this number had

may serve as an effective approach for the internationalisation of grown to 252 researchers participating in 528 actions. With higher education institutions.

regard to the ongoing COST actions, KTU has been the most successful university in Türkiye, with 29 active members of the

REFERENCES

Management Committee. In the context of the ongoing actions,

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Katz, J. S., & Martin, B. R. (1997). What is research collaboration?.

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Wagner, C. S., & Leydesdorff, L. (2005). Network structure, self-organization, and the growth of international collaboration in science.

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Olson, G. M., & Olson, J. S. (2000). Distance matters. Human–computer year internationalisation strategy.

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The COST programme has been instrumental in facilitating a

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Glänzel, W., & Schubert, A. (2004). Analysing scientific networks through co-authorship. In Handbook of quantitative science and significant increase in the number of international project technology research: The use of publication and patent statistics in studies applications, with a 92.3% rise observed between 2019 and 2023.

of S&T systems (pp. 257-276). Dordrecht: Springer Netherlands.

Additionally, there has been a notable surge in project

[5]

COST (European Cooperation in Science and Technology). “What are COST

Actions?”.

https://www.cost.eu/cost-actions/what-are-cost-

acceptances, with a 366% increase during the same period.

actions/. 09 August 2024.

Participation in COST Actions was not only associated with an

[6]

COST 2023, COST Annual Report, COST (European Cooperation in increase in the number of project applications and acceptances,

Science and Technology), 2023.

but also with the administration of surveys to KTU researchers

[7]

COST 2022, COST Annual Report, COST (European Cooperation in Science and Technology), 2022.

who took part in the actions in 2021 and 2023. The objective was

[8]

COST 2021, COST Annual Report, COST (European Cooperation in to ascertain the additional benefits that researchers derive from

Science and Technology), 2021.

the COST Programme. The results of the surveys indicated that

[9]

COST 2020, COST Annual Report, COST (European Cooperation in Science and Technology), 2020.

the researchers had participated in numerous training

[10]

COST 2019, COST Annual Report, COST (European Cooperation in programmes, workshops and conferences, and had developed a

Science and Technology), 2019.

network of contacts. They had also published more international

[11]

COST Türkiye 2023, Türkiye Factsheet, COST (European Cooperation in collaborative papers, worked on multidisciplinary projects with

Science and Technology), 2023.

[12]

COST Türkiye 2022, Türkiye Factsheet, COST (European Cooperation in researchers from other countries, and had access to research and

Science and Technology), 2022.

laboratory facilities that would not otherwise have been available

[13]

COST Türkiye 2021, Türkiye Factsheet, COST (European Cooperation in to them in their home countries. Furthermore, they had

Science and Technology), 2021.

[14]

COST Türkiye 2020, Türkiye Horizon Factsheet, COST (European disseminated their work more widely.

Cooperation in Science and Technology), 2020.

The findings of this study demonstrate that the strategy employed

[15]

COST Türkiye 2019, Türkiye Factsheet, COST (European Cooperation in by KTU has led to an increase in participation in COST actions.

Science and Technology), 2019.



21





The Effect of Evaluating Graduate Thesis Topics as Invention Notification Form on Industrial and Intellectual

Property Applications: The Case of Karadeniz Technical

University

Kerim SÖNMEZ*

İslam YILDIZ

Yalçın AYKUT

Technology Transfer Application and

Technology Transfer Application and

Technology Transfer Application and

Research Center,

Research Center,

Research Center,

Karadeniz Technical University

Karadeniz Technical University

Karadeniz Technical University

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

kerimsonmez@ktu.edu.tr

islamyildiz@ktu.edu.tr

yalcin.aykut@ktu.edu.tr

Hülya SABIR

Gözde SAĞLAM

Aleyna AYDIN

Technology Transfer Application and

Technology Transfer Application and

Technology Transfer Application and

Research Center,

Research Center,

Research Center,

Karadeniz Technical University

Karadeniz Technical University

Karadeniz Technical University

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

hulyahacisalihoglu@ktu.edu.tr

gozdesaglam@ktu.edu.tr

aleynaaydin@ktu.edu.tr

Sedanur KALYONCU

Müslüm Serhat ÜNVER

Ayhan KOÇ

Technology Transfer Application and

Technology Transfer Application and

Technology Transfer Application and

Research Center,

Research Center,

Research Center,

Karadeniz Technical University

Karadeniz Technical University

Karadeniz Technical University

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

berildegermenci@ktu.edu.tr

serhatunver@ktu.edu.tr

ayhankoc@ktu.edu.tr

Emrah AYVAZ

Eren YILMAZ

Dilek İSKENDER BALABAN

Technology Transfer Application and

Technology Transfer Application and

Technology Transfer Application and

Research Center,

Research Center,

Research Center,

Karadeniz Technical University

Karadeniz Technical University

Karadeniz Technical University

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

emrahayvaz@ktu.edu.tr

erenyilmaz@ktu.edu.tr

dilekiskender@ktu.edu.tr

Beril DEĞERMENCİ

Güler Tuğba GÜLTEKİN

Oktay YILDIZ

Technology Transfer Application and

Technology Transfer Application and

Okta Arge Mühendislik Hiz. San ve Tic. Ltd.

Research Center,

Research Center,

Şti,

Karadeniz Technical University

Karadeniz Technical University

Üniversite Mh. Hastane Cd.Trabzon

Trabzon / TÜRKİYE

Trabzon / TÜRKİYE

Teknokent Trabzon / TÜRKİYE

sedanursaglam@ktu.edu.tr

gulertugbagultekin@ktu.edu.tr

oktayyildiz@hotmail.com





ABSTRACT

necessary for KTU that is the application authority, to develop

new strategies to increase industrial property assets. This study

Industrial and intellectual property is an important structure

aims to reveal the effect on the number of patent applications by

that is popular all over the world. Each country has legal Karadeniz Technical University (KTU) as a result of the

regulations in the field of intellectual and industrial property in evaluation of graduate thesis topics without request. Within the

order to protect one's invention. The 6769 Industrial and

scope of the new strategy, a methodology was applied for the Intellectual Property Law, which entered into force in 2017, evaluation of patent and utility model application data in the paved the way for universities in Türkiye to have rights in KTÜ patent portfolio, the distribution of data by year, and patent applications for inventions such as patents, utility models and registration documents. In this study, direct patent and utility designs. Thesis studies that young researchers start during their

model application data were evaluated. When the application postgraduate period are focused solely on publication. The

data was examined, it was seen that the new strategy

commercialization and patenting potential of theses determined

implemented increased the industrial property assets.

without analyzing the needs of the industrial sector is low, and

this makes the thesis work of many engineers inefficient. It is KEYWORDS

Industrial rights, Intellectual rights, patent, utility model, 6769

*Lect. Kerim SÖNMEZ is Coordinator of the ARC for Technology Transfer Karadeniz Technical University in Trabzon, Türkiye.

law, KTU



Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full 1 INTRODUCTION

citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s)

The concept of intellectual property refers to all rights that

Information Society 2024, 7–11 October 2024, Ljubljana, Slovenia are the product of the human mind and have economic value even

© 2024 Copyright held by the owner/author(s).

22

if they do not have a tangible equivalent. In other words, it PhD) were filtered from patent applications for each year and the

includes ideas that arise as a result of the creative efforts of a effect of the developed strategy on the applications was revealed.

person or organization, inventions, literary and artistic works, When the application data were examined, it was seen that the

symbols, names, shapes and designs used for commercial

new strategy applied increased the industrial property assets.

purposes. With the application of an intellectual product, the absolute right provided to the inventor in material and spiritual

terms is recognized for a certain period of time [1]. If these rights 3 HISTORICAL DEVELOPMENT OF

are defined in a different term, intellectual property rights (IPRs) PATENT RIGHTS IN TÜRKİYE

can be defined as the rights that enable sanctions to be imposed

The first important legal arrangement regarding patent rights

on the products created by the human mind [2]. It is necessary to

in Türkiye was made in 1879 during the Ottoman Empire. The

analyze the concept of intellectual property in two separate French Patent Law of that time was amended and translated into

sections. The first of these concepts includes industrial property the Ottoman Patent Law enacted in 1879. In parallel with the rights including inventions (patents and utility models),

developments in the world, valid patent laws could not be trademarks, industrial designs, integrated circuit topographies enacted in Türkiye until 1995, except for the international and geographical indications. The second concept includes all agreements signed, and the patent laws of the Ottoman Empire

intellectual and artistic works, including works of art, works of

continued to be applied with some changes until 1995.

science, works of literature, music and musical works, fine art

Subsequently, Türkiye became a party to the Paris Convention in

and cinematographic works, depending on copyright [3].

1925 and signed the WIPO founding treaty in 1976. Furthermore,

Intellectual and industrial property rights give the inventor the Türkiye acceded to the London amendment in 1956, Articles 13

ability to manage all commercial activities thanks to the absolute through 30 of the Stockholm amendment in 1976 and Articles 1

rights it gives to the inventor. Both the desire of the inventor to through 12 of the Stockholm amendment in 1995 [6]. Türkiye

protect his/her invention and the desire to prevent imitation in signed the Customs Union Agreement in 1994. With this

commercial activities increase the number of applications of agreement, the "TRIPS" agreement, the "Strasbourg Agreement Intellectual and Industrial Rights in legal protection processes.

on the classification of patents" (IPC) and the "Patent Patent, utility model, trademark, etc. industrial assets and Cooperation Agreement" (PCT) and the "Agreement

copyrights are subject to very serious court-based sanctions in Establishing the World Trade Organization" entered into force.

case of infringement of the intellectual assets in question. [4].

Later on, the "Budapest Agreement" on the international Violations or infringements of rights by third parties have legal

protection of microorganisms entered into force, as well as the

and criminal sanctions to protect the rights of right holders [5].

"Patent Law Treaty" (PLT) and the "European Patent The purpose of patents is to provide protection that facilitates

Convention" (Munich Convention) [6].

technological development. A patent not only gives the inventor

Table 1 presents data on Türkiye's status as a party to the exclusive rights to create an invention, but also provides conventions on intellectual property rights to which Türkiye is a

incentives

for

the

technological

development

and

party [7].

commercialization of that invention. Instead of obtaining a patent, the inventor publishes the technical specifications of the Tablo 1: International Agreements to which Türkiye is a Party invention, enabling others to make different new inventions

[7]

based on the invention. An increase in the number of patents in a

First

Türkiye’s

country indicates a high level of technological development in Participatio

Agreements

Signatur

Membershi

the country. The transformation of industrial and intellectual n Date

e Date





p

assets into the economy through the sale of inventions, the World

Intellectual

production of inventions and the sale of products positively Property Organization

affects the welfare of the country.

1967

WIPO Articles of



YES

12.05.1976

This research aimed to determine if recognizing master's and

Association

doctoral theses as invention disclosure forms, without requiring

Treaty

Establishing

additional notifications, would lead to an increase in the number

the World Intellectual

of granted patents. Since Karadeniz Technical University is a 1995

Property Organization



YES

26.03.1995

research university, the number of industrial property assets is

(WIPO)

significant. It is necessary to develop new strategies to increase European

Patent

industrial property assets. When the application data was

1973

Convention (EPC)



YES

01.11.2000



examined, it was seen that the new strategy implemented

Stockholm

increased the industrial property assets.

(Articles 1-

Paris Convention for

YES

12)

2 METHODOLOGY

the

Protection

of 1883

(10.10.1925

01.02.1995

Industrial Property

)

(Articles

The application change status was revealed by using the

13-30

patent and utility model application data of Karadeniz Technical

16.05.1976)

University. In addition, the registration numbers were evaluated

Signed

with a similar method. Among the patent applications in the KTU

Patent Law (PLT)

2000

02.06.200





patent portfolio, applications between the years 2017-2023 were

Trademark Law (TLT) 1994

YES

01.01.2005

evaluated. In the relevant years, student applications (Master and 23

Singapore Agreement

Signed

The

education institutions defined in subparagraph (c) of the first on Trademark Law

28.03.2006

agreement

paragraph of Article 3 of Law No. 2547 and higher education 2006

has not yet

institutions affiliated to the Ministry of National Defense and the entered into

Ministry of Interior.

force

(2) When an invention is realized as a result of scientific BUDAPESTE

studies or research conducted in higher education institutions, the Agreement on the

inventor is obliged to notify the higher education institution in 1977

International Storage



YES

30.11.1998

writing and without delay. If a patent application has been made,

of Microorganisms

the higher education institution shall be notified of the

LAHEY Agreement

application.

on the International

(3) The higher education institution is obliged to file a patent

Registration

of 1999

YES

1.01.2005

application if it claims right ownership over the invention.

Designs

(Geneva

Otherwise, the invention becomes a free invention

Text!

On this occasion, studies for the protection of the knowledge

Protocol

to

the

accumulation in universities with intellectual and industrial 1989

MADRID Agreement



YES

01.01.1999



rights have been carried out as of 2017.

Patent

Cooperation 1970

Treaty (PCT)



YES

01.01.1996



LOCARNO

4 KARADENİZ TECHNICAL UNIVERSITY

Agreement on the 1968

YES

30.11.1998

INDUSTRIAL PROPERTY NUMBERS

Restriction of Designs

Founded in 1954, Karadeniz Technical University is the first

NIS Agreement on the

technical university established in Anatolia in Türkiye. In International

addition, as of 2021, it continues to produce science in the Classification

of

Research University category. New generation universities are 1957

Goods and Services in



YES

01.01.1996

universities that transform the knowledge they produce into Trademark

added value while producing knowledge, coordinate these

Registration

processes, and involve every individual from students to faculty

STRASBORG

members in innovation-based commercialization activities.

Agreement on the

Karadeniz Technical University has assumed an important role

International

1971

YES

01.10.1996

in serving this basic mission with the Technology Transfer Classification

of

Application and Research Center (TTC).

Patents (IPC)

With the Industrial Property Law No. 6769, which entered

VIENNA Agreement

into force in 2017, Karadeniz Technical University has made a

on the Classification

total of 262 industrial property applications with 166 national 1973

of

Figurative



YES

01.01.1996

patents, 28 national utility models, 16 national designs and 52

Elements of Marks

international patent applications with access to more than 300



inventors and more than 3000 students. With these applications,



39 national patents, 20 national utility models, 16 national designs and 5 international patents were registered. In addition,

2.1 INDUSTRIAL PROPERTY LAW NO. 6769

6 copyright registrations and 24 trademark applications were also

In Turkish law, industrial property rights were first regulated

carried out by Karadeniz Technical University [8].

by the Decree Law No. 551 on the Protection of Patent Rights,

No. 554 on the Protection of Industrial Designs, No. 555 on the

5 A NEW STRATEGY for INVENTION

Protection of Geographical Indications and No. 556 on the

Protection of Trademarks, which entered into force in 1995.

DISCLUSURE

These Decree Laws were repealed by the Industrial Property Law

As stated in subparagraph c of Article 121 of the Industrial

No. 6769 ("IPL"), which entered into force in 2017.

Property Law No. 6769, there is an obligation to notify the According to the IPL No. 6769, Articles 113-122 include the

university of an invention made at the university before applying

provisions on "Employee Inventions". Especially with Article for industrial property. This notification is referred to as the 121, universities and public institutions are entitled to have rights invention disclosure form in the literature [9]. As of 2017, in patent applications [10].

universities collect invention disclosure forms and make patent



applications by evaluating these forms according to criteria such

ARTICLE 121

as patentability, commercialization, etc.

(1) Without prejudice to the provisions of special laws and

As of 2023, a new strategy was developed by Karadeniz

regulations under this article, the provisions regarding the Technical University Technology Transfer Application and

inventions of employees shall apply to the inventions made as a

Research Center and it was decided to consider the thesis result of scientific studies or research conducted in higher subjects of graduate and doctoral students as invention disclosure 24

forms without notification. With this decision, the technology Karadeniz Technical University continues its support in the

and/or information of the relevant invention was protected at an

field of Industrial Property with the 6769 IP Law published in early stage. The number of invention notifications received by

2017. Before 2017, the number of patents belonging to

Karadeniz Technical University since 2017 is shown in

academicians at the university was 7, while 262 industrial following figure 1.

property applications were realized under the university's



ownership as of 2024.

In 2020, there was a global COVID-19 pandemic, the effects

Number of Invention Notifications

of which continued in 2021, and a national stagnation in



200

industrial property applications in 2022-2021. However, even n

156

oti

during these periods, the know-how at the university was

n

sn

107

111

108

119

transformed into industrial property assets. Figure 2 shows an veIn

81

100

increase in industrial assets with the normalization process after f

64

o

ficatio

the pandemic.

er

tio

22

The 25 national patent applications until 2022 increased to

mb

N

u

0

31 national patent applications with the evaluation of the thesis

N

subjects of master's and doctoral students in postgraduate

education as invention disclosure forms without notification, Year

which was put into effect in 2023. In the first 8 months of 2024,



Figure 1 : Number of Invention Notifications Received at the number of national patent applications reached 45

Karadeniz Technical University

applications, and 12 applications are based on given information



from theses.



While international applications are examined, 18

The number of national patents, national utility model,

international patent applications were submitted as of 2024.

national design and international patent applications applied as In 2023, a new strategy was put into effect as a new strategy

Karadeniz Technical University since 2017 is given in Figure 2.

in which the thesis subjects of master's and doctoral students in



postgraduate education were evaluated as invention disclosure Number of National Patent Applications

forms without notification, and the knowledge accumulation at

Industrial Property Numbers

Number of International Patent

Applications

Karadeniz Technical University was protected at an early stage.

Number of National Utility Model

Applications

It is thought that the use of this practice in all universities will Number of National Design Applications

60

produce positive results and increase the number of national and

international patents.

40

The new strategy provides early awareness to young

researchers and supports patent applications that adopt industrial 20

needs and have high commercialization potential.

0

The strategy of evaluating theses as invention notifications

was introduced to international partners (8 European Countries)

as an example of good practice in the projects of strengthening



technology transfer with innovative approaches, in which KTU

Figure 2: Karadeniz Technical University Industrial

is a partner, within the scope of the ERASMUS+ and

Property Numbers

INTERREG NEXT Programs.



REFERENCES

Table 2 shows the comparative number of patent applications

[1]

Geven, Zeki. 2011, "Fikri Mülkiyet Hukukunda yenilik ve of Karadeniz Technical University compared to Trabzon

orijinallik." İnönü Üniversitesi Hukuk Fakültesi Dergisi 2.2, 327-401.

[2]

Dıjk, T., 1994, The Economic Theory of Patente: A Survey”, Merit province.

Research Memorandum, 2/94-017.



[3]

WEB, (Access Date: 12.08.2024), Telif Hakları Nelerdir?

https://www.tahanci.av.tr/telif-hakki/

Table 2: Number of patents in Trabzon province - Karadeniz

[4]

Başlar, Y., 2019, Fikir ve Sanat Eserleri Kanunu’nun Ek Madde 4

Technical University and the contribution of the university to the Hükmünün İhlali Suçları. Ankara Barosu Dergisi, 77(4), 37-74.

number of patents

[5]

Turan, H. S., 2012, Fikir ve Sanat Eserlerinin Cezai Himayesi, Seçkin Yayıncılık, Ankara, s. 119, Türkiye





2017

2018

2019

2020

2021

2022

2023

[6]

Gökovalı, U., & Bozkurt, K., 2006, Fikri Ve Sinaî Mülkiyet Hakki (Fsmh) Number of Trabz

Olarak Patentler: Dünya Ve Türkiye Açisindan Tarihsel Bir Bakiş. Muğla National

on

48

28

29

24

28

51

51

Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (17), 135-146.

Patent

(City)

[7]

Toker Köse, M., 2018, Fikri mülkiyet hakları çerçevesinde patentin iktisadi boyutu ve Türkiye örneği, Master's Thesis, Hitit Üniversitesi Applicatio

Sosyal Bilimler Enstitüsü, Türkiye

11

ns



14

7

9

12

23

41



KTU

[8]

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23%

50%

24,1

37,5

42,8

45%

80,3

[9]

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(Access

Date: 13.08.2024), Buluş Bildirim Formu,

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%

5%

9%



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6 CONCLUSION

25





Using Open-Access Resources and Platforms to Create a Technology Transfer Ecosystem *

Viatcheslav Britchkovski†

Informatiom Center/National Library of Belarus

v_britch@nlb.by



ABSTRACT

offices. There are several main approaches to technology

transfer.

Technology transfer is a complex process that requires up-to-date

Business assistance: companies providing services on specific and reliable information on various aspects of a technological issues related to technology can be considered as specialized solution. Approaches to improving the efficiency of technology

organizations working in the scientific and technical sectors. In

transfer systems through the use of open access resources and order to correctly navigate among such companies, many TTOs

platforms are considered.

have extensive databases.

Technology dissemination means the transfer of specific

KEYWORDS

knowledge from research institutes to a group of small and medium-sized enterprises with common technology needs.

open access resources, open access services, digital ecosysytem,

Technology search consists of analyzing the national and

technology transfer office

international market in order to acquire promising technologies

and commercial opportunities that can be used by companies in

a certain region.

1. INTRODUCTION

This task is often carried out independently of specific industry

needs.

Improving the national innovation system is a key factor in In addition to these direct approaches to technology transfer, increasing the country's competitiveness in the modern

TTOs are increasingly focusing on the use of various indirect environment, often defined as a "knowledge economy" and technology transfer mechanisms, such as technology exchange

focused on the commercialization of scientific results. Of

through networks of companies, technology and innovation

particular importance in this context are studies aimed at support centers, product development centers, outsourcing, etc.

improving technology transfer and organizing effective

This means that attention is paid not only to technology transfer

interaction between all participants.

from research institutes to industry, but also to stimulating Technology transfer is considered as one of the most important

technology exchange directly within industry.

instruments for national and regional economic growth.

