Journal of Management, Informatics and Human Resources ISSN 1318-5454 Volume 55, Issue 3, August 2022 Revija za management, informatiko in kadre Organizacija (Journal of Management, Informatics and Human Resources) is an interdisciplinary peer-reviewed journal which is open to contributions of high quality, from any perspective relevant to the organizational phenomena. The journal is designed to encourage interest in all matters relating to organizational sciences and is intended to ap­peal to both the academic and professional community. In particular, journal publishes original articles that advance the empirical, theoretical, and methodological understand­ing of the theories and concepts of management and or­ganization. The journal welcomes contributions from other scientific disciplines that encourage new conceptualiza­tions in organizational theory and management practice. We welcome different perspectives of analysis, including the organizations of various sizes and from various branch­es, units that constitute organizations, and the networks in which organizations are embedded. Topics are drawn, but not limited to the following areas: • organizational theory, management, development, and organizational behaviour; • human resources management (such as organization & employee development, leadership, value creation through HRM, workplace phenomena etc.); • managerial and entrepreneurial aspects of education; • business information systems (such as digital business, decision support systems, business analytics etc.); • enterprise engineering (e.g., organizational design, business process management, enterprise transformation paradigms etc.); • papers that analyse and seek to improve organizational performance. Organizacija (Revija za management, informatiko in cloveške vire) je interdisciplinarna recenzirana revija, ki objavlja visoko kakovostne prispevke z vseh vidikov, ki so pomembni za organizacijske procese in strukture. Revija je zasnovana tako, da spodbuja zanimanje za razlicne vidike v zvezi z organizacijskimi vedami in je namenjena tako akademski kot strokovni skupnosti. Revija objavlja izvirne clanke, ki spodbujajo empiricno, teoreticno in metodološko razumevanje teorij in konceptov managementa in organizacije. Pozdravljamo tudi prispevke iz drugih znanstvenih disciplin, ki spodbujajo nove koncepte v organizacijski teoriji in praksi. Objavljamo clanke, ki analizirajo organiziranost z razlicnih vidikov, so usmerjeni na organizacije razlicnih velikosti in iz razlicnih sektorjev, na enote, ki sestavljajo organizacije, in na mreže, v katere so organizacije vpete. Teme so pokrivajo predvsem naslednja podrocja: • organizacijska teorija, upravljanje, razvoj in organizacijsko vedenje; • management cloveških virov (kot so organizacija in razvoj zaposlenih, vodenje, ustvarjanje vrednosti s pomocjo cloveških virov, organizacijski pojavi na delovnem mestu itd.); • vodstveni in podjetniški vidiki izobraževanja; • poslovni informacijski sistemi (kot so digitalno poslovanje, sistemi za podporo odlocanju, poslovna analitika itd.); • podjetniški inženiring (npr. organizacijsko oblikovanje, upravljanje poslovnih procesov, paradigme preoblikovanja podjetij itd.); • clanki, ki analizirajo organizacijsko uspešnost in prizadevanja za izboljšanje le-te. Saeed NOSRATABADI, Roya Khayer ZAHED, Vadim Vitalievich PONKRATOV, Evgeniy Vyacheslavovich KOSTYRIN Hasan TUTAR, Teymur SARKHANOV Sohrab GHANIZADEH, Farzad Sattari ARDABILI, Mohammad KHEIRANDISH, Eshagh RASOULI, Mohammad HASSANZADEH Mohammad SLEIMI, Malek Bakheet ELAYAN, Lamar ABU HAJLEH Artificial Intelligence Models and Employee Lifecycle Management: A Systematic Literature Review Tracing Management Fashions in Selected Indices: A Descriptive Statistical Study Psychological Capital and Organizational Performance: The Mediating Role of Organizational Ambidexterity Core Job Characteristics and Personal Work Outcomes: The Mediating Role of Critical Psychological States: Empirical Evidence from Northern Cyprus Hotel Sector RESEARCH PAPERS 181 199 214 228 EDITOR / UREDNIK Jože Zupancic University of Maribor, Faculty of Organizational Sciencies, Slovenia CO-EDITORS / SOUREDNIKI Petr Doucek Prague University of Economics, Faculty of Informatics and Statistics, Czech Republic Matjaž Maletic University of Maribor, Faculty of Organizational Sciencies, Slovenia Maja Meško University of Maribor, Faculty of Organizational Sciencies, Slovenia Wlodzimierz Sroka WSB University, Department of Management, Dabrowa Górnicza, Poland EDITORIAL BOARD / UREDNIŠKI ODBOR REVIJE Hossein Arsham, University of Baltimore, USA Franc Cuš, University of Maribor, Slovenia Sasha M. Dekleva DePaul University, School of Accountancy and MIS, Chichago, USA Vlado Dimovski, University of Ljubljana, Slovenia Daniel C. Ganster, Colorado State University, USA Jože Gricar, University of Maribor, Slovenia Werner Jammernegg Viena University of Economics and Business Administration, Austria Marius Alexander Janson, University of Missouri-St. Louis, USA Stefan Klein, University of Münster, Germany Aleksandar Markovic, University of Belgrade, Serbia Hermann Maurer, Technical University Graz, Austria Matjaž Mulej, University of Maribor, Slovenia Valentinas Navickas, Kaunas University of Technology, Lithuania Ota Novotny, University of Economics, Prague, Czech Republic Milan Pagon, Independent University, Bangladesh (IUB), Dhaka, Bangladesh Björn Paape, RWTH-Technical University Aachen, Germany Matjaž Perc University of Maribor, Slovenia Dušan Petrac, NASA, Jet Propulsion Laboratory, California Institute of Technology, USA Nataša Petrovic University of Belgrade, Serbia Tetyana Pimonenko, Sumy State University, Balatsky Academic and Scientific Institute of Finance, Economics and Management, Ukraine Hans Puxbaum, Vienna University of Technology, Austria Vladislav Rajkovic, University of Maribor, Slovenia Gábor Rekettye, University of Pécs, Hungary Henk G. Sol, Faculy of Economics and Business, University of Groningen, Netherlands Eugene Semenkin Reshetnev Siberian State University of Science and Technology, Krasnoyarsk, Russian Federation Velimir Srica, University of Zagreb, Croatia Paula Swatman, University of Tasmania, Australia Brian Timney, The University of Western Ontario, Canada Maurice Yolles, Liverpool John Moores University, UK Douglas R. Vogel, Harbin Institute of Technology-HIT, School of Management, China Gerhard Wilhelm Weber, Middle East Technical University, Turkey Anna Lucyna Wziatek-Stasko, Jagiellonian University in Kraków, Poland Yvonne Ziegler, Frankfurt University of Applied Sciences, Germany Hans-Dieter Zimmermann, FSH St. Gallen University of Applied Sciences, Switzerland DOI: 10.2478/orga-2022-0012 Artificial Intelligence Models and Employee Lifecycle Management: A Systematic Literature Review Saeed NOSRATABADI1, Roya Khayer ZAHED2*, Vadim Vitalievich PONKRATOV3, Evgeniy Vyacheslavovich KOSTYRIN4 1 Doctoral School of Economic and Regional Sciences, Hungarian University of Agriculture and Life Sciences, Gödöllo, Hungary, saeed.nosratabadi@gmail.com 2 Department of Management, Faculty of Administrative Sciences and Economics, University of Isfahan, Isfahan, Iran, R.khayer@yahoo.com (*Corresponding Author) 3 Department of Public Finance, Financial University under the Government of the Russian Federation, Moscow, Russian Federation, ponkratovvadim@yandex.ru 4 Department of Finances, Bauman Moscow State Technical University, Moscow, Russian Federation, evgeniy.kostyrin@yandex.ru Background and purpose: The use of artificial intelligence (AI) models for data-driven decision-making in different stages of employee lifecycle (EL) management is increasing. However, there is no comprehensive study that ad­dresses contributions of AI in EL management. Therefore, the main goal of this study was to address this theoretical gap and determine the contribution of AI models to EL management. Methods: This study applied the PRISMA method, a systematic literature review model, to ensure that the maximum number of publications related to the subject can be accessed. The output of the PRISMA model led to the identifica­tion of 23 related articles, and the findings of this study were presented based on the analysis of these articles. Results: The findings revealed that AI algorithms were used in all stages of EL management (i.e., recruitment, on-boarding, employability and benefits, retention, and off-boarding). It was also disclosed that Random Forest, Sup­port Vector Machines, Adaptive Boosting, Decision Tree, and Artificial Neural Network algorithms outperform other algorithms and were the most used in the literature. Conclusion: Although the use of AI models in solving EL management problems is increasing, research on this topic is still in its infancy stage, and more research on this topic is necessary. Keywords: Artificial intelligence, Deep learning, Machine learning, Human resource management, Employee lifecy­cle, PRISMA, Systematic literature review 1 Introduction Innovations, new technologies, and the Covid 19 pan­demic have posed new challenges to human resource man­agement (HRM). These changes have not only required a new set of skills for employees, but also affected the way tasks are performed, and have intensified the platform economy and the emergence of platform workforces (Il­léssy, Huszár, & Makó, 2021; Makó & Illéssy, 2020). In addition, information systems have greatly facilitated the processes of storing and collecting data related to individ­uals, which provide the basis for decision-making about the organization’s workforce. Many statistical models are proposed in the literature for analyzing this information, but with the prevalence of artificial intelligence (AI) mod­els, the use of these models in HRM has become common. Two features of AI models distinguish them from statisti­cal models and have made the use of these models more popular than statistical models. Their first feature is the high performance of these models in nonlinear and noisy data (Ardabili et al., 2019; Nosratabadi, Szell, et al., 2020). The second feature is that these models have the ability to learn from the data to improve their performance. In other words, machine learning and deep learning models, which are subsets of AI models, are able to identify trends in data, even nonlinear and noisy data, during the training phase to classify the data or predict the behavior of phenomena based on identified patterns (Nosratabadi, Ardabili, Lak­ner, Mako, & Mosavi, 2021; Nosratabadi et al., 2020). Therefore, the AI models have been used to take advan­tage of these features and to find appropriate solutions to problems in different stages of HRM. However, there is no integrated and comprehensive study in the literature that identifies which HRM problems are addressed by AI mod­els. Therefore, the present study was conducted to bridge this gap in the literature using a systematic review study to determine how AI has been able to help HR managers. In order to evaluate the contribution of AI in HRM, the present study uses the employee lifecycle (EL) model. The EL model is actually an HRM model that explains all the different life stages of the workforce from the time they are hired to the time they leave the organization. Inspired by this model, the present study aims to identify contributions of AI models to each stage of the EL management. There­fore, the research questions that the present study intends to answer are: • What AI models have been used in each stage of EL? • What human resource problems have AI models been used to solve? • What data sources have been used to test AI mod­els? This research contributes to the HRM literature and AI literature. The findings of this study provide HR manag­ers with suggestions for selecting the appropriate AI mod­el to address issues related to each stage of HRM. In the continuation of this article, first the methodology used in this article is described in detail and then the findings of this article are presented in order to answer the research questions, which is accompanied by a discussion on the findings and the conclusion. 2 Literature Review Machine learning is driving an explosion in AI capa­bility, helping software make sense of the messy and un­predictable real world. Today, machine learning is used in various sciences and can examine a large amount of data and discover certain trends and patterns that are unknown to humans. On the other hand, with the help of machine learning, there is no need for humans to intervene direct­ly in every step of the project process. Therefore, the ma­chine can make predictions on its own and also improve its algorithms to increases accuracy and efficiency. These al­gorithms perform well in examining multidimensional and multivariate data in dynamic or unknown environments. Today, AI algorithms are expanding widely in organ­izations. These algorithms can promote and improve the organization’s performance Olan et al. (2022) and prevent problems in the organization. When a system breaks down, it imposes huge costs such as time, productivity, and mon­ey to the business, machine learning and deep learning al­gorithms make it possible to quickly identify the cause of a problem and also predict the problems and solve them. On the other hand, with artificial intelligence algorithms, suitable data can be prepared for detailed analysis on im­portant business decision criteria. For example, the behav­ior of different groups of buyers can be deeply investigated and better offers can be made to them (Jiang et al., 2022) to increase customer satisfaction. In an online store, one of the metrics is the amount of time a customer spends on a particular product page and AI here provides advanced analytics. In addition, AI can help predict organizational resource planning. By searching among the collected data, AI can make predictions that increase the ability of the organization. It also identifies seasonality in the business and make recommendations on increasing or decreasing production accordingly. Another application of AL in or­ganizations is that it helps organizations to identify their behavioral patterns by considering the history of custom­ers and predict how much of what type of product they should produce in the future (Jiangang et al., 2022). On the other hand, with the help of AI, it is possible to simplify sales (Irfan, et al, 2022), accounting (Leitner-Hanetseder et al., 2021), inventory (Praveen, Farnaz, & Hatim, 2019) etc., and create a centralized platform for managing cus­tomer relations (Deb, Jain, & Deb, 2018), as well as the product and sales life cycle (Ren, Patrick Hui, & Jason Choi, 2018). One of the important considerations of AI in organizations is to identify new opportunities for sales and marketing. Artificial intelligence and machine learning al­low a business to not only identify the buying behavior of customers (Jiang et al., 2022), but also investigate what each person is willing to buy. AI can identify processes that cause unacceptable energy consumption in the organ­ization or are mechanically inefficient, thereby helping to reduce energy consumption and resource wastage (Giaglis, 2001). Organizations face different challenges for HRM, whether it is during recruitment, or during the collabo­ration with the employee, or when the employee’s rela­tionship with the organization is to be terminated for any reason (Susmita and Singh, 2022). Human resource is the key asset of the organization, which is known today as or­ganizational capital. Organizations seek to attract the best and most suitable people in the organization, carefully im­plement the socialization process and familiarize employ­ees with the basic principles and the main culture of their organization, as well as the necessary training on how to do the job (Morozevich et al., 2022). These are to keep the capabilities of the employees up to date and prepare them to adapt to the work environment. On the other hand, compensation is one of the most important measures of HRM in creating motivation in employees. An effective compensation system can make the employee feel a sense of belonging to the organization and consider the organiza­tional goals as part of their own goals. Therefore, employ­ee lifecycle management is brought up and its importance becomes necessary. The EL model proposed by Peisl and Shah (2019) is an HRM model that explains the challeng­es of human resource management at different stages of a workforce’s life from the time he/she is recruited to the time he/she leaves the organization. This model constitutes of five stages of recruitment, on-boarding, employability and benefits, retention, and off-boarding. In this model, the recruitment phase includes all the processes that lead to the recruitment of a new employee. Recruitment is the process of searching, evaluating and bringing in new talents when a specific job position is va­cant. This Process begins when an employee resigns, or a new position is created to meet the needs of the company. Therefore, recruitment is a need-based procedure that oc­curs only when there is an immediate need for it. This usu­ally involves advertising a job vacancy and letting people know that the company is looking for a worker/employee with a particular talent or skill. At on boarding stage, the staff is provided with the necessary information and tools to be more efficient and integrate into the culture of the organization (Khayer Zahed, Teimouri, & Barzoki, 2021). Onboarding or aligning new employees in the company is the process of adapting these people to the company’s activity process as well as its organizational culture. It also includes providing the tools and information needed to in­crease the productivity of the workforce in the team. Ac­cording to Peisl and Shah (2019), the next stage of an EL is employability and benefits. Employability refers the abil­ity to retain the employee and, if necessary, “move” him/her to a new job and role in the same organization to meet new job needs, and benefits mean how to assign financial and non-financial benefits to employees in order to create a sense of belonging and commitment to the organization. Retention refers to the mechanisms by which HRM seeks to maintain the employees and their potentials. Employee retention depends on a combination of factors including flexible working conditions, professional development op­portunities, and company culture, and more. The last stage of an EL is called off-boarding, in which the employee, for various reasons such as finding a new job, retirement, dismissal, personal reasons, stops working with the organ­ization. 3 Methodology In this study, four criteria were set to ensure finding the maximum number of articles related to AI models used in HRM (see Figure 1). The first criterion is to use Pre­ferred Reporting Items for Systematic Reviews and Me­ta-Analyses (PRISMA) method to obtain final articles. The PRISMA is an evidence-based systematic literature review method that consists of four stages (1) identification (2) screening, (3) eligibility, and (4) inclusion (Moher, Libe­rati, Tetzlaff, & Altman, 2010) to systematically maximize the possibility of finding the most relevant articles. The second criterion is the selection of databases in which the search for articles took place. For this purpose, two data­bases, i.e., Scopus and Web of Science, were used. Scopus covers 42,180 journals, conference proceeding, and book series and web of Science includes 21,894 journals, books, and conference proceedings while, the overlap rate of articles in these two databases is 99.11% (Singh, Singh, Karmakar, Leta, & Mayr, 2021). The third criterion for ac­cessing the maximum number of related articles is the use of appropriate keywords. Table 1 summarizes the literature search strategy implemented in this study. It is worth men­tioning the search inquiry took place among article title, abstract, keywords. The fourth criterion used in this study to validate the path to find articles ready for review is the use of a multi­disciplinary approach when searching for articles. This approach allows the search for keywords in all journals of different disciplines and this search is not restricted to certain journals or specific categories of journals. The present study names the articles that were even­tually identified for the review as the study database. As mentioned above, the PRISMA model was used to form the study database. Figure 2 summarizes the PRISMA model steps performed in this study. In the identification step, the keywords presented in Table 1 were searched in Scopus and Web of Science databases. It should be not­ed that this search was conducted in August 2021 and no time limit was considered for it. However, the search for articles was limited to original English-language articles in journals or conference proceedings. This means that in this search, articles written in another language, review articles, as well as documents that were either a book or a chapter of a book were removed. The output of the first stage resulted in the identification of 6753 articles. In the screening phase, a copy of duplicate articles found in both databases was removed. The output of this step was to identify 6050 unique articles. The second screening step examined the titles and abstracts of the papers and exclud­ed those that were irrelevant. At this point, the criteria for keeping relevant articles were that they should use an AI model to address a problem in HRM. This step resulted in the identification of 580 relevant articles. Eligibility is the third step of the PRISMA and the whole text of the output articles from the screening step is thoroughly examined in this step, and only those articles that are absolutely rele­vant to the research’s aim advance to the inclusion phase. Following a thorough examination of the complete text of 580 articles, 23 relevant articles were identified and ad­vanced to the inclusion stage. The inclusion step resulted in the creation of the study database, which now contains 23 papers and is ready for further analysis. 4 Findings and Discussion Figure 3 depicts a trend of publications using AI mod­els to solve a problem related to HRM. Findings disclosed that the use of AI models in the field of HRM is very new as the first article was published in 2014. The present study found 23 related articles in the literature, of which 14 were journal articles and 9 were conference papers. 21 unique sources have published the articles (i.e., 14 journals and 9 conference proceedings) from which Jour­nal of ‘Automation in Construction’ and ‘ACM Interna­tional Conference Proceeding Series’ in 2018 have pub­lished 2 articles on this topic. The full list of these journals and conference proceedings is given in Table A1 in the Appendix. The articles found by the PRISMA method were ana­lyzed from three aspects, and their findings are presented in the form of three subsections below. First, it was deter­mined what problems the AI models were used to solve. In the next subsection, the articles were analyzed in terms of data sources. That is, it revealed what kind of HR data AI algorithms have been implemented on. Finally, AI al­gorithms that have been used in different phases of the EL management have been reviewed and the models whose performance has been repeatedly confirmed in the litera­ture have been explained. 4.1 Applications of Machine learning models in Human Resource Management Once an employee arrives, he or she embarks on an adventurous journey and goes through various stages in his/her employment lifecycle. HRM experiences different challenges at each stage of the EL. Table 2 categorizes the reviewed articles based on the problem they addressed at each stage of the EL. Although the distribution of articles is almost the same at different stages, the share of articles dealing with employee attrition and off-boarding has been higher. 4.1.1 Recruitment The most important challenge of the recruitment phase is identifying and selecting the right person who, firstly, has the most skill matching with the job and, secondly, has the necessary commitment to continue working. Recruit­ment, training and retaining an employee is very costly and employees become the intellectual capital of the or­ganization and therefore, replacing them will be very dif­ficult and costly for the organizations. Hence, Chuang et al. (2020), N. Li et al. (2016), Xie (2020), and Zaman et al. (2018) have tried to provide models that optimize the process of recruiting and selecting the right person for the job. Chuang et al. (2020) consider recruitment as a multi­ple-attribute decision-making (MADM) problem and use a rough set theory (RST) model to optimize staff recruitment by prediction of person skill match. Because they believe that the previous models were based on human judgment and taste, but the use of MADM makes hiring employees more purposeful and objective. They use performance data from a Chinese food company to test the model. Zaman et al. (2018) applied a decision tree (DT) classification technique model to predict the degree to which job skills and staff skills match in order to recruit talent. To do so, they used the data available on users’ LinkedIn to test the model. N. Li et al. (2016) develop a K-nearest neighbors (KNN) model to predict skill match of the potential can­didates. They also proved the accuracy of their proposed model using UCI Machine Learning Repository data. Xie (2020) designs a hybrid machine learning model of Latent Factor Model-multi Grained Cascade Forest (LFM-gcFor­est) to measure the degree to which employees’ skills and job required skills are matched. They used secondary data from Africa Health Placements to test the model. The find­ings of this study showed that the LFM-gcForest model plays an important role in the HR recruitment system in the intelligent manufacturing industry. All these studies, in turn, have attempted to use AI models to measure the degree to which an individual’s skills match the skills needed to work so that they can as­sist HRM in making decisions about hiring people. Hence the following proposition can be derived from these find­ings: P1: AI models help HRM in job-person skills match prediction. 4.1.2 On-Boarding The findings revealed that there are studies in the lit­erature that have used machine learning and deep learning models to address problems in the on-boarding stage of EL. In general, studies related to this stage of EL have fo­cused more on staff training. For instance, Kaewwiset et al. (2021) and Liu, Li et al. (2019) use random forest (RF) model to enhance and personalize staff training and to pre­dict the potential growth of employees in the workplace. Using secondary data from the HRM information system database and interpersonal environment factors, Liu, Li, et al. (2019) develop a quantitative model that predicts an employee’s growth rate at different stages of employment. Findings of this study showed that relationships with col­leagues and the quality of relationships with people are very important and necessary for employee development. Using the Artificial Neural Network (ANN) model, Col­omo-Palacios et al. (2014) also propose a model that can anticipate the competencies required by members of soft­ware development teams and subsequently suggest related development programs. Besides training purposes, two other articles were found that developed quantitative models using machine learning models for the management of working people. In order to manage occupational health and safety, for exam­ple, X. Li et al. (2021) developed the Multi-task Cascad­ed Convolutional Networks (MTCNN)-MobileNet- Long Short-Term Memory (LSTM) model, which allows them to monitor workers’ health and generate personalized safe­ty and health alerts for workers in high-risk jobs. Akhavian and Behzadan (2016) also develop an ANN model that is able to track workers body movements by tracking their smartphones, to examine the behavior and the state of con­struction workers. These studies disclose that the main purpose of using machine learning and deep learning models at this stage of the EL was to identify the skills needed by the person to design personalized training programs and predict em­ployee growth rates. Therefore, the second proposition of this study is presented as follows. P2: AI models help HRM in staff training planning. 4.1.3 Employability and Benefits In the employability and benefits stage of EL, articles are categorized that focus more on issues related to staff promotion. Liu, Wang et al. (2019), for example, used the Adaptive Boosting (AdaBoost) model to examine the promotion and advancement of employees in the work­place, and tested this model in data from a state-owned enterprise in China. Long et al. (2018) also use the RF to develop a model for predicting employee promotion and use data from a Chinese state-owned enterprise to test the model. Findings of this study show that job experience (by year), number of positions held and the position level (i.e., seniority level) in the organization are the factors affect­ing staff promotion. Jayadi et al. (2019) develop a Naive Bayes (NB) classification method to predict employee per­formance. Utilizing the available data from 310 employees from the KAGGLE database in 2019, Jayadi et al. (2019) proved that their proposed model has a good power to pre­dict employee performance. In addition to these studies, Singer and Cohen (2020) use the Classification and Re­gression Trees (CART) model to design a model for the prediction of the absence of employees and the service compensation system in order to prevent the absence of employees of a Brazilian company. These studies have used AI models to help HRM to predict employee perfor­mance and predict employee promotion. Therefore, the third proposition of this research is designed as follows. P3: AI models help HRM in employee promotion pre­diction. 4.1.4 Retention The articles categorized in the retention mainly focus on the issues of work quality and employee well-being. In other words, these articles consider the creating proper working conditions as employee retention requirements. Zhe and Keikhosrokiani (2021), for example, use the ex­treme learning adaptive neuro-fuzzy inference system (ELANFIS) model to develop a model for predicting the mental workload of knowledge workers (i.e., Delft Uni­versity of Technology students). To manage the well-being of employees and their mental health, Jebelli et al. (2018) also uses an Electroencephalography (EEG) device (for the data collection) and the Support Vector Machine (SVM) model (for the data analysis) to design a model to predict the stress of construction workers. In addition, Moyo et al. (2018) use multinomial logistic Regression (MLR) model to develop a model for predicting the length of practice of employees in the health sector. In fact, they came up with a quantitative model that has the ability to accurately predict how long health care workers will stay in their jobs. A look at the objectives of these articles reveals that they try to predict the level of stress, mental and physical health of employees by using machine learning models so that they can use them in managing and improving work quality and employee well-being. Therefore, the fourth proposition of this research is written as follows. P4: AI models help HRM in work quality management. 4.1.5 Off-Boarding Predicting off-boarding and factors affecting employee attrition has been one of the most important trends in the HRM literature. There are studies that have tried to use machine learning models to predict employee attrition. Jain et al. (2020), for example, claim the RF model to be the best model for predicting employee attrition. Khera and Divya (2018) used the SVM model to predict employ­ee attrition and tested the model by archiving employee data (including 1,650 employees) from three Indian IT companies. Fallucchi et al. (2020) use the Gaussian Naďve Bayes (GNB) classifier model to analyze how objective factors affect employee attrition and test the predictive accuracy of their model using IBM analytics data that in­cludes 35 features and 1,500 samples. Yadav et al. (2018) compare the accuracy of RF, AdaBoost, DT, Logistic Re­gression (LR) and SVM models to create accurate and re­liable models that optimize the cost of hiring and retaining quality staff. They report that DT outperforms other mod­els in prediction of attrition in their dataset. The findings of this article showed that salaries and other financial aspects and promotions are not adequate incentives for retaining employees. On the other hand, since employee turnover costs are high in organizations, Zhao et al. (2018) using the Extreme Gradient Boost (XGBoost) model provide a mod­el for predicting employee turnover. To analyze the model, they employed data from an IBM database and a bank da­tabase (9089 bank employees and 1470 IBM employees). Liu et al. (2018) also compare the accuracy of LR, Support Vector Classifier (SVC), RF, and Adaboost in prediction of employee turnover. Besides, Anh et al. (2020) combine SVM, LR and RF models to develop a model to predict fu­ture employee churn. They test the accuracy of their model on the data of 1470 employees of an organization. These findings show that AI models have the ability to predict employee attrition and employee turnover and HR man­agers can use these models to identify the effective causes of employee attrition so that they can avoid the high costs that the outflow of human capital imposes on the organi­zation. Subsequently, the fifth proposition of this study is designed as follows. P5: AI models help HRM in employee attrition predic­tion and employee turnover prediction. 4.1.6 Contributions of AI Models to Employee Lifecycle Management The findings of this study illustrated that the use of AI predictive models in HRM is increasing, and these mod­els provide managers with appropriate and approved tools through which they can cope with the challenges in each stage of EL. In this study, five propositions were designed based on the purposes for which an AI model was used. A summary of these proposals is given in Figure 4. The stage of recruiting and selecting the right person for a task is one of the most important stages of HRM and managers face many challenges to select the right person. According to the first proposition of this article, AI models can help managers in deciding to choose the right person for the task by predicting the degree to which the skills of the in­dividual are matched with those skills needed for the job. Job and task dynamics, innovations, the use of new tech­nologies, changes in organizational strategies are some of the factors that impose new requirements on employees to perform tasks. The second proposition of the present study clarified that at this stage, AI models have the abil­ity to propose personalized training programs to develop the skills of individuals by examining personal skills and required skills. Creating motivation and a sense of com­mitment in employees is another important challenge of HRM. Therefore, managers design reward and promotion systems through which employees can perform their best performance in the organization. The third and fourth prop­ositions of this research refer to these issues and state that AI models can both predict the performance and promo­tion of employees and can help managers in managing the quality of work. Up to this point in EL, organizations have spent a lot of money on recruitment, training, promotion and retention of the employees, and the employees are the intellectual capital of the organization and losing them will be very costly for the organizations. Hence, managers try to minimize and manage employee attrition. In this regard, the fifth proposition of this study shows that AI models can help HR managers in managing the attrition of employees by predicting the factors affecting employee attrition and employee turnover. 4.2 Data Sources One of the most important issues in implementing AI models is the data. In other words, it is very important where the data source comes from. It is revealed that the articles to test their proposed models used both primary data (collected through case studies, observations, user profiles on social media, and questionnaires) and second­ary data (which have been collected from databases such as Kaggel.com, UCI Machine Learning Repository, IBM Analytics, and past records of a case study). Figure 5 shows the taxonomy diagrams of data sources. 4.3 Artificial Intelligence Models A closer look at the models used among the reviewed articles shows that these articles, in total, examined the performance of 26 different models (see Table 3). The pro­cedure has been that each article first examines the perfor­mance of several models and then introduces the model that had the highest accuracy (or the lowest level of error) as the main model of that article. In this article, in the find­ings and discussion section, we only reported the model that had the highest performance. In the end, it was found that 16 of these models presented in Table 3 had the lowest level of error and their higher performance was repeated among different articles. Table 4 summarizes the AI models and their applica­tions in the various stages of HRM. In other words, these sixteen models outperformed other models in data related to HRM. RF is a model whose high performance has been confirmed in three different stages: on-boarding (Kaew­wiset et al., 2021; Liu, Li, et al., 2019), employability and benefits (Long et al., 2018), and off-boarding (Jain et al., 2020; Liu et al., 2018). In addition, the SVM is another model whose high performance has been proven to address retention (Jebelli et al., 2018) and off-boarding (Khera & Divya, 2018) issues. Another model whose performance has been approved in more than one stage of the EL is the Adaboost model, whose performance has been approved in the stages of employability and benefits (Liu, Wang, et al., 2019) and off-boarding (Liu et al., 2018). DT is also another model that its high performance is proved in two stages of EL, i.e., recruitment (Zaman et al., 2018) and off-boarding (Yadav et al., 2018). The rest of the models have been examined only in one stage of the EL stages, but among them is the ANN model whose performance in the on-boarding stage has been examined and confirmed by two different studies (Akhavian & Behzadan, 2016; Colo­mo-Palacios et al., 2014). Therefore, a short introduction to these 5 models (i.e., RF, SVM, AdaBoost, ANN, and DT) are provided as follows. 4.3.1. 4.3.1 Random Forest (RF) By mixing a set of weak learners to generate a strong­er learner, random forests offer an enhancement over the basic decision tree structure (Breiman, 2001). In other words, RF is an ensemble model. To optimize algorithm performance, ensemble techniques use a divide-and-con­quer strategy. Random forests are constructed by building a number of decision trees, using bootstrapped training sets and selecting a random sample of m predictors as split candidates from the entire set P predictors for each deci­sion tree. 4.3.2 Support Vector Machines (SVM) SVM is often used as a discriminative classifier to cat­egorize fresh data samples. The fundamental principle of SVM is to design a hyperplane that divides n-dimensional data into two classes and maximize the geometric distance between the nearest data points, referred to as support vec­tors. Notably, practical linear SVM often produces compa­rable results to logistic regression (Raschka, 2015). 4.3.3 Adaptive Boosting (AdaBoost) Boosting is a machine learning technique that is based on the concept of combining several very weak and faulty prediction rules to create a highly accurate prediction rule. AdaBoost, an acronym for Adaptive Boosting, is a me­ta-algorithm for statistical categorization. The output of the other learning algorithms (referred to as ‘weak learners’) is merged into a weighted sum that reflects the boosted classifier’s final output. AdaBoost is adaptive in the sense that it adjusts succeeding weak learners in favor of cases misclassified by prior classifiers. It may be less prone to overfitting than other learning algorithms in neural certain cases (Schapire, 2013). 4.3.4 Decision Tree (DT) The decision tree approach is a supervised technique that uses a tree-like structure to construct classification or regression models. DT is very powerful (Friedman, Hastie, & Tibshirani, 2001) and it can manage missing values and mixed features (Efron & Hastie, 2016), and it is capable of automatically selecting variables (Efron & Hastie, 2016). 4.3.5 Artificial Neural Network (ANN) Neural networks, also known as multi-layer percep­tron, are used to imitate the human nervous system’s pro­cesses. A neural network in its simplest form is a single perceptron. The input values, associated weights, bias, ac­tivation functions, and calculated output are all required components of a perceptron. To solve difficult issues, a neural network may comprise several layers between the input and output. Given sufficient hidden units, networks are a universal approximation technique capable of mode­ling any smooth function to any desired degree of accuracy (Murphy, 2012). 