Participation in network organizations allows TTOs:

Much attention in Belarus is paid to improving the functioning

of technology transfer offices (TTOs).

•

develop and maintain high standards for their services;

The activities of TTOs are aimed at commercializing the results

•

significantly increase opportunities for finding

of R&D, ensuring the acceleration of solutions for technical and partners for technology commercialization projects.

technological problems of enterprises, improving the quality of

•

implement innovation policy at the interregional and

their products, and mastering the production of new types of international levels.

products.

TTOs, participating in the work of technology transfer

The main activities of TTOs aimed at the implementation of a set

networks, can more effectively provide their clients with the

of measures related to transferring innovations from the sphere

following services:

of their development to the sphere of practical application. They

include:

•

search for partners for the joint implementation of

•

conducting market research to identify opportunities

technology commercialization projects for R&D, entry

for implementing innovations by universities,

into new markets, etc;

•

scientific and other organizations;



dissemination of technological information is a

•

performing work to ensure legal protection and

relevant service for scientific organizations that are

introduction of innovations into civil circulation;

interested in widely informing industry and companies

•

about their research capabilities and competencies;



providing engineering and consulting services.

•

The implementation of new technologies and research results promotion of technological projects using various

from the scientific and technical sectors in industry is a networking tools;

•

traditional task, and often the main activity of technology transfer a primary analysis of supply and demand in certain

subject areas of research.

The main role in the Belarusian technology transfer network infrastructure is played by the Republican Technology Transfer

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed Center (RCTT).

for profit or commercial advantage and that copies bear this notice and the full The organizational structure of the RCTT network includes

citation on the first page. Copyrights for third-party components of this work must members, clients, partners and a coordinating organization.

be honored. For all other uses, contact the owner/author(s).

Information Society 2024, 7–11 October 2024, Ljubljana, Slovenia Members of the network are research organizations, higher

© 2024 Copyright held by the owner/author(s).

education institutions, enterprises and organizations of all forms of ownership that have TTOs or divisions responsible for

26

technology transfer in their structure. Within the framework of Taking into account such limitations, in 2009 the World

the methodology adopted in the RCTT network, network

Intellectual Property Organization (WIPO) launched an

members help their clients prepare proposals for cooperation, international project to create a network of Technology and requests for the implementation of R&D. [1]. There are 3 options Innovation Support Centers (TISCs), the purpose of which is to

for disseminating them:

simplify access to technical knowledge and improve the

•

they are posted by network members on the RCTT

efficiency of using patent information.

Internet portal;

The National Intellectual Property Center (NIPC) is creating a

•

they are posted at the request of network members by

network of TISCs in the Republic of Belarus in accordance with

the coordinating organization in foreign technology

the Agreement between WIPO and NIPC dated October 10,

transfer networks;

2016. As part of its implementation, NIPC performs the

•

they are posted on the websites of foreign partners of

functions of a coordinating body.

the coordinating organization.

Currently, there are 29 TISCs operating in the Republic of Network members help their clients prepare information on the

Belarus.

products and services of the organization for posting them at a

The creation of the TISCs has improved information and

virtual exhibition on the Internet portal of the Russian Center for Technology Transfer. Network members also monitor external

scientific-methodological support for information and patent

and internal markets to find the target consumers for the activities, increasing the efficiency of using IP objects.

organizations. Clients of the network are suppliers and

High-quality scientific information is also one of the most consumers of technologies (research and design organizations, important factors facilitating technology transfer.

educational institutions, enterprises and organizations of all Underdeveloped information infrastructure and the lack of

forms of ownership).

objective data on advanced scientific knowledge and

The RCTT is a consortium for coordinating activities in the field

developments create serious barriers to the further development

of technology transfer, which includes

of science and its commercialization, significantly reducing the

•

head office in Minsk;

efficiency of TTOs. The so-called "serial publication crisis" [2]

•

5 branches in the regions of the Republic of Belarus

has a negative impact on the quality of information support for

and 30 branches at research organizations, higher

TTOs, caused by the fact that the traditional commercial

education institutions and enterprises of the Republic

economic model of scientific communication leads to a rapid of Belarus;

increase in subscription prices with relatively unchanged budgets

•

97 foreign organizations in 23 countries.

for organizations. The problem is that both TTOs specialists and

The main objectives of the activities of the RCTT branches at researchers working in various subject areas face significant manufacturing and industrial enterprises are:

difficulties in the process of searching, obtaining and using improving the quality and reducing the cost of manufactured information. In the context of the constant growth of scientific products;

output and the simultaneous increase in the cost of access to assisting in the expansion of sales markets.

information resources due to the fact that publishers seek to maximize their profits through the sale of subscriptions to OPEN

ACCESS

SERVICES

FOR

scientific journals, scientists and other consumers of scientific INFORMATION SUPPORT OF TTOs

information experience serious difficulties when it is necessary

to find a potentially useful scientific result and get acquainted with it [3]. The deficit of high-quality scientific information TTOs use various information system and resources to

resources deprives specialists of the opportunity to analyze and

effectively manage and transfer technologies. Some of them are:

objectively evaluate the quality of research and development

•

Patent and invention databases: these resources help

results.

track and manage intellectual property.

The important place in the activities of the technology transfer

•

Scientific publications databases: these resources

offices is occupied by legal problems and issues of protecting allow TTOs to stay abreast of the latest advances and

intellectual property, including problems of legislative and innovations in various fields.

judicial protection of copyright. The lack of relevant and up-to-

•

Collaboration and knowledge sharing platforms: such

date information in this area significantly reduces the

platforms help researchers and developers exchange

effectiveness of the commercialization of scientific research [4].

ideas, find partners, and collaborate on projects.

•

To overcome these challenges, we suggest to use open access Project management information systems: these

resources and platforms for facilitating information support of systems help coordinate project work.

•

business processes during transfer knowledge and technology.

Marketing and analytics tools: these tools are used to

analyze the market and identify needs and

Open Access (OA) as a movement has been steadily gaining

opportunities

for

the

commercialization

of

strength for roughly the last two decades. This is due to the technologies.

following factors:

To operate effectively TTOs need high-quality and timely

The number of publications in open access reaches 47% [5].

information.

Research funding programs and foundations require that research

Although patent information has become more accessible in

results must be published in the OA repositories or OA journals.

recent years, including through services provided via the Internet Many organizations support the requirements for the openness of

primary data and research results.

on a paid or free basis, the coverage and availability of patent The citation rate of OA scientific publications is higher than that data in some countries, including Belarus, remain limited.

of those distributed by subscription [6].

27

Open access resources are increasingly considered like an option AMiner integrates academic data from multiple sources by data

to replace expensive commercial databases necessary for the mining and social network analysis and mining technology to information services of TTOs [7].

catch paper indexes.

Using OA resources can significantly improve the efficiency of

AMiner cooperates with scholars and academic institutions to Technology Transfer Offices (TTOs). Below are some of the

share papers and scholar data and purchase copyright.

ways in which they can be used.

CORE provides access to the world's largest collection of open

1. Access to scientific publications. Open access provides free access scholarly papers by collecting and indexing research from

and unrestricted access to scientific articles and research. This repositories and journals. It is a non-profit service dedicated to allows TTOs to stay up-to-date with the latest advances and the open access mission and a signatory to the Principles for innovations in various fields of science and technology.

Open Scholarly Infrastructures (POSI) [8]. CORE serves a global

2. Analysis of patent information. Many patent databases also network

of

repositories

and

journals

by

improving

provide open access to information. This helps TTOs track new

discoverability and preventing misuse of their content; ensuring

patents, analyze trends, and find potential partners for licensing and commercializing technologies. For example, Espacenet

that metadata records are uniquely identified; supporting data provides free access to millions of patents worldwide

providers in applying best practices by providing tools for 3. Collaboration and knowledge sharing. OA platforms facilitate

metadata validation, content management, enrichment, and OA

collaboration between researchers and developers. This allows compliance; and facilitating machine access to open research.

TTOs to find partners for joint projects and share ideas.

CORE's mission is to index all open access research worldwide

Examples of such platforms include ResearchGate and

and make it accessible to all. In doing so, CORE:

Academia.edu.

4. Training and professional development. OA resources can also

•

enriches scientific data using modern text and data

be used for the training and professional development of TTOs.

mining technologies to make it easier to find;

Online courses and webinars available on platforms such as

•

enables others to develop new tools and use cases

Coursera and edX help TTOs staff stay up-to-date with new based on the CORE platform;

techniques and technologies.

•

supports the network of OA repositories and journals

5. Market Research. Using open data and analytics tools helps with innovative technical solutions;

TTOs conduct market research. This allows for a better

•

promotes the creation of a scalable and cost-effective

understanding

of

the

needs

and

opportunities

for

way to provide open scientific information.

commercializing technologies. Examples of such tools include CORE aggregates research papers from data providers around

Google Scholar and Microsoft Academia.

the world, including institutional and subject repositories and There are many integrated platforms and services for facilitating

journal publishers. This process, also called data harvesting, OA resources usage.

enables CORE to offer search, text mining, and analysis

OpenAIRE (the Open Access Infrastructure for Research in

capabilities not only on metadata but also on the full text of Europe) enables the search, discovery and monitoring of the publications and datasets from 100,000+ research projects.

research articles, making CORE a unique service in the research

OpenAIRE actively supports the Open Science initiative. On the

community.

one hand, OpenAIRE is the network of dedicated Open Science

BASE is one of the largest search engines in the world,

experts promoting and providing training for Open Science.

particularly for academic web resources. BASE provides over On the other hand, OpenAIRE is a technical infrastructure

300 million documents from over 10,000 content providers. Full

harvesting research output from connected data providers.

texts of about 60% of indexed documents are available free of OpenAIRE aims to establish an open and sustainable scholarly

charge [9]. BASE indexes the metadata of all types of

communication infrastructure responsible for the overall

academically significant resources (journals, institutional

management, analysis, manipulation, provision, monitoring and

repositories, digital collections, etc.) that provide an OAI cross-linking of all research outcomes.

interface and use OAI-PMH to provide their content. The index

This combination of knowledge and a pan-European Research

Information platform enables OpenAIRE to provide services for

is constantly being expanded by integrating new sources/content

researchers, research support organizations, funders, content

providers. Database managers can integrate the BASE index into

providers and TTOs such as:

their local infrastructure (e.g., metasearch engines, library catalogs).

•

Integrate scientific information.

International research collaborations can bring TTOs new

•

Monitor and report on research outcomes for funders

opportunities for collaborative research, increase the impact of and partners.

•

their research, and boost the commercialization of scientific Train and support on all subjects related to OA.

•

results. For instance, knowing which institutions globally work



Discovery of OA output per project, funder, and data

on similar research can help identify new partnership

provider.

AMiner is a new generation of scientific and technological opportunities.

Identifying

existing

connections

among

intelligence analysis and mining platform with completely

researchers between those institutions can help drive

independent intellectual property rights. It was established by a

development opportunities. These data have come through costly

team led by Professor Tang Jie from the Department of Computer

subscriptions to restricted databases. OpenAlex now provides the

Science and Technology of Tsinghua University.

data required for international intelligence freely to all users AMiner's scientific research data includes 331 million papers, across the globe [10].

135 million scholars, 1.122 billion paper citation relationships and 8.79 million knowledge entities (this data is in dynamic change).

28

CONCLUSION

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the digital ecosystem of technology transfer, which includes

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Virginia Tech Commission on Research, University Libraries, Virginia Tech. – 2009.

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systems).

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Science and Technology of the Republic of Belarus for their The citation advantage of linking publications to research data // PLoS

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29





Fostering Open Innovation and Technology Transfer:

Insights from the Euro-Mediterranean Innovation Camp

(EMIC)

Prof. Dr. Abdelhamid El-Zoheiry

Karen Gladović,

FirstName Surname

President

Lecturer of Law

Department Name

Forum for Euro-Mediterranean

Euro-Mediterranean University

Institution/University Name

Innovation in Action, France

(EMUNI)

City State Country

zoheiry@gmail.com

Piran, Slovenia

email@email.com



karen.gladovic@emuni.si



ABSTRACT / POVZETEK

transfer within the Euro-Mediterranean region, using the Euro-

Mediterranean Innovation Camp (EMIC) as a case study. The

The global marketplace is rapidly evolving, demanding

paper explores how EMIC serves as a successful model for

innovative approaches to technology transfer that can bridge the

bridging the gap between academic research and commercial

gap between research and commercial application. The Euro-

applications in a region that presents both challenges and

Mediterranean region, with its diverse socio-economic landscape,

opportunities due to its socio-economic diversity. Overall, the

presents both challenges and opportunities for such endeavors.

paper contributes to the literature on technology transfer by

This paper presents the Euro-Mediterranean Innovation Camp

providing a detailed exploration of how structured innovation

(EMIC) as a successful model for implementing open innovation

programs like EMIC can drive economic growth, address

and technology transfer, particularly within the strategic

pressing global challenges, and create marketable solutions,

framework of the Jožef Stefan Institute (JSI) and its partner institutions. The analysis not only draws on the outcomes of the

particularly in the complex and diverse Euro-Mediterranean

recent EMIC initiatives but also aligns these practical insights context.

with the theoretical foundations of open innovation as discussed



in the doctoral disposition on technology transfer.

The EMIC initiative has attracted applicants from over 17

countries, with a significant portion of the applications coming

KEYWORDS / KLJUČNE BESEDE

from Egypt and Jordan. The charts below illustrate the diversity

and distribution of applicants by country of residence across the

Open Innovation, Technology Transfer, Euro-Mediterranean

Region, EMIC, Jožef Stefan Institute

two seasons of the program.





(1)

1 INTRODUCTION

The global marketplace is rapidly evolving, demanding

innovative approaches to technology transfer that can bridge the

gap between research and commercial application. The Euro-

Mediterranean region, with its diverse socio-economic

landscape, presents both challenges and opportunities for such

endeavors. This paper presents the Euro-Mediterranean

Innovation Camp (EMIC) as a successful model for

implementing open innovation and technology transfer,

particularly within the strategic framework of the Jožef Stefan

Institute (JSI) and its partner institutions. The analysis not only draws on the outcomes of the recent EMIC initiatives but also

aligns these practical insights with the theoretical foundations

of open innovation, as discussed in the doctoral disposition on

technology transfer. The main purpose of the paper is to

examine the application of open innovation and technology





Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed Figure 1: Number of applicants by country of residence –

for profit or commercial advantage and that copies bear this notice and the full Season 1

citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

Information Society 2024, 7–11 October 2024, Ljubljana, Slovenia

© 2024 Copyright held by the owner/author(s).

30



The Euro-Mediterranean Innovation

Camp (EMIC): A Model of Open

Innovation

The Euro-Mediterranean Innovation Camp (EMIC) is a flagship

initiative that embodies the principles of open innovation within

the Euro-Mediterranean region. Launched by the Euro-

Mediterranean University (EMUNI) in collaboration with the JSI

and the EuroMed University of Fes (UEMF), EMIC provides a

platform for young innovators to develop and showcase their ideas in response to pressing global challenges. The camp

focuses on three critical areas: health, renewable energy, and climate change—fields that are not only relevant to the region but also globally significant.



The EMIC initiative is structured to promote iterative learning and development. Participants, who are selected through a



rigorous process, receive mentorship and technical support from

Figure 2: Number of applicants by country of residence –

experts in their respective fields. This support is crucial in Season 2

helping them refine their ideas and develop viable prototypes.

The average age of participants was 24 years, with the youngest

being 18 and the oldest 35, showcasing the youthful energy Theoretical

Foundations:

Open

driving innovation in the Euro-Mediterranean region.

Innovation and Technology Transfer

Selection Process of EMIC

Open innovation, a concept popularized by Henry Chesbrough,

has significantly reshaped our understanding of how innovation

The Euro-Mediterranean Innovation Camp (EMIC) follows a

occurs in the modern business environment. Unlike traditional rigorous and multi-stage selection process to identify and support closed innovation models where companies rely solely on

the most promising young innovators from across the Euro-

internal resources for R&D, open innovation promotes the use of Mediterranean region. Here’s an overview of the selection

both internal and external knowledge sources. This approach process:

accelerates the innovation process and expands the potential market for new technologies (Chesbrough, 2005a). In the context

1.

Application Submission:

of technology transfer, open innovation facilitates the

o Eligibility: Applicants must be between 18

commercialization of intellectual property (IP) through various and 35 years old, reside in one of the Euro-channels, including licensing, joint ventures, and spin-offs, thus Mediterranean countries, and possess at least

driving economic growth and enhancing competitiveness

a high school diploma. The innovation they

(Chesbrough, 2003b).

propose must address one of the three

thematic areas: Health, Renewable Energy,

The Euro-Mediterranean region is a fertile ground for applying

or Environment (including Climate Change)

open innovation principles. However, the integration of public and must be capable of being converted into

research outputs with industry needs has been a persistent a prototype within three months.

challenge. Slovenia, for instance, excels in scientific output, o Application Process: Interested candidates

ranking high in terms of research publications. Yet, as the submit their applications through an online

OECD’s 2012 report highlights, the country struggles with the

form available on the EMUNI website. The

commercialization of research findings, particularly in

application requires a detailed description of

converting scientific discoveries into marketable products and the

innovative

idea

or

invention,

services. This gap underscores the critical role of initiatives like highlighting its novelty, feasibility, and

EMIC, which aim to bridge the divide between academic

potential for commercialization.

research and industrial application through structured innovation

2.

Initial Screening:

programs.

o A panel of experts reviews all submitted

applications. The review process evaluates

The thematic focus of the EMIC projects aligns well with global

the novelty of the idea, its practical

challenges, as evidenced by the distribution of project types: 45%

applicability,

and

the

feasibility

of

focused on health, 35% on renewable energy, and 20% on

implementation

within

the

specified

environmental issues, reflecting the alignment of participant timeframe.

interests with critical global needs.

o Shortlisting: Based on the initial screening,

a subset of applicants is shortlisted to

advance to the next phase. For instance, in

Season 2, out of 124 applications,

approximately

40

candidates

were

31

shortlisted for the online pitching phase

The Euro-Mediterranean Innovation Camp (EMIC) Season 2

(EMUNI).

brought together some of the brightest minds across the region to

3.

Online Pitching:

develop innovative solutions addressing critical challenges. This

o Pitch Preparation: Shortlisted candidates

section highlights the top three projects that stood out for their prepare a pitch presentation, which they

creativity, technical expertise, and potential for real-world deliver via an online platform. During this

impact.

phase, they present their ideas to a jury

comprising experts from relevant fields.

1.

Muhammad Mounir (Egypt) – "SugarHeal"

o Jury Evaluation: The jury evaluates the

o Project Overview: Muhammad Mounir, a

pitches based on several criteria, including

Molecular Biotechnology student from

innovation, feasibility, potential impact, and

Galala University, developed "SugarHeal,"

the candidate’s ability to articulate and

an innovative wound dressing material

defend their idea. The most innovative and

designed to accelerate the healing process of

viable projects are selected to move forward.

chronic and acute wounds. During his time

4.

Innovation Bootcamp:

at the Jožef Stefan Institute (JSI),

o Workshops and Mentorship: The selected

Muhammad explored two main fabrication

finalists, known as the "Innovation Squad,"

techniques:

are invited to participate in a 10-week

▪ Electrospinning: He created a

bootcamp held at facilities like the Jožef

cellulose-based

solution

with

Stefan Institute in Slovenia or the EuroMed

antibacterial

properties

for

University of Fes in Morocco. During this

electrospinning, resulting in a

period, they receive technical assistance,

biodegradable wound dressing

mentorship from subject matter experts, and

that promotes faster healing.

support in refining their prototypes.

▪

o



3D Bioprinting: Muhammad also



Elimination

Stages:

Throughout

the

developed a cellulose-based ink

bootcamp, participants go through multiple

enriched with natural antibacterial

elimination stages. These stages are

extracts, which was used in 3D

designed to progressively challenge the

bioprinting

to

produce

innovators, focusing on proof of concept,

customizable wound patches.

engineering,

prototyping/testing,

and

o Current

Stage:

Muhammad

has

customer validation. The best performers in

successfully developed prototypes of the

each stage advance to the next round

wound dressing through 3D bioprinting,

(EMUNI).

which have shown promising results in terms

5.

The Finale:

o

of mechanical stability and biological



Final

Presentation:

The

competition

response. His next steps include further

culminates in a live finale event where the

optimization and exploring commercial

remaining candidates present their fully

applications (EMUNI).

developed prototypes. This event is attended

2.

Rahma

M.

Tolba

(Egypt)

– "Interactive

by a live audience, including mentors,

Augmented Reality for Lisp Correction"

representatives from partner institutions, and

o Project Overview: Rahma Tolba, a PhD

other stakeholders.

o

researcher from Ain Shams University,



Scoring: Final scores are determined by

developed an interactive Augmented Reality

both the jury and audience voting, with each

(AR) application designed to assist in speech

accounting for 50% of the final score. The

therapy for individuals with a lisp. Her

winners are announced based on the

project focuses on improving phonetic

combined results of these evaluations

learning through the use of 3D animated

(EMUNI).

models that demonstrate correct tongue

movements. The app guides users through

This selection process is designed to ensure that the most pronunciation exercises, providing real-time

innovative and feasible ideas are given the support they need to

feedback through an AI-based Automatic

develop into successful market-ready products. It also

Speech Recognition (ASR) system.

emphasizes the importance of mentorship and iterative

o Current Stage: Rahma has developed a

development, helping young innovators turn their ideas into fully functional prototype for Android

impactful solutions.

devices, which has been tested on a small

group of individuals. The next steps involve

Case Studies: Innovations from EMIC

gathering user feedback from speech

therapists and phoniatricians to refine the

Season 2

design and functionality (EMUNI).

The impact of EMIC is best illustrated through the success stories 3.

Med Aziz Mhalla (Tunisia) – "Drowsy Driver

of its participants. The most recent season of EMIC, concluded

Detection System"

in June 2024, showcased a range of groundbreaking innovations

o Project Overview: Med Aziz Mhalla, an

that have the potential to address significant challenges in health electronics engineering student from the

and sustainability.

National Engineering School of Sousse,

32

created the "Drowsy Driver Detection

initial stages of development, these institutions can help ensure

System" (DDDS). This system leverages

that the innovations produced at EMIC reach their full potential.

machine learning, computer vision, and

embedded hardware to monitor drivers in

real-time, detecting signs of drowsiness,

Opportunities for Enhancing Open

distraction, and sleep onset. The system uses

Innovation

a Convolutional Neural Network (CNN)

model to classify eye states and detect blinks

and yawns, which are key indicators of

Despite these challenges, the EMIC model also presents

drowsiness.

significant opportunities for enhancing open innovation in the o Current Stage: Med Aziz has successfully

Euro-Mediterranean region. One of the key opportunities lies in

developed a proof of concept and prototype

the potential for cross-border collaboration. By bringing together that

has

been

tested

in

controlled

participants from different countries and backgrounds, EMIC

environments and on a laptop. He is

fosters a rich exchange of ideas and approaches. This diversity is currently optimizing the system for real-time

a strength as it allows for the development of solutions that are

performance using NVIDIA Jetson Nano

informed by a wide range of perspectives and experiences.

and preparing for on-road testing (Med Aziz

- Drowsy Driver…).

The full cycle of open innovation and technology transfer has yet

to be fully achieved, as both processes require more than just These projects not only exemplify the innovative spirit fostered

innovative ideas and technological breakthroughs. For these

by EMIC but also demonstrate the potential for significant cycles to reach their full potential, business entities must engage contributions to healthcare, road safety, and speech therapy.

early and consistently, starting from the initial stages of research Each of these top three finalists utilized the mentorship and and development. Their investment and involvement are crucial

resources provided during the EMIC bootcamp to bring their in ensuring that ideas and technologies not only progress beyond

ideas closer to real-world application.

the conceptual phase but also successfully transition from labs to the market. Without the proactive participation of businesses, the promise of open innovation and effective technology transfer The diversity of innovations emerging from EMIC highlights the

may remain unfulfilled, with many promising projects never

program’s success in fostering creativity across different fields.

realizing their full impact.

These projects are not just theoretical exercises; they represent tangible solutions that can have a real-world impact, addressing

The collaborative model of EMIC, supported by the JSI’s

some of the most pressing challenges in the Euro-Mediterranean

region and beyond.

extensive research infrastructure, offers valuable insights into how open innovation can be effectively implemented in a

complex and diverse region. The partnerships between academic

Challenges in Implementing Open

institutions, industry players, and government bodies are crucial

Innovation

in providing the necessary resources for young innovators to translate their ideas into impactful technologies. These

partnerships also help to ensure that the innovations produced at

Despite its successes, the implementation of open innovation EMIC are aligned with market needs, increasing their chances of

within the EMIC framework has not been without challenges.

success.

One of the primary challenges is the alignment of the diverse objectives of the program’s international partners. The Euro-Another opportunity for enhancing open innovation in the Euro-

Mediterranean region encompasses a wide range of economic,

Mediterranean region is through the development of stronger social, and political contexts, each with its unique set of networks and ecosystems. By fostering closer ties between

challenges. Coordinating efforts across such a diverse region research institutions, industry, and government, it is possible to requires careful planning and robust frameworks for

create a more supportive environment for innovation. This

collaboration.

includes not only providing funding and resources but also creating opportunities for mentorship, networking, and

Intellectual property (IP) management is another critical

collaboration. Such ecosystems can help to sustain the

challenge in open innovation environments. While open

momentum generated by initiatives like EMIC, ensuring that the

innovation encourages the sharing of ideas and resources, it also

innovations produced continue to evolve and have a lasting raises questions about how IP is managed and protected. In the

impact.

context of EMIC, ensuring that participants retain control over their innovations while still benefiting from the collaborative environment is crucial. This requires clear guidelines and

Conclusion

agreements on IP management, which can be complex to

negotiate across different legal and regulatory frameworks.

The Euro-Mediterranean Innovation Camp (EMIC) serves as a

compelling example of how open innovation can be successfully

Another challenge is the scalability of the solutions developed implemented within a structured technology transfer framework.

through EMIC. While the innovations produced during the camp

By leveraging the strengths of regional partnerships and focusing

are often groundbreaking, bringing these solutions to market on

on critical areas such as renewable energy, health, and climate a larger scale requires resources that may not be immediately change, EMIC has successfully fostered a culture of innovation

available to the participants. This is where the support of across the Euro-Mediterranean region. The initiative has not only

institutions like JSI and the involvement of industry partners provided a platform for young innovators to develop their ideas

become critical. By providing continued support beyond the

but has also facilitated the transfer of these ideas from research 33

to market, demonstrating the potential of open innovation to initiatives like EMIC can help to unlock the full potential of the drive economic growth and address global challenges.

region’s young innovators, driving economic growth and

addressing some of the most pressing challenges of our time. As

Moving forward, it will be crucial to address the challenges of IP

we look to the future, it is clear that open innovation will continue management and resource allocation to sustain the momentum

to play a critical role in shaping the global innovation landscape, generated by these initiatives. The ongoing collaboration

and initiatives like EMIC will be at the forefront of this exciting between academic institutions like JSI, industry partners, and journey.

government bodies will be key to enhancing the commercial

viability of the innovations emerging from EMIC. As Slovenia

REFERENCES

and the broader Euro-Mediterranean region continue to refine

[1]

Chesbrough, H. W. (2003a). Open Innovation: The New Imperative for their approaches to technology transfer, the lessons learned from

Creating and Profiting from Technology. Harvard Business School Press.

EMIC will serve as a valuable guide for future innovation

[2]

Chesbrough, H. W. (2003b). The era of open innovation. MIT Sloan Management Review, 44(3), 35-41.

policies and practices.

[3]

Chesbrough, H. W. (2005a). Open Business Models: How to Thrive in the New Innovation Landscape. Harvard Business School Press.

[4]

EMIC Status Report 2022-23.

The success of EMIC highlights the importance of fostering

[5]

EMIC Status Report 2023-24.

innovation among young people across the Mediterranean

[6]

OECD (2012). Science, Technology and Industry Outlook. OECD

region. By providing the necessary support and resources,

Publishing.



34





Research Organisation-Industry Cooperation and State Aid Rules in Slovenia and Europe

Tomaž Lutman

Urška Florjančič

Urška Fric

Office for Substantive Project

Office for Substantive Project

Knowledge and Technology

Support, Technology Transfer and

Support, Technology Transfer and

Transfer Office

Innovation

Innovation

Faculty of Information Studies in

Jožef Stefan Institute

Jožef Stefan Institute

Novo mesto

Ljubljana, Slovenia

Ljubljana, Slovenia

Novo mesto, Slovenia

tomaz.lutman@ijs.si

urska.florjancic@ijs.si

urska.fric@fis.unm.si



ABSTRACT

good practices have been collected from different types of groups, i.e. researchers, industry, technology transfer managers,

This study provides an international comparative view on state

contract research managers and accounting officers. We have aid regulation in infrastructure use and intellectual property focused on Slovenian research organisations, in addition to rights transfer in cooperative research and development projects

which we included two European research organisations in order

within the European Research and Innovation Ecosystem.

to make international comparison. In spring 2024 we concluded

Technology transfer officers or similar profiles at research 8 in-person or online semi-structured interviews with R&D

organisations were interviewed. Additionally, a desk research managers from 7 research organisations.

was performed. Annual reports were studied in order to identify

the differentiation of economic and non-economic activity as well as good practices. Desk research included also rulebooks 2 DESK RESEARCH RESULTS

and related Slovenian & EU legislature in the field of contract and collaborative research.

2.1 Share of economic activity, rulebooks and

pricelists

KEYWORDS

Our study comprised 13 Slovenian, 1 Czech and 1 Italian public

research organisation – industry cooperation, research services,

research organisation (Table 1). As foreseen in articles 16 (ff) intellectual property rights transfer, state aid rules, Slovenian

and 19 of EC Communication (2022/C 414/01), the research

and European research organisations, research and innovation

organisation has to account for the costs and the revenues of the

ecosystem

economic activities separately. Different practices on how to do

INTRODUCTION

this exist among European research organisations. It was

The European Commission has set specific rules in the field of

observed that most research organisations generate up to 20% of

research, development, and innovation (R&D&I) to prevent their revenues from economic activities. This correlates well market distortion. These rules are described in the European with the maximum 20% capacity limit as foreseen in 2022/C

Framework for State aid for R&D&I (2022/C 414/01 [1]) and 414/01 (it should however be noted that % of income may differ

relate to the Article 107 (1) Treaty on the Functioning of the from % of capacity, which is the actual threshold value).

European Union.

Some organisations in the study have around 50% of their

We believe that knowledge and implementation of state aid rules

activities classified as economic in nature. They most likely regarding research services (economic activity), collaboration surpass 20% of economic activities’ capacity limit. For this projects (non-economic activity) and intellectual property rights

reason, they as whole cannot be considered as research

(IPR) are insufficient and could be improved, which was

organisations according to 2022/C 414/01. Only departments,

identified also by other authors [2], [3].

laboratories or similar subunits of such organisations which do

not surpass 20% of economic activities’ capacity limit can be considered ‘research organisations’.

1 METHODOLOGY

In Slovenia, the new Law on Scientific Research and Innovation

In order to understand how state aid rules in academia-industry

Activities (ZZrID) entered into force on 1 January 2022 [15]. In cooperation work in practice, we have performed a detailed the same period, a Rulebook on procedures for implementing the

analysis with an international comparative view. Experience and

budget of the Republic of Slovenia was updated. Article 119(b)

requires each public research organisation to have an internal rulebook and pricelist regarding sale of products and services, Permission to make digital or hard copies of part or all of this work for personal or i.e. economic activity [16]. Up to date, several Slovenian classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full research organisations have prepared their rulebooks and

citation on the first page. Copyrights for third-party components of this work must pricelists, while many have not yet (at least they are not publicly be honored. For all other uses, contact the owner/author(s).

Information Society 2024, 7–11 October 2024, Ljubljana, Slovenia available).

© 2024 Copyright held by the owner/author(s).



35

The sizes of analysed organisations vary a lot, i.e. from 58 to 9560 employees. This strongly affects the organisational



structure and extent of experience in a specific organisation.





Table 1: Selected Slovenian and European research organisations and their info on economic activities.

Organisation

Country Share of

Rulebook for sale of

Pricelist of products Number of

Source

economic activity products and services

and services

employees in

in 2023

2023

Slovenian National Building and Civil

SI

53.6%

16.08.2022

11.01.2022

254

[4], [5]

Engineering Institute

University of Ljubljana, Faculty of

unpublished / under

unpublished / under

SI

48.2%

829

[4]

Medicine

preparation

preparation

unpublished / under

Agricultural Institute of Slovenia

SI

23.7%

28.11.2023

258

[4], [6]

preparation

Geological Survey of Slovenia

SI

15.0%

11.08.2022

23.02.2023

124

[4], [7]

unpublished / under

unpublished / under

Institute of Metals and Technology

SI

14.9%

58

[4]

preparation

preparation

University of Ljubljana, Faculty of

unpublished / under

unpublished / under

SI

12.0%

362

[4]

Electrical Engineering

preparation

preparation

Jožef Stefan Institute

unpublished, to be



SI

10.2%

under preparation

1206

[4]

updated

University of Ljubljana, Faculty of

unpublished / under

unpublished / under

SI

10.0%

433

[4]

Mechanical Engineering

preparation

preparation

National Institute of Biology

SI

8.7%

3.11.2023

9.02.2023

194

[4], [8]

different guidelines,

not identified,

Czech Academy of Sciences

CZ

7.4%

9560

[9], [10]

decentralised

decentralised

University of Ljubljana, Faculty of

unpublished / under

SI

6.2%

unpublished

199

[4]

Pharmacy

preparation

National Institute of Chemistry

SI

5.0%

24.08.2022

24.08.2022

437

[4], [11]

unpublished / under

6.11.2023 (UM-FVV),

University of Maribor

SI

4.5%

2121

[4], [12]

preparation

decentralised

not identified,

8457 (year

Consiglio Nazionale delle Ricerche

IT

0.47%

not identified

[13], [14]

decentralised

2022)

Faculty of Information Studies in Novo SI

0.03%

under preparation

under preparation

82

[4]

mesto

2.2 Good and bad examples of transparent

outside Slovenian Research and Innovation Agency – ARIS; or

bookkeeping and economic activity

everything related to for-profit organisations).

management



Several Slovenian institutes, such as National Institute of The transparency of studied research organisations is good.

Biology, Institute of Metals and Technology, Slovenian National

Yearly reports support this observation. However, due to

Building and Civil Engineering Institute, National Institute of differentiation in the reports’ structure, the comparison is Chemistry, and Agricultural Institute of Slovenia present their sometimes difficult. An additional challenge is the lack of contract and collaborative research activities well. Some

standardisation in terminology.

unclarity persists, which is also highlighted below in the translated sections of the annual reports. We assume that this is

One of the important messages of EC Communication 2022/C

caused due to the use of vague terminology, as explained above,

414/01 is the requirement to differentiate economic (such as and the lack of differentiation between economic and non-research service) and non-economic activities (such as

economic activities.

collaborative research and knowledge transfer activities). It should be noted that in the Slovenian legislature and

The Consiglio Nazionale delle Ricerche defines its income and

consequently other documents, terminology ‘market activity’ is

outcome well, but unlike other annual reports, its annual report

used, which is not well defined. Sometimes it is used as is not supplemented with qualitative description. The annual

‘economic activity’ and sometimes as activity on the ‘market’,

report of the Czech Academy of Sciences (CAS) is very

with again different interpretations (‘market’ as everything informative. Subunits (i.e, institutes of CAS) have their own 36





annual reports, which present their technology transfer activities as a market activity in the annual report 2023. However, it is not well, while contract and collaborative research are inadequately

clear from the annual report that this is a non-economic activity.

described. Additionally, the financial part contains non-machine



readable text, which cannot be easily translated.

In Table 2, we can see a very good delimitation between contract research (‘laboratory services’) and collaborative research

Examples

(‘research projects with industry’). However, these two

At the Jožef Stefan Institute, Horizon 2020 and Horizon Europe

categories are later wrongly joined into one category, ‘income projects were classified as market projects, which were changed

from goods and services on the market’ (Table 3). We believe in 2022. From the total number of market activities' income, it

this is not an isolated case among research organisations.

was thus unclear which activities were economic and which non-

economic.

Table 2. Income from market activity of the Institute of



Metals and Technology (IMT). Annual report of IMT for

At the National Institute of Chemistry, royalties and other 2023, p. 99 [1].

revenues from patents are classified as a group of market revenues instead of a group of non-economic activities. In the case that market revenues are considered economic activities, this classification is false.



At the National Institute of Biology as well as some other Slovenian research organisations, collaboration projects with industry such as ARIS applied projects (TRL1-4) are classified



Table 3. Statement of income and expenses of the Institute of Metals and Technology (IMT). Annual report of IMT for 2023, p.

80 [1].



allowed to be performed, and accountants that believe there should be no margin included in prices of public research 3 QUALITATIVE ANALYSIS

organisations’ services.



Awareness and knowledge about state aid legislation varied

3.1 Contract research

among the interviewees. Most of them are well acquainted with

Different approaches to establish a pricelist of services and goods EC Communication 2022/C 414/01, especially those whose main

exist. They can be structured using either a cost based approach

profession is technology transfer or accounting. In accounting, or market based approach. In a market based approach,

managers get familiar with state aid rules when there are organisations observe the prices of other service providers, while investments in bigger infrastructure and financer monitors the in a cost based approach, the costs are summed up and a margin

economic/non-economic activities of the unit using the

is added.

infrastructure.





In a cost based approach, direct costs are sometimes joined in During the semi-structured interviews, the organisational

cost blocks composed of work costs, depreciation of the cost of

structure of academia – industry cooperation management was the infrastructure, costs for maintenance and running of the discussed. Intellectual property management (patenting,

infrastructure (electricity, water, heating, ventilation ...) and licensing etc.) is often centralized, even at large research materials. Such cost blocks are then multiplied based on the organisations such as Consiglio Nazionale delle Ricerche,

number of samples or complexity of the task. Some organisations

University of Ljubljana and University of Maribor. On the

add direct costs in % of work, while others in % of all direct costs.

contrary, contract research is decentralised and managed in Both options can be found in public funded calls.

smaller units. Comprehensive and standardised management,



established rulebooks and pricelists often lack at the institutions Prices are often established and then regulated by the inflation that have a very low percentage of contract research. The rate or other changes in cost structure. Sometimes this does not

management is often left to departments which leads to different

take place, especially when the activities are less important for

approaches in price setting etc. Interestingly, there are still some the department or institute.

researchers that are surprised to hear that economic activity is 37

3.2 Intellectual property in collaboration

from the Slovenian Ministry of Higher Education, Science and

projects and start-up companies

Innovation, which will consider this recommendation.

Management of intellectual property rights (IPR) in

ACKNOWLEDGMENTS

collaboration projects was discussed with technology transfer This project has received funding from the European Union’s managers. In most cases it is advised to discuss and agree to IPR

in advance. Sometimes even the IPR’ price is evaluated in Horizon 2020 research and innovation programme under grant

advance. Internal policy of one interviewed research organisation

agreement No. 101004462, project ATTRACT, ExSACT. We

regarding the 2022/C 414/01 article 29(c) is that a company can

would also like to thank all interviewees for taking time to share be co-owner of invention or other IPR only when they provide

their valuable experiences.

intellectual contribution, not financial or other in-kind

REFERENCES

contribution such as equipment usage. Another research institute



has interpreted this article in a way that a financial contribution

[1]

Communication from the Commission. (2022). Framework for State aid for research and development and innovation (2022/C 414/01).

of the company to the project, for example 25% in cash, can

https://eur-lex.europa.eu/legal-

result in an automated 25% co-ownership of IPR, generated in

content/EN/TXT/?uri=CELEX%3A52022XC1028%2803%29.

[2]

Belusky M. (2022). Subsidizing Knowledge Transfer with Public Funds.

the project. It is important to note that this institute has a policy 15th

International

Technology

Transfer

Conference.

that in case of IPR exploitation, the co-owner has to (financially)

http://library.ijs.si/Stacks/Proceedings/InformationSociety/2022/IS2022_

compensate the other co-owner(s).

Volume-E%20-%20ITTC.pdf.

[3]

Schwendinger, G. (2013). State Aid and Intellectual Property in Contract Research and R&D&I Collaboration. European State Aid Law Quarterly.

The most common procedure to conclude a licence or sale

Vol. 12, no. 4, p. 685–698. https://doi.org/10.21552/ESTAL/2013/4/385.

[4]

Agency of the Republic of Slovenia for Public Legal Records and Related agreement is thus to use arm’s length negotiations – article 30(c).

Services. Slovenian Business Register (2024). https://www.ajpes.si/prs/.

The licence agreement commonly involves lump sum and

[5]

Zavod za gradbeništvo Slovenije. (2022). Pravilnik ZAG o prodaji blaga in storitev na trgu. Cenik storitev ZAG, november 2023.

royalties. One research organisation mentioned that they

https://www.zag.si/o-nas/katalog-informacij-javnega-znacaja/.

negotiate with their spin-out companies in the same manner as

[6]

Kmetijski

inštitut

Slovenije.

(2024)

Cenik

storitev

KIS.

with other companies, which is fair. However, the specific

https://www.kis.si/Storitve/.

[7]

Geološki zavod Slovenije. (2023). Pravilnik GeoZS o prodaji blaga in characteristics of start-up companies should be taken into

storitev na trgu. Cenik GeoZS za opravljanje prodaje blaga in storitev na consideration.

trgu. https://www.geo-zs.si/?option=com_content&view=article&id=286.

[8]

Nacionalni inštitut za biologijo. Storitve in produkti. (2023). Ceniki NIB.



Pravilnik

o

prodaji

blaga

in

storitev

na

trgu.

With the implementation of the new Law on Scientific Research

https://www.nib.si/images/Prodaja-blaga-storitev_2023.pdf.

and Innovation Activities, research organisations in Slovenia are

[9]

Czech Ministry of Education and Culture. (2024). Research Organisations.

https://www.msmt.cz/vyzkum-a-vyvoj-2/vyzkumne-

now permitted to establish spin-off companies, which they enter

organizace.

into ownership with equity. To our knowledge, no such

[10]

Czech

Academy

of

Sciences.

(2023).

Annual

Report.

https://www.avcr.cz/cs/o-nas/vyrocni-zprava/.

companies have yet been established in Slovenia. In the last 2

[11]

Kemijski inštitut. (2022). Cenik in pravilnik o tržni dejavnosti.

years, CAS has established 5 such companies encountering many

https://www.ki.si/za-gospodarstvo/cenik-in-pravilnik-o-trzni-dejavnosti/.

[12]

Univerza v Mariboru. Fakulteta za varnostne vede. (2024). Dokumentno difficulties throughout the process. One of the main concerns is

središče. Cenik FVV UM za prodajo blaga in storitev na trgu.

the accuracy and changeability of IPR price.

https://www.fvv.um.si/vstopna-stran/o-fakulteti/dokumentno-sredisce/.

[13]

Consiglio Nazionale delle Ricerche. (2024) Documenti di bilancio.

https://www.cnr.it/it/documenti-bilancio.