5 Conclusions The integration of technology with HRM has provided the basis for the use of AI models in the management of EL processes. In different stages of HRM, a lot of data is gen­erated that data-driven decision-making approaches use this data to optimize all stages of the EL, from the recruit­ment stage to the off-boarding stage. It was found that em­ployee attrition and the management of off-boarding stage is a stage on which more research has been done. This in­dicates the value that employees, which are the intellectual capital of the organization, have for an organization. Most of the articles published at this stage of the EL focus on predicting the factors influencing employees’ decision to leave the organization. Intellectual capital belongs to the employees and with their departure from the organization, the organization loses this capital, while it has spent a lot of money on the development of HR. Hence, the loss of manpower is very costly for organizations, especially if the costs of recruiting and training new staff are added to it. However, less research has been done on the retention phase, which requires more attention from researchers. The findings of this study also revealed that not only machine learning models (such as SVM) and Deep Learn­ing models (such as ANN) have contributed to HRM de­cision-making, ensemble models (such as RF) and hybrid models (such as Adaboost) have also been developed to address HRM problems. Ensemble models are models that combine two or more machine learning models to increase the predictive power, while hybrid models combine an op­timization model with a machine learning or deep learning machine model to increase the accuracy of the model. Findings of the present study contribute to the literature of HRM and AI using a systematic review of the literature and by providing the state-of-the-art of advancements of AI models in EL management. Organizations, especially HR managers, can use the findings of this study to easily select the appropriate AI model to address the challenges of each stage of the EL and use the benefits and high per­formance of these models in their decisions. On the other hand, this study provides a foundation for future research. Within the HRM practices, ‘retention’ and ‘off-board­ing’ represent two extreme challenges for HR managers. Searching new models of ‘work’ and ‘employment’ or the ‘new-normal’ of work and employment in the post-Covid pandemic period, there is a growing need to better under­stand the ‘practice/process of the new model of work (i.e., remote work, telework, etc.). The necessity of new models of work does vary importantly by sectors of economic ac­tivities, reflecting the importance of ‘physical proximity’ syndrome. In addition, the mainstream of HRM literature focuses almost exclusively on the ‘Standard Employment Relations’ (SER) practice but neglects the fast-growing share of the Non-Standard Employment Relations (Non-SER) - this is the so-called ‘prevarication of work’ (e.g., grate majority of the web-based platform work mentioned in the conclusion too - practiced in the form of non-SER or in an entrepreneurial status). Therefore, the use of AI models to address these challenges is also suggested for future research References 1Received: 15th September 2021; revised: 13th April 2022; accepted: 23th July 2022 Table 1: Literature search strategy Query Terms • “human resource*” OR employee OR “human capital” OR staff OR HR OR HRM AND • artificial intelligence OR AI OR “machine Learning” Or “deep learning” Figure 1: The current study strategies to validate the findings Figure 2: Systematic selection of the study database using PRISMA Figure 3: Categorizing the reviewed articles by year of publication and document types Table 2: Categorizing the reviewed articles by their solution in employee lifecycle Employee Lifecycle Recruitment On-Boarding Employability and Benefits Retention Off-Boarding Sources Chuang, Hu, Liou, and Tzeng, (2020), Xie (2020), Zaman, Kamal, Mohamed, Ahmad, and Zamri (2018), N. Li, Kong, Ma, Gong, and Huai (2016) X. Li et al. (2021), Kaewwiset, Tem­dee, and Yooya­tivong (2021), Liu, Li, Wang, and He (2019), Akhavian and Behzadan (2016), Colomo-Palacios, González-Carrasco, López-Cuadrado, Trigo, and Varajao (2014) Singer and Cohen (2020), Jayadi, Jayadi, and Firmantyo (2019), Liu, Wang, et al. (2019), Long, Liu, Fang, Wang, and Jiang (2018) Zhe and Keikhosrokiani (2021), Moyo, Doan, Yun, and Tshuma (2018), Jebelli, Khalili, Hwang, and Lee (2018) Jain, Jain, and Pamula (2020), Fallucchi, Coladange­lo, Giuliano, and William De Luca (2020), Anh et al. (2020), Khera and Divya (2018), Yadav, Jain, and Singh (2018), Liu et al. (2018), Zhao, Hryniewicki, Cheng, Fu, and Zhu (2018) Figure 4: Contributions of AI models in different stages of employee lifecycle Figure 5: A taxonomy of data sources used for AI models to solve a human resource management problem Table 3: Machine learning models used in human resource management literature Methods Source Methods Source AdaBoost Liu, Wang, et al. (2019), Yadav, Jain, and Singh (2018), Liu et al. (2018) LR Fallucchi et al. (2020), Anh et al. (2020), Liu, Wang, et al. (2019), Liu, Li, et al. (2019), Yadav et al. (2018), Liu et al. (2018), Zhao et al. (2018), Akhavian and Behzadan (2016) ANFIS Zhe and Keikhosrokiani (2021) LSVM Fallucchi et al. (2020) ANN Zhao et al. (2018), Akhavian and Behzadan (2016), Colo­mo-Palacios, González-Car­rasco, López-Cuadrado, Trigo, and Varajao (2014) MLR Moyo et al. (2018) DT Kaewwiset, Temdee, and Yooyativong (2021), Jain, Jain, and Pamula (2020), Fallucchi et al. (2020), Zaman et al. (2018), Moyo et al. (2018), Yadav et al. (2018), Zhao et al. (2018), Akhavian and Behzadan (2016) MLP Singer and Cohen (2020), Liu, Li, et al. (2019) ELANFIS Zhe and Keikhosrokiani, (2021) MTCNN-MobileN­et-LSTM X. Li et al. (2021) Fed-GRU X. Li et al. (2021) NB Singer and Cohen (2020), Jayadi et al. (2019), Moyo et al. (2018), Zhao et al. (2018) Fed-LSTM X. Li et al. (2021) NB-MB Fallucchi et al. (2020) Fed-SWP X. Li et al. (2021) Ordinal CART Singer and Cohen (2020) GBoost Zhao et al. (2018) RF Kaewwiset et al. (2021), Singer and Co­hen (2020), Jain et al. (2020), Anh et al. (2020), Liu, Wang, et al. (2019), Liu, Li, et al. (2019), Yadav et al. (2018), Long et al. (2018), Liu et al., (2018), Zhao et al. (2018) GNB Fallucchi et al. (2020) RST Chuang et al. (2020) KNN Singer and Cohen (2020), Fallucchi et al. (2020), Zhao et al. (2018), Akhavian and Behzadan, (2016), N. Li et al. (2016) SVC Liu et al. (2018) LDA Zhao et al. (2018) SVM Kaewwiset et al. (2021), Jain et al. (2020), Fallucchi et al. (2020), Anh et al. (2020), Khera and Divya (2018), Yadav et al. (2018), Zhao et al. (2018), Jebelli et al. (2018), (Akhavian and Behzadan (2016) LFM-GcForest Xie (2020) XGBoost Singer and Cohen (2020), Zhao et al. 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Employee turnover prediction with machine learning: A reliable approach. Paper presented at the Proceedings of SAI intelligent systems conference. ht­ tps://doi.org/10.1007/978-3-030-01057-7_56 Zhe, I. T. Y., & Keikhosrokiani, P. (2021). Knowledge workers mental workload prediction using optimised ELANFIS. Applied Intelligence, 51(4), 2406-2430. ht­ tps://doi.org/10.1007/s10489-020-01928-5 Saeed Nosratabadi has recently graduated from the Doctoral School of Economic and Regional Sciences, Hungarian University of Agriculture and Life Sciences, Gödöllo, Hungary. His main research interests are digital transformation, sustainability, and business models. Roya Khayer Zahed holds a PhD in Business Man­agement at the Faculty of Administrative Sciences and Economics at the University of Isfahan in Iran. She has taught management courses in the past eight years and is an employee in Iranian National Tax Administration, Fars province. Her areas of interest include human re­source management, talent management and organiza­tional behavior. She has several articles in these areas. Vadim V. Ponkratov, Ph.D. in Economics, director of Financial Policy Center of the Public Finance Department in Financial University under the Government of the Russian Federation; corresponding member of International Academy of Technological Sciences. Obtained PhD degree in 2006 in Financial Academy under the Government of the Russian Federation. Member of Government and Federal Assembly of the Russian Federation working groups; member of energetic strategy and developing fuel-energetic complex committee in the chamber of commerce and industry of the Russian Federation; member of expert council for improving tax legislation and law enforcement practice in the chamber of commerce and industry of the Russian Federation. Published more than 150 works. Area of scientific interest: government financial policy and assessing its effectiveness; managing oil and gas budget income, strategies of forming and implementing means of sovereign funds; natural rent and instruments for its expropriation; instruments of government financial stimulation of economic development. https://orcid.org/0000-0001-7706-5011 Evgeniy V. Kostyrin - professor of the Department of Finances in Bauman Moscow State Technical University. Graduated as Doctor of Economic Sciences from Bauman Moscow State Technical University. He is also cooperating with Moscow State University of Medicine and Dentistry. Prof. Kostyrin’s research interests are models of medical services administration, economical-mathematical modeling processes of medical organizations development administrations, medical savings accounts as advanced technology of Russian Federation healthcare funding, sovereign issue as an instrument of salary and Russian economy growth. https://orcid.org/0000-0003-2569-1146 Modeli umetne inteligence in upravljanje kariere zaposlenih: sistematicen pregled literature Ozadje/namen: Uporaba modelov umetne inteligence (AI) za odlocanje na podlagi podatkov v razlicnih fazah upravljanja kariere zaposlenih (EL) narašca. Vendar pa ni celovite študije, ki bi obravnavala prispevke umetne inte­ligence pri upravljanju EL. Zato je bil glavni cilj te študije osvetliti to teoreticno vrzel in ugotoviti prispevek modelov AI k upravljanju EL. Metode: Ta študija je uporabila metodo PRISMA, model sistematicnega pregleda literature, da bi zagotovila dostop do najvecjega števila publikacij, povezanih z obravnavano temo. Rezultati modela PRISMA so pripeljali do identifika­cije 23 povezanih clankov, ugotovitve te študije pa so bile predstavljene na podlagi analize teh clankov. Rezultati: Algoritmi AI so bili uporabljeni v vseh fazah upravljanja EL. Pokazalo se je tudi tudi, da so algoritmi Ran­dom Forest, Support Vector Machines, Adaptive Boosting, Decision Tree in Algoritmi umetne nevronske mreže boljši od drugih algoritmov in so bili najpogosteje uporabljeni v obravnavanih študijah. Zakljucek: Ceprav se uporaba modelov umetne inteligence pri reševanju problemov upravljanja EL povecuje, so raziskave na to temo še vedno v povojih in potrebnih je vec raziskav. Kljucne besede: Umetna inteligenca, Globoko ucenje, Strojno ucenje, Upravljanje cloveških virov, Življenjski cikel zaposlenih, PRISMA, Sistematicni pregled literature Appendix Table A1: A summary of reviewed articles in this study Authors Year Source title Li X., Chi H.-L., Lu W., Xue F., Zeng J., Li C.Z. 2021 Automation in Construction Teoh Yi Zhe I., Keikhosrokiani P. 2021 Applied Intelligence Kaewwiset T., Temdee P., Yooyativong T. 2021 2021 Joint 6th International Conference on Digital Arts, Media and Technology with 4th ECTI Northern Section Conference on Electrical, Electronics, Computer and Telecommunication Engineering, ECTI DAMT and NCON 2021 Singer G., Cohen I. 2020 Entropy Chuang Y.-C., Hu S.-K., Liou J.J.H., Tzeng G.-H. 2020 Technological and Economic Development of Economy Jain P.K., Jain M., Pamula R. 2020 SN Applied Sciences Xie Q. 2020 Enterprise Information Systems Fallucchi F., Coladangelo M., Giuliano R., De Luca E.W. 2020 Computers Anh N.T.N., Tu N.D., Solanki V.K., Giang N.L., Thu V.H., Son L.N., Loc N.D., Nam V.T. 2020 International Journal of Sensors, Wireless Communications and Con­trol Jayadi R., Firmantyo H.M., Dzaka M.T.J., Suaidy M.F., Putra A.M. 2019 International Journal of Advanced Trends in Computer Science and Engineering Liu J., Wang T., Li J., Huang J., Yao F., He R. 2019 Conference Proceedings - IEEE International Conference on Systems, Man and Cybernetics Liu J., Li J., Wang T., He R. 2019 Proceedings - 5th IEEE International Conference on Big Data Service and Applications, BigDataService 2019, Workshop on Big Data in Water Resources, Environment, and Hydraulic Engineering and Workshop on Medical, Healthcare, Using Big Data Technologies Khera S.N., Divya 2019 Vision Kamaru Zaman E.A., Ahmad Kamal A.F., Mohamed A., Ahmad A., Raja Mohd Zamri R.A.Z. 2019 Communications in Computer and Information Science Moyo S., Doan T.N., Yun J.A., Tshuma N. 2018 Human Resources for Health Yadav S., Jain A., Singh D. 2018 Proceedings of the 8th International Advance Computing Conference, IACC 2018 Long Y., Liu J., Fang M., Wang T., Jiang W. 2018 ACM International Conference Proceeding Series Liu J., Long Y., Fang M., He R., Wang T., Chen G. 2018 ACM International Conference Proceeding Series Zhao Y., Hryniewicki M.K., Cheng F., Fu B., Zhu X. 2018 Advances in Intelligent Systems and Computing Jebelli H., Khalili M.M., Hwang S., Lee S. 2018 Construction Research Congress 2018: Safety and Disaster Manage­ment - Selected Papers from the Construction Research Congress 2018 Akhavian R., Behzadan A.H. 2016 Automation in Construction Li N., Kong H., Ma Y., Gong G., Huai W. 2016 International Journal of Advanced Manufacturing Technology Colomo-Palacios R., González-Carrasco I., López-Cuadrado J.L., Trigo A., Varajao J.E. 2014 Information Systems Frontiers Table A2: Acronyms Acronym Explanation AdaBoost Adaptive Boosting ANFIS adaptive neuro-fuzzy inference system AI Artificial Intelligence ANN Artificial Neural Network DEMATEL Decision Making Trial and Evaluation Laboratory DT Decision Tree EL Employee Lifecycle XGBoost Extreme Gradient Boosting ELANFIS Extreme Learning Adaptive Neuro-Fuzzy Inference System Fed Federated Learning GRU Gated Recurrent Unit Neural Network Framework GNB Gaussian Naďve Bayes GBT Gradient Boosting Trees HR Human Resource HRM Human Resource Management KNN K-Nearest Neighbors LFM Latent Factor Model LDS Linear Discriminant Analysis LSVM Linear Support Vector Machines LR Logistic Regression LSTM Long Short-Term Memory gcForest Grained Cascade Forest MLP Multi-Layer Perceptron MLR Multinomial Logistic Regression MADM Multiple-Attribute Decision-Making MTCNN Multi-Task Cascaded Convolutional Networks MB Multivariate Bernoulli NB Naďve Bayes Ordinal CART Ordinal Classification and Regression Tree PRISMA Preferred Reporting Items for Systematic Reviews and Meta-Analyses RF Random Forest ROS Random Over-Sampling RST Rough Set Theory SER Standard Employment Relations SVC Support Vector Classifier SVM Support Vector Machine SWP Smart Work Packaging DOI: 10.2478/orga-2022-0013 Tracing Management Fashions in Selected Indices: A Descriptive Statistical Study Hasan TUTAR1, Teymur SARKHANOV2 1 Bolu Abant Izzet Baysal University, Public Relations Department, 14030 – Bolu, Turkey, hasantutar@ibu.edu.tr (corresponding author) 2 Azerbaijan State Economic University (UNEC), Department of Economics and Business, Istiqlaliyyat str.6, AZ1001, Baku, Azerbaijan, teymur.sarkhanov@gmail.com Background and purpose: Although management fashions have been discussed for nearly 30 years, a certain amount of time had to pass before the discussions were based on factual data. This research mainly aims to trace management approaches in some selected international indices over nearly half a century. In this study, the basic question of how the historical course of management fashions has developed has been answered by following the development course. Methods: The Descriptive Statistical method was preferred in the study because of its suitability to the subject’s essence, the purpose of the research, and the research question’s answer. The research was carried out based on the data collected about management trends by scanning the Web of Science and Scopus databases covering 1975-2020. Results: Management fashions follow rapid adoption, implementation, disappointment, and abandonment. Research results; show that the lack of knowledge and awareness of management fashions poses a significant waste of time and intellectual capital. This determination is crucial, especially for young researchers and new generation manag­ers. Conclusion: In conclusion, it can be said that while new approaches that have tangible counterparts and can be grounded continue, approaches that do not have concrete counterparts disappear, causing a waste of time and mental effort. Keywords: Management trends, Management fashion, Management fads, New management, Management thinking 1 Introduction Management fashions are techniques and practices that are very popular; like all fashions, they are rapidly dis­appearing in popularity and are extremely popular when they appear but quickly cause disappointment (Miller et al., 2004). However, every effort made in scientific activity can continue its existence as long as it finds an applica­tion area and has an accurate response. The importance of scientific activities, especially in a technical and rational field such as management, is measured by their opera­tional value (Abrahamson, 1996; Bondarouk et al., 2019; Klincewicz, 2017; Piazza and Abrahamson, 2020). If any scientific activity is not just for intellectual enthusiasm, the activity in question must have a corresponding response in practical life. In this study, fashion approaches are exam­ined through some selected indexes. Although many kinds of research have been conducted on fashion approaches in management, it is seen that the analysis of these approach­es is not included in this study for about half a century. In this respect, it can be argued that this research has the importance of filling the gap in the literature and contrib­uting to practice and theory. It is important to follow the course of the interest shown in the subject to make a sound evaluation of management trends. For this purpose, it can be argued that answering how management trends have progressed in major international indexes in half a century and keeping a projection for future studies will contribute to the literature and practice. Although some criticisms about management fash­ions parallel the emergence of fashion approaches, some indicators emerged based on factual data. This research is important in seeing the course of the management fashion process after meeting this requirement. It can be claimed that this aspect of the research will make a signif­icant contribution to the literature and practice. Based on the half-century experience of management fashion, this study’s results confirmed that fashion concepts progress in the form of continual adoption, application, insistence, dis­appointment, and abandonment despite the inaccuracies. There is still the risk of the emergence of fashionable ap­proaches, which fashion industry makers have put forward and controversial management gurus as well-intentioned, resulting in disappointing time, labor, and cost losses in a relatively short period (Madsen et al., 2017; Madsen, 2020; Bondarouk et al., 2019; Zorn, 2017). It is neces­sary to carefully read the history of management theories against the said risk and look at the phenomenon of fashion approach with the possibilities of philosophy of science. Recently, when the management literature is exam­ined, we generally encounter a “New Management Ap­proaches” jungle. When subjected to a deep analysis, rhetoric, expressed as new management approaches today, means nothing other than renaming the traditional concep­tual framework with “metaphorical neologies.” Discussing a rhetorical change in management approaches rather than innovation is better. About sixty years ago, Koontz ex­pressed the result of his curiosity about being different as “The Theories of Management Changed” (Koontz, 1961). It is a manipulation, if not scientific, to highlight one of the features of the already known management approaches as if there were no precedents (Tutar & Sarkhanov, 2020). A management industry is revealed with new management approaches, CEOs, management gurus, and young acad­emicians who are the actors of this industry, who are not able to analyze the subject in-depth, exploit this industry (Jackson, 2001; Huczynski, 2012; Jackson, 2001; Great­batch & Clark, 2005). New management approaches are inadequate in science’s philosophy (Abrahamson, 1996). New management fashions continue today as a tool of exploitation of “management gurus” who devoted them­selves to producing new management knowledge. Management fashions are embraced with great hope from the illusion that corporate performance and efficien­cy will increase (Spell, 2001; Piazza & Abrahamson, 2020; Klincewicz, 2017). When management fashion approach­es are examined carefully, it is seen that two issues stand out. The first is “impermanence,” and the other is “enthusi­asm.” According to Abrahamson (1996), attempting to ap­ply “fashion” and “whim” in a technical and rational area such as management may cause various problems and then abandon it with disappointment. Management fashions, which find a living space for themselves due to rootless­ness and lack of philosophy, continue as a tool of abuse. A “fashion approach industry” based on fashion approach­es is an industry with great interest in its media, gurus, consultants, and business schools. Scientific methods and reliable scientific information are not easily encountered in the industry’s so-called approaches in question. New management approaches or fashions rely on classical or­ganizational theory concepts and principles, although their past has been denied under the postmodern paradigm’s in­fluence. The main purpose of this study, which examines the emergence, reasons for adoption, dissemination patterns, disappointment, and abandonment adventures, which are presented in the management literature and spreading es­pecially among young academicians and practitioners, is to raise awareness about fashion approaches (Newell et al., 2001; Collins, 2013; Williams, 2004; Abrahamson, 1991). Spending time and intellectual capital for these approach­es, sometimes expressed as guru discourse, metaphoric neologism, or “enthusiasm for management” because it has no scientific and factual counterpart, wastes time and mental labor. This study’s main purpose is to draw atten­tion to the factors that affect the emergence of management fashion literature and contribute to the purification of the so-called approaches to management fashion in the liter­ature. For this purpose, 46 years of data on management trends obtained using Web of Science and Scopus databas­es were analyzed with a Descriptive Statistical study. With the findings obtained from the data mentioned above, it is aimed to answer the basic question of how management trends have followed a course for half a century and to answer the following sub-questions: - What are the factors that cause management fashions to emerge? - How is the course of management trends in the period under study? - What measures can be taken against the management fashion approach? 