[14]

Consiglio Nazionale delle Ricerche. https://www.cnr.it/.

4 CONCLUSIONS

[15]

Pravno-informacijski system Republike Slovenije. (2022) Slovenian Law on

Scientific

Research

and

Innovation

Activities.

Differentiation between contract research and collaborative

https://pisrs.si/pregledPredpisa?id=ZAKO7733.

research in Slovenian research organisations is not well known

[16]

Pravno-informacijski system Republike Slovenije. (2023). Rulebook on procedures for implementing the budget of the Republic of Slovenia.

and could be improved. There are many projects between

https://pisrs.si/pregledPredpisa?id=PRAV7654.

research organisations and companies that fall somewhere

[17]

Kaiser, M. Neu, F. Teernstra. (2021) State Aid on R&D&I – The Right between contract research and collaborative research. For

Way. EARTO Report. https://www.earto.eu/wp-content/uploads/EARTO-

Report-on-State-Aid-on-RDI-The-Right-Way-Final.pdf.

example, different methodologies in literature were tested ([17],

[18]

Kebapci, H., Von Wendland, B. & Kaymaktchiyski, S. (2020). State Aid

[18]), which produced two different results for the same project.

Rules in Research, Development & Innovation. Addressing Knowledge and Awareness Gaps among Research and Knowledge Dissemination Nevertheless, due to the obligation to account for the economic

Organisations. Decision Tree, Kaiser, L. (Ed.), Neu, M. (Ed.), Teernstra, activities separately, each such project should be labelled as F. (Ed.), Nicolaides, P. (Ed.), EUR 30436 EN, Publications Office of the either (i) a contract research or (ii) a collaborative research.

European Union, Luxembourg. https://op.europa.eu/en/publication-detail/-/publication/10740aa6-223a-11eb-b57e-01aa75ed71a1/

According to our discussion, this happens only rarely. As



discussed above, the activities in Slovenia are divided into public service and market activities which makes it more complicated

to introduce another set of classification. Label ‘economic activity’ or ‘non-economic activity’ should be assigned during

the process of bookkeeping, i.e. when the invoice is issued or contract concluded. A more significant, but important change of

replacing wording ‘public service/market activity’ with

‘economic/non-economic activity’ in Slovenian legislation

should be made. We communicated this with representatives

38





Feasibility Analysis for the New Mechanism of Knowledge Transfer within the INDUSAC Project

Duško Odić

Urška Mrgole

Marjeta Trobec

Office for Project Informatics,

Office for Project Informatics,

Office for Project Informatics,

Organization of Thematic Events

Organization of Thematic Events

Organization of Thematic Events

and Conferences (SPIK)

and Conferences (SPIK)

and Conferences (SPIK)

Jožef Stefan Institute

Jožef Stefan Institute

Jožef Stefan Institute

Ljubljana, Slovenia

Ljubljana, Slovenia

Ljubljana, Slovenia

dusko.odic@ijs.si

urska.mrgole@ijs.si

marjeta.trobec@ijs.si



ABSTRACT

1 INTRODUCTION

In September 2022, the Horizon Europe INDUSAC project

introduced a novel mechanism for knowledge transfer, extending



the usual company-researcher partnerships to include students as

In September 2022, the Horizon Europe INDUSAC project

well. Between March and May 2024, thirteen co-creation

(www.indusac.eu; EU project number 101070297) introduced a

projects involving international teams of students and

novel mechanism for knowledge transfer, extending the usual researchers solving companies’ challenges, were carried out.

company-researcher partnerships to include students as well. It

This study describes results of surveys given to companies, comprises a methodology that would allow for a streamlined students and researchers about their experience in the projects,

facilitation of collaboration between industry and academia, and

and the level of usefulness of solutions made possible by the an online platform to support that methodology [1]. In November

collaboration. We analyzed data collected from 10 companies,

2023, the INDUSAC project, coordinated by the Jožef Stefan 57 students and 4 researchers. Measured on the Likert scale, satisfaction of companies with technical aspects of the

Institute, commenced its piloting phase wherein universities, methodology ranged from average to good (average values

public research organisations, and companies were invited by the

between 3.1 and 4.2), whereas their satisfaction with the solution international project consortium to join the project. The idea to their challenge, and with the work done by the team, had a

behind the methodology is to bring together a company and an

narrower range between 3.2 and 3.8. Financial support to student

international team of 3-6 students and/or researchers to solve a

members of co-creation teams, in the amount of up to 1,000 EUR

company challenge within 4-8 weeks, with the company

gross per student, was perceived as sufficient by 67% of students.

providing assistance during regular meetings with the team. The

Initial results indicate that the INDUSAC mechanism is

team delivers results in the form of pre-defined types of relatively well accepted among companies, with room for

deliverables specific for the type of challenge, and the

improvement in certain aspects such as the user-friendliness of

deliverables are evaluated by companies. Being the main target

the platform and the time allowed to solve a challenge. Overall,

around 30 % of co-creation projects have demonstrated true audience, during the project, special attention was given to value to the company involved, and there is potential in the students / researchers from EU widening countries, and

further 50 %. Selected testimonials from companies,

geographical and gender balance was ensured by the criteria that

complimenting the work of students and expressing their own team members must be from at least three different countries, and

belief that the students are richer for the experience as well, must include representatives of at least two gender groups; demonstrate that the INDUSAC mechanism shows promise in

student members of the co-creation teams were financially

knowledge transfer.

rewarded for successfully completing the project. First such collaborations started in March 2024 and wrapped up in May KEYWORDS

2024. This study describes results of surveys given to companies,

INDUSAC project, international cooperation, student-industry

students and researchers about their experience in the project, cooperation, knowledge transfer

and the level of usefulness of solutions made possible by the collaboration. Implications for the feasibility of this concept of knowledge transfer are discussed.



2 METHODS

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full As per the methodology of the project, students and researchers

citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

were surveyed before they started working on the solution to the

Information Society 2023, 9–13 October 2023, Ljubljana, Slovenia company's challenge, and after they finished. Topics in the

© 2020 Copyright held by the owner/author(s).

survey, relevant to the scope of this study, included the students'

feedback on how the collaboration affects social impact, and how

appropriate the funding is. In addition, companies were surveyed

39





after the project, mainly about the quality of work performed by

the students / researchers, and the impact that their work has. All surveyed individuals were asked to provide short testimonials about their impressions and satisfaction. Students / researchers

were asked to fill in separate surveys for separate co-creation projects (maximum three) and companies were likewise asked to

fill in separate surveys for each team they worked with. Further

details are indicated in the Results section. In this study, we analyzed data collected from 10 companies, 57 students and 4

researchers.



3 RESULTS





Figure 2: Satisfaction of companies with work of the co-

In the first round of the INDUSAC co-creation projects,

creation team and the solution delivered. Average values ±

taking place between March and May 2024, thirteen co-creation

sd are shown (n = 10). Of the categories surveyed, Satisfaction,

projects took place that resulted in proposed solutions, two of Quality of Work, and Soundness refer to the work done by the

which were rejected and eleven approved by companies.

co-creation team, whereas Relevance, Market Potential,

Companies' overall satisfaction with the INDUSAC process after

Improvement over existing solutions, Creativity, and

the projects, expressed as various aspects of the methodology, is

Innovativeness refer to the solution delivered. Satisfaction was

shown in Figure 1. Satisfaction was evaluated on a Likert scale

measured on a Likert scale: 1 – very poor, 2- poor, 3 – average,

from 1 to 5. On average, the processes of registering on the 4 – good, 5- very good.

platform, publishing Challenges, and reviewing Motivation



Letters (ie., students' applications) ranked highest at 4.0, 4.0, and 4.2, respectively, while the user-friendliness of the INDUSAC

In terms of delivery of results, the companies have reported

platform and the time allowed to solve a challenge ranked lowest,

that all requested deliverables had been delivered by the co-each at 3.1.

creation teams in all cases except one (representing one of the

Companies' overall satisfaction with the solution to their

projects where the solution was rejected). In terms of follow-up

challenge, and with the work done by the team, expressed as on the solution within the company, indicating its usefulness, two various attributes, is shown in Figure 2. Satisfaction was companies have already started, a third company has confirmed

evaluated on a Likert scale from 1 to 5. On average, relevance of

that they will follow up on the solution, while 5 have not yet the solution, quality of work of the team, and satisfaction with

decided and in two cases it will probably not happen.

the work of the team ranked highest at 3.8 each, while the market

Since the INDUSAC project put a fair amount of emphasis on

potential of the solution ranked lowest, at 3.2.

social aspects such as geographically and gender-balanced



collaboration, the survey for students and researchers included

questions on agreement with (i) incorporation by the co-creation

process of customer research and insights to understand the end-

users' needs and preferences, (ii) solutions that specifically addressed gender-related issues or considerations, and (iii) successful prioritisation of the human aspect (Inclusivity, Gender dimension, Interdisciplinarity, User Perspective, Collaboration,

Iterative Feedback, Ethical Considerations) and creation of a meaningful and inclusive environment. Results are shown in

Figure 3. Agreement was evaluated on a Likert scale from 1 to 5.

On average, all three categories ranked fairly high, between 4.0

and 4.5.

Lastly, questions about the adequateness of financial support

to students, were also included in the survey. As per the INDUSAC methodology, each student received up to 1.000 EUR

gross for a successfully finished project, and this amount was reduced as the number of students per team increased, as each



team received up to 3.000 EUR gross. Results, demonstrated as

Figure 1: Satisfaction of companies with technical aspects of

distribution of opinions among different geographical groups the methodology. Average values ± sd are shown (n = 8 for

(ie., EU member states, widening countries, and EU associated

assistance to the team, n = 9 for support material, submission of

countries), are given in Figure 4, and indicate that overall, deliverables and punctuality of submission, and n = 10 for the

between 58% and 70% of students agree that funding was

other nine categories). Satisfaction was measured on a Likert

sufficient.

scale: 1 – very poor, 2- poor, 3 – average, 4 – good, 5- very



good.



40





and taking two out of thirteen solutions rejected into account, companies have expressed a fair level of general satisfaction with the solutions and the work done by the teams (Figure 2). It is likely that this was aided by the methodology sections which defined interim reviews and evaluation steps (eg., reviews of challenges before publishing, reviews of Motivation Letters



before starting, etc.), and regular communication between



companies and co-creation teams during the project. In all except

Figure 3: Agreement of students / researchers with

in one case, all deliverables were satisfactorily produced by the

incorporation of customer-oriented and human-focused

teams, indicating that the supporting documents that comprised

elements in the projects. Average values ± sd are shown (n =

the deliverables, and which were developed within the

61). Agreement was measured on a Likert scale: 1 – very poor,

INDUSAC consortium, served as useful guidelines for particular

2- poor, 3 – average, 4 – good, 5- very good.

type of challenge.



Having the project open to a wide range of challenge types



also proved beneficial as among the 13 projects for which solutions were provided, seven out of nine possible challenge types were represented, and distribution among different

challenge types was fairly even, with 'Marketing campaigns' and

'Service and product ideas' being most preferred.

An additional advantage was presented by the fact that the efforts to facilitate knowledge transfer between industry and academia are financially supported within the INDUSAC

scheme. This type of support is particularly welcome, as the lack

of funding is a frequent barrier for student-industry collaboration

[5,6]. Around two thirds of surveyed students found funding to

be adequate, and the largest percentage of this opinion was found



among students from widening countries (Figure 4) indicating that the funding scheme shows promise for the major target Figure 4: Perception of adequacy of funding within the

group of the project.

scheme in the INUDSAC project, as surveyed among

There is, however, room for improvement – not least based

students and researchers from different countries of

on comments given by the companies themselves. Geographical

residency. Within EU member states, there were no opinions balance, for example, may in some cases be an obstacle, as, in

towards [moderate]. Total number of individuals responding

one company's opinion, having a team with members from

was 5 in EU Member States, 37 in widening countries, and 12

different countries can make it difficult to work on projects that in associated countries.

require physical experience with a product. It is likewise important to be able to streamline the process, which needs to be

backed by a reliably functioning platform, as well as to unify the 4 DISCUSSION

working space, as it was, in one company's opinion, difficult to



keep track which information they received from which

The INDUSAC approach set out to bring several advantages

platform. Lastly, as mentioned, companies have expressed

to the existing landscape of knowledge transfer practices, such as interest in a more flexible data management, as the project's inclusiveness represented by gender balance, international

timeline may prove too rigid. In terms of funding, one student

cooperation by mandatory geographical diversity, enhanced

pointed out that it would have been preferable to receive funding

support to widening countries by mandatory representation in the

during the project rather than after, to allow for traveling to teams, and expansion to include students via mandatory

companies and collecting data. The problem of limited mobility

participation of at least one student per team solving companies'

was also perceived by companies, two of which stated that the

challenges; some of these have already shown to be

biggest challenge in projects related to physical products was that advantageous for companies [2-4]. Our results point to initial the participants cannot get to know and test the products live, and indications that the INDUSAC mechanism, comprising the

that creativity may be limited due to the lack of face-to-face methodology and the platform, is relatively well accepted among

interaction with products and colleagues.

companies (Figure 1), with room for improvement in certain aspects such as the user-friendliness of the platform and the time allowed to solve a challenge. The latter points to a general 5 FUTURE PERSPECTIVES

enthusiasm among companies to engage in finding solutions for



more serious challenges as well, which is encouraging – in two

The INDUSAC project set out to show that companies

cases, work is already under way to continue with the projects,

benefit from a particular type of knowledge transfer in the form

and overall, around 30 % of co-creation projects have

of creative young minds, that this knowledge transfer brings demonstrated true value to the company involved, and there is

satisfactory results and useful solutions, and that the gender and potential in the further 50 %. So even with the constraints given, geographical balance, as well as the inclusion of social elements

41

(Figure 3) have a positive effect on the overall process ACKNOWLEDGEMENTS

(satisfaction by teams, satisfaction by companies). While we did



not perform any control studies (for example, with single-gender

Work described in this manuscript has received funding from

teams) to truly test the effect of gender balance, there was a slight the European Union’s Horizon Europe Programme under grant

positive effect of (i) number of team members and (ii) ratio of

agreement No 101070297.

female-vs-male team members, on company's satisfaction with

results and quality of work (unpublished data). Other results and

REFERENCES

selected testimonials from companies, complimenting the work

of students and expressing their own belief that the students are

[1]

Odić D, U Mrgole, M Trobec. 2023. New initiatives for knowledge transfer between industry and academia : the INDUSAC Project. In: 16th richer for the experience as well, demonstrate that the INDUSAC

International Technology Transfer Conference : 8 October 2023, mechanism shows promise in knowledge transfer, and the

Ljubljana, Slovenia : Information Society - IS 2023 : Proceedings of the 26th international multiconference E: 58-61

rejected solutions stand as reminders that even following the

[2]

Cavero-Rubio JA, A Collazo-Mazón, A Amorós-Martinez. 2019. Public

careful process of team assembly and selection, monitoring of recognition of gender equality in the workplace and its influence on firms'

performance. Women’s Studies International Forum 76: 102273

the work done needs to be vigilant for it to lead to satisfactory

[3]

Chang T-LS, C-M Chuang, W-S Jan. 1998. International Collaboration of results. With this in mind, the INDUSAC methodology is

Law Firms: Modes, Motives and Advantages. Journal of World Business continuously improving and mechanisms are put in place to

33, 3: 241-262

[4]

Ratten V. 2016. International Collaboration and Knowledge Transfer minimize such occurrences. The challenges that remain also

among Universities and Firms Affecting Regional Competitiveness.

include attracting larger numbers of companies and students /

Thunderbird International Business Review 58, 1: 91-93

[5]

Ejubovic A, G Cerinsek, T Davey, A Meerman, V Galan-Muros, B

researchers to engage into cooperation, but the level of success

Orazbayeva. 2017. State of University-Business Cooperation: Slovenia -

described here represents a strong starting point.

University Perspective. EC University-Business cooperation in Europe; Country Reports - Slovenia



[6]

Morisson A, M Pattinson. 2020. University-Industry Collaboration. Lille: Interreg Europe Policy Learning Platform





42





Approaches to Monitoring and Impact Assessment in Research Infrastructures

Jure Plaskan

Barbara N. Brečko



Faculty of Social Sciences

Faculty of Social Sciences



University of Ljubljana

University of Ljubljana



Ljubljana, Slovenia

Ljubljana, Slovenia



jure.plaskan@fdv.uni-lj.si

barbara.brecko@fdv.uni-lj.si





ABSTRACT

In recent decades the significance of research infrastructures has become increasingly evident across all fields.

Impact assessment is a critical process in understanding the broader effects of research infrastructures (RI) on various sectors Although RIs are primarily designed to meet research needs, such as science, society, the economy, and policy-making. It their influence extends well beyond promoting scientific

helps RI identify their strengths, weaknesses, and areas for excellence. The advanced technological capabilities and

concentration of skilled expertise they provide can stimulate improvement. The paper addresses the challenges of monitoring

innovation, create or expand markets, attract foreign investment,

and evaluating the impact of RI, focusing on the distinction boost economic activity, and potentially enrich the social and between performance monitoring and impact assessment. It

cultural life of a region. [2]

emphasizes the importance of demonstrating the broader



societal, economic, and scientific impacts of RIs to inform public RIs necessitate relatively large and long-term financial

policy and secure funding. In the article we address different investments, making it crucial for investors, policymakers, and

other stakeholders to ensure that these infrastructures operate methodological approaches to impact assessment and self-successfully and effectively, contributing to scientific

evaluation of RIs as well as the possible challenges in these advancement and addressing societal and economic challenges.

processes. The paper advances the integration of multiple



evaluation approaches to provide a robust and detailed

Although reflections and publications on defining and measuring

assessment of the contributions RIs make to society, the

impact have increased in recent years, there is still no unified economy, and scientific development.

framework or consensus on how to assess the impact of RIs.

Therefore, it is crucial to explore the potential for developing such a framework and investigating its practical application.

KEYWORDS



Impact assessment, monitoring, research infrastructures

2

PERFORMANCE MONITORING AND

IMPACT ASSESSMENT

1

INTRODUCTION

To this end, various solutions have been developed to enable Research Infrastructures (RIs) are essential facilities that offer stakeholders to monitor performance and evaluate the impact of

resources and services to research communities, enabling them

RIs. However, there is a distinction between these two activities, to conduct research and drive innovation. Beyond their primary

which this paper aims to clarify. The concepts of performance role in research, these infrastructures can also support education, monitoring and impact assessment represent two distinct yet public services, and other non-research activities. They may take

related processes for evaluating the activities of institutions.

various forms, including single site, distributed, or virtual setups.

Although both processes involve data collection and analysis of

RIs encompass human resources, major equipment, and/or sets

RI performance outcomes, their focus, scope, and objectives of instruments, as well as resources containing knowledge, such

differ.

as collections, archives, and databases. They are used by



scientists from various disciplines – e.g. astronomy, biology, Performance monitoring, often simply referred to as

chemistry, physics, human and social sciences, etc. RIs can

“monitoring”, involves the systematic and regular collection and

maintain their competitive advantage only if they keep pace with

analysis of data related to activities and outcomes. This process

the latest advancements in relevant scientific fields and the is crucial for assessing progress toward predefined goals,

newest techniques and technologies. Therefore, it is crucial for

identifying areas where activities are achieving success, and RIs to connect with the research community and industry to stay

pinpointing areas that require improvement. Typically,

aligned with developments in both science and technology. [1]

performance monitoring focuses on tracking key performance



indicators (KPIs), which serve as measurable values that reflect

the effectiveness and efficiency of the activities being evaluated (e.g. Number of publications, Number of master and PhD



Permission to make digital or hard copies of part or all of this work for personal or students using the RI, Outreach through media, ...).

classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full Impact assessment, in contrast, focuses on identifying and citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).

evaluating the changes within the broader ecosystem that result

Information Society 2024, 7–11 October 2024, Ljubljana, Slovenia from the activities and outcomes of RIs. This process aims to

© 2024 Copyright held by the owner/author(s).

determine which specific RI activities lead to impacts across 43

various domains. A well-established approach, developed 2.1 Defining Areas for Impact Assessment

through European initiatives (such as the RI-PATHS [3] project),

is the concept of “impact pathways”. This method enables

Impact assessment becomes especially crucial in times of limited

evaluators to trace the different routes through which activities

public funding for science. By highlighting the effects of RIs on

translate into impacts at various socio-economic levels.

science, society, the environment, the economy, and other



sectors, impact assessments can demonstrate the value of both Impact assessments can be conducted either before or after the

potential and actual investments in RIs. This analysis helps to implementation of RI. When carried out during the planning underscore the relevance of these investments in addressing phase, this process is known as an “ex-ante” impact assessment.

societal needs. Moreover, impact assessments provide

Its purpose is to forecast the potential impacts of the RI, policymakers with a clear picture of the broader benefits that RI

anticipate its effects, and inform strategic planning to ensure activities offer, thereby supporting the development of informed

those outcomes are realized. This type of assessment is largely

public policies and decision-making.

conceptual and, to some degree, abstract. Once the RI is

established and fully operational, an “ex-post impact

assessment” is conducted to evaluate whether the RI has

Impact assessment is closely tied to the goals of RIs and the successfully met its intended objectives.

expectations they set. The ESFRI 1 working group on RI



performance monitoring has identified nine objectives which are

When determining criteria and indicators for monitoring and relevant to RIs [7], and largely correspond to the following five

evaluating (e.g., research infrastructures, measures, programs, impact areas:

policies), it is crucial to recognize the differing roles of these two

•

Contribution to Scientific Excellence: At the heart of processes. Monitoring focuses on real-time oversight of

every RI is the drive for scientific excellence. RIs

implementation: as a funder, one needs to know the current contribute in numerous ways, including data collection and

status, whether progress is on track, whether funds have been preservation, providing access to infrastructure and

appropriately allocated, whether a sufficient number of target databases,

sample

collection

and

dissemination,

audiences has been engaged, etc. While monitoring can alert us

facilitating analytical experiments, offering software, and

that things are not proceeding as planned, it does not reveal the

providing general support to researchers. These activities

causes of deviations nor provide adequate information for

are fundamental to the research process, fostering scientific

making necessary corrective actions [4].

progress by advancing innovative research, expanding the



frontiers of knowledge, and generating new insights and

On the other hand, the role of evaluation is to explain how the

discoveries.

institution/measure/program/policy functioned, how successful

•

Addressing Societal Challenges: In recent years,

it was in achieving its objectives, and what its impacts were.

addressing societal challenges has become an increasingly

Evaluation allows us to determine success, identify what worked

important focus for RIs. Their impact ranges from

and what did not, and, if not, what changes need to be made in

contributing to the United Nations’ Sustainable

future planning. The focus of evaluation may be on assessing the

Development Goals and the European Green Deal to

degree to which objectives are achieved, or it may focus on the

enhancing public understanding of science.

process of implementing the instrument/program/policy itself.

•

Contribution

to

Innovation

and

Economic



Development: Given the substantial financial investments

Impact assessment is beneficial for RIs when used to evaluate required by RIs, it is crucial to highlight their role in and enhance their functioning. It plays a crucial role in the driving innovation and economic growth. This can be

strategic planning of an RI by informing decisions on internal reflected in job creation, economic development, or

resource allocation and driving continuous improvement and

increased competitiveness, particularly at local, regional,

alignment of services with the needs of users and other

and national levels. Large RIs, in particular, employ a

stakeholders.

Additionally,

impact

assessment

fosters

significant workforce and, in some cases, make substantial

accountability and transparency, thereby enhancing the

investments in constructing and offering high-value-added

legitimacy, visibility, and overall value of the RI. Furthermore, it components.

serves as a platform for meaningful dialogue and exchange

•

Contribution to Policy-Making: Research facilitated by among relevant stakeholders regarding the objectives, direction,

RIs can significantly inform policy-making across various

and operations of RIs, which can be exceptionally valuable. [5]

thematic areas. This is especially important for



The OECD defines impact as “the extent to which an intervention

organizations responsible for policy development at the

European or national level.

has produced, or is expected to produce, positive or negative, intended or unintended effects at a higher level.” [

•

5] The



Contribution to Human Resource Development: Many

European Commission mandates the implementation of impact

RIs also focus on education and training, often dedicating

assessments for every policy intervention or law (including significant resources to these efforts. As centers of

investments in research infrastructure and their activities) scientific excellence, they play a crucial role in developing

expected to cause significant effects or require substantial human resources and training the next generation of

financial resources. Impacts represent all “direct or indirect scientists. They impact their users and their careers through

changes” relative to the baseline scenario. Such impacts may enhanced scientific excellence, productivity, networking,

occur over different time periods, affect different stakeholders, and training opportunities.

and be relevant at different levels (local, regional, national, and EU) [6].

1 European Strategy Forum on Research Infrastructures

44

Listed areas are not relevant only to RIs, but can be relevant also defining “impact pathways”. The impact pathway approach was

to other research organizations.

further developed in the RI-PATHS project, which explores

more details than the logical framework and provides a

descriptive vision with more information on causes and effects.

3

METHODS AND APPROACHES FOR

6. Case studies: This approach involves an in-depth analysis of MEASURING IMPACT

a specific case to understand the effectiveness of a policy or In the RI-PATHS project [3] a comprehensive review of

project. The analysis focuses on the specific context, identifying literature was conducted on methodologies for evaluating and factors contributing to success or failure and deriving lessons that measuring the socio-economic impacts of RIs. The project

can be applied to future policies and projects. When used in focused on ex-post impact evaluation methodologies, which are

impact evaluations, case studies aim to better reflect the employed during the operation of RIs when it is possible to uniqueness and complexity of RIs.

ascertain whether they are creating certain impacts and in what



manner. The effectiveness of the analysis is demonstrated

It is evident that some approaches are more suitable for assessing quantitatively (e.g., through indicators) or qualitatively (e.g., economic rather than social or scientific impact, and vice versa.

through case studies). [8]

In general, these approaches can complement each other—some



are more quantitative, such as macroeconomic modelling or cost-

Six main approaches/methods for measuring impact based on the

benefit analysis (CBA), while others are more qualitative, like literature review were identified:

case study descriptions.

1. Socio-economic assessment based on impact multipliers: The RI-PATHS project systematically evaluated each of the

This approach evaluates the socio-economic impact of a policy

mentioned approaches using criteria such as reliability, validity, or project by quantifying the effects on various economic sectors.

precision, cost and time efficiency, and relevance to both The assessment is based on impact multipliers that estimate the

policymakers and research infrastructure managers. It is evident

indirect effects of the policy or project on the economy. This that no single methodological approach can comprehensively

approach expresses impacts on aggregated macroeconomic

address all the questions intended for impact evaluation.

variables such as GDP, gross value added, or employment. The

However, combining different approaches can offer greater value

main advantage of this methodology, which is grounded in a and effectiveness compared to relying on existing methods alone.

well-established theory and uses input/output analysis tools, is its reliability in producing reproducible and comparable project 4

IMPACT PATHWAYS AND

results. However, its limitation is its restricted validity, as it often INDICATORS

cannot reliably measure non-monetary effects (e.g., cultural, social, and environmental).

While there is not a universally accepted approach to impact 2. Methodologies utilizing the knowledge production

assessments in RIs, the work of the RI PATHS project has, as function: This approach focuses on the impact of research and mentioned, become well established in Europe. Indeed, results development activities on the economy. The knowledge

from the survey conducted by ESFRI among RIs [7] show that

production function method quantifies the relationship between

impact pathways have become a common method for impact

research and development investments and economic growth.

assessments among European RIs. Several RIs have conducted

The approach focuses on only a small portion of the expected their impact assessments with the help of impact pathways as part

socio-economic impacts of RIs.

of the RI-PATHS pilot exercises (for example, ALBA, ELIXIR,

3. Cost-benefit analysis (CBA): This approach compares the EATRIS) [9]. Identifying impact pathways was also an integral

advantages and disadvantages of a policy or project and

component of the impact assessment of ICOS [10].

determines whether the benefits outweigh the costs. The analysis



considers both quantitative and qualitative factors to enable well-The mechanism of impact pathways is recommended as a way to

informed decision-making. All costs or benefits are monetized,

demonstrate causal links between inputs, various activities and even if the effects are not solely financial. Governments and outputs of RIs, and their identifiable impacts [3] [11]. These can economists frequently use this approach to assess the impact of

be both intended or unintended – while impact pathways always

various investment projects. It is reliable for comparing positive have a clear origin in one or few related activities, which are and negative effects and can capture numerous RI impacts.

under control of RIs, these activities branch out into different However, it can be expensive and time-consuming and has

directions and trigger effects in different areas, which can be limited causal explanatory power. Additionally, it may not

outside the sphere of influence of RIs. An example of exploring

always capture all drawbacks.

impact pathways according to spheres of control, influence, and

4. Multi-methods multiple partial indicators: This approach interest can be seen in AnaEE’s position paper [12], which combines multiple methods and indicators to evaluate the impact

sought to build a framework that would specify AnaEE’s position

of policies or projects. Methods can include surveys, focus in the chain of actors generating impact in its scientific field.

groups, and statistical analysis, while indicators encompass economic, social, and environmental factors. An example of this

In order to map the path from activities of RIs to outcomes and

approach is the OECD framework for socio-economic impacts,

impacts, it is crucial to systematically collect data. This is which includes a list of 25 essential impact indicators and 58

recommended for both performance monitoring and impact

additional standard indicators.

assessment. Several lists of indicators have been proposed in 5. Theory-based approaches: These approaches rely on

recent years (OECD, RI PATHS, ESFRI WG). The indicators

established economic or social theories to evaluate the impact of

can vary – from those that primarily measure performance, also

a policy or project. They depend on theoretical models and known as key performance indicators (KPIs) [5], and those

empirical evidence to predict impact. A typical example is the which are focused on impact (e.g. OECD prepared a list of

“logical framework/model”, which is based on a logical

impact indicators) [13]. The purpose of impact indicators is to sequence of steps from inputs to impacts. Theory-based

create a link to strategic objectives of RI, as well as to different approaches share common features such as considering the

areas of impact that RIs create. In addition to the connection of

broader context and external factors that can affect success and

indicators with strategic goals, the OECD recommends that the

45

indicators provide information related to operational issues and It is important to note that some challenges may be specific (or

that the data is measured in a specific time frame.

more common) to a certain type of RI or to certain thematic areas



they cover. To address this challenge, the recommendation is to

Impact indicators can be quantitative or qualitative, e.g. in form avoid directly comparing impacts of RIs, and to consider the of “narratives”. This information is usually collected via tailored diversity of RIs. When deciding on a methodology, it is advisable

methods, such as interviews, surveys, or case studies. These to tailor the selected methodology to each RI, and first establish indicators are more difficult to be standardised and must be a consensus between RIs, funders, governments and other

tailored for specific RIs and depend on the context. These relevant stakeholders. This agreement should establish clear methods can help RIs to report on intangible impacts.

expectations regarding the objectives of the RI and the



assessment itself. However, all RIs should strive to demonstrate

impact in the field of scientific progress, while considering 5

INTERNAL AND EXTERNAL IMPACT

various other socio-economic impacts.

EVALUATION

Providing adequate resources for the implementation of an

impact assessment is indeed challenging, in particular as it is Both external and internal evaluations are relevant for assessing

necessary to adopt a long-term plan for evaluation in order to the impact of RIs, each with its advantages and disadvantages.

capture impacts that take years to reveal. At the same time the

External evaluations are conducted by independent evaluators data collection needs to be done systematically and begin early

who assess the institution's impact. This approach ensures an enough, which can be more resource intensive although also objective and impartial assessment, as external evaluators are not helps to lower the amount of “ad-hoc” data collection when affiliated with the evaluated institution and are, therefore, less conducting impact assessments.

likely to be influenced by internal biases or personal interests.



Additionally, external evaluations can provide new perspectives

In spite of these challenges, impact assessments provide

and insights that are not available to internal evaluators.

important information for all RI stakeholders, as well as the However, external evaluations are often costly and time-general public, as they allow RIs to demonstrate their

consuming and may sometimes fail to account for the contextual

contributions to science, society and the economy, and help nuances and priorities of the evaluated institution.

improve their performance. As such, they can be used as means



to communicate about RI activities. Promoting and

In contrast, internal impact evaluations rely on an evaluation disseminating the results of these evaluations can subsequently

process conducted by the institution's staff or stakeholders. This help promote positive RI development and funding.

approach is more cost-effective and efficient, as internal

evaluators are already familiar with the institution and its operations. Internal evaluations may also better consider the 7

CONCLUSIONS

institution's contexts and priorities and be more adaptable to Despite the growing focus on this area, there remain significant

changes in RI goals. However, internal evaluations may be

challenges in developing a unified and comprehensive

biased due to internal motivations and conflicts of interest and framework for evaluating such impacts, particularly when

may lack the objectivity and independence of external

accounting for both economic and non-economic factors. There

evaluations. Moreover, internal evaluators may be limited by is a reason for that – the unified methodology cannot adequately

their knowledge and expertise, reducing their ability to bring new address all aspects of variety of RIs and the diversity of fields

insights and perspectives.

where they operate. There is a number of methods which can be



applied, and future work could explore how combinations of The choice between external and internal evaluation often

different methods (e.g. quantitative, such as macroeconomic

depends on internal capabilities, available resources, evaluation

modeling and cost-benefit analyses and qualitative such as case

objectives, and so on. To ensure a comprehensive and balanced

studies or theory-based assessments) can be effectively balanced.

assessment, it is beneficial to combine both approaches. It is also This could provide more holistic view on RI impacts, especially

increasingly common for institutions (including RIs) to

in understanding intangible impacts like societal and

periodically self-evaluate, thereby preparing for external

environmental changes.

evaluation.



There are already lists of indicators suggested to be used for 6

CHALLENGES AND OBSTACLES

impact assessment, nevertheless the selection of indicators

should be done with a great deal of prudence and not to be used

There are several challenges that RIs encounter while conducting

to compare RIs, given the diversity in their structure and impact assessments. Some of them were outlined by respondents

objectives.

to an ESFRI survey among RIs (2023). According to the survey,



a recurring challenge was to identify an appropriate method or



framework or finding appropriate indicators. Other respondents

ACKNOWLEDGEMENT

mentioned the amount of resources required and the time frame



needed to properly evaluate the impacts of their infrastructure. In The research was supported by Slovenian research agency, grant

general, some RIs are concerned that impacts may not be

number V5-2283.

properly detected. This is a similar issue to what was described

in the ERIC forum’s “Report on Socio-economic impact

REFERENCES

framework” [14] as a “traceability” problem – there is

uncertainty about how to link RI activities or data generated

[1] ESFRI Scripta Vol. 2 (2017). Long-Term Sustainability of Research Infrastructures

within an RI to their subsequent use. One of the RIs responded

https://www.esfri.eu/sites/default/files/ESFRI_SCRIPTA_SINGLE_PAGE_19102

that measuring innovation or social impacts could take several

017_0.pdf.

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[2] Griniece, E., Reid, A., Angelis J. (2015). Evaluating and Monitoring the Socio-Economic Impact of Investment in Research Infrastructures. Technopolis Group.

Available

at:

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https://www.researchgate.net/publication/275037404_Evaluating_and_Monitoring _the_Socio-Economic_Impact_of_Investment_in_Research_Infrastructures

[3] RI-PATHS. Research Infrastructures’ Impact Assessment Toolkit. https://ri-

paths-tool.eu/en

[4] BUČAR, M. (ur.), ČRNIGOJ, M. (ur.), LIPNIK, A. (ur.). (2020). Vrednotenje sodelovanja med znanostjo in gospodarstvom. Ljubljana: Fakulteta za družbene vede, Založba FDV

[5] OECD (2021). Applying Evaluation Criteria Thoughtfully, OECD Publishing, Paris, https://doi.org/10.1787/543e84ed-en.

[6] EC (2023). Better Regulation Toolbox

[7] ESFRI (2019). Working Group Report. Monitoring of Research Infrastructures Performance.

Available

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https://www.esfri.eu/sites/default/files/ESFRI_WG_Monitoring_Report.pdf

[8] Giffoni F, Schubert T, Kroll H, Zenker A, Griniece E, Gulyas O, Angelis J, et al (2018) State of play - literature review of methods to assess socio-economic impact of research infrastructures. RI-Paths project. H2020 grant 777563. Available at

https://ri-paths.eu/wp-content/uploads/2018/03/D3.2_Report-on-stocktaking-results-and-initial-IA-model.pdf (last accessed 1 August 2024)

[9] Griniece,E., Angelis,J., Reid,A., et al. (2020). Guidebook for Socio-Economic Impact Assessment of Research Infrastructures.

Doi: https://doi.org/10.5281/zenodo.3950043

[10] Van Belle,J., Van Barneveld,J., Bastiaanssen,V., et al. (2018). ICOS Impact Assessment Report. Technopolis Group. Available at https://www.icos-

cp.eu/sites/default/files/2018-09/ICOS_Impact_Assessment_Report_2018.pdf

(last accessed 18th September 2024)

[11] Lutz, G. Kolar, J., Brečko, B. N., Plaskan, J., et al. (2023). Assessment of impact of RIs : policy brief. [Brussels]: European Strategy Forum on Research Infrastructures (ESFRI), 2023. DOI: 10.5281/zenodo.8091633

[12] Boer,M., Chavel,S., Mahé,S., and Plaude,S. (2021). Setting a relevant framework

to

assess

AnaEE’s

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/setting_a_relevant_framework_to_assess_anaees_impact.pdf (Last accessed on 18th September 2024)

[13] OECD (2019). Reference framework for assessing the scientific and socio-economic impact of research infrastructures. OECD Science, Technology and Industry

Policy

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[14] ERIC Forum Implementation Project (2022). Report on SEI ERIC Framework.

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2024,

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content/uploads/D4.3-EF-Report-on-SEI-ERIC-Framework.pdf





47





Intellectual Property Valuation

in the Cyber Security Sector



Marta E. Wachowicz



Technology Transfer Unit



NASK - National Research Institute



Warsaw, Poland



marta.wachowicz@nask.pl





ABSTRACT / POVZETEK

to understand the economic value of cyber IP assets by carrying

out an IP valuation. The article addresses a topic specific and This paper explores the applicability of intellectual property relevant to the digital economy, the literature abounds with rights (IPR) valuation methods in cyber security by using the methodologies for different approaches to valuing IPR [9], [1],

criteria of the Artificial Intelligence development phase model.

but there is no guidance on how to consider the importance of After analysis of the interconnections and interdependency in data, learning models, and all aspects of AI in new inventions.

cyber security products, an approach to data quality is proposed.

The challenges faced by the cyber security sector are defensive

It is worth emphasizing that the process of valuating IPRs is AI and machine learning technology, sophisticated cyber attacks,

highly contextual and requires professional judgment based on reinforcement learning-based cyber attacks, AI-enabled

the experience of the appraiser, now also in terms of data malware, the vulnerability of IoT technology, cloud security management. This issue has not been discussed in the literature,

issues, and the involvement of cryptography. However, future an article is a contribution to the discussion on the importance of directions, in cyber security, such as quantum-secure encryption,

valuation in the cyber sector, given the specific characteristics of biometric authentication, advanced artificial intelligence, and cyber start-ups using AI and machine learning solutions. Despite

machine learning, may be able to address these issues.

all these difficulties, IPR valuation will become increasingly necessary and induce further questions regarding the valuation of

1.2 Cyber security products

a given intellectual property (IP). Firstly, how to value a patent According to the American Authorities, precisely Cyber Security

with Artificial Intelligence (AI), secondly how to assess the level and Infrastructure Security Agency, cyber security is “the art of

of sophistication of model training, and thirdly how to rate and

protecting networks, devices, and data from unauthorized access

value data quality, or more broadly data sets. The findings can

or criminal use and the practice of ensuring confidentiality, help practitioners, especially from Technology Transfer Offices,

integrity, and availability of information” [2]. The current cyber to develop roadmaps for IP valuation in the cyber security security situation is characterized by the regular emergence of industry.

new cyber threats. The most common types of cyber threats include malware, phishing attacks, ransomware, threats against

KEYWORDS / KLJUČNE BESEDE

data or availability, disinformation, supply chain targeting, and

IPR valuation, IP in cyber security, data quality in AI model

distributed denial of service (DDoS) attacks. The level of digital resilience varies from different industries and countries,

however, effective cyber security remedies use security

1. CYBER SECURITY SPECIFICITY

technologies and techniques such as intrusion detection and

prevention systems, firewalls, antivirus software, and encryption

VERSUS IPR VALUATION

[8]. Cyber attackers are constantly evolving their approach to penetrate the computer systems of enterprises which means that

1.1 Introduction

organizations must continuously monitor their networks against

The growth in importance of IPR is unquestionable, in every potential attack vectors, using a broad array of cybersecurity sector of the economy, and in those key to the digital

solutions to protect the entire ecosystem, including clouds and transformation an undisputed. The IPR valuation is gaining in several applications [8].

importance and reliable valuation is relevant in the cyber security Typical products are software for stopping the biggest,

sector. The valuation approach dedicated to the cyber market is

bandwidth-busting DDoS attacks, software that proactively

not described in the literature and represents an unexplored reduces attack surfaces, Edge DNS, authentication services,

research question. In IPR valuation, whatever the method, the clouds for protecting customers and providing data security, essential characteristics of an intellectual asset should be taken which reduce friction during registration, authentication, and into account. There is a fundamental complication arising from

sign-ins while making it easy for customers to control their the difficulty of determining the essential characteristics of IP, accounts from any device. Products are, on the one hand, closely

the scope of protection, and the need to consider source data related to IT or ICT. On the other hand, they use the latest related to potential cyber exploitation on an unprecedented scale.

developments in biometrics, behaviorism, psychology, and the

IP assets can be independently identified, are transferrable, sociology of human behavior. They use, as in criminology,

protected and that protection can be enforced. In the case of knowledge about human behavior, but the implementation of

cyber, they have an economic lifespan, defined by their

knowledge is strictly technical, in a digital world.

characteristics. Depending on the nature of intangible assets, there are different legal instruments by which protection is possible and ultimately benefit from using them. It is important

48

2. MULTIDIMENSIONAL IP

appear numerous, including AI inventorship, patent eligibility, PROTECTION

and AI-related copyright issues, particularly important are data

issues.

2.1 Impact of cyber product features on IP

protection

2.2. FLDX system – an example of IPR

The development of new solutions to combat or prevent

protection

cybercrime requires the proactive action and the creation of new

inventions combating the criminal incidents. Since AI is widely

An example of a cyber security product is the FLDX system, used in cyberspace, AI-based products are also tools for

patent protected by NASK, a Polish National Research Institute,

mitigating attacks. Ransomware and phishing attacks encrypt

whose mission is to develop and implement solutions that

critical data, demand high ransoms, and disrupt a wide range of

facilitate the development of information and communication

operations. The growing use of Internet of Things devices is networks in Poland, in addition to improving their effectiveness

introducing new security vulnerabilities, while cyber attacks and security. Patent – PL241005- Method and system for adaptive targeting the software supply chain are exploiting third-party creation of network traffic filtering rules on a network device vulnerabilities to gain access to sensitive information. Artificial spontaneously

detecting

anomalies

and

automatically

intelligence technologies enable cybercriminals to launch

suppressing volumetric attacks (DDoS) protects digital services sophisticated attacks. These AI-based threats are often not and network devices from DDoS attacks and a sudden and

subject to traditional security measures, making them difficult to unpredictable increase in user activity. Sudden and unexpected

detect

and

mitigate.

The World

Intellectual

Property

bursts of Internet traffic can saturate network links or

Organization (WIPO), the United Nations agency that serves the

overloading application servers. Therefore, protecting networks

world’s innovators, is following the trend of consumer interest in and digital services from intentional attacks must go along with

AI in various economic, social, and cultural sectors, having fair distribution of network resources. The FLDX system is a fast

published some very interesting and important reports on AI over

and extremely effective way to protect the availability of services the past few years. [6], [10]. WIPO Technology Trends 2019 –

on the network - whether the source of the threat is a volumetric

Artificial Intelligence reveals trends in patenting of artificial DDoS attack or a sudden increase in user activity. Maintaining a

intelligence innovations [10]. AI-related patents disclose AI fair distribution of network bandwidth is the primary goal of the

techniques and applications and refer to an application field or

FLDX system, achieved in a time of up to 10 seconds. Unlike the

industry. WIPO analysis shows that many sectors and industries

solutions currently offered in the anti-DDoS market, the FLDX

are

exploring

the

commercial

exploitation

of

AI,

system is not based on a database of signatures and static rules.

telecommunications (mentioned in 15 % of all identified patent

It dynamically self-adjusts filters to the current situation. This documents), transportation (15 %), life and medical sciences (12

approach allows us to react extremely quickly to the observed

%), and personal devices, computing and human-computer

changes in network load, as well as forecast them. The FLDX

interaction (11 %), the rest - other sectors including banking and system is therefore not only a protection tool - it is also a network security. In the WIPO patent landscape report on Generative AI,

knowledge discovery tool. The object of the invention is a there are the latest patent trends for GenAI with a comprehensive

method for adaptively creating network traffic filtering rules on

and up-to-date understanding of the GenAI patent landscape, a network device spontaneously detecting anomalies and

alongside insights into its future applications and potential automatically suppressing volumetric attacks (DDoS).

impact. The report explores patents relating to the different That FLDX example may illustrate the challenges of protecting

modes, models, and industrial application areas of GenAI. Deep

IPR in this area. The speed and precision of the FLDX system

neural networks can be adapted to be either discriminative or are the result of years of scientific research in the fields of control generative tasks, which has led to the development of various theory and adaptive signal processing, the IP behind the solution

types of GenAI models, which can support different types of is not only a patent, but also a copyright protecting the software input and output data. This opens up a new perspective on the and the user's system, trade secret, the implicit knowledge of the protection of inventions and products.

implementation as well as the knowledge contained in the

There is a need to answer the threshold question of whether such

technical documentation. Solutions are sporadically planned to AI-related inventions qualify for patent protection. The United be patent-protected, due to non-compliance with requirements States Patent and Trademark Office (USPTO) has issued

for implementations of mathematical theorems or new

guidelines to clarify the requirements for patenting AI-assisted applications of functional analysis. However, even an obtained inventions. For an invention to be patentable, there must be exclusive right is not sufficient protection in the market. It is significant human input into its conception. Human inventors necessary, as with other software-based products, to supplement

must make a significant contribution to the invention that goes

protection not only with copyright protection due to the nature of beyond the mere use of AI tools. Otherwise, the invention is not

the solution but also to keep in secret any know-how resulting eligible for patent protection. In addition, the USPTO has created from the implementation and to circumvent technical problems

five principles for evaluating AI-assisted inventions, the fifth is arising from software development and installation in the cloud

worth mentioning here - namely, merely owning or supervising

or at the customer's site.

an AI system does not qualify a person as an inventor without a

3. IPR VALUATION ISSUES

significant contribution to the concept of the invention [7]. This 3.1 Valuation approach selection

principle ensures that human ingenuity remains at the heart of Valuation of IPR regardless of the subject of valuation

patentable inventions while recognizing the supporting role of AI

strictly depends on the potential area of application of the in the inventive process. In the cyber industry, solutions can be

protected technology. In the cyber sector, the issue of the protected by patents and then there is a need to value IPR in the

valuation of IP goods is becoming increasingly challenging, for

form of a patent on an AI-related property. The number of cyber

several reasons. First, this is due to the obvious development of

security patent applications per year shows that the amount of the cyber market and the growing demand for all kinds of investment going into finding new ways to help prevent cyber services and products protecting digital assets. Secondly, AI attacks is huge. However, it is usually a bundle of different IPs

technologies are finding applications in this sector, which makes

that is valued. Apart from the fact that AI-related IP problems the valuation problem more complicated, and thirdly, a complex

49

method of product IPR protection is common. The issue of IPR

related know-how, there is an issue directly related to the valuation in high-growth sectors, for new technologies, and understanding of the operation and use of AI models [4].

cutting-edge technologies, has been addressed in the literature for years. Major researchers (such as Damodaran) describe the 3.2. Data in Artificial Intelligence model

challenges of estimating value for technology [1], [9]. However,

During training, the artificial intelligence model is exposed to a the growing cyber market introduces a significant level of prepared dataset and tries to learn the patterns and relationships complexity to the subject, due to the dynamics of development,

present in the data. This process involves adjusting the internal

key development trends, market estimation, and the scalability parameters of the model based on the input data and the desired

and adaptability of solutions in this market.

outcome. In a situation where AI is used, another problem arises.

Depending on the nature of intangible assets, various

When is the product in question completed? AI models need to

legal instruments are offered to protect and ultimately profit from be taught. What does AI model training include?

them. IP management is a key element of the business strategy

AI model training includes three main aspects:

of entities developing cyber services. The linkage of copyright a)

data collection

protection, patent, trade secret, and confidential know-how

There are ready-to-use open-source data sets. Data collection and

protection makes IP valuation difficult. Trade secrets may be other resources are also collected and used. Internal data preferable to patents in several circumstances, such as when the

collection provides access to proprietary information and control

patentability requirements may not be satisfied; the cost of over data quality. Web scraping is the process of extracting data

pursuing patent protection outweighs the benefits; and/or the from websites using various tools. Automation eliminates the need for IPR protection extends beyond the available patent term

need for manual data collection, which in itself is impractical

[9].

when it comes to training AI models. Regardless of the data Regardless of the method used, the valuation process

collection technique, the data should be relevant, accurate, requires gathering a lot of information about intellectual property consistent, presentable, and complete. Such data increases the assets, as well as an in-depth understanding of the economy, accuracy of the AI model, reduces bias, and increases user industry, and specific businesses that directly affect their value.

confidence and trust in the AI model.

It is well known that there are three basic categories of valuation b) data processing

methods for evaluating intellectual property and intellectual Having a rich data set, it is necessary to validate the data. Data property rights: income-based, market-based, and cost-based.

validation involves preparing the data to match the requirements

The choice of the appropriate method for valuing intellectual of the specific learning mechanism used by the artificial

property depends on the type of intellectual property, the stage

intelligence model. Each learning technique requires the data to

of development, the purpose of the valuation, and the available

be presented in a specific way. An artificial intelligence model

data. The cost method establishes the value of an IP asset by incorporating algorithms that learn through supervised learning

calculating the cost of a similar (or exact) IP asset. The cost aims to predict or classify new data points. So, to select data for method is particularly useful when the IP asset can be easily an artificial intelligence model equipped with supervised

reproduced and when the economic benefits of the asset cannot

learning algorithms, label your data. Then divide the selected be accurately quantified. This method does not account for data into training, validation, and test sets. Using the training set wasted costs, nor does it consider any unique or novel

is needed to teach the artificial intelligence model, the validation characteristics of the asset. Although a cost-based method is used set to evaluate performance, and the test set to evaluate the final for software value estimation, the combination of various

model. For unsupervised learning, the artificial intelligence elements of protection makes one think about the wisdom of model aims to reveal underlying structures, group similar data,

choosing a revenue-based method [9]. The income method

and discover patterns without the help of labels. The model needs

values the IP asset based on the amount of economic income that

to understand the data by finding commonalities and

it is expected to generate, adjusted to its present-day value. This understanding the features that define a particular dataset. In this method is easiest to use for IP assets with positive cash flows, for case, feature-based clustering of the data is required. This makes those whose cash flows can be estimated with some degree of it easier for the AI model to navigate and learn from unlabelled

reliability for future periods, and where a proxy for risk can be

data. The situation becomes a little more complicated taking into

used to obtain discount rates. The market method is based on a

account reinforcement learning (learning through interaction) comparison with the actual price paid for the transfer of rights to

[5]. Artificial intelligence models involving reinforcement

a similar IP asset under comparable circumstances. This method

learning learn by exploring the specifics of a task in a particular has the advantage of being simple and based on market

environment and performing functions by trial and error. In information, so it is often used to establish approximate values

reinforcement learning, an environment must be simulated for for use in determining royalty rates and inputs for the income the AI model to interact with. However, another level of

method. For cyber industry this type of approach can be highly

complication relates to deep learning (neural networks and

problematic, since products in the cyber crime market are

beyond) , it is an advanced learning mechanism that drives the

evolving very quickly and there is considerable difficulty in AI model and enables it to handle complex actions. AI models

comparing them. Often, it is only possible to make inferences on

with deep learning algorithms require large-scale data collection

the level of effects offered, i.e. expected rather than concrete based on what the model is supposed to do. As deep learning results, due to the widespread confidentiality of information.

algorithms use multiple layers of learning, the goal is to have Companies do not necessarily boast about the ineffectiveness of

different versions of large data sets.

protecting their computers, resources, or access to the cloud.

c)

providing selected data to the AI model and iterative

While one approach may seem particularly well-suited, the final

refinement

value estimation should merge the value indications obtained Once the data has been structured based on the AI model's under different approaches [1], [9]. Irrespective of the choice of learning technique, the data is fed into the AI model. The model

valuation approach, in the situation of innovation, patent, or AI-

learns from the algorithms on which it is built. During the 50

learning stage, the capabilities of the model should be explored based on technology; personal, sensitive, and business data are

for refinement. Without iteration, the model cannot adapt to stored on computers, smartphones, and tablets, so an extensive

changing data and cannot improve its performance when exposed

range of concepts are covered by cyber security - from

to other data sets.

communication to transport, and shopping to healthcare. It is This raises further questions regarding the valuation of

crucial to consider the interrelationships and relationships a given IP. Firstly, how to value a patent with AI, secondly how

between the different types of IP. Depending on the business to assess the level of sophistication of model training, and thirdly needs, an appropriate valuation method should be chosen, taking

how to assess and value the quality of training and validation into account whether the IP relates to AI. When analyzing an AI-data, or more broadly data sets. In addition, in the cyber area, related patent, the relationship to the data, the individual datasets, matters are further complicated by the use of sensitive or and the way the models are taught should be explored. Particular

confidential data, such as tools for detecting illegal, offensive or care should be taken to analyze the quality of the data and to harmful content based on data from law enforcement agencies.

understand the principles of data management (from collection,

An additional legal complication arises.

description, sharing, archiving, etc., including the FAIR principle



– it is an acronym for Findable, Accessible, Interoperable, and

4. RECOMMENDATIONS AND

Reusable). In addition, the origin of the data in the cyber sector CHALLENGES OF VALUATION IN

should be taken into consideration. Moreover, in the cyber area,

further complications are caused by using sensitive or

CYBER SECURITY SECTOR

confidential data, such as tools for detecting illegal, offensive, or harmful content based on data from law enforcement agencies.

4.1 Exploring difficulties

Without high data quality, even the most advanced artificial Nowadays, cyber security plays a crucial role in the global intelligence models will fail. Data quality in the new era of AI

economy. The risk of cyber threats becomes more prevalent and

highlights the key role of data quality in shaping effective data

cyber attacks can have devastating consequences leading to

strategies. The task of the IPR evaluator in cyber products or financial losses, reputational damage, and national security solutions is to evaluate the AI model, and assess how each dataset breaches. Therefore, it is imperative that governments prioritize

is used, how the evaluation process works, which IPRs use it, and

cyber security measures to safeguard their interests. In addition

to what extent, and what parameters influence the business aspect

to economic implications, cyber attacks also pose significant of the entire evaluation process. The process of valuing IPRs is

risks to national security. Governments around the world are highly contextual and requires professional judgment based on increasingly concerned about hacking activities that aim to steal

the experience of the appraiser, now also in terms of data sensitive information or disrupt critical infrastructure systems.

management and understanding of AI development and

Cyber attacks usually modify, access, or destroy sensitive

application phase.

information, extort users' money, or disrupt normal business processes. In 2024, the cyber security industry is expecting a REFERENCES

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[10] WIPO Technology Trends 2019 – Artificial

completely new problems are gaining importance, the valuation

Intelligence, Geneva, Switzerland: World Intellectual

of IPR in the cyber sector will be a further stage of complication Property

Organization,

2019,

and will require knowledge of a great level of AI invention https://doi.org/10.34667/tind.29084

protection and data management. A large part of everyday life is



51





The Challenge of Licensing Artificial Intelligence Technology for Cybersecurity Applications



Michał Rotnicki†



Technology Transfer Department



NASK – national research



institute



Warsaw, Poland

michal.rotnicki@nask.pl





ABSTRACT

It's difficult to quantify the impact of cybercrime on the banking sector, but public data from the US[17] and the EU [16]

The central question of this article is whether the transfer of cyber suggest it is around €4 billion each. The criminals are highly security technology based on neural networks into a production

effective in the search for the optimal strategy of action in order environment poses significant challenges due to the complexity

to steal money from Internet users, while at the same time and time variation of the technical environment, constantly minimizing the legal risk and the resources (effort) involved evolving threats, and regulatory requirements.

Error! Reference source not found.

The article uses observational research techniques for

The criminal’ss resources involved are the use of a technical

cybercrime activities, and experimental research for product method, a socio-technical method, or both, leading to a

management since 2011.

successful theft [5].



The article presents an application case study of behavioural biometrics and artificial intelligence (AI) techniques to detect remote desktop attacks, and technology transfer adaptations to 2 METHODOLOGY

changing conditions.

Since 2007, cybercrime data has been based on natural

The added value of the paper is to draw conclusions from a real

observations. NASK provides Computer Emergency Response

business case observed in internal business activities.

Team (CERT) services at the national level and commercial

threat intelligence services to the main financial institutions in KEYWORDS

Poland.

Cybersecurity, Artificial Intelligence, software licensing,

The case study is an original commercialisation case provided as

software development, low compliance, behavioral biometric, AI

part of the BotSense product offered by NASK.

licensing.

3 THE BANKS, THE THIEVES AND EVEN

1 INTRODUCTION

THE SCIENTISTS

NASK activities are focused on issues of security in

Poland has a population of about 38 million and in the first

cyberspace.

quarter of 2024, the Polish banking sector operates

One of the areas of influence on cyberspace [6] is the approximately 43,5 million accounts retail accounts with

provision of new technologies for counteract cybercrime and contracts allowing access to internet banking. About 23 million

transfer them to commercial IT products. The goal is to increase

accounts are actively accessed via internet banking and about 22

resilience of the banking services and key services supplier [1].

million users access via mobile applications [15]. Since 2007, The banking sector is particularly vulnerable to the activities

NASK has been working with the Polish banking sector to

of commercially motivated criminals [7], who are believed to be identify and counteract theft from Internet banking users. Over

personally motivated in their criminal activities. These are the years, with the improvement of technical methods of

criminals who directly seek to make a profit by seizing the funds

protecting electronic banking, both on the side of the banks and

of electronic banking users.

on the side of the end user, attacks based on vulnerabilities of IT

systems, have been significantly reduced [2] [3]. They required sophisticated technical knowledge, considerable technical



resources and centralised malware management, making such

Permission to make digital or hard copies of part or all of this work for personal or criminal infrastructure vulnerable to law enforcement.

classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full Socio-technical attacks , on the other hand, have experienced

citation on the first page. Copyrights for third-party components of this work must a renaissance, using voice communication techniques to

be honored. For all other uses, contact the owner/author(s).

Information Society 2024, 7–11 October 2024, Ljubljana, Slovenia persuade the victim to provide the criminal with login and

© 2024 Copyright held by the owner/author(s).

authentication credentials for banking transactions and, crucially, 52





to give the criminal access to their device's desktop via a legal

must operate, we can distinguish between technical layers:

remote access application.

device category, hardware, operating system, components of

As a result, the attack scenario does not require any specialist

operating system, web browser.

IT knowledge [9], which has made this method of criminal activity accessible to a wider group of criminals, resulting in a

sharp increase in the number of remote desktop attacks.

At the same time, in a social engineering and remote desktop

attack scenario, there is virtually no event that can be classified as technically incorrect. The user voluntarily provides his or her credentials to the criminal, voluntarily agrees to open a remote

desktop connection, and is often persuaded by the criminal to deliver the final blow by turning off the monitor. This means that no cybersecurity incident occurs in the data transmission channel

between the endpoint and the bank's server.

Analyzing the above, it can be said that a dynamic market model is emerging in which criminals are effectively and

efficiently adapting to the limitation of increasing the resistance of information systems to cyber-attacks. Criminals are creatively



and rationally searching for new effective techniques and crime

scenarios to carry out successful theft. The specific type of Figure 1: Technical layers

attacks mentioned above are those carried out with the unwitting

participation of the victim.

However, overcoming the additional complications posed by



However, banking institutions in particular, burdened by

the diversity of devices, operating systems and web browsers legislation [11], are forced to search for ever new technical does not guarantee the achievement of a stable, transferable solutions to identify electronic banking sessions compromised by

technology. The whole technical environment described above is

criminals.

evolving. For example, the major web browsers, Chrome [13]



From a technology transfer perspective, this raises the non-

and Firefox [14], are released on a monthly basis. This means obvious problem of how to organize the process of technology

that, the technical conditions under which cybersecurity

transfer to combat criminals.

technology should operate are constantly changing.



It should also be noted that changes affecting the security of



the operating system and web browser may be made between the

scheduled release dates of new versions and may involve

4 Case Study - Behavioral biometrics and

unpredictable technical changes.

artificial intelligence techniques to detect a

In addition, there are other elements in the formal-legal field

[11] that we should consider, such as: international and national access via Remote Desktop

legislation,

technical

legislation,

standards,

norms,

NASK set up an internal research project to work on an AI

recommendations and internal company regulations.

model capable of analysing how an end user uses a keyboard to



identify themselves. In a laboratory environment, this is a task

that requires a certain number of experiments, the construction

of relevant data sets and the application of technical expertise,

but in principle the level of scientific risk is limited. However, when it comes to transferring the developed technology to a production application that is expected to operate at a certain minimum level of effectiveness for the entire population using ebanking, the issue becomes much more complicated.

Even if the expected level of efficacy is auxiliary, e.g. 70%,

and unrepresentative individuals are discarded from the user population.

4.1 The cybersecurity technology ecosystem

Cybersecurity technologies require deep and precise technical



integration with the environment to be protected. For example,

tracking the use of a keyboard via a web browser, as a function

Figure 2: Formal layers

of the time can be disrupted by the security mechanism

We are also seeing dynamic changes in the way criminals

embedded in that web browser. One of the security mechanism

operate: variability of attack scenario and variability of tools.

implemented by vendors is randomization of selected user



behavior data and disrupt the time line data.





If we take the oversimplification of identifying the main

layers of the environment in which cybersecurity technology 53





4.2 The challenge of licensing

As a result, a solution developed in the laboratory will either

start to fail immediately when deployed on the entire population,

or it will start to fail over a finite period of time (as a function of time). This phenomenon has no risk characteristics, but is an inherent feature of the cybersecurity technology ecosystem.



The question is how to structure the process of technology transfer and licensing in this dynamic ecosystem?

In the process of technology transfer, we can distinguish:

1.

Stage I - licensing the results of the R&D team and



transferring them to the product development team (in

this case software),

Figure 3: Criminal activity

2.

Stage II - advising the product development team on

how to incorporate the innovation into the

And, of course, criminals are constantly identifying banking

manufacturing environment.

security techniques and bypassing or neutralising them [10].

We can think of cyber technology as a black box influenced

Such an approach is not rational and will fail if we apply it to the by the forces of many independent parameters.

transfer of cybersecurity technology.

As in physics, the degrees of freedom (DOF) of a mechanical



system is the number of independent parameters that define its

This is because there is a high probability that the transferred

configuration or state.

technology will need to be modified before it is fully



implemented in the product.

This will make the whole process infeasible and banks will

start looking for non-IT methods to fight crime.



4.3 Practices applied

For technology transfer in the cyber domain, the NASK

has adopted its own specific operating procedures.

First, the cybersecurity technologies developed in the NASK

R&D teams are transferred to internal development teams.

By technology, we mean the form of a method, algorithm or

learned AI model. The development team then builds a finished

software component on top of it.

After that, the R&D team still, support and develop



technology. The R&D teams are prepared for long-term

development of the technology for detection of specific types of

Figure 4: Forces affecting cyber security technology

attacks, including its modification in the event of a change in the conditions of the technical environment in which the technology

A useful technology should be in balance between these

is to operate (e.g. loss of access to data relevant for detection).

parameters. If one vector increases, it means there's a need for

Such organisation of technology production and preparation

action.

for transfer enables the temporary licensing of the finished A multi-layered dynamic model of the variability of the

software component, which allows the use of the cybersecurity

environment is thus created, which seeks an equilibrium that technology for implementation in software. The license contains

includes the success rate of attacks. The stimulating (agonistic)

a number of specific conditions tailored to the cybersecurity factor is the activity of criminals and the antagonistic (inhibitory) ecosystem, the main ones are:

factor is the development of security technologies. Another two

parameters, which can be both agonistic and inhibitory, are 1.

an assurance that the licensee will adapt the technology

changes in the technical or formal domain. Both can improve or

to changes in the technological environment,

reduce the effectiveness of cybersecurity technology. What is 2.

an obligation on the licensee to improve the technology

certain, however, is that all of these parameters create a need for in the event of a decline in the effectiveness of attack

constant review and adaptation of the technology.

detection,



3.

an limitation of the licensor's liability for failure to



adapt the technology to changes in the technological



environment or to changes in the activity patterns of

the perpetrators.

54

These points are almost impossible to define precisely. They are declarative in nature, with no strict guarantees from either For future work, it is possible to approach techniques to assist in party. The technology provider cannot reliably guarantee the predicting the effects of the changing environment.

effectiveness, cost or time it will take to modify its technology, and the recipient cannot guarantee the conditions under which it

REFERENCES

expects the technology to be effective.



In other words, the factor that determines the balance between

[1]

Directive (EU) 2016/1148 of the European Parliament and of the Council of 6 July 2016 concerning measures for a high common level of security the technology provider and the technology recipient is a

of network and information systems across the Union

common rational economic interest. And the basis for deciding

[2]

Raport Roczny z Działalności Cert Polska 2023, NASK 2023

on such a cooperation model should not be so much an

[3]

Annual Report From The Actions Of Cert Polska 2022, NASK 2023

[4]

Successful Technology Licensing, World Intellectual Property assessment of the effectiveness of the technology at the time of

Organization (2015), ISBN 978-92-805-2633-2,

its production, but rather the ability of the technology provider to

[5]

Lella I., Tsekmezoglou E., Theocharidou M., Magonara E., Malatras A., Svetozarov Naydenov R., Ciobanu C. Enisa Threat Landscape 2023, modify and develop the technology to keep pace with changes in

October 2023, ISBN: 978-92-9204-645-3

the application environment within a reasonable period of time.

[6]

Hogan M., Newton E, Supplemental Information for the Interagency Report on Strategic U.S. Government Engagement in International Standardization to Achieve U.S. Objectives for Cybersecurity, NISTIR

8074 Volume 2, 2015

5 Conclusion

[7]

Troy E. S., A Conceptual Review and Exploratory Evaluation of the Motivations for Cybercrime, August 2013

The transfer of ICT technologies for cybersecurity may force

[8]

Gargir Sarkar, Sandeep K. Shukla, Behavioral analysis of cybercrime: a different way of thinking about building a collaborative model

Paving the way for effective policing strategies, Journal of Economic Criminology, Volume 2, December 2023

with business [12]. Thinking of collaboration with business as a

[9]

Phiri. J., Lavhengwa, T., Segooa M.A., Onlinebanking fraud detection: one-off design phenomenon may prove to be a dead end. To Acomparative study of casesfrom South Africa and Spain, South African Journal of Information Management 26(1), a1763., 2024

ensure a steady flow of solutions for business in a rapidly

[10]

Tapiwa Mazikana A., Development of a Predictive Model for Online changing environment, it is worth considering a process model

fraud Detection in the Banking Sector. Case Study of First Capital Bank, of collaboration [4].

Journal of Machine Learning Research, May 2024,



[11]

Harnay S., Scialom L., The influence of the economic approaches to The example case study analyses the behavioral biometrics

regulation on banking regulations: A short history of banking

project and the AI technology used. However, the issue seems

regulations, Cambridge Journal of Economics 40(2), April 2015

[12]

Larsson B, Rolandsson B. , Ilsøe A., Masso J., Digital disruption relevant to any application of technology or methodology in an

diversified-FinTechs and the emergence of a coopetitive market unstable cyberspace environment.

ecosystem, Socio-Economic Review, July 2023

[13]

The fundamental value of collaboration is to ensure the ability



Chrome RoadMap, https://chromestatus.com/roadmap , 10.08.2024

[14]

Firefox Release Calendar

to solve a class of research problems within a reasonable time

https://wiki.mozilla.org/index.php?title=Release_Management/Calendar

and cost. The process for sharing further technologies developed

&redirect=no, 10.08.2024

[15]

Barbrich P., Nocoń B., NetB@nk bankowość internetowa i mobilna, on the basis of the first project should be proposed in advance.

płatności bezgotówkowe, Polish Bank Association Raport I Kwartał, The initial project or technology licensing is therefore only a 2024

starting point for long-term collaboration. It's also necessary to

[16]

2024 Report On Payment Fraud, European Central Bank 2024

[17]

Global Banking Fraud Index 2023,

rethink the organisation of technology transfer agreements.

https://www.ecb.europa.eu/press/pr/date/2024/html/ecb.pr240801~f21cc

Towards a collaborative framework and the definition of a

4a009.en.html , 18.09.2024



dynamic research process.



55





Technology Transfer: Revenues Estimation

in the Cyber Security Sector

Michal J. Falkowski†

Jaroslaw Kaminski

Marta Wachowicz

Technology Transfer Department

Technology Transfer Department

Technology Transfer Department

NASK National Research Institute

NASK National Research Institute

NASK National Research Institute

Warsaw, Poland

Warsaw, Poland

Warsaw, Poland

michal.falkowski@nask.pl

jaroslaw.kaminski@nask.pl

marta.wachowicz@nask.pl

ABSTRACT

1.1 Defining cyber security product

This study investigates the complexities of technology transfer

within the cyber security sector, focusing on the financial and

Given the multidisciplinary nature of cyber security and its

operational challenges posed by its dynamic nature. The primary

widespread impact on society, it is essential to establish, utilize, research problem is understanding how to define final cyber

and elaborate a standardized terminology and develop a

product and estimate associated costs, particularly in the context comprehensive, shared understanding of what constitutes cyber

of both traditional and new economy revenue models.

security product and economic risks associated with it [7].

Preliminary findings reveal significant discrepancies in cost

In defining a cyber security product, it is crucial to recognize

estimation and revenue forecasting, particularly due to the non-

the role of interdisciplinary contributions, ranging from

linear contributions of scientists, which complicate the creation

computer science and engineering to law, economics, and human

of effective license agreements. The paper offers a framework to

factors. For instance, a cyber security product may include not

better align technology transfer processes with the unique

only technical components, such as encryption algorithms or

characteristics of cyber security innovations, thus improving the

intrusion detection systems, but also legal frameworks and

accuracy of cost projections and licensing strategies.

organizational practices that enhance security. The integration of these diverse elements requires a standardized terminology that

KEYWORDS

can be universally understood across disciplines, enabling

effective communication and collaboration.

Technology transfer, cyber security sector, revenue estimation,

Moreover, the definition of a cyber security product must

AI models, new economy, science contribution, license

account for its intended purpose and scope. Products may vary

agreements

significantly in their focus - some are designed to prevent

unauthorized access, others to detect intrusions, and yet others to 1 UNCERTAINTIES IN CYBER SECURITY

respond to or recover from cyber incidents. This diversity

TOOLS SPECIFICATION

necessitates a clear classification system that categorizes

products based on their functionality, target environment, and the Cyber security is a term with widely varying definitions that are

specific threats they address. For example, network security

frequently subjective and, in some cases, lack precision.

tools, endpoint protection software, and identity management

According to the America’s Cyber Defense Agency (CISA), it is

systems each serve different purposes but collectively contribute

defined as the art of protecting networks, devices, and data from to a comprehensive cyber security strategy.

unauthorized access or criminal use and the practice of ensuring Economic considerations also play a critical role in defining

confidentiality, integrity, and availability of information [11].

cyber security products. The value of a cyber security product is

The absence of a clear, universally accepted definition that

often measured by its effectiveness in mitigating risks, which are encapsulates the multidimensional nature of cyber security

themselves subject to economic assessment. The economic

hinders progress in technology and science [6]. This is because it impact of cyber threats, the cost of deploying and maintaining

reinforces a technical perspective on cyber security, while

cyber security products, and the return on investment are all

simultaneously isolating disciplines that should be collaborating

factors that influence how a cyber security product is defined and to address complex cyber security challenges effectively. The

evaluated. This underscores the importance of aligning technical

complexities involved significantly affect the determination of

definitions with economic realities to ensure that cyber security

what constitutes a cyber security product, the criteria for deeming investments are both effective and sustainable.

it complete, and the estimation of production costs within defined Furthermore, the lifecycle of a cyber security product must be

timeframes and budgetary constraints.

clearly delineated, from initial development through deployment,



operation, and eventual decommissioning. A comprehensive

†Author Footnote to be captured as Author Note

understanding of this lifecycle is necessary to establish criteria for when a product can be considered complete and to identify

Permission to make digital or hard copies of part or all of this work for personal or potential risks and vulnerabilities that may arise at various stages.

classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full This lifecycle approach also highlights the importance of

citation on the first page. Copyrights for third-party components of this work must adaptability in cyber security products, as they must evolve to

be honored. For all other uses, contact the owner/author(s).

Information Society 2024, 7–11 October 2024, Ljubljana, Slovenia address emerging threats and changing environments.

© 2024 Copyright held by the owner/author(s).

56

In summary, defining a cyber security product requires a vulnerabilities, which can involve both software

multidisciplinary approach that integrates technical, legal,

patches and hardware upgrades. Additionally,

economic, and operational perspectives. Standardized

operational costs include the resources required to

terminology and clear classification systems are essential to

monitor the product's performance, respond to security

fostering a shared understanding across disciplines, while

incidents, and conduct regular security assessments.

economic considerations and lifecycle management provide the

The need for highly skilled personnel to manage these

framework for evaluating the effectiveness and sustainability of

tasks further contributes to operational costs, as cyber

cyber security products.

security expertise is often in high demand and short

supply.

1.2 Estimating cyber product costs

4. Decommissioning Costs: At the end of its lifecycle, a

A standardized method for measuring and managing the costs

cyber security product must be decommissioned,

associated with implementing cyber security programs has yet to

which involves safely removing it from the

be established. To advance research and practice in this field,

environment and ensuring that no residual

various cost estimation frameworks related to the development

vulnerabilities remain. Decommissioning costs may

and deployment of cyber security products have emerged in

include data migration, system reconfiguration, and the

recent years [9]. Estimating the costs associated with cyber disposal of outdated hardware. Additionally,

security products is a critical aspect of cyber security planning

organizations may need to invest in new cyber security

and management. However, this task is fraught with uncertainties

products to replace those being decommissioned,

due to the dynamic and evolving nature of cyber threats, the

adding to the overall cost.

complexity of cyber security products, and the diverse

Estimating these costs is complicated by several factors,

environments in which they are deployed [8]. Unlike traditional including the unpredictability of cyber threats, the rapid pace of products, cyber security products must continuously adapt to an

technological change, and the variability in organizational needs

evolving threat landscape, where new vulnerabilities and attack

and environments [10]. It means that a cyber security product vectors emerge regularly. This requires ongoing updates, patches,

may require extensive customization and integration efforts,

and upgrades, leading to unpredictable and often escalating

which further complicates cost estimation. For example, the

operational costs over time.

introduction of disruptive technologies, such as quantum

Cost estimation for cyber security products involves several

computing, can render existing cyber security products obsolete,

key components: development costs, deployment costs,

necessitating additional investments.

operational costs, and decommissioning costs. Each of these

The need for specialized personnel to manage and maintain

components must be carefully assessed to provide an accurate

cyber security products, combined with the scarcity of cyber

estimate of the total cost of ownership (TCO) for a cyber security security expertise, adds another layer of complexity to cost

product.

forecasting. Furthermore, the consequences of underestimating

1. Development Costs: These include the expenses

the costs must be carefully considered, as they are often

incurred during the design and creation of the cyber

significant and far-reaching, potentially resulting in insufficient security product. Development costs can vary widely

protection and increased risk exposure. This contrasts with other

depending on the complexity of the product, the

products, where cost overruns might primarily affect financial

technologies involved, and the level of expertise

performance without posing immediate security risks. Therefore,

required. For example, developing an advanced threat

the cost estimation of cyber security products must account for

detection system may involve significant investment in

not only the tangible costs of development, deployment, and

research and development, including the use of

maintenance but also the intangible costs associated with risk

machine learning algorithms, data analysis tools, and

management and the potential impact of cyber incidents.

security protocols. Additional y, the need for

To address these uncertainties, organizations must adopt a

compliance with industry standards and regulations

flexible and adaptive approach to cost estimation. This may

can add to development costs, as products must be

involve using scenario analysis, which considers different

designed to meet specific security requirements.

potential future states and their impact on costs, as well as

2. Deployment Costs: Once a cyber security product is

incorporating risk assessments to identify and quantify potential

developed, it must be deployed within the target

cost drivers. Additionally, organizations should consider the total environment. Deployment costs include the expenses

cost of ownership over the entire lifecycle of the cyber security

related to integrating the product with existing systems,

product, rather than focusing solely on upfront costs. This

configuring it to meet organizational needs, and

approach ensures that all relevant costs are accounted for and

training personnel to use it effectively. In some cases,

provides a more accurate estimate of the long-term financial

deployment may also involve significant infrastructure

commitment required to maintain cyber security.

upgrades, such as installing new hardware or

enhancing network capabilities. These costs can be

substantial, particularly in large or complex

2 METHODOLOGY

organizations with extensive IT environments.

To address issues, this study employs a mixed-method approach.

3. Operational Costs: The ongoing operation of a cyber

An extensive literature review is conducted. Relevant academic

security product generates costs related to maintenance,

journals, industry reports, and government publications are

monitoring, and updates. Cyber security products must

examined. Additionally, qualitative data is collected through

be continuously updated to address new threats and

semi-structured interviews with key specialists and experts.

57

3 REVENUE ESTIMATION AND The income method of technology valuation is grounded in COMPANIES VALUATION

the belief that for a potential investor, a particular asset is worth as much as he can get income from that asset. The risk of the

Cyber security is the practice of protecting individuals’ and

business and the time value of money should be considered.

organizations’ systems, networks, applications, computing

Valuation of technology using the income approach requires

devices, sensitive data, and financial assets against any digital

determination of the period of economic usefulness of the valued

attacks [3]. It refers to any technology, measure, or practice for technology. It is done based on projected cash flows discounted

preventing cyberattacks or mitigating their impact. We could

at an appropriate discount rate. The income method is most often

categorize the main components of cyber security into the

indicated as the most appropriate for valuing technology for

following areas: cyber security Governance, Policies, and

which there is a high degree of confidence in the forecasts of

Procedures, User Identity and Access Management, Network

operating income.

Security, Application Security, Data Protection, Business

Market (comparative) methods of valuing intellectual

Continuity and Disaster Recovery Plan, Education. The number

property, on the other hand, involve estimating the value of

of fields results in miscellaneous cyber security business models, technology based on a comparison to market transactions for

reflecting various comprehensive solutions in the evolving

similar assets. However, information on transactions for the

landscape of cyber threats and swift pace of technological

purchase or sale of intellectual property is rarely publicly

advancement. The differences are both in revenue streams, cost

available. Therefore, the method often uses an analogy with the

structures and scalability.

valuation of technology companies, whose value depends largely

3.1 Cyber security business models

or entirely on the technology they own. The main shortcoming

of this method is the inability to identify comparable technology.

We can distinguish three basic revenue streams: subscriptions,

As a rule, each innovative technology is unique and has specific

professional services, and licensing [5]. In first case cyber parameters, which leads to limited possibilities of comparison to

security firms offer their services on a subscription basis,

existing solutions known to date.

providing continuous protection with regular updates and

support in exchange for a recurring fee. This model ensures a

3.3 Companies’ valuation in cyber security

steady and predictable revenue flow, development of customer

sector

relationships, mutually beneficial vendor relationships with

major focus on customer procurement. Cyber security companies

The Market Multiples method is a key tool for valuing companies

focused on professional services as business model often offer

in the cyber security industry. This approach involves valuing a

consulting, threat assessment, and response services. These

firm by comparing it to similar private or recently acquired

include penetration testing, incident response teams and security

companies in the sector. Specifically, it focuses on two primary

audits. Finally, many companies operate under licensing model -

types of multiples: Revenue Multiple and EBITDA (Earnings

selling licenses for proprietary security software or technology

Before Interest, Taxes, Depreciation, and Amortization)

solution could be significant revenue stream, creates an easier

Multiple. For startups (especially those that are pre-profit) the

entry into foreign markets, does not require capital investment or Revenue Multiple is often more relevant. It compares the

presence of the licensor in new geographical regions.

company's value to its revenue, offering a perspective on how the

market values the revenue generated. For more mature

3.2 Classic technology valuation

companies (with significant earnings), the EBITDA Multiple

provides a view of the company's value relative to its profitability Tech spending as a percentage of revenue has increased from

before accounting for financial and accounting factors.

3.28% in 2016 to 5.49% in 2023 [4]. With bigger budgets often Applying the Market Multiples method effectively requires a

comes increased oversight and expectations from the business-

deep understanding of market trends and financial metrics

tech leaders are becoming thoughtful about allocating capital for

specific to the cyber security sector. The rapidly evolving nature tech investments. 2023 Deloitte research shows that 6 in 10

of cyber security, with frequent technological innovations and

executives struggle with measuring the value of these

varying threat landscapes combined with investor confidence in

investments. The choice of an appropriate valuation method

the sector's growth can significantly influence these multiples.

depends on the circumstances, scope, and purpose of the

The most common purpose of technology valuation is the needs

valuation – the three main approaches concentrate on the cost,

for commercialization of completed development work in R&D

market, and income.

Units. It is determined as part of the commercialization of

Cost methods determine the value of intellectual property

technology, the value of the sale to an external investor or in-kind based on the historical cost of production or the estimated cost of contribution to a special purpose vehicle (SPV or Spin-off). Prior replacement with assets of comparable utility. These methods

to the commercialization of intellectual property, there is often a involve considering any expenses that need to be incurred to

need to determine the value of these intangible assets and whole

remanufacture the asset or replace it with an asset comparable to

company. Another reason, also encountered, for the valuation of

the one being valued. Cost methods are applied mostly to

technology is the need to recognize the fair value in the

unfinished or easily manufactured technologies. It is possible to

accounting books. Less common are cases of estimating the

imagine situations in which a relatively considerable sum of

value of technology for litigation, where it is required to

money has been spent on a technology that does not produce the

determine the value of the subject matter of the dispute or under

anticipated benefits. In such a case, the valuation of technology

collateral for financial instruments. In the case of cyber security by the cost method may significantly overestimate its value, and

technology and company valuations, it is useful to define the

income methods will come to the rescue.

circumstances valuation determines purpose: accounting, market

58

(for the current owners or new investors) or liquidation. It would programmers and software developers, and there is no space for

be desirable to strike a balance between qualitative and

discovering independent universal truths in the sense of

quantitative measures.

breakthrough ideas or inventions. We observe the non-linear

contribution of the researcher to the development of the cyber

security product. For TTOs, this is an additional complication,

4 IMPLICATIONS FOR TECHNOLOGY the connection of the author to his work is strong, and the cyber TRANSFER OFFICES

security market forces not only close teamwork but also IT and

From the point of view of technology transfer and

data professionals themselves are gaining in importance. Data

commercialization of scientific results, managing the process of

stewards have a significant impact on the development of AI

new solution building using AI models is particularly difficult.

models and thus cyber products. For TTO is a difficulty related

The problematic question of revenue estimation implies further

to the progress and commercialization plans for a specific

issues related to the creation of licensing or distribution

solution.

agreements; additional complications also arise from the very

characteristics of AI models. First, there are several problems

4.3 Risks in license agreement

associated with the application and obtaining Intellectual

Forming a license agreement for a product or solution using an

Property Rights (IPR) protection for such solutions. Secondly,

AI model requires considering the strict characteristics of

cooperation with scientists is done in close cooperation with

training AI models, the difficulty of determining milestones for

software developers, and scientific input is expected not in the

model development, and the system of subscription or license

entire process. Third, the solutions for specific markets generate fees depending on the stage of learning or re-learning the model.

several difficulties in shaping models for licensing agreements

The fundamental difficulty in estimating and establishing profit

for the cyber security industry.

or revenue models depending on the development of machine

learning lies in the indefiniteness of the solution itself. Models 4.1 Intellectual Property Rights protection

need successive iterations, the cost of software development

When considering patenting AI-related inventions, there is a

changes, and the demand for certain solutions also changes,

need to answer the fundamental questions of whether inventions

which makes it exceedingly difficult to forecast profits and build qualify for patent protection. In European system, while a

a model of fees and payments in a license agreement. The

computer program or software may not be patentable, artificial

described problem of revenue estimation forces the adaptation of

intelligence and machine learning that serve or achieve a

cyber security solutions using AI models of licensing agreements

technical purpose may be a desirable alternative. The newest

and billing systems, a thorough reflection is needed in the society EPO guidelines [2], require the mathematical methods and of technology transfer professionals on this subject.

training data used by an AI-related invention to be disclosed in

sufficient detail to reproduce the technical effect of the invention over the whole scope of the claims. To address these issues and

5 CONCLUSION

prepare a commercialization plan for the cyber security market,

Developing a more precise and universally accepted definition of

Technology Transfer Offices should identify the territories for

cyber security products is essential for standardizing cost and

patent protection for their AI inventions and assess whether such

revenue estimation processes. Authors will focus on robust

inventions meet the relevant subject matter eligibility criteria. If methodologies to account for the non-linear contributions of

AI-related patent protection seems unfeasible and ineligible,

R&D teams in cyber security, as current models are inadequate.

TTO should consider protection using trade secrets or other

These areas will dictate the trajectory of future research, reducing alternatives. Protecting rights to training data, AI output, and

uncertainties in product finalization and financial forecasting.

other crucial training data requires attention, awareness, and

careful action.

REFERENCES

[1] Science Council, August 2024, <https://sciencecouncil.org/about-

4.2 Relations with scientists

science/10-types-of-scientist/>

[2] Guidelines for Examination in the European Patent Office (2024), AI is forcing a change in the attitude of scientists, from that of a ISBN 978-3-89605-361-9

strict researcher to one that is far more oriented toward creating

[3] CISCO, August 2024, <https://www.cisco.com/site/us/en/learn/topics

/security/what-iscyber security.html>

a working IT system. In terms of describing the types of scientists

[4] Global Technology Leadership Study, Deloitte 2023

according to the Science Council, one can explain the change in

[5] Cyber security Startup Valuation Report, Finro 2024

[6] Diakun-Thibault, Nadia. (2014). Defining Cybersecurity. Technology attitude of the Explorer Scientist to the Developer Scientist [1].

Innovation Management Review. 2014. DOI: 10.22215/timreview/835

This reflects a commitment to the area of creating AI solutions

[7] Cains M.G., Flora Liberty, Taber Danica, King Zoe, and Henshel Diane.

for specific and demanding markets.

(2021). Defining Cyber Security and Cyber Security Risk within a

“The Explorer Scientists

Multidisciplinary Context using Expert Elicitation. Risk Analysis. 42.

rarely focus on a particular outcome or impact, rather they want DOI: 10.1111/risa.13687.

to know the next piece of the jigsaw of scientific understanding

[8] Leszczyna Rafal and Litwin Adrian. (2020). Estimating the Cost of Cyber security Activities with CAsPeA: A Case Study and Comparative and knowledge. […] The Investigator Scientist digs into the

Analysis. DOI: 10.1007/978-3-030-65610-2_17.

unknown observing, mapping, understanding, and piecing

[9] Radziwill Nicole. (2017). Cyber security Cost of Quality: Managing the Costs of Cyber security Risk Management. Software Quality

together in-depth knowledge and data, setting out the landscape Professional. 19. DOI: 10.48550/arXiv.1707.02653

for others to translate and develop” [1]. The scientist is needed

[10] Basholli Fatmir and Juraev Davron. (2024). Framework, tools and at specific moments, the innovation forces seasonal involvement,

challenges in cyber security. 1. 96-106. DOI:

10.13140/RG.2.2.21009.24161

the product is created more as a result of collaboration with

[11] America’s Cyber Defense Agency, August 2024,

<https://www.cisa.gov>

59





Prospects for the Use of AI Tools in the Republican Centre for Technology Transfer Network

Alexander Uspenskiy

Aliaksei Uspenski

Maxim Prybylski

Republican Centre for

Republican Centre for

Republican Centre for

Technology Transfer

Technology Transfer

Technology Transfer

Center for System Analysis and

Center for System Analysis and

Center for System Analysis and

Strategic Research of the National

Strategic Research of the National

Strategic Research of the National

Academy of Sciences of Belarus

Academy of Sciences of Belarus

Academy of Sciences of Belarus

Minsk, Belarus

Minsk, Belarus

Minsk, Belarus

uspenskiy@mail.ru

auspen79@gmail.com

m.pribylsky@hotmail.com



ABSTRACT

documentation associated with files that will remain accessible

even several years after the file is closed (the data is the

The paper informs about services and information resources

property of the client);

provided by the Republican Centre for Technology Transfer

– automation of interaction between all participants in

(RCTT) to innovation activity agents and prospects for the use

international cooperation;

of AI tools in the RCTT Network in order to improve the

– direct access to file information from anywhere where

quality and speed of preparing profiles (technology

there is an Internet connection, even from mobile devices and

offers/requests, business offers/requests and R&D requests),

smartphones.

creating promotion and marketing content to find potential

United Nations System White Paper on AI Governance [2]

partners, drafting contracts, etc.

suggests an increasing recognition of AI's role in amplifying the

KEYWORDS

work of governments and international bodies. Additionally,

Gartner predicts a staggering 80% of project management tasks

Technology transfer (TT), AI, generative AI, technology

will use AI by 2030 [3], a testament to the growing reliability

transfer offices (TTOs)

and trust in AI technologies within structured operational

frameworks.

1 INTRODUCTION

Since 2023 the use of AI in the work of technology transfer

offices (TTOs) has been regularly discussed at webinars of the

"Will AI be replacing people in the near future?" "It looks to me Association of University Technology Managers (AUTM).

like, and for a while, AI is much better at doing tasks than

On May 5, 2023, a webinar "Generative AI has Arrived:

doing jobs. It can do these little pieces super well, but

Essential Knowledge for TTOs" was held, which explained:

sometimes it goes off the rails. It can't keep very long

What is generative AI? Why should you care? The current state

coherence. So, people are instead just able to do their existing

of AI and applications, such as ChatGPT, that are already at

jobs way more productively, but you really still need the human

your disposal. How you can implement these tools in your

there today." Sam Altman, CEO of Open AI.

office, some of the most pressing risks and concerns your office

As noted in the UNECE White Paper on the use of Artificial

might face, and a look into what's coming next.

Intelligence in Trade Facilitation [1], artificial intelligence (AI) On March 3, 2024, a webinar "The AI Enabled TTO" was

is an enabling technology impacting the global economy and

held, where the use of AI by TTOs to improve the efficiency of

international trade. Combined with business-process-oriented

their work was discussed, in particular to: automate routine

automation and more efficient data flow exchanges, AI further

tasks, analyze market trends, assess competitors, assess

promises to lift barriers to international trade, stimulate growth intangible assets, speed up decision-making and optimize

in global electronic commerce and allow for better predictions

resources.

and associations to inform policy decisions.

On May 2, 2024, a webinar "Tailoring Your AI Tools for

The benefits of AI-based systems include:

Tech Transfer Transformation" was held. This webinar explores

– reducing the time spent on working with one document by

customizing AI tools to better support unique tech transfer

more than 80%;

processes and goals.

– reducing the number of errors in procedures;

Video recordings and presentations of these webinars can be

– creating centralized repositories of information and

found on the Internet portal of AUTM [4].



Participation in the above webinars, as well as the analysis

Permission to make digital or hard copies of part or all of this work for personal or of publications [1–6] shows that, AI can be used in the work of

classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the TTOs to:

the full citation on the first page. Copyrights for third-party components of this

– improve the quality of profiles (technology offers/requests,

work must be honored. For all other uses, contact the owner/author(s).

Information Society 2024, 7–11 October 2024, Ljubljana, Slovenia business offers/requests and R&D requests) published in the TT

© 2024 Copyright held by the owner/author(s).

networks;

60

– analyze big data to identify potential technologies for TT, the NAS of Belarus"; "New partnership opportunities", to as well as to predict market trends and demand;

present in real-time offers and requests from RCTT, NATT,

– monitor patents and publications – AI can monitor

AUTM and EEN networks; "Catalogs"; "Manuals"; "Media"; publications and patents related to a particular technology to

"Commercialization", with subsections "IP auctions", assess interest from the scientific community and industry;

"Investment and venture funds", "Crowdfunding" and

– search for technologies – use machine learning algorithms

"Technoparks of Belarus"; "IP insurance"; "Legislation", to search for and compare technologies, patents and research

covering the laws and regulations applicable to innovation

results that can be commercialized or licensed;

activity in Belarus and foreign countries, and others.

– automate processes – AI can help automate routine tasks

RCTT provide services to more than 250 Belarusian state

such as technology and intangible asset assessment, document

organizations, private enterprises and individuals. The National

management and licensing processes;

Academy of Sciences, Belarusian State University, Belarusian

– predict risks – analyze risks and possible obstacles in

National Technical University are among its clients. In 2003–

technology transfer using machine learning methods to predict

2024 with the support from RCTT more than 8500+ persons

the likelihood of project success;

improved their skills in the filed of technology transfer at 650+

– improving communication – using chatbots or neural

national and international events (workshops, conferences,

networks to interact with potential partners and clients.

exhibitions).

RCTT is the coordinator of the Republican Center for

Technology Transfer Network which contains more than 3000

2 SERVICES AND INFORMATION

technology offers, technology requests, business offers,

RESOURCES PROVIDED BY THE

business requests, and offers for cross-border R&D

REPUBLICAN CENTER FOR

collaboration of Belarusian enterprises and organizations.

TECHNOLOGY TRANSFER TO

As of August 2024 the Internet portal of RCTT contains:

INNOVATION ACTIVITY AGENTS

– 1120+ cooperation offers from NASB organizations in

Russian language and 1010+ in English language,

Tasks set for RCTT:

– 45+ catalogs, presenting services and products of

– create and maintain information databases meant for

organizations of the National Academy of Sciences of Belarus

serving clients in the technology transfer sector;

in Russian, English and Chinese,

– provide RCTT clients with access to foreign technology

– information about 250+ exhibitions, 50+ brokerage events,

transfer networks;

210+ webinars and events in the field of intellectual property

– assist innovation activity agents in development and

management, transfer and commercialization of technologies

promotion of their innovation and investment projects;

where organizations of the NAS of Belarus took part (will take

– train specialists in research- and innovation-related

part) in 2019–2024,

entrepreneurship;

– 50+ educational materials in the field of IP management,

– establish RCTT offices across the country, to create a

technology transfer and commercialization.

unified national network of technology transfer centers;

– promote international technical and scientific cooperation

and exchange of experts.

3 PROSPECTS FOR THE USE OF AI TOOLS

RCTT is a consortium with the headquarters in Minsk that

IN THE RCTT NETWORK

comprises [7, 8]:

– 5 regional offices and 30 branch offices at research

RCTT plans to use AI tools to solve the following problems:

organizations, institutes, universities, enterprises in Brest,

– automation and improvement of the quality of profile

Vitsebsk, Homel, Hrodna, Lida, Minsk, Mahileu, Novapolatsk

preparation (technology offers/requests, business

and other cities and towns across Belarus;

offers/requests and R&D requests);

– 98 foreign partners in 23 countries: Armenia (3),

– creation of promotion and marketing content to find

Azerbaijan (2), China (25), the Czech Republic (2), Denmark

partners;

(1), Germany (4), Georgia (1), India (1), Iran (1), Italy (1),

– automatic scanning and analysis of Internet resources,

Kazakhstan (6), Lithuania (1), Moldova (1), Poland (3), Russia

scientific publications, patents, catalogs and other data sources

(25), South Africa (1), South Korea (4), Sweden (1), UK (2),

to identify competitors and potentially valuable technologies;

the USA (3), Ukraine (7), Uzbekistan (1), Vietnam (2);

– identification of technologies that can be successfully

– 2 overseas field offices in China.

commercialized by matching the proposed technologies and

RCTT has implemented over 400 projects, including over

services with market needs;

100 international projects funded by UNDP, UNIDO, CEI, EU,

– determination of optimal product promotion channels and

the Swedish Institute, etc.

optimization of marketing strategies;

RCTT experts are certified members of 14 foreign

– support of the negotiation process by providing

technology transfer networks.

information on market prices, transaction terms, etc.;

RCTT offers its services to innovation activity agents in

– monitoring and management of the commercialization

Belarus as well as foreign companies and investors.

process. After a contract is concluded, AI can be used to track

RCTT has a web-portal [9], with several subject sections

progress in commercializing the technology and identify

and databases such as: "Virtual exhibition of the NAS of

possible problems or opportunities;

Belarus"; "Catalogue of innovation offers by organizations of

– improvement of communication – use of chatbots or

neural networks to interact with potential partners and clients. A 61

chatbot is created to build a dialogue with the user. It simulates

– Dataminr is a platform for monitoring news and social a conversation between real people and can respond briefly to a

media using machine learning. It allows you to discover events,

simple request or construct a complex conversation with a high

trends and competitors that may be important for a specific

level of personalization. Neural networks are a type of machine

business or research;

learning in which a computer program works on the principle of

– Crayon is an online competitor and technology monitoring the human brain, using various neural connections. A neural

platform. It uses machine learning to automatically scan

network can be either a learning or self-learning system.

websites, social media, and other data sources to provide

As part of the modernization and development of the

insights into the competitive landscape and emerging

automated system of information support for innovation

technologies;

activities and technology transfer in the NAS of Belarus (ASIS

– Cortico is a data analysis tool that uses artificial IATT), commissioned in December 2021 [10], on the basis of

intelligence to process and classify information from various

which the RCTT network operates, the following work is

sources, such as the Internet, news articles, and social media. It planned:

can help identify trends, competitors, and new technologies.

1. Analysis, selection and adaptation of AI models for

Integration of AI tools into the ASIS IATT subsystems will

carrying out work aimed at integrating the selected AI models

reduce time, labor, and technological costs and improve the

into the ASIS IATT subsystems;

quality and speed of preparing profiles, creating promotion and

2. Integration of AI tools into the subsystems of the ASIS

marketing content to find potential partners, and preparing

IATT.

contracts in the RCTT Network.

Here are some examples of generative AI tools that can be

used when preparing profiles, creating promotion and

marketing content, scanning and analyzing Internet resources,

4 CONCLUSIONS

and solving other problems:

The paper informs about prospects for the use of AI tools in the

a) AI tools for profile descriptions and other texts could be:

RCTT Network for reduce time, labor, and technological costs,

– OpenAI GPT-3 or Generative Pre-trained Transformer 3 is improve the quality and speed of services provided.

a powerful neural network model capable of generating text

Examples of generative AI tools, that planned to be used in

based on provided contextual data. It can be used to

the RCTT Network for preparing profiles, creating promotion

automatically generate technology descriptions, technical

and marketing content, scanning and analyzing Internet

concepts, and other text materials;

resources, preparing contracts, and solving other problems are

– IBM Watson Natural Language Generator is a tool that given.

allows you to automatically generate text based on specified

templates and parameters. It can be used to create descriptions



of technology features, product specifications, and other

technical materials;

ACKNOWLEDGMENTS

– Copy.ai is a platform that provides a wide range of tools We would like to thank the National Academy of Sciences of

for generating text content, including descriptions, headlines,

Belarus and the State Committee on Science and Technology of

articles, and more. It can be used to create excellent

the Republic of Belarus for their constant support of RCTT

descriptions of technologies and products;

activities and express gratitude to all our colleagues who work

– Jasper (Adobe's AI Copywriting Assistant) is a tool that in technology transfer for their help and advice.

uses AI to generate text that can be used to create technology

descriptions, blogs, and advertising materials;



– ChatGPT by OpenAI is a generative neural network model that can hold a conversation and generate text content based on

REFERENCES

user input. It can be used to chat with the user, provide

information about technology, and answer questions;

[1] Sray Agarwal (Ed.). 2023. UNECE White Paper on the use of Artificial Intelligence in Trade Facilitation. UNECE – UN/CEFACT.

– Writesonic is another AI-powered writing assistant that

[2] Inter-Agency Working Group on Artificial Intelligence (IAWG-AI).

enables users to generate a variety of content types quickly and

2024. United Nations System White Paper on AI Governance: An

analysis of the UN system's institutional models, functions, and existing efficiently;

international normative frameworks applicable to AI governance. United

– ShortlyAI is an AI writing assistant focused on helping Nations System.

[3]

users generate long-form content efficiently.

Katie Costello. 2019. Gartner Says 80 Percent of Today's Project

Management Tasks Will Be Eliminated by 2030 as Artificial Intelligence b) There are a number of AI and machine learning tools

Takes Over (March 20, 2019). Retrieved September 11, 2024 from

available to automatically scan, analyze, and identify

https://www.gartner.com/en/newsroom/press-releases/2019-03-20-

gartner-says-80-percent-of-today-s-project-management.

competitors and potentially valuable technologies. Here are

[4] AUTM. Webinar Library. Retrieved from

some of them:

https://imis.autm.net/customer/customer/Ext/Webinar_Library.aspx

[5] Berna Uygur, Steven M. Ferguson. 2024. Will Artificial Intelligence

– Scite.ai is a platform for analyzing research articles and Shape The Future Of Technology Transfer? A Guide For Licensing

academic publications using AI. It allows you to identify

Professionals.

Retrieved September 11, 2024

from

connections between studies, evaluate their reliability, and find

https://www.techtransfer.nih.gov/sites/default/files/documents/Ferguson

%20-%20les%20Nouvelles%20Vol%20LIX%20no%201%20pp%201-

new technological directions;

11%20(March%202024)%5B2%5D.pdf.

– PatSnap is an AI-powered patent and intellectual property

[6] Ming-Hui Huang, Roland T. Rust. 2021. A strategic framework for artificial intelligence in marketing. Retrieved September 11, 2024 from scanning tool that helps you research competitors, identify new

https://link.springer.com/article/10.1007/s11747-020-00749-9.

technologies, and assess their business potential;

62

[7] Успенский А.Ал. 2024. Республиканский центр трансфера

технологий: 20 лет в национальной инновационной системе

(история развития, структура, методология, деятельность,

перспективы). Центр системного анализа и стратегических

исследований НАН Беларуси, Минск. ISBN 978-985-6999-29-4.

[8] Alexander Uspenskiy, Aliaksei Uspenski and Maxim Prybylski. 2021.

Technology Transfer in Belarus. In Proceedings of the 24th International Multiconference INFORMATION SOCIETY – IS 2021 Volume E – 7

October 2021, Ljubljana, Slovenia. 62–64. ISBN 978-961-264-224-2

(PDF).

[9] Republican Centre for Technology Transfer. Retrieved from

https://www.ictt.by.

[10] Григянец Р.Б., Успенский А.А., Венгеров В.Н. 2023. Формирование

и ведение единого информационного ресурса по обеспечению

инновационной деятельности и трансфера технологий в НАН

Беларуси. Материалы конференции "Развитие информатизации и

государственной системы научно-технической информации

(РИНТИ-2023)" 16 ноября 2023. Минск. Беларусь. 164–167.

63





64





Indeks avtorjev / Author index



Aydin Aleyna ................................................................................................................................................................... 14, 18, 22

Aykut Yalçın .................................................................................................................................................................... 14, 18, 22

Ayvaz Emrah .................................................................................................................................................................... 14, 18, 22

Baş Seda ....................................................................................................................................................................................... 18

Britchkovski Viatcheslav ............................................................................................................................................................. 26

Değermenci Beril ............................................................................................................................................................. 14, 18, 22

E. Wachowicz Marta .................................................................................................................................................................... 48

El-Zoheiry Abdelhamid ................................................................................................................................................................ 30

Falkowski Michal J. ..................................................................................................................................................................... 56

Florjančič Urška ........................................................................................................................................................................... 35

Fortun Novak Maja ........................................................................................................................................................................ 7

Fric Urška ..................................................................................................................................................................................... 35

Gladović Karen ............................................................................................................................................................................ 30

Gültekin Güler Tuğba ....................................................................................................................................................... 14, 18, 22

Hafner Ana ................................................................................................................................................................................... 10

İskender Balaban Dilek .................................................................................................................................................... 14, 18, 22

Kalyoncu Sedanur ............................................................................................................................................................ 14, 18, 22

Kaminski Jaroslaw ....................................................................................................................................................................... 56

Koç Ayhan ............................................................................................................................................................................. 18, 22

Lutman Tomaž ............................................................................................................................................................................. 35

Mrgole Urška ............................................................................................................................................................................... 39

N. Brečko Barbara ........................................................................................................................................................................ 43

Odić Duško ................................................................................................................................................................................... 39

Plaskan Jure .................................................................................................................................................................................. 43

Prybylski Maxim .......................................................................................................................................................................... 60

Rotnicki Michał ............................................................................................................................................................................ 52

Sabir Hülya ....................................................................................................................................................................... 14, 18, 22

Sağlam Gözde .................................................................................................................................................................. 14, 18, 22

Sönmez Kerim .................................................................................................................................................................. 14, 18, 22

Trobec Marjeta ............................................................................................................................................................................. 39

Ünver Müslüm Serhat ...................................................................................................................................................... 14, 18, 22

Uspenski Aliaksei ......................................................................................................................................................................... 60

Uspenskiy Alexander ................................................................................................................................................................... 60

Wachowicz Marta ........................................................................................................................................................................ 56

Yildiz İslam ...................................................................................................................................................................... 14, 18, 22

Yildiz Oktay ..................................................................................................................................................................... 14, 18, 22

Yilmaz Eren ..................................................................................................................................................................... 14, 18, 22

Yüksel Harun ............................................................................................................................................................................... 14





65



17. Mednarodna konferenca

o prenosu tehnologij

17th International Technology

Transfer Conference

Uredniki > Editors:

Urška Florjančič, Robert Blatnik, Špela Stres





Document Outline


02 - Naslovnica - notranja - E - DRAFT

03 - Kolofon - E - DRAFT

04 - IS2024 - Predgovor

05 - IS2024 - Konferencni odbori

07 - Kazalo - E Blank Page





08 - Naslovnica - notranja - E - DRAFT

09 - Predgovor podkonference - E

10 - Programski odbor podkonference - E

11 - Prispevki - E 01_Intellectual property as a success factor for startups_Maja Fortun Novak_ITTC 2024_final

02_ITTC2024 paper Hafner corrections_final

03_Dilek İskender Balaban's Paper_final

04_Rev. The Impact of International Networks on Grants, R&D, Knowledge and Technology Transfer - Case of COST Network and KTU_final

05_ITTC- KTU Evaluation Thesis_final

06_Britchkovski_NLB_corrected_final

07_ARTICLE ITTC AHZ KG formal submission(1)_final

08_Lutman_et al_17_ITTC_final - Tomaz Lutman

09_Odić et al - Feasibility analysis for the new mechanism of knowledge transfer within the INDUSAC project_final

10_Impact assessment_ IS_Plaskan_brecko_review_final

11_IPValuationCyberSector_MWachowicz_17092024_final

12_NASK_Rotnicki_The challenge of licensing artificial intelligence technology for cybersecurity applications 2024-09-19_final

13_IS-Word_MF_JK_MW final_19092024

14_Uspenskiy_RCTT24_08_12En24_09_12fin – final





12 - Index - E

Blank Page

Blank Page

Blank Page