2 Literature Review 2.1 Fashion Approaches in Management Literature Management fashions have become very popular in recent years, both regarding the spread of fashion ap­proaches and criticism of management fashions (Clark, 2004; Czarniawska, 2005; Newell et al., 2001; Sturdy, 1997; Swan, 2004). In these criticisms, researchers criti­cize management fashion approaches by seeing the futile effort of “reinventing the wheel.” Some researchers defend these approaches to better wheel rotation (Sturdy, 1997; Newell et al., 2001). Management fashions are initially seen as the basic tool to be innovative, functional, effec­tive, and efficient and increase organizational performance (Rossem & Veen, 2011). This approach tries to replace the traditional management paradigm with new management approaches for efficiency and performance. For example, management fashions deal with competitive conditions in turbulent environments, overcome problems encountered in entering the market, overcome economic crises, or pre­vent customer losses. However, although this intention has led to the rapid adoption of fashionable approaches, it is not enough to sustain it. This rapid adoption process, de­fined in the literature as “management fads and fashions,” is soon abandoned, disappointingly, with various doubts about these approaches’ validity (Carson et al., 1999; Ryan & Hurley, 2004; Christensen & Michael, 2003). Therefore, managers must be subjected to a more critical analysis of management fashions and be more cautious about new ap­proaches to avoid disappointment. The key determinant of whether any management ap­proach is a “management fashion” is the number of arti­cles published on that topic and the trend followed. If a management approach has been discussed over 3-5 years, and the number of articles produced on that subject has decreased significantly, this approach is most likely a man­agement fashion (Ponzi & Koenig, 2002). Some manage­ment fashions and fads compiled by Furnham (2004) and arranged in rough chronological order from the 1950s to the 1990s are Management by Objectives, Matrix Manage­ment, Theory Z, One-Minute Management, Management By Wandering Around, Total Quality Management Busi­ness Process Reengineering, Delayering, Empowerment, 360-Degree Feedback, Reengineering, Reorganization, and Teamwork. In this study, some of the fashionable ap­proaches were examined in line with the research’s pur­pose. Especially in the 1980s and 1990s, analyzes were made on the main management fashions such as Quality Circles, Total Quality Management, and Restructuring of Business Processes to increase product quality. For ex­ample, Quality Circles were seen in the early 1980s as a means of competition in other industrialized countries to close the quality gap with Japan, and it spread rapidly like an epidemic, ignoring cultural and other factors in Japa­nese business systems. This management technique has been adopted without hesitation to achieve greater quality and labor productivity. For example, it is seen that between 1980 and 1982, 90% of Fortune 500 companies adopted the Quality Circle technique (Ponzi & Koenig, 2002; Lawler & Mohrman, 1985). However, more than 80% of Fortune 500 companies that adopted the Quality Circles approach in the early 1980s gave up the fashion approach by 1987 (Ponzi & Koenig, 2002). Abrahamson (1996) confirmed with his studies that the quality circle approach is a management fashion. Ob­taining the article numbers from ABI Inform, Abrahamson drew a ten-year trend line representing articles that include “Quality Circles” in the title or abstract. Abrahamson’s findings revealed that the Quality Circles movement had a bell-shaped pattern. The model shows a rapid growth start­ing in 1978 and returning in 1982 (Ponzi & Koenig, 2002). Abrahamson’s (1996) study shows that publications on Quality Circles peaked in five years. Considering the life cycles of Total Quality Management (TQM) and Business Process Restructuring, it is understood that these are not different from other fashion approaches (Ponzi & Koenig, 2002). The debate is whether Total Quality Management is an approach with its essence, a systematic and theoret­ical framework like other contemporary management ap­proaches. There is no consensus on whether total quality management is a program, a management tool, or a man­agement approach. Management fashions are criticized for not paying at­tention to context and interpretation, approaching techni­cal knowledge and science as if they approach commercial products, not defining human roles correctly in the man­agement fashion market, and being an abused tool. For example, management fashions are criticized for offering a specific terminology or jargon instead of knowledge, having difficulties developing a common understanding of techniques, containing ambiguities and paradoxes, and lacking systematic and poor technical aspects (Carson et al., 1999; Dedeoglu, 2008; Amount, 2009). Also, since management fashions are not based on a factual basis, it is seen that they usually do not have their concepts; in­stead, they try to express themselves with contentless rhet­oric and metaphoric neologism. The management fashion market is so lively that it is approached with irony to the concept of management, a rational and technical field, by being influenced by postmodern thought approaching events with irony. The absence of a philosophical tradition of manage­ment thought has a share in this. Today, neo-capitalism radically transforms work and business life, and the labor market is being restructured based on flexibility, temporal­ity, fluidity, and adhocracy (Tutar & Sarkhanov, 2020a). The new understanding, embodied with features such as continuous and rapid change, being short-term, tran­sient, and saving the day, substitutes short-term for being long-term in every field, and temporality for permanence (Bauman, 2005). This process rapidly dissolves the past into stable and stable structures, causing a comprehensive deformation in the social field. Flexibility and transience in business life create a suitable ground for the spread of fashion approaches. While traditional management thought has mental-log­ical explanations and a philosophical basis, strange ap­proaches can arise because the management fashions ap­proach lacks a philosophical basis. Although management has an interdisciplinary character, the interdisciplinary feature of contemporary management approaches is weak. There is uncertainty about the limits of fashion approach­es. However, it is not easy to think together with science and uncertainty. The main purpose of science is to elimi­nate uncertainties based on scientific data. That is to guide uncertainty. A scientific effort is made to describe, under­stand, explain, or preface. However, management fashions approaches are too vague to fall into these categories. 2.2 The Reasons for the Emergence of Management Fashion The cultural, economic, and social changes that oc­curred during the transition from an agricultural society to an industrial society and an information society led to new techniques and management approaches. Shortly af­ter Business Management thought they started to be han­dled with a scientific approach with F. Taylor, fashion ap­proaches gradually emerged. Especially in the 1980s, the production conditions and the developments in the field of information technologies, shaped by globalization, contributed to creating a suitable environment for fashion approaches by rapidly changing traditional organizational structures. Although this rapid change led to a paradigm change in management approaches, this paradigm change also formed a suitable ground for developing fashion ap­proaches (Ugurlu, Ibrahimoglu & Ayas, 2013; Bao & Tan, 2009; Spell, 2001). This radical change process was ex­ploited by management gurus, young academics in busi­ness schools, and management consultants and paved the way for fashionable management approaches. The adoption and spread of management fashions rep­resent a radical deviation from the traditional understand­ing of management. It often creates a high motivation and excitement during the adoption phase. When this excite­ment is lost, it is criticized that management fashions mean nothing more than presenting existing approaches, man­agement principles, and theories with new rhetoric. The promise will produce definitive solutions to management problems in management fashions, and the ambiguity of the language used causes these approaches to be adopt­ed with great enthusiasm (Madsen et al., 2017; Madsen & Slatten, 2019). Simultaneously, the fact that it is based on descriptions of what to do with authoritarian and impera­tive expressions causes it to be quickly adopted by manag­ers who seek practical solutions. The simple expression of the basic assumptions on which fashion discourse is based and its slogan-like style facilitate the adoption and spread of these approaches. The simple expression of the basic concepts on which fashion approaches are based, the ex­cessive use of slogans (the snake that cannot change its skin dies) and abbreviations (TQM, HRM, CRM, MbO, etc.) are other reasons that facilitate its adoption. Ignoring Japanese business discipline and diligence, the illusion that Total Quality Management is behind Jap­anese success has led to the rapid spread of this approach to other countries and business schools around the world (Abrahamson & Fairchild, 1999) (Van Der Wiele et al., 2000; Longo & Cox, 1997). Although management fash­ions have not yet been sufficiently tested, they are still seen as an indicator of achieving a sustainable competitive ad­vantage, extending the life of fashion approaches. On the other hand, the commercialization of management knowl­edge in management information markets is another com­pelling reason for the spread of fashionable approaches. Scientific activities require intense curiosity, patience, per­severance, great effort, and mental and intellectual capac­ity. On the other hand, management fashions are so-called scientific activities disguised as scientific. Unfortunately, management fashions prepared more theoretically oriented to practice various disappointments (Miller & Hartwick, 2002; Longo & Cox, 1997). Although management fash­ions do not have operational value and theoretical basis, they embellish the narrative with rhetoric and enrich it with a metaphorical neologism that creates an attraction and causes it to be adopted rapidly. 2.3 General Features of Management Fashions Many factors play a role in the emergence and spread of fashion approaches. As shown in Figure 1 above, we can express the general characteristics of management fashions implemented in the form of rapid adoption, ab­sorption, disappointment, and sustaining life with the sup­port of loyal viewers and the factors that cause them to spread as follows: They were produced with a simple and average in­tellectual capacity. Therefore, the emergence of fashion approaches is easy to understand and quick to spread, as they are produced with a limited intellectual capacity and low mental labor. It is generally adopted quickly, not re­quiring deep academic knowledge and mental proficien­cy. Although it contains many rhetorical and metaphorical neologisms, it applies few scientific and factual concepts. It is inspiring and descriptive. Managerial fashion ap­proaches are not analytical thinking and logical inference, but they have been designed for the market rather than the scientific mind because they are produced with commer­cialization. The language of fashion approaches is not gen­erally open to interpretation and expresses itself in strict propositions. It has a normative and imperative style, not questioning. Statements are simple and descriptive. Assumptions are based on raw imagination, not cre­ativity. Management trends promise high productivity, motivated and high-performance employees, and satisfied consumers for practitioners. Unfortunately, these expres­sions used in the adoption phase of fashionable approaches are not credible and soon disappoint. Their lifetimes de­pend not on their content’s strength but the management gurus’ status and reputation. It claims to be suitable for every situation and every environment. Because management fashions are produced with ignorant courage, it claims to be a suitable recipe for any occasion and at any time. Fashion approvers claim that the approach they produce has precise solutions to every event and phenomenon. However, the “contingency approach,” which assumes that there cannot be an appro­priate approach for every situation and all times, claims that there can never be general management principles. Although many of these approaches are produced for a specific company, they believe they are valid for all busi­nesses. Lack of theoretical foundation. Scientific activities must be based on a principle, a model, a theory, or a sci­entific law. Since the fashion approaches are unfortunately not put forward on a theoretical basis, their assumptions are unfounded. The fact that they are not based on scientif­ic principles or theory causes the illusion that they have a large operational possibility. Conformity to the spirit of the times. Management fad approaches are often articulated in a style appropriate to the times’ spirit to legitimize management’s role. Fash­ionable approaches that give the impression that they are suitable for every environment and situation are unsuitable for a scientific test and an effective management practice. Management trends are often produced and propagat­ed by management gurus who do not know management’s theoretical foundations. Gurus are highly manipulative people who believe they have the right recipe for every problem. Academics who are easy to follow are often dis­appointed when they see that fashion approaches have no real-world counterpart. However, young academicians and loyal followers who have not sufficiently digested man­agement theories cause the prolongation of management fashions. 3 Material and Methods 3.1 Design The theoretical basis of this research was made accord­ing to the critical literature review technique. The “descrip­tive statistics” technique was used in the research method. In such studies, it is very important to do the research in the form of a critical literature review in terms of contrib­uting to the literature. A literature review is mostly used for investigation studies, estimations and statistical results. The scanning method can also be classified within itself. These; can be in the form of scanning the existing liter­ature through documents, archival analysis and scanning the literature on the web. Clear connections are established between the literature review and the research’s purpose, questions or hypotheses (Hartley, 2008; Padem, Göksu, & Konakli, 2012; Adams et al., 2007). It is critically exam­ined that needs to be studied in a critical literature review. Critical literature review forms the basis of descriptive re­search. Descriptive research aims to portray an organiza­tion, individual, group, situation or phenomenon. Descriptive statistics are concerned with collecting, in­terpreting and summarizing data. Descriptive statistics en­able the data to be converted into information and used in the decision-making process using several numerical and (or) graphical methods, and descriptive statistical tech­nique is used to analyze numerical data. The main purpose of descriptive statistics is to summarize the data with the help of tables and graphs and to reveal a data group consist­ing of many values. Since descriptive statistics summarize the information in a dataset using numerical and graphical methods, it is a suitable technique for the main purpose of this research (Özsoy, 2010; Spiegel & Stephens, 2013; Gürsakal, Oguzlar, & Gürsakal, 2019). The descriptive statistics technique was used in this research because it is suitable for the research and easy to explain the problem. 3.2 Results and Discussion This study analyzed the data on fashion approaches in Descriptive Statistical courses from 1975-2020. The course of fashion approaches since 1975 has been visual­ized and quantified with tables and graphics. It is important to follow the historical adventure of fashion approaches, frequently used in management today, to keep a future pro­jection. Since it is impossible to examine many fashion ap­proaches in one article in this study, only total quality man­agement, reengineering, quality circles, and management by objectives, matrix management, and theory Z fashion approaches have been emphasized in the period examined here. In the study, 24,306 publications in the Web of Sci­ence (WoS) database indexed SCI-EXPANDED, SSCI, A & HCI, CPCI-S, CPCI-SSH, ESCI, and 36,697 scientif­ic publications in the Scopus database between 1975 and 2020 were examined. The main fashion approaches were chosen in the study, and the number of publications by year was shown. The number of publications on manage­ment fashion approaches in Web of Science and Scopus databases is given in table 1. Total Quality Management The Web of Science database on Total Quality Man­agement, one of the fashionable approaches in the period examined, shows that the first publication on this fashion­able concept was in 1985. In the first phase of the period under consideration (1975-1983), no publication was made on TQM. As shown in Table 1, the number of publications in the following periods increased rapidly in line with the rapid adoption of fashion approaches and began to de­cline. By 2020, a total of 1413 publications will be made. In the same period, the total number of publications made in Scopus on TQM is 2258. The data from the databases show that in the 1993-2001 period, TQM was the peak of the approach. During this period, 645 publications were made in WoS and 977 in Scopus. Between 2002 and 2010, 190 publications were made in WoS and 361 in Scopus. From 2002-2010, 354 publications were made in WoS and 624 in Scopus. In Figure1, there was a rapid increase in publications on Total Quality Management from 1993-2001. It is seen that there is a rapid decline in TQM for the period of 2002-2010 as well as other fashionable approaches. However, it has been observed that there has been a low-slope rise since 2010. It is understood that similar trends are followed in both Webs of Science and Scopus. It can be argued that the increase here may have resulted from the insistence of those with a high level of loyalty to fashion approaches. Reengineering As with other management fashions, reengineering has emerged with great promise that innovation and process reengineering will contribute to sustainable development. Due to global environmental changes and increasing­ly stringent environmental legislation and competition, reengineering has become the primary goal of enterprises (Verbic et al., 2009). However, it did not go from being a management fashion to a new one after a short time. Reengineering, the findings obtained from the Web of Sci­ence and Scopus database data show that the situation is not different from other fashion approaches. Two reengi­neering publications were published in the first phase of the period under consideration (1975-1983). In the follow­ing periods, the number of publications increased rapidly in line with the rapid adoption of fashion approaches, and by 2020, 2766 publications were published on the Web of Science and 3698 in Scopus. The peak point of the publi­cations on the reengineering fashion approach is the peri­od 1993-2001. During this period, 1235 publications were published on the Web of Science and 654 in Scopus. From 2002-2010, publications decreased by about fifty percent, becoming 654 on the Web of Science and 993 on Scopus. While the reengineering fashion approach followed a horizontal course from 1975 to 1992, there was a rapid adoption process in line with fashion trends. There appears to be a rapid decline from 2001 to 2100 and then a slight increase in interest. Quality Circles The WoS database on Quality Circles, one of the fash­ionable approaches examined, shows that this fashionable concept is not different. From 1975-1983, 71 publications were made on Quality Circles. In later periods, less atten­tion was paid to this fashion approach, and by 2020, 18 publications were published on the Web of Science and 57 in Scopus. Interest in this fashion approach decreased expense; by 2002-2010, it decreased to 26 publications on the Web of Science and 66 in Scopus. Unlike other fashion approaches, the Quality Circles fashion approach seems to be disappointing in an earlier period. Looking at the Web of Science and Scopus data­bases, it is understood that the Quality circles fashion ap­proach was adopted in 10 years and then abandoned quick­ly with disappointment when the expected benefit could not be obtained. Management by objectives Regarding the Management by Objective fashion ap­proach, the Web of Science and Scopus databases and Scopus databases show that this fashion concept’s situa­tion is not different from other fashion approaches. From 1975-1983, 76 publications were published on Manage­ment by Objectives in Web of Science and Scopus, and 70 in Scopus. In the following periods, the number of publi­cations decreased rapidly, and by 2020, 22 were published in Web of Science and Scopus and 32 in Scopus, resulting in disappointment. Looking at the graphs above, researchers have not shown much interest in the MbO fashion approach since its emergence. It appears disappointing before it can go through a rapid adoption phase, as observed in other fash­ion approaches. In the MbO fashion approach, it is under­stood that similar trends are followed in both WoS and Scopus. Matrix management In the period examined, 15 publications were published in Web of Science and Scopus, and 17 in Scopus on Matrix Management, one fashion approach. This approach has not observed the rapid adoption of many publications’ fashion approaches. Interest in this approach has been decreasing steadily, with 6 Web of Science publications and 14 publi­cations in Scopus in 2020. In this fashion approach, 1984-1992 is the peak point of the number of publications. After this period, the number of publications decreased rapidly, and by the year 2002-2010, it went down to seven publica­tions on the Web of Science and Scopus and Scopus. From 2011 to 2020, the interest in six Scopus in Web of Science and Scopus increased slightly and reached 14. It is understood that researchers approach matrix man­agement with this fashionable approach with some hesi­tation. However, the Scopus database has shown slight interest in this fashion approach after 2010. Theory Z Data on Theory Z in Web of Science and Scopus and Scopus database show that this fashionable concept is not different. Between 1975 and 1983, 50 publications on The­ory Z were published in Web of Science and Scopus, and 18 in Scopus. In later periods, the number of publications in SCOPUS followed the same trend in Theory Z in line with the rapid adoption of fashion approaches, and by 2020, it decreased to one publication in Web of Science and Scopus and one publication in Scopus. 1984-1992 is the peak point of the Theory Z fashion approach publi­cations. Twenty-one publications were made in Scopus during this period, and in 2002-2010, 2 publications were made in WoS and Scopus. It is seen from both Webs of Science and Scopus and Scopus databases that people’s interest in the fashion ap­proach developed by William Ouchi is weak from the beginning. However, this so-called approach continues to occupy students’ agenda in business schools today, as included in management books. Table 2 below shows the data obtained from the Web of Science and Scopus and Scopus databases regarding the not fashionable approaches described as “new manage­ment approaches.” In the period examined in the table, hu­man resources instead of personnel management concept draw attention to the scarcity of publications on personnel management. However, it is observed that human resourc­es management publications are increasing daily. Unlike fashion approaches, it is seen that non-fashion approaches tend to increase regularly in Web of Science and Scopus and Scopus databases. It is observed that there is a regular increase in publications on strategic human resources man­agement, which is one of the new management approach­es, and talent management. The 360-degree feedback ap­proach, on the other hand, has shown a steady increase, especially due to the increasing interest in organizational democracy. Personnel empowerment, which has risen as a requirement of human-oriented approaches, stems from the expectation of higher performance in human resources. Since teamwork is an important management tech­nique applied in all periods of history with the expecta­tion of synergy, it is understood that the interest shown in teamwork continues. Since teamwork is necessary for jobs people cannot do alone, it is expected to increase interest in this subject. The strategic management approach con­tinues to be important in administering states and manag­ing institutions and organizations throughout history. With the globalization trend and the opportunities provided by the developments in information and communication technologies, the necessity of doing business in different parts of the world and benefiting from external resources (outsourcing) is increasing. Outsourcing has content close to the concept of “supply” in terms of meaning. Unlike fashion approaches, new management approaches present traditional management approaches as a new management approach with minor differences. Interest in such ap­proaches continues today, as new management approaches have traditional roots. 4 Discussion and Conclusion While the criticism of management fashion and fash­ions has continued for about 30 years, the production of new management fashion continues. It can be said that the increasing criticism of management fashion in the interna­tional literature has reduced the interest shown in fashion approaches. Approaches without tangible and operational value are quickly abandoned due to disappointment. These results also answer the research question of how the his­torical course of management trends has developed. As has been said, new approaches are not based on objective reality and a scientific basis. Objects subject to sense expe­rience determine the subject of knowledge. Human knowl­edge is limited to visible and directly experienced objects. If there is human knowledge, there is a reality to which this knowledge corresponds. However, in management fash­ions, the situation is not bye. For this reason, management fashions, mostly produced with neological expressions and concepts that do not have a counterpart in nature, emerge as approaches that can be grounded and do not have con­crete counterparts. Management fashion approaches that have no scientific and operational value, management fashions that only waste time and mental effort; Organ­izational Silence continues with trendy concepts such as organizational citizenship, Job Burnout, Anti-productive Work Behaviors, Psychological Contract, Organizational Commitment and Organizational Trust (Under & Gerede, 2021; Al-Madadha et al., 2021; Lubbadeh, 2021; Huy et al., 2020; http://organizacija.fov.uni-mb.si/index.php/or­ganizacija/article/view/1388Akkaya, 2020). Theoretical implications. A critical approach to man­agement fashion approaches will contribute to a better understanding of this approach. It can be argued that this will benefit from contributing to which area the intellectu­al and scientific mind and labor should focus. Otherwise, approaches with no operational value and equivalent fields cannot go beyond intellectual enthusiasm. It is seen that there are generally constructive, destructive, and under­standing-oriented criticisms about fashion approaches. For example, criticisms made under Abrahamson and his influence often use derogatory or even insulting language towards fashion approaches (Abrahamson & Eisenman, 2001; Ramsay, 1996; Kieser, 1997; Benders & Van Veen, 2001; Jackson, 2001). It is the confusion between the con­cept of management fashions and the concept of “man­agement ideology.” This situation causes the criticism of management ideologies to be directed to management fashions. Another aspect is that while management ideolo­gies are based on the claim that they have social concerns, management fashions are more directed towards individ­ual benefit (Parush, 2008; Chiapello & Fairclough, 2002; Anthony, 2005). This situation hinders studies from under­standing management modes. The main rationale for con­structive approaches to management fashions is that what has been done is not “reinventing the wheel” but making it turn better. Over the past three decades, new management ap­proaches and management fashions have attracted great at­tention in management circles worldwide. Quality circles, TQM, restructuring of business processes, learning organ­izations, and many other fashionable concepts were eager­ly addressed and implemented by academics and practi­tioners. However, disappointingly, these approaches were soon abandoned due to their low operational value (Parush, 2008). Management fashions spread by academia, consult­ants, and management gurus quickly disappeared as they spread. It should be noted that many researchers, especial­ly Abrahamson, played a role in this (Abrahamson, 1996; Benders & Veen, 2001; Czarniawska, 2005; Czarniawska & Joerges, 1995; Huczynski, 1993; Jackson, 2001; Kieser, 1997; Micklethwait & Wooldridge, 1996; Rřvik, 1996). The criticisms made by these researchers have been effec­tive in keeping young researchers away from management fashions. When Abrahamson (1996) classified the manage­ment fashion process as “management fashion setters” and “management fashion users,” this situation led to a cau­tious view of management fashions and a move away from fashion approaches after a short time. Management fashions were not justified during the ex­amined period, causing disappointment in these approach­es. Management fashions could not confirm the scientific assumption that the best approach or theory should be ver­ified by practice. For example, in 2002, Harvard Business Review magazine announced that approximately 60% of companies implementing thousands of customer relation­ship management systems do not meet their customers’ expectations. Although the management fashion approach was presented as a solution by the “fashion setting organ­izations” (consultancy firms, management gurus, acad­emicians) under uncertain conditions, it was understood that this was not valid in the end. Also, cultural and so­cial-psychological factors have led to prudent behavior in adopting and using a management innovation. Fashion approaches that appeal to emotions rather than the mind quickly caused disappointment in such a technical and ra­tional area as management. Practical implications. On the one hand, impatient managers who want to overcome the uncertainties of business life and, on the other hand, sloppy and scientif­ic researchers who want to publish easily and reach their career goals quickly play an important role in the spread of fashion approaches. Another problem is that far from philosophical depth, management gurus pollute the liter­ature with metaphorical neologies. These research results and international literature confirm this claim. Today, it is possible to understand the efforts of organizations to make their employees more productive and to increase their per­sonal development and professional competencies. How­ever, all these good intentions cannot justify the production of unscientific literature based on management fashions. Moreover, it is not possible to institutionalize the prin­ciples and rules regarding management fashion approach­es, and institutional success, efficiency and effectiveness cannot be achieved with such approaches. Achieve suc­cess and competitive advantage for the institution; It can be possible with better marketing activities, developing financial control systems and using technology more ef­ficiently. Organizational efficiency and effectiveness are impossible with fashionable approaches unless organiza­tional innovation, marketing innovation, process innova­tion and effective human resource management (Guest, 1987; Tichy, 1981; Wright & McMahan, 1992). The ev­er-expanding market requires intense collaboration agree­ments, increased consumer expectations and technology transformations. In addition, businesses make great efforts to survive in a politically and economically turbulent envi­ronment. Strategic management and other new approach­es play an important role in adapting to rapidly chang­ing environmental conditions, especially after the 1980s (Morgan and Strong, 1998; Panagiotou, 2003). It may be possible to provide high performance, sustainable growth, opportunity and competitive advantage within the frame­work of strategies to be determined according to contem­porary developments. Management is a rational activity, and it is not following the rational nature of management activity to place hope and trust in fashionable approaches, such as fashion approaches, which are emotionally domi­nant and without content. Limitations and accommodation for future research. This research is research that covers a certain period. Re­search is also limited to the Web of Science and Scopus databases. Results may differ in different national databas­es. In addition, if scholar google and other databases are included in the process, different results can be obtained. Contribution to the discussion can be made by making na­tional and international comparisons. In future research, the subject can be examined with quantitative, qualitative and mixed research methods and meta-analysis. Research should also be supported by real data on fashion approach­es’ operational value and practical value. The reasons for the success and failure of successful companies in a certain period can be associated with fashionable approaches. In addition, the factual data that fashion approaches do not give a positive result in the field can be searched. References 1Received: 11th July 2021; revised: 19th July 2022; accepted: 1st August 2022 Figure 1: Life Cycle of Management Fashion. Source: Ettorre, 1997: 34 Table 1: Number of Publications Regarding Fashion Approaches in Web of Science and Scopus Database (1975-2020) Years 1975-1983 1984-1992 1993-2001 2002-2010 2011-2020 Total Approaches WOS Scopus WOS Scopus WOS Scopus WOS Scopus WOS Scopus WOS Scopus Total Quality Management 0 0 224 296 645 977 190 361 354 624 1413 2258 Reengineering 2 0 60 57 1235 1511 654 993 815 1137 2766 3698 Quality Circles 71 129 149 237 29 102 26 66 18 57 293 591 Management by objectives 76 70 12 20 4 12 7 17 22 32 121 151 Matrix man­agement 15 17 11 21 6 9 7 7 6 14 45 68 Theory Z 50 18 20 21 2 4 2 2 1 1 75 46 Figure 2: TQM development course in WoS and Scopus databases between 1975-2020 Figure 3: Reengineering development progress in WoS and Scopus databases between 1975-2020 Figure 4: Quality circles development course in WoS and Scopus databases between 1975-2020 Figure 5: MbO development progress in WoS and Scopus databases between 1975-2020 Figure 6: The development course of matrix management in WoS and Scopus databases between 1975-2020 Figure 7: The development course of theory Z in WoS and Scopus databases between 1975-2020 Table 1: Number of Publications Regarding Fashion Approaches in Web of Science and Scopus Database (1975-2020) Years 1975-1983 1984-1992 1993-2001 2002-2010 2011-2020 Total Approaches WOS Scopus WOS Scopus WOS Scopus WOS Scopus WOS Scopus WOS Scopus Personnel Management 195 89 124 113 58 74 39 73 116 175 532 524 HRM 36 42 213 226 379 460 644 1150 1595 2438 2867 4316 Strategic HRM 1 1 19 25 43 39 51 97 131 164 245 326 Talent Management 0 0 0 0 0 2 45 120 471 694 516 816 360-degree feedback 0 0 0 0 31 35 29 40 30 38 90 113 Employee Empowerment 0 0 9 12 26 33 15 36 56 102 106 183 Teamwork 137 192 251 313 519 778 751 1430 2201 2726 3859 5439 Strategic Management 69 51 286 212 331 348 448 700 1012 1381 2146 2692 Outsourcing 0 0 29 27 641 892 1972 3888 3183 4644 5825 9451 Abrahamson, E. 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Hasan Tutar, Ph.D. in management and organization (2000, Atatürk University, Turkey); Associate Professor (2009, Sakarya University, Turkey); Professor (2013, Sakarya University, Turkey). His research interests include organizational strategy, organizational theories, human resource management, and organizational behavior. ORCID: 0000-0001-8383-1464 Teymur Sarkhanov, Bachelor’s degree in management and organization (2005, The Academy of Public Administration, Azerbaijan); Master’s in management and organization (2010, Azerbaijan University of Architecture and Construction, Azerbaijan); Ph.D. (2021, Sakarya University, Turkey). His research interests include organizational theories, strategic management, human resource management, and organizational behavior. ORCID: 0000-0002-2022-9342 Sledenje modi v managementu na osnovi izbranih indeksov: deskriptivna statisticna študija Ozadje/namen: Ceprav se o nacinih vodenja in managementa razpravlja že skoraj 30 let, je moralo preteci nekaj casa, preden so razprave lahko temeljile na dejanskih podatkih. Cilj te raziskave je predvsem izslediti pristope vode­nju in managementu v nekaterih izbranih mednarodnih indeksih v zadnjem skoraj pol stoletja. Osnovno raziskovalno vprašanje študije je, kako se je razvijal zgodovinski tok mode v managementu. Metode: V študiji je bila uporabljena deskriptivna statisticna metoda - zaradi njene ustreznosti bistvu subjekta, namenu raziskave in odgovoru na raziskovalno vprašanje. Raziskavo smo izvedli na podlagi podatkov, zbranih o trendih upravljanja s analiziranjem podatkovnih baz Web of Science in Scopus za obdobje 1975-2020. Rezultati: Moda vodenja in managementa sledi ciklu: hitro sprejemaneje, izvajanje, razocaranje in opustitev. Rezul­tati raziskav kažejo, da pomanjkanje znanja in zavedanja o modi vodenja predstavlja veliko izgubo casa in intelektu­alnega kapitala. Ta ugotovitev je kljucna predvsem za mlade raziskovalce in menedžerje nove generacije. Zakljucek: Medtem ko se novi pristopi, ki imajo oprijemljive protipostavke in jih je mogoce utemeljiti, nadaljujejo, pristopi, ki nimajo konkretnih protipostavk, izginjajo, kar povzroca izgubo casa in duševnega napora. Kljucne besede: Trendi menedžmenta, Moda menedžmenta, Modne muhe menedžmenta, Novi menedžment, Raz­mišljanje menedžmenta DOI: 10.2478/orga-2022-0014 Psychological Capital and Organizational Performance: The Mediating Role of Organizational Ambidexterity Sohrab GHANIZADEH1, Farzad Sattari ARDABILI1*, Mohammad KHEI­RANDISH1, Eshagh RASOULI1, Mohammad HASSANZADEH2 1 Department of Management, Ardabil Branch, Islamic Azad University, Ardabil, Iran (*corresponding author: F.sattari@iauardabil.ac.ir) 2 Department of Economics, University of Mohaghegh, Ardabili, Iran Background and purpose: Today’s dynamic environment is increasingly pressuring public organizations to be simultaneously flexible and efficient. The purpose of this study was to examine the mediating role of organizational ambidexterity in the relationship between psychological capital and the perfor-mance of public organizations that have bureaucratic limitations to their activity and are not as competitive as the private sector. Methods: A questionnaire was developed and distributed among the employees of Management and Planning Orga­nizations in 31 provinces in Iran, and a total of 373 questionnaires were returned. The data was analysed using CFA to validate the measures, and then the mediating effects of organi-zational ambidexterity was tested. Results: The results indicated the significant relationship between psychological capital and organizational perfor­mance (B=0.55) and the positive mediation effect of organizational ambidexterity on this relationship (0.333). Conclusion: The findings can help managers of public organizations to enhance their organizational perfor-mance by strengthening psychological capital and ambidexterity. Keywords: Organizational ambidexterity; Psychological capital; Organizational performance; Public Organizations 1 Introduction The rapidly changing and increasingly competitive business environment has driven organizations to focus on efficient activities in the short and long term and gaining competitive advantages (Cao et al., 2009). In addition to the for-profit sector, these changes have also challenged government agencies to improve their ability to adapt to the environment. However, government agencies have high degrees of centralization and bureaucracy and are subject to various laws that put them under immense pres­sure to create stability and maintain balance. Meanwhile, due to environmental pressures in the service sector, the only way for these organizations to adapt is to develop their ability to simultaneously exploit existing assets and capabilities while exploring new, fundamental capabilities (Markides, 2013). This means that ambidexreity may be helpful to better adapt with the environment. Ambidexter­ity is the combination of both efficiency-oriented and nov­eltyoriented innovation practices (e.g., exploitation and exploration) for short-term success and long-term survival (Clauss, 2021). While various studies have highlighted the important role of organizational ambidexterity in the growth and sur­vival of organizations and its positive effect on organiza­tional performance (Kauppila & Tempelaar, 2016; Junni et al., 2013; Gibson & Birkinshaw, 2004), these studies have mainly focused on the private sector (Smith & Umans, 2015). There are very few studies on ambidexterity and performance in the public sector (Cannaerts et al., 2020; Ghanizadeh et al., 2020) with mixed results (Junni et al., 2013). Some studies have found a positive relation-ship (Gibson & Birkinshaw, 2004; Lubatkin et al., 2006), some a negative relationship (Atuahene-Gima, 2005) and some a contingent effect (Lin et al., 2007). Public organizations face pressures for greater in­novation and meeting pre-determined tar-gets (Plimmer et al., 2017). However, engaging in both innovation and optimization activities simultaneously can create tensions between them (Gieske et al., 2020), which requires pub­lic organizations to be ambidextrous. However, there is evidence suggesting that a U-shaped relationship exists between ambidexterity and performance (Yang & Atua­hene-Gima, 2007), while a number of studies have found no relationship (Venkatraman et al., 2007). The dearth of evidence has led some to view ambidexterity as a public sector problem (Lee et al., 2012) and even question wheth­er public organizations in general can be ambidextrous. While the term organizational ambidexterity itself may not have been used in the context of the public sector, its com-ponents have been considered in the literature (Smith & Omans, 2015). According to Bryson et al. (2008), pub­lic organizations can have the capacity and opportunity to adopt ambidextrous structures and cultures (Bryson et al, 2008), since environmental pressure for delivery of new services in the public sector force these organizations to innovate similar to the private sector. But in public or­ganizations such as Iran’s Ministry of Management and Planning, which is a highly centralized and beurucratic or­ganization, ambidexterity is defined not by organizatrional performance, but also by the management’s ambidexteri­ous behavior. Organizations affiliated with the Ministry of Management and Planningin all the provinces of Iran have the same structure, but with different managers who must carefully adapt to environmental changes. Therefore, their ambidexterity could be considered for prediction of organ­izational level ambidexterity. Individuals and managers are a key element in explo­ration and innovation in the public sector. Studies have shown that individuals play a fundamental role (Raisch et al., 2009) and that the characteristics, capabilities, and behaviors of the members of the organization should be considered to better understand organizational ambidex­terity (Kauppila & Tempelaar, 2016). Managers of or­ganizations in particular provide an important context for exploration and exploitation through their decisions and actions (Gibson & Birkinshaw, 2004). They play a more sig-nificant role than environmental forces in determining organizational outcomes, and their bounded rationality is reflected in their decisions and consequently organization­al outcomes (Smith & Umans, 2015). Similar to the private sector, the managers and employees of public organiza­tions work in a competitive environment and have to keep pace with changes in the environment. Psychological traits of these individuals are an important driver of innovation. For this reason, organizations are increasingly focusing on the psychological needs and psychological capital of their employees (Qiu et al, 2015). Psychological capital goes beyond human and social capital and is positive associat­ed with work motivation and performance (Larson & Lu-thans, 2006) and could be a key factor in individual and organizational ambidexterity and improve performance through efficiency and innovation. Therefore, this study aims to consider the psychological capacities of individu­als and managers as a useful approach to enabling public organizations to become ambidextrous through individual ambidexterity. In other words, the ambidexterity of public organizations should be expressed by the explorative and exploitative behaviors of the managers. 2 Theoretical Framework and Hypotheses 2.1 Organizational ambidexterity and psychological capital Organizational ambidexterity challenges managers in organizations (Jansen et al., 2008). Managers play a cru­cial role in achieving organizational goals by allowing the organization to redeploy resources efficiently and ef­fectively while pursuing new opportunities or respond to threats quicker than competitors (Hodgkinson et al, 2011). Together with the environment, they create an important context for ambidextrous behavior (Lavie et al, 2010) and should be able to flexibly shift between exploration and exploitation (Good & Michel, 2013), reconcile conflicting demands, balance seemingly contradictory forces in the organization (Jansen et al., 2008), and serve as the main driving force behind ambidexterity (Jansen et al., 2009). This role of managers and employees in public organiza­tions is far more complex than in the private sector. Public sector actors are not only limited in terms of authority and decision-making, but also have different organizational missions that are not primarily related to competition with other organizations. Moreover, the managers of public or­ganizations are accountable to various politi-cal and com­munity stakeholders and thus operate under a great deal of pressure, which makes their ability to foster ambidextrous behavior much more important. This could be challeng­ing as public organizations are under pressure to innovate (Nowacki & Monk, 2020) and public sector employees tend to resist innovation (Gieske et al., 2020). A review of the literature on innovation in the public sector shows that most studies have focused on the antecedents of innova­tion and less attention has been paid to its actual outcomes (Gieske et al., 2019). Adopted from Gibson and Birkinshaw (2004), Fiset and Dostaler (2017) suggest four ambidextrous behaviors (initiator, cooperator, broker, and multitasker) and explain how to create an organizational structure for ambidexterity to align and adapt at the individual level. Individual differ­ences underpin the ambidextrous behavior of the members of the organization (Kauppila & Tempelaar, 2016, 2016; Raisch et al., 2009) and understanding them is essential to under-standing ambidextrous behavior at the individual level (Raisch et al., 2009). However, achieving individual ambidexterity is very difficult, since innovation and op­timization require completely different structures and ca­pabilities that can create conflicting challenges for each individual (Eisenhardt et al., 2010). These challenges af­fect emotions and, consequently, individual performance is affected because factors such as positive reinforcement, positive affect, and attitudes of employees (including man­agers) affect their performance (Luthans, 2002), and indi­vidual performance is a function of individual ability and motivation (Wright et al., 1995). However, despite docu­mented role of emotions, there is still little known about what accounts for individual ability to manage conflicting demands (Eisenhardt et al., 2010) and the psychological characteristics that can be used as predictors of these be­haviors have not received much attention (Kauppila & Tempelaar, 2016). Luthans has developed the theory of psychological capital to explain how the psychological capacities of in­dividuals can be measured, developed, and managed to enhance both individual and organizational effectiveness (Newman et al., 2013). Research suggests that high psy­chological capital can trigger innovative behaviors in the workplace (Avey et al., 2010) and look for alternative path­ways to achieve goals when faced with obstacles. They ac­tively work on creative ideas to solve problems and look at problems and opportunities from different angles (Zhou & George, 2003), and have the willpower to overcome the risks and challenges of failure. These individuals feel in control of their destiny, show resilience in the face of problems and adversity, expect positive incomes, develop innovative ideas (Sweetman et al., 2011), and pursue new and creative approaches to problem solving (Peterson & Byron, 2008). Ambidexterity in public organizations such as gov­ernment agencies is mostly influenced by the managers who play a key role in the decision-making process and in balancing the environmental pressure to explore and the internal pressure to exploit. They need to be more self-ef­ficacious to have more work control and make better deci­sions (Narangerel & Semerci, 2020), a characteristic that is associated with their psychological capital. By being open to organizational change, individuals with high psycholog­ical capital are able to develop new paths to achieve goals, have a positive outlook on the future, and adapt to changes and problems (Youssef & Luthans, 2007). Psychological capital allows individuals to move beyond the challenges and setbacks that are inherent to creative work (Sweetman et al., 2011). In addition, psychological capital helps ex­plain the behavioral differences between individuals and managers which could be useful for predicting resistance to or support of innovation (Ghanizadeh et al., 2020). Due to their positive affective and cognitive appraisals, indi­viduals with high psychological capital persevere in the face of problems, find and implement more constructive and useful solutions to problems, and view the outcomes of their effort in a more positive light. Therefore we can expect the following: H1: Psychological capital has a positive effect on or­ganizational ambidexterity. 2.2 Ambidexterity and organizational performance The performance of public organizations is a multi­dimensional construct (Andrews et al., 2010), which is evaluated based on criteria such as efficiency, effective­ness, quality, responsiveness, and legitimacy toward stake­holders (Yang & Panday, 2007). Public organizations are concerned about competitiveness, fiscal sustainability, the growing demands of citizens, and lowering of costs (Rinal­di et al., 2015) and need to adapt to changes to maintain le­gitimacy, improve performance, and create value (Daman­pour et al., 2009). Of course, situations may arise where it is not possible to maintain or improve public service performance without breaking with established practices (Hartley et al., 2013). Tackling these challenges and the complex and evolving mix of technical and social factors require innovative ideas and unconventional approaches (Eisenhardt et al, 2016), since they are perceived by in­dividuals as new (Rogers, 1995) and represent disconti­nuity with the past (Osborne & Brown, 2011). In addition to improving the performance of public organizations as an intangible organizational resource, innovation is in­creasingly recognized under new public management as a means for effectively addressing social challenges such as growing citizen expectations, globalization, and demo­graphic and climate change as well as boosting economic growth (Cannaerts et al., 2020). Innovation in the public sector can take place in delivery, coordination, regulatory, and analytical areas (Lodge & Wegrich, 2014). However, public organizations face tensions between pressures for innovation (Plimmer et al., 2017) and the demand for efficiency and accountability (Hartley et al., 2013). Instead of increasing their innovation capacity, managers of public organizations tend to focus on improv­ing the ability of public servants to deliver, regulate, and coordinate tasks (Lodge & Wegrich, 2014) and streamlin­ing internal and external operations to optimize efficiency (Nowacki & Monk, 2020). Bureaucracies have tradition­ally been organized around exploitation of existing re­sources and capabilities, and are often incompatible with explorative activities that produce innovation (Boukamel & Emery, 2017). They are characterized by centralized decision-making, standardized work processes, and high levels of specialization, and their structure stimulates ex­ploitation, while suppressing innovation (Cannaerts et al., 2016). Hence, public organizations have always faced challenges in improving performance through innovation (Osborne & Brown, 2011). However, the public sector is urged to innovate and at the same time enhance efficiency and lower costs (Pollitt & Bouckaert, 2004) since relying on formal organizational routines is not enough to improve performance (Brown & Duguid, 1991). Public organiza­tions must be both efficient and innovative to overcome today’s challenges (Cannaerts et al., 2016) and finding the right balance between exploitation and exploration is es­sential to improving organizational performance (March, 1991). Individual ambidexterity is a key factor in organiza­tional performance (Kammerlander et al., 2015) that helps organizations overcome the structural inertia caused by the focus on exploitation, while preventing excessive explora­tion that is without results (Levinthal & March, 1993). De­spite the emphasis of new public management on establish­ing exploration units in public organizations (Boukamel & Emery, 2017;) and despite the initial research on ambidex­terity in the public sector (Smith & Umans, 2015; Plimmer et al., 2017; Gieske et al., 2019), there is little evidence on how public organizations can simultaneously balance effi­ciency and innovation (Smith & Umans, 2015) and little insights as to the conditions under which it can emerge in the public sector (Umans et al., 2020). While focus on op­timization can improve the current performance of public organizations and allow them to provide existing services at a lower cost and with higher efficiency, pressures from the external environment require them to engage in explor­ative activities. Although ambidexterity is a useful concept for un­derstanding the non-financial outcomes of public organ­izations (Umans et al., 2020), it is difficult to explain its effects on performance (Junni et al., 2013). Disagreements seem to stem from the context in which it is studied, and the relationship between ambidexterity and organizational performance needs further investigation, especially in the public sector. Therefore, the second hypothesis is devel­oped as follows: H2: Organizational ambidexterity has a positive effect on organizational performance. 2.3 Mediating role of organizational ambidexterity Psychological capital is an individual’s positive ap­praisal of circumstances and probability of success based on motivated effort and perseverance (Luthans et al., 2007;). It gives individual the conviction to face challeng­es and difficulties and to recover from setbacks. Psycho­logical capital contributes to an individual’s organizational performance. However, the way in which psychological capacities transform into tangible outcomes such as high productivity and better organizational citizenship be­havior is often mediated by other factors . For example, psychological capital helps individuals balance explora­tion and exploitation (Gibson & Birkinshaw, 2004) and enables them to mobilize their affective, cognitive, and positive organizational behavioral resources to organiza­tional citizenship behavior and to achieve organizational goals (Pouramini, Fayyazi, & Yahyavi Ghasem Ghesh­laghi, 2018). From this perspective, psychological capital helps improve performance by enhancing ambidexterity, and ambidexterity acts as a mediator between contextual factors and organizational performance to encourage be­haviors needed to improve performance (Gibson & Birkin­shaw, 2004). Employees with high levels of psychological capital are more resilient to tensions, conflicts, and stress and can make better decisions. Therefore, they will be more adaptive to change and make the right optimization decisions, which can ultimately lead to high behavioral ambidexterity and better performance. Patel et al. (2013) showed that ambidexterity mediates the relationship between high-performance work systems and firm growth, and that firms with such systems achieve higher performance through ambidexterity (Patel et al., 2013). In addition, ambidextrous behavior has been shown to mediate the relationship between career adaptability and performance and facilitate effective service delivery (Affum-Osei et al, 2020). Ambidexterity also mediates the relationship between ambidextrous organizational culture and innovation outcomes (Wang & Rafiq, 2014), human resource flexibility and performance (Úbeda-García et al., 2017), and management team behavioral integration and performance (Lubatkin et al., 2006). Therefore, it can be assumed that: H3: Organizational ambidexterity mediates the rela­tionship between psychological capital and performance. Given this background, the present study follows the conceptual model shown in Figure 1 in which the psycho­logical capital of employees strengthens organizational ambidexterity and organizational ambidexterity improves the performance of public organizations. 3 Methodology 3.1 Sample and Procedure The participants of this study are the managers of Man­agement and Planning Organizations in the 31 provinces of Iran, which are responsible for planning and budgeting and should continuously evaluate the performance of their respective organizations and ensure that budget targets are met. These organizations are bureaucracies with central­ized decision-making. Therefore, due to the similarity of tasks and uniformity of structures throughout the country, simple random sampling was used to select the partici­pants in each province. To this end, the middle and top managerial of each organization was used for sampling (N = 644). Then, the questionnaire was emailed to the managers of each organization between March and May 2021Finally, 373 participants returned the questionnaire, of whom 68.4% were male and 31.6% female; 6.2% had a doctoral degree, 64.6% had a master’s degree, 27.1% had a bachelor’s degree, and 2.1% had an associate degree or lower; 58% were in the 40-50 years age group, and none of the participants was below 30 years of age. The Kai­ser-Meyer-Olkin (KMO) index was 0.932 and chi-square was 3272.918, which indicate sample size adequacy. 3.2 Measures 3.2.1 Organizational ambidexterity Ambidexterity is considered a paradox whereby its components, i.e. exploration and exploitation, create per­sistent and conflicting demands on an organization (Ko­ryak et al., 2018). We used individual ambidexterity to measure organizational ambidexterity, because in public organizations that are highly centralized and bureaucrat­ic, it is the ability of managers to behave ambidextrously that determines the organization’s approach to exploration and exploitation, and it is the managers’ innovative behav­ior that promotes creative and explorative activities in the organization. Therefore, we argue that organizational am­bidexterity in government agencies is driven by the ambi­dextrous behavior of managers. In the present research, ambidexterity is assessed using the questionnaire of Sharma et al. (2020), which consists of 10 items, 5 for exploration and 5 for exploitation, rated on a 5-point Likert scale. Examples of items in this section are “Our organization bases its success on its ability to ex­plore new methods”, and “Our organization continuously improves the reliability of its services.” The items are rated from 1 for “Completely Disagree” to 5 for “Completely Agree”. The Cronbach’s alpha for the two subscales are 0.88 and 0.857, respectively. 3.2.2 Psychological capital Psychological capital is one of the important concept in positive psychology that focuses on individual strengths and performance improvement in different aspects of life (Youssef & Luthans, 2007). In addition to the four main components of psychological capital, namely hope, effi­cacy, resilience, and optimism, many other positive psy­chological resources such as creativity, gratitude, spiritual­ity, and courage can be included in the measurement of psychological capital (Luthans & Youssef, 2017). These eight components are adopted in the present research: 6 items for efficacy, resilience, optimism, and hope (Luthans et al., 2007a) with a Cronbach’s alpha of 0.89, 0.89, 0.89, and 0.88, respectively; 12 items for courage (Norton & Weiss, 2009) with a Cronbach’s alpha of 0.877; 6 items for gratitude (McCullough et al., 2002) with a Cronbach’s alpha (0.82); 22 items for spirituality (Delaney, 2005) with a Cronbach’s alpha of 0.94; and 4 items for creativity (Jaiswal & Dhar, 2015) with a Cronbach’s alpha of 0.93. These items are rated on a 5-point Likert scale from 1 for “Strongly Disagree” to 5 for “Strongly Agree”. Examples of items in this section are: “I feel confident in represent­ing my work area in meetings with management”; “At the present time, I am energetically pursuing my goals”; “I can get through difficult times at work because I’ve ex­perienced difficulty before”; “I always look on the bright side of things regarding my job”; “I am grateful to many people”; “I tend to face my fears”; “I believe that all liv­ing creatures deserve respect”; “I seek new ways to solve problems.” 3.2.3 Organizational performance Organizational performance can be defined as the actu­al results of an organization as measured against its intend­ed outputs. In the present research, organizational perfor­mance is measured using the scale of Gieske et al. (2019) with six items. Examples of these items are: “we deliver more quality against similar costs and time”; and “stake­holders are satisfied with the organization”. These items are rated on a 5-point Likert scale from 1 for “Strongly Disagree” to 5 for “Strongly Agree”. A Cronbach’s alpha of 0.856 has been obtained for this scale by Gieske et al. (2019). 4 Results 4.1 Analysis results Smart PLS and SPSS 20 were used to analyze the data. Before testing the hypotheses, the validity of the instru­ment was evaluated using convergent validity and discri­minant validity. In addition, confirmatory factor analysis (CFA) was used to evaluate the measurement model. Several goodness of fit indices such as relative fit in­dex (RFI), normed fit index (NFI), and comparative fit in­dex (CFI) that have been suggested for structural equation modeling (SEM) (Kline, 2015) were used to evaluate the fit of the proposed model. Table 1 shows the measures of central tendency and dispersion as well as the correlation of the variables. 4.2 Discriminant validity of constructs First, CFA was performed to test the construct validi­ty of psychological capital, organizational ambidexterity, and organizational performance. To this end, two models were selected and compared. First, first-order CFA was performed and the results showed the validity of the eight components of the psychological capital (efficacy, hope, resilience, optimism, gratitude, courage, spirituality, and creativity) (NNFI = 0.95, CFI = 0.94 , NFI = 0.94, RM­SEA = 0.042), the mediator variable organizational ambi­dexterity (NNFI = 0.94, CFI = 0.90, NFI = 0.91, RMSEA = 0.048), and the dependent variable organizational perfor­mance (NNFI = 0.91, CFI = 0.92, NFI = 0.90, RMSEA = 0.022), indicating that the model is a good fit. In the second path, the structural equation model of the research was evaluated using standard errors and all factor loadings are greater than 0.05 (NNFI = 0.99, CFI = 0.99, NFI = 0.98, RMSEA = 0.056), thus confirming the overall fit of the model. In addition, divergent validity was tested by comparing the average variance extracted (AVE) for each construct with the square of correlation coeffi­cients. AVE for each construct was greater than the square of the related correlation coefficients, indicating the di­vergent validity of the constructs. We also used Harman’s single-factor test to check for common method bias, and the results showed that all correlation coefficients did not exceed 0.90 and that there was no common method bias. Table 2 shows the overall reliability of the constructs and the factor loadings, and Table 3 shows the results of the validity test. In the present study, SmartPLS 3.0 is used to examine the theoretical framework. Prior research reveal that the PLS technique is the best in handling both complex large and simple models, and there is no need to meet the nor­mality criteria (Hair et al. 2016). Cross-validated redundancy (Q2) as a measure of pre­dictive relevance was used in this study to measure the effects of latent variables. All values must be greater than 0, and Table 4 shows that the present study satisfies this criterion. VIF values are also considered as the reciprocal of tol­erance. The resultsshow that all VIF values are less than 3.30 (Table 4). Therefore, the data set is not subject to common method bias. In this study, the value of the coefficient of determina­tion (R2 = 0.569) indicates that psychological capital and organizational ambidexterity together explain 46.9% of the variance in organizational performance (Table 4). 4.3 Hypothesis testing Table 5 provides the results of testing the hypotheses. Regarding the first hypothesis, the results indicate the pos­itive effect of psychological capital on organizational am­bidexterity (F = 141.336, p = 0.000), and R indicates that this effect is significant (R = 0.525). According to the results in Table 4, the second hypoth­esis for the positive effect of organizational ambidexterity on organizational performance is confirmed (F = 327.963, p = 0.000) at the 99% confidence interval (CI).. The results also indicate the significant effect of the components of or­ganizational ambidexterity (exploration and exploitation) on organizational performance (R coefficient of 0.659 and 0.628, respectively). The relationship between exploration and organizational performance (B = 0.757) was stronger than the relationship between exploitation and organiza­tional performance (B = 0.743). Table 4 also shows the effects of the mediator variable. 5 Discussion Previous studies on organizational ambidexterity have mainly focused on the development of this ability at the organizational and team levels (Gibson & Birkinshaw, 2004), but this study sought to gain a deeper understand­ing of the psychological factors that underlie different behaviors among individuals and explore the relationship between the contexts of individual behaviors and develop­ment of ambidexterity in the organization. The results showed that psychological capital can have a direct impact on the components of organizational ambi­dexterity, which is consistent with Kauppila and Tempe­laar (2016). For example, Kauppila and Tempelaar (2016) highlight the significant role of psychological capital, including efficacy, in the capacity of individuals for am­bidextrous behavior, because high levels of efficacy pro­motes ambitious goal-setting and greater effort, thus help­ing individuals to manage the challenges associated with paradoxical orientations and conflicting work demands. This is consistent with the findings of Katou (2021), with one difference in that Katou shows that ambidexterity is affected by human capital, which is itself positively in­fluenced by the dynamically changing environment. This indicates the importance of acquiring and strengthening capabilities for public sector organizations that enable in­dividuals and managers to be effective in both optimization and innovation and gain mastery in dealing with existing tensions (Gieske et al., 2019) and the changing environ­ment to achieve higher productivity. As another compo­nent of psychological capital, hope encourages individuals to persevere toward goals and redirect paths toward them if necessary. Especially in public organizations, past suc­cesses can give individuals greater hope in innovative ide­as and help them better enforce laws in the face of change. As expected, ambidexterity was associated with higher levels of perceived performance. This is consistent with previous studies that have found the positive effect of am­bidexterity on performance (e.g., Junni et al., 2013; Plim­mer et al., 2017; Gieske et al., 2019). Of course the level of analysis and the method of measurement can affect the relationship between ambidexterity and organizational performance (Junni et al., 2013). In public organizations, performance is defined as achieving public goals effective­ly and efficiently, while preserving present and future qual­ity of public services and maintaining legitimacy among stakeholders (Verbeeten, 2008). Even when faced with diminishing financial resources, public organizations are expected to continuously improve the quality of their ser­vices to maintain public confidence (Pablo et al., 2007). Organizations that are able to simultaneously pursue ex­ploration and exploitation are more likely to outperform those that focus on one of these at the expense of the oth­er (Tushman & O’Reilly, 2013), because it will inevita­bly create problems and tensions (Gibson & Birkinshaw, 2004) that undermine long-term performance (Floyd & Lane, 2000). Lack of functionality of rules promotes ambi­dextrous behavior, while compliance burden is negatively associated with ambidexterity (Sharma et al., 2020). While public organizations are required to comply with the rules regardless of their burden, lack of functionality can stimu­late search for new paths and more innovative approaches. The results of the present research also showed the sig­nificant positive relationship between the components of ambidexterity and performance. This finding is consistent with the results of Gieske et al. (2020), and Gieske et al. (2019). To fulfill employee obligations, organizations not only must increase their performance in providing exist­ing services, but also need to innovate (Nowacki & Monk, 2020). Acquiring and strengthening capabilities enable public organizations to both optimize and innovate and deal with existing tensions more proficiently (Gieske et al., 2019). Organizations with limited resources are more in need of balancing explorative and exploitative activities (Cao et al., 2009; Junni et al., 2013), which is essential to improving organizational performance (Damanpour et al., 2009). This is extremely challenging in public organiza­tions that are accountable for government budgets, which could encourage them to focus more on exploitation than innovation to meet budget targets and avoid conflicts or even penalties. However, in a dynamic environment, ex­cessive exploitation reduces the ability of the organization to effectively adapt to changes (Wang & Li, 2008) and in general. As such, performance improvement in the pub­lic sector largely depends on innovation, which does not receive enough attention in the current organizational dis­course (Choi & Chandler, 2015; Osborne & Brown, 2011; Gieske et al., 2019) and requires a shift from overexploita­tion to ambidexterity. According to the present findings, exploration has a stronger effect on performance than exploitation, which is inconsistent with the results of a number of studies. Damanpour et al. (2009) found that optimization has a stronger effect on performance than innovation, implying that public organizations often try to enhance their perfor­mance through continuous improvement of policies, pro­cesses, techniques, and services rather than by engaging in innovation due to its perceived risks and higher trans­action costs (Damanpour et al., 2009; Gieske et al., 2019). The literature disproportionately emphasizes innovation, while the potential cost or risks are underestimated (Choi & Chandler, 2015). Public organizations usually have a high degree of formalization, which is positively associ­ated with exploitative innovation, but not with explorative innovation (Jansen et al., 2006). These organizations have well-designed procedures, facilitate performance, encour­age employee commitment, and reduce role conflict and ambiguity. Research on the effect of formalization on am­bidexterity has yielded mixed results (Junni et al., 2015). Nonetheless, the positive effect of innovation is notewor­thy and directly affects organizational performance as an organizational capability (Lin & Chen, 2007). The results of this study also showed that organiza­tional ambidexterity not only affects organizational perfor­mance directly, but also mediate the relationship between psychological capital and organizational performance. Psychological capital is a key construct in positive psy­chology, which focuses on the positive aspects of individ­uals instead of what is wrong or dysfunctional with them (Luthans et al., 2006) and improves performance and ad­aptability relying on the strengths of individuals and the organization (Luthans et al., 2007b; Pouramini, Fayyazi, & Yahyavi Ghasem Gheshlaghi, 2018). Psychological capital affects individual productivity and can be a source of com­petitive advantage for organizations (Pouramini, Fayyazi, & Yahyavi Ghasem Gheshlaghi, 2018). It is also positively associated with organizational performance (Luthans & Youssef, 2017), and this effect is reinforced by ambidex­terity. Our findings in this regard are consistent with the results of Patel et al. (2013), Úbeda-García et al. (2017), and Affum-Osei et al. (2020), which have confirmed the mediation effect of ambidexterity on various organiza­tional outcomes. As Gibson and Birkinshaw (2004) have argued, ambidexterity is not only an organizational capa­bility, but also a meta-capability that mediates the rela­tionship between various contextual features and organi­zational performance. Ambidexterity is a vital mechanism (Affum-Osei et al. 2020) that creates new capacities for the organization while strengthening other beneficial rela­tionships. The overall model of the effect of psychological capital and ambidexterity on organizational performance is consistent with Katou (2021), who found that human capital management practices constitute an antecedent of organizational ambidexterity and organizational perfor­mance constitutes a consequence. Finally, psychological capital not only plays a crucial role in the implementation of ambidexterity, but is also among the factors that directly and indirectly contribute to organizational success. Public organizations need to iden­tify and evaluate different dimensions of psychological capital in their managers and employees, and promote and develop them by implementing short and long-term pro­grams. These organizations should also take full advantage of psychological capital in their attempt to achieve organ­izational ambidexterity, and consider it when appointing individuals to management positions, which will be crucial to improving organizational performance. This study has a number of limitations. Firstly, it uses cross-sectional data, which means that it fails to capture the dynamic interplay between psychological capabilities and ambidexteity. Secondly, our findings are limited by the nature of the sample, which consists of government organizationas with higly centeralized decision-making processes. The results may be different in future studies on other industries, e.g., in private companies with decentralized management sys­tems. Thirdly, the data on the independent variable (psycho­logical capital), the dependent variable (organizational performance), and the mediating variable (organizational ambidexterity) was collected using the same survey. Al­though this is a common practise in the field, we tested for common method bias and found no cause for concern (Podsakoff et al., 2003). Future researhers are encouraged to replicate the pro­posed model in other organizations that compete with oth­ers to survive. References 1Received: 16th March 2022; revised: 9th June 2022; accepted: 15th June 2022 Figure 1: Conceptual model Table 1: Correlation index between variables Table 2: Validity of the constructs and factor loadings of the items Construct Items Loading PsyCap NFI = 0.94 IFI = 0.96 CFI = 0.94 Chi-square = 32.41 RMSEA= 0.042 Cronbach’s a = 0.966 Efficacy .815 Hope .809 Resilience .751 Optimism .653 Gratitude .758 Courage .745 Spirituality .836 Creativity .663 Organizational Performance NFI = 0.90 IFI = 0.92 CFI = 0.834 Chi-square = 10.55 RMSEA = 0.022 Cronbach’s a = 0.966 My organization has improved performance over the last five years for my work field on: Efficiency (results remain the same or improve against lower costs) .696 Quality (quality increases against similar costs and time) .736 Effectiveness (we reach our goals more effectively) .795 Collaboration (we reach our goals better by combining them with the goals of others) .694 Legitimacy (stakeholders are satisfied with the organization) .664 Future-proofing (we can face the future with confidence and expected future developments are included in policies and plans) .645 Ambidexterity NFI = 0.91 IFI = 0.91 CFI = 0.90 Chi-square = 62.66 RMSEA = 0.048 Cronbach’s a = 0.891 Exploration .596 Exploitation .579 Table 3: Validity test results Subscales CR AVE MSV ASV PsyCap 0.952 0.714 0.276 0.276 Ambidexterity 0.898 0.470 0.469 0.469 Performance 0.836 0.462 0.469 0.336 Table 4: Assessment of the structural model R2 Q2 F2 VIF Organizational Performance 0.569 0.439 0.428 1.000 Table 5: Structural model results Variable B SE t P PsyCap on Performance .55 .006 9.717 0.000 Ambidexterity on Performance .425 0.23 18.110 0.000 Exploitation on Performance .743 .048 15.535 0.000 Exploration on Performance .757 .045 16.891 0.000 Variable Value SE Z P Indirect effect and significance using normal distribution 0.333 0.044 7.534 0.000 Sobel Variable M SE LL95%CI UL95%CI Bootstrap results for indirect effect 0.537 0.054 0.425 0.640 Effect Note: N = 373 Bootstrap sample size = 1000, LL = lower limit, UL = upper limit, CI= confidence interval Testing the significance of indirect paths using bootstrapping and the Sobel test showed that organizational ambidexterity sig-nificantly mediates the relationship between psychological capital and organizational performance at the 95% CI (LL = 0.425; UL = 0.640). 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The Leadership Quarterly, 14(4-5), 545-568. https://doi.org/10.1016/S1048-9843(03)00051-1 Sohrab Ghanizadeh is a PhD student in the Department of Management, Islamic Azad University, Ardabil Branch, Iran. He has experiences about 20 years in public sector as a HRM manager. He mainly studies on Am-bidexterity. ORCID: https://orcid.org/0000-0001-6003-3486, E-Mail: s_ganizade@yahoo.com Farzad Sattari Ardabili is Assistant Professor in the Department of Management, Islamic Azad University, Ardabil Branch, Iran. Farzad has worked as executive manager in consultant company and as a research head at University. His practical experience in research and educational organizations, had persuaded him to study on organizational behaviour. He is mainly studying and conducting research in leadership and organizational behav-iour. Currently he is working on wisdom and its relationships with career adaptability and ambidextrous behav-iour. Because of his educational background in operational research, he is particularly interested in mixed method research in different multicultural organizations. ORCID: https://orcid.org/0000-0001-9734-7921, E-Mail: F.sattari@iauardabil.ac.ir Mohammad Kheirandish is Assistant Professor in the Department of Management, Islamic Azad University, Ardabil Branch, Iran. Mohammad is mainly studying and conducting research in organizational strategy and flex-ibility in accordance with dynamic environment. ORCID: https://orcid.org/0000-0002-3913-3017, E-Mail: m_khirandish1358@yahoo.com Eshagh Rasouli is the president of Islamic Azad Uni­versity, Ardabil Branch, Iran. He has worked as a man­age-ment consultant in public sectors more than 15 years. He is interested in Organizational Agility, Strate­gic Human Resource Management, and Organizational Culture. He has supervised more than 20 PhD students in Man-agement. ORCID: https://orcid.org/0000-0003-1253-5507, E-Mail: e.rasouli@iauardabil.ac.ir Mohammad Hassanzadeh is an associate professor of economics in Mohaghegh University. He is collabo­rat-ing in supervising PhD and master students in the field of management and business. He is working as a consult-ant in public sector for 10 years and is familiar to the organizational culture in public sectors and the prob­lems of the flexibility of these organizations. ORCID: https://orcid.org/0000-0002-7768-2471, E-mail: m.has­sanzadeh@uma.ac.ir Psihološki kapital in organizacijska uspešnost: posredniška vloga organizacijske ambideksternosti Ozadje: Današnje dinamicno okolje vse bolj pritiska na javne organizacije, da so hkrati fleksibilne in ucinkovite. Namen te študije je bil preuciti posredniško vlogo organizacijske ambideksternosti v razmerju med psihološkim kapi­talom in uspešnostjo javnih organizacij, ki imajo birokratske omejitve pri svojem delovanju in niso tako konkurencne kot zasebni sektor. Metodologija: Razvit je bil vprašalnik, ki je bil razdeljen med zaposlene v organizacijah za upravljan-je in nacrto­vanje v 31 provincah v Iranu. Vrnjenih je bilo skupaj 373 vprašalnikov. Podatki so bili analizirani z uporabo CFA za validacijo ukrepov, nato pa smo testirali posredovalne ucinki organi-zacijske ambideksternosti. Rezultati: Rezultati so pokazali pomembno razmerje med psihološkim kapitalom in organizacijsko uspešnostjo (B=0,55) ter pozitiven mediacijski ucinek organizacijske ambideksternosti na to razmerje (0,333). Zakljucek: Ugotovitve lahko pomagajo menedžerjem javnih organizacij izboljšati njihovo organi-zacijsko uspešnost s krepitvijo psihološkega kapitala in dvosmernosti. Kljucne besede: Organizacijska ambideksternost, Psihološki kapital, Organizacijska uspešnost, Javne organizacije DOI: 10.2478/orga-2022-0015 Core Job Characteristics and Personal Work Outcomes: The Mediating Role of Critical Psychological States: Empirical Evidence from Northern Cyprus Hotel Sector Mohammad SLEIMI1, Malek Bakheet ELAYAN2, Lamar ABU HAJLEH3 1 Business and Economic Faculty, Palestine Technical University – Kadoorie, Tulkarm, Palestine, mohammad.sleimi@ptuk.edu.ps 2 Institute of Public Administration - IPA, Riyadh, Saudi Arabia, elayanm@ipa.edu.sa 3 Higher Education Faculty, Near East University, Girne, Northern Cyprus, lamar.a.hijleh@gmail.com Background and purpose: The purpose of this study is to investigate the relationship between core job character­istics (CJC) and personal work outcomes (OUT), as well as the roles of experienced meaningfulness of work (EMW) and experienced responsibility for outcomes of work (EROW) in mediating the CJC–OUT relationship. Specifically, this study attempts to examine the effectiveness of CJC in improving EMW and EROW and to shed light on the roles of EMW and EROW in enhancing the OUT of employees in the Northern Cyprus hotel sector. Methods: This study adopted a quantitative approach to collect and analyze the data from 420 tourism stakeholders in Northern Cyprus hotel sector. A partial least squares (PLS) technique using Smart-PLS was applied to test the direct relationships within the research model and determine any mediating effects. Results: The analysis revealed strong support for meaningfulness of work and experienced responsibility for out­comes of work acting as partial mediators in the relationship between core job characteristics and personal work out­comes. Moreover, core job characteristics was found to have a reasonable direct effect on personal work outcomes, experienced meaningfulness of work, and experienced responsibility for outcomes of work. Conclusion: The current study points to the importance of including experienced meaningfulness of work and experienced responsibility for outcomes of work as mediating variables to understand better the relationship between core job characteristics and Personal work outcomes. Several theoretical and practical implications are included before pinpointing the directions of potential future studies that makeup on the evidence-based argument regarding the results of this study. Lastly, top management in hotel sector would benefit from job redesign because the results demonstrated that the core job characteristics have a positive effect on their work outcomes. Keywords: Core job characteristic, Experienced meaningfulness, work outcome 1 Introduction The role of human resource management is to organise and handle individuals within the workplace environment (Huang and Su, 2016). Within a real work environment, each person’s work consists of several tasks or duties/roles and is dependent on specific circumstances that give a lev­el of speciality to this work. On the other hand, individual personalities and preferences, by their very nature, vary from one person to another, and these differences usually lead to several attitudes and behaviours being expressed within the workplace environment. Under these complex conditions, the aim of management is to achieve optimal employee performance and business output (Grant, 2007). Thus, job design can be an invisible guiding hand that leads to making a vital connection between individuals’ needs and management goals is not saturated (Baig and Zaid, 2020; Luz et al., 2018). Nowadays, the determination and distribution of tasks for every job within an organization play a vital role in attaining organizational goals by in­creasing employee performance (Tang et al., 2017). How­ever, identifying and allocating such tasks is not easy and is considered a major organizational challenge (Siengthai and Pila-Ngarm, 2016). Moreover, when these tasks and duties are not distributed well, this can lead to negative effects instead of positive ones, and ultimately to failure in human resource management practices (Grant, 2007). In this context, individual performance cannot be con­sidered a luxury in any sector or organization. Instead, it is an essential issue for all modern, forward-thinking organi­zations and cannot be ignored. Abuhjeeleh et al. (2019) in­dicated that the five-star hotel workplace in particular suf­fers from several negative elements such as: low employee motivation, high work stress, conflicts of tasks among team members, instances of poor productivity, all of which are a result of not getting the appropriate job design for their tasks and because of some shortcomings in their man­agers’ motivational practices. Consequently, Al-Hawary and Al-Smeran (2017) asserted that the shortcomings in job designs and motivational systems can negatively affect individual performance. Therefore, the following question arises: How can management give employees tasks and duties to meet organizational goals that will also improve employee satisfaction and achieve the optimal individual performance level? The workers in a five-star hotel can have a positive ef­fect on the overall image of the hotel. However, that is not all, their importance goes beyond the scope of their own job and can have several positive impacts within the wider tourism industry environment, such as increasing custom­er satisfaction with a destination maximising occupancy rate opportunities (Amin, 2016). The current study seems to be one of only a few empirical studies in the hotel sector in order to highlight job design as a useful non-material motivational tool. Why? Because, when hotel employees are internally motivated, they should offer a better service to their customers. In addition, how this aspect can be uti­lized to improve the sector. Lastly, evidence from the liter­ature shows a clear shortage of empirical studies that focus on the role of job design and its relationship with motiva­tion, especially in the context of Northern Cyprus and the hotel sector in particular (Krambia-Kapardis et al., 2016). 2 Literature Review 2.1 Core job characteristics Hackman and Oldham first developed the CJC concept in their job characteristics model which they proposed in 1974 (Astrauskaite et al., 2015). According to Park’s (2017) definition, CJC involves the factors that able to motivating employees internally. This means that under appropriate workplace conditions, employees are inter­nally motivated to perform their roles effectively. The job characteristics model describes five job dimensions that are linked to positive personal- and work-linked results. The dimensions are job autonomy, feedback, task identity, task significance, and variety. A lack of these dimensions of CJC has been identified by Kim et al. (2020) as contrib­uting to lower motivation, lower job satisfaction, reduced work quality, and higher absenteeism and staff turnover. It has also been reported by (Grant, 2007), that CJC has an ultimate impact on OUT, with psychological states acting as a mediator between job characteristics and OUT. Ac­cordingly, the CJC concept has attracted immense interest among researchers who have sought to understand how CJC influence personal work outcomes and satisfaction in assigned functions (Wegman et al., 2018). As this study focus on the linkage between CJC, three of the five dimensions of CJC have been chosen in the re­search model (i.e., skills variety, task identity, and task sig­nificance), because these three dimensions are considered to be closely associated with experienced meaningfulness comparing to autonomy and feedback dimensions which are linked with responsibility of outcomes and knowledge of results respectively (Hackman and Oldham, 1974). In this context, CJC has been defined in the work context as the condition where employees consciously think and feel certain things about their jobs, and it is these conscious thoughts and feelings that ultimately lead to personal work outcomes (Hackman and Oldham, 1974). The current study proposes that the possession of these CJC dimen­sions will largely influence the personal work outcomes (OUT). According to Matilu and K’Obonyo (2018), CJC lead to success in outcomes of work when job satisfaction con­structs, employee well-being, and employee competence are at play. However, there is limited research on the in­fluences that job characteristics may have on the outcomes of the work of employees. Recently, Jasko et al. (2020) stressed that CJC are distinct, and their influence on the outcomes of work varies. Jasko et al. (2020) also point­ed out that irrespective of the possession of similar CJC by a number of individuals, the job outcomes and success attributes will be distinct and unique to each of those in­dividuals. Also, Matilu and K’Obonyo (2018) proposed that the link between CJC and job outcomes is only evi­dent when satisfaction and motivation lead to lower staff turnover and absenteeism. These considerations led to the development of the following hypotheses: H1: Core job characteristics positively affect personal work outcomes. Work outcomes have been defined by Rudolph et al. (2017) as the process in which individual feedback or knowledge on the extent to which an individual has been successful in their work roles is evident. This can be iden­tified from the information obtained from production rates or even customer satisfaction scores. Likewise, Cerne et al. (2017) pointed out that the obtained feedback contrib­utes to a high level of knowledge among employees about the results of their work. Where the employee is offered appropriate feedback regarding their results, the level of motivation would be improved. Johari et al. (2018) introduced the idea that job char­acteristics’ behavioural and attitudinal constructs are ap­plicable in measuring OUT. This later affirmed this is be­cause a job design consists of the CJC that significantly influences the outcomes of employees’ job performed at work. The revised model of job design affirmed this prop­osition by Garg and Rastogi (2006), who noted that job characteristics are a significant implication for employee performance. Kataria et al. (2013) also argued that out­comes could be enhanced or improved when specific job roles offer improved autonomy and challenges to employ­ees. It is nevertheless worth noting that because the CJC of employees vary significantly, they are critical antecedents for determining the final outcomes of work. On the other hand, experienced meaningfulness of work in organizations is substantially a recent concept and, as yet, minimal research has been carried out with reference to this construct. Stein et al. (2019) defined this construct as work experienced as mainly being significant. Bailey et al. (2019) noted that all jobs could be experi­enced as more and less meaningful roles in terms of prin­ciple. The foundation of work meaningfulness stems from a distinct source and it includes developing and becoming an individualised authentic self, being of service to oth­er people, and expressing full individual potential (Sleimi and Davut, 2015). Importantly, lack of EMW is identified by Martela and Pessi (2018) as the inexistence of control over and the inability to see individual work value. Summing up the definitions proposed in other studies, Stein et al. (2019) identified EMW as inclusive of mean­ingfulness in work and OUT. EMW is used to focus on the quality of the work, focusing on how the work roles are implemented. From the above definitions of EMW, it is evident that there is a significant appreciation that the construct is identified by the feeling that the work is sig­nificant, leading to increased autonomy. The reasons for a lack of EMW have not been evaluated in depth. However, Bailey et al. (2019). found that a lack thereof is mainly the result of the existence of feelings of self-estrangement, powerlessness, and lowered intrinsic fulfilment. These forms of experiences are equally inclusive of feelings of being used for a purpose other than one’s own, being giv­en tasks/roles that are seen as ‘pointless’, unfair treatment, failure to be recognised, feelings of being isolated and there being an absence of a supportive relationship. Ac­cording to Lepisto and Pratt (2016), the of a lack of EMW identified characteristics may often manifest as alienation (i.e., the sense of being separated from oneself and per­sonalised control) or having a sense of anonymity (i.e., the presence of uncertainties and ambiguities pertaining to the basic value of an individual’s role at work). The existing gap in past studies on EMW is primarily related to the fact that they focused on the concept of EMW and its lack as an equivalent aspect despite the two concepts being concep­tually and significantly distinct Lips-Wiersma and Morris (2009). In introducing the concept of EMW, Aguinis and Gla­vas (2019) noted that EMW can act as a mediating variable of job characteristics and the extent to which it plays this role leads to positive outcomes for employees, for their organizations, and for external stakeholders. Similarly, Pierce et al. (2009) found that EMW could influence CJC and OUT, but not primarily in terms of providing jobs with more meaningfulness, but rather in terms of allowing in­dependent operations in complex and rich jobs. This sup­ports Astrauskaite et al. (2015), who described the autono­my factor of the Hackman and Oldham job characteristics model as the freedom and discretion of employees in de­ciding on how to carry out their own work. Therefore, the following hypothesis were formulated as follows: H2: Core job characteristics positively affect experi­enced meaningfulness of work. H3: Internal experienced meaningfulness of work me­diates between core job characteristics and personal work outcomes. Barrick et al. (2013), reviewed the literature on CJC and EMW and found evidence that EMW triggers the task-specific motivation process that then influences the attainment of a variety of OUT. Therefore, the following hypotheses was constructed: H4: Experienced meaningfulness of work positively af­fects personal work outcomes. Hackman and Oldham (1974) defined EROW as the individual’s ability to feel personally accountable for the outcomes or results of their work or assigned tasks. This means that, for EROW to be present, the employee needs to be offered some degree of freedom in the performance of their role/tasks. They must be allowed to utilise this freedom to make appropriate decisions on how best to per­form their job in terms of making changes to processes and scheduling decisions. Van Yperen et al. (2016) described EROW as the extent to which a job offers substantial free­dom, independence, and discretion to people to undertake their work activities and determine the procedures they ap­ply in the implementation of their assigned tasks. Indeed, it has been noted that EROW is critical for establishing a successful sense of responsibility in employees (Daileyl and Kirk, 1992). However, it is also essential to point out that EROW cannot exist in isolation as a single indicator; rather, it is also inclusive of latent constructs, such as resources. As affirmed by Johari et al. (2018), despite the majority of employees having the will to work within the broad con­straints of an entity, they also require appropriate resources so that they can work with a certain amount of freedom. Furthermore, as evidenced by Gordon et al. (2018), job and personal resources are interlinked, with personal re­sources acting as an independent predictor of EROW. However, organizational resources are applied in the pro­cess of developing personal resources. This is more spe­cifically identified in Batchelor et al. (2014) to include the critical psychological states detailing on EMW, gaining a professional responsibility for OUT. Therefore, the follow­ing hypothesis were constructed: H5: Core job characteristics positively affect experi­enced responsibility for outcomes of work. H6: Experienced responsibility for outcomes of work positively affects personal work outcomes. Lastly, in testing the mediating roles of EMW and EROW on OUT, Aguinis and Glavas (2019) convincingly demonstrated that these two factors have moderating ef­fects on OUT and CJC. In fact, when there is no direct link between CJC and OUT, this is an indication that there is no EMW or EROW. Based on the above, the following hypotheses was developed: H7: Internal experienced responsibility for outcomes of work mediates between core job characteristics and personal work outcomes. Based on the above discussion of the findings in the literature, a conceptual model was developed to attempt to reveal the relationship between CJC and OUT and wheth­er EMW and EROW act as mediating variables between CJC and OUT. Figure 1 illustrates the conceptual model that guided this study and how the study hypotheses were related to the model. 3 Methodology This research aims to investigate the direct relation­ship between CJC and OUT and the indirect relationship through EMW and EROW in the context of Northern Cyprus. Regarding this aim, the positivism research tech­nique was chosen as it is the best approach for causal\ impact relationships of a set of variables (Malhotra et al., 2017). Thus, deductive and quantitative mechanisms were chosen to collect research data; this indicates that the ques­tionnaire represents the main tool for gathering the need­ed data due to its ability to make it easier for measuring variables relationships and to test the research hypothesis (Malhotra et al., 2017). A simple random sampling tech­nique was used to determine the needed sample size. The population was 5930 potential respondents. According to Sekaran (2003, 2006), and relying on 95% confidence lev­el and 5% margin error, 365 is the minimum sample size needed for this population size. For this research, SMART PLS software has been se­lected due to its ability to deal with structural equation modelling (SEM) analysis (Hair et al., 2013). Lee et al. (2011) asserted that structural equation modelling (SEM) represents one of the best techniques to analyse business studies especially studies that contain a wide range of di­rect and indirect variables. 3.1 Questionnaire design A survey questionnaire was employed to test the com­prehensive model developed for this study. As this study relied on the job characteristics model by Hackman and Oldhman and for more measurement accuracy, all ques­tionnaire items were adapted from Hackman and Oldham (1974) study and modified to be applicable for research scope and population nature. This process in fact can prove the reliability and validity of the research instrument (Se­karan, 2006). Before administering the questionnaire, sev­eral steps were undertaken to check its validity and consist­ency. First, a group of five academics experts reviewed the survey and proposed sides modifications. After that, a pilot test was conducted in which 30 completed surveys were analysed using SPSS v23 software to test the reliability of the instrument. In the pilot testing phase, the reliability test and the if-item-deleted test were used. The reliability test clarifies how closely questionnaire paragraphs are related to each other as a group. The if-item-deleted test allows the researcher to exclude any questions which harm instru­ment reliability. In addition, a Cronbach’s alpha test was performed for each group of variables and the instrument as a whole, and it was found that all of the Cronbach’s al­pha values were higher than the lowest level of acceptance of 0.70 (Collis and Hussey, 2013; Sleimi, 2020). Thus, the internal consistency was acceptable for the instrument and for each group of questions related to one variable. The final version of the survey contained 29 sentences (items) for assessing the research variables. Survey organ­ization has four main variables namely: core job charac­teristics (CJC) 12-items, experienced meaningfulness of work (EMW) 4-items, and experienced responsibility for outcomes of work (EROW) 5-items, and personal work outcomes (OUT) 8 items. Respondents were requested to evaluate their opinion for each item using a 5-point Likert scale 1-strongly disagree and 5-strongly agree. The survey was written in the English language. It was not converted into Turkish language “Country Language” because it was judged that the potential respondents would mostly likely be fluent in the English language and would have sufficient experience in the tourism sector. 3.2 Data collection Data was collected in Northern Cyprus in 2020. The survey was targeted at some of the Northern Cyprus tour­ism stakeholders as the study community because they are the main players in shaping the marketing efforts for Northern Cyprus as a tourist destination. Accordingly, the study population consisted of managers of 3- to 5-star ho­tels in Northern Cyprus, sales and marketing directors of 3- and 5-star hotels in Northern Cyprus, and first-line em­ployees of 3- to 5-star hotels in Northern Cyprus. This type of population was chosen because it consists of the most qualified people who can provide accurate information re­garding the destination of Northern Cyprus. A total of 700 sets of questionnaires were sent via email to hotel managers from the beginning of September 2020 until the end of December 2020. A total of 580 ques­tionnaires were returned. Among the 580 retrieved ques­tionnaires, only 420 were complete and were thus usable; this represents a response rate of 60%. The result showed that there was no substantial variance at p < 0.05, which indicated that non-response bias was not present. 4 Data Analysis and Results 4.1 Demographic data Realizing the basic demographic statistics of the pop­ulation is essential for carried by similar studies (Bouzari, 2012). Research data and regarding nationality composi­tion showed that most of them come from the Republic of Turkey, then Africa and Asia (37.5%; 25.9%; 22.3) re­spectively. The findings indicating that a majority of the sampled expatriates are male 61.7% and 38.3 are female. About 41.6% of participants are less than 30 years old, 33% are between 31 and 39 years old, 18.3% are between 40 and 39 years and the residuals are 50 years old or more. Moreover, about 64.8% of the participants have bachelor’s degrees; 24.6% have higher education degrees, while the rest have secondary certificates only. In terms of length of stay, 54.7% remain for 1-2 years in Northern Cyprus, 31% stay for less than one year while the rest stay for more than three years. 4.2 Hypothesized model For this research work, SmartPLS3.2.7 software was employed to test H1 to H7. The structural equation model­ling (SEM) technique was chosen due to its ability to deal with large numbers of variables and relationships (Hair et al., 2014). Table 1 shows the results of the measurement model in terms of convergent validity (as shown by average vari­ance extracted (AVE)), composite reliability (CR) and item (factor) loadings. In this research, the measurement model included 29 reflective indicators. The initial test showed that three out of the 29 model indicators, namely, TS4, TI4 and TV4, recorded loading values that were less than the minimum acceptable level. Therefore, these indicators were eliminated to enhance model validity and the reliabil­ity results (see Figure 2). The CR value indicates the lev­el of internal consistency of the reflective constructs. The cut-off point for CR is 0.7. Hence, Table 1 shows that all of the constructs of the model recorded an appropriate level of internal consistency. As for convergent validity, which is indicated by the AVE value, this value ranges from 0 to 1. Statistically, it should be more than 0.5 to prove that every construct is correlated with its indicators more than the other constructs )Ramayah et al., 2016). Table 1 shows that all of the AVE values were more than 0.5. Therefore, every construct in the model was able to explain more than 0.5 of the variance of the related indicators. Hence, con­vergent validity was confirmed. Discriminant validity is another important test that was conducted because it is used to test whether the indica­tors of a construct are correlated together more than with other indicators that belong to another construct (Henseler and Sarstedt, 2013). The Fornell and Larcker test was used to check for discriminant validity. This test is based on cross-loading values. The results of this test showed that the AVE value for the correlation of every construct with itself was higher than the values of the correlation with the other constructs (see Table 2). Thus, discriminant validity was approved. In addition, the heterotrait-monotrait ratio (HTMT) test was utilised to discriminant validity. According (Henseler et al., 2015; Sleimi et al., 2020), every construct the HTMT table must have a value of less than 0.85. The results of the test showed that this was the case. Further­more, the Stone–Geisser Q˛ coefficient, the coefficient of determination (R2) and the relative effect size (f 2) for each construct were determined, and all the results were found to be satisfactory. The final step in evaluating the structural model is to examine the research hypotheses by assessing the path co­efficients. The results of testing of the hypothesised direct effects are displayed in Figure 2. It was observed that the proposed model predicted 74.7% of the variance for OUT, 56.2% of the variance for EROW, and 56% the variance for EMW, through the analysis of Smart-PLS 30. This indicated that all of the standardised path coefficients were significant. The results supported all the direct relationship hypotheses (H1, H2, H3, H4 and H5). Table 5 summarises the results of hypoth­esis testing for the direct effect of CJC on the dependent variables. The results in Table 3 show that the relationships between CJC and EMW, EROW and OUT are positive, supporting H1, H1 and H3, respectively. The results also show that the relationships between EMW and OUT and EROW and OUT are also positive, supporting H4 and H5, respectively. Regarding the mediation test, the results in Table 4 show that EMW mediates the nexus between CJC and OUT, thus supporting H6. Similarly, EROW mediates the nexus between CJC and OUT; hence H7 is also supported. 5 Discussion This research examined the nexus between CJC and OUT by investigating whether EMW and EROW play mediating roles in the CJC–OUT relationship. Based on the analysis, the results showed that there was a positive relationship between CJC and EMW (supporting H1). This finding supports Kim et al. (2020), which identified that CJC has a positive impact on motivation, job satisfaction, work quality, and lowers absenteeism and staff turnover. In a positive manner, Iqbal et al. (2018) identified that CJC directly influences employees’ thinking and having specif­ic aspects on their job roles eventually contributing to per­sonal work outcomes such as job satisfaction and personal performance. The results also indicated that there was a significant relationship between CJC and EROW (support­ing H2). This is in line with Gordon et al. (2018), who not­ed that job and personal resources are interlinked with per­sonal resources being an independent predictor of EROW. It is these resources that are developed by integrating CJC in organizational operations. In addition, a positive relationship was found between CJC and OUT (supporting H3). This finding supports Alkhateri et al. (2018), who found that CJC significantly impacts employee performance. Also, Garg and Rastogi (2006) noted that OUT is promoted through prioritising specific job functions because improving an event-specific job role generates improved autonomy and challenges for employees. A positive relationship was also found to exist between EMW and OUT (supporting H4). Indeed, in the context of the Northern Cyprus hotel sector, this study asserted that EMW is a variable that can be identified as signifi­cantly affecting OUT, especially when direct and indirect effects are integrated (Abuhjeeleh et al., 2019). As noted by Martela and Pessi (2018), the significance of this re­lationship is particularly apparent where there is a lack of EMW, which occurs as a result of employees having a lack of control over their work and an inability to identify the value of their own work. Research results also supported Allan et al. (2018), who showed that EMW contributes to OUT through assisting others to contribute directly to the broader good of all stakeholders. This is done by creating a sense of meaning for an individual work function. In addition, the current study also found a positive re­lationship between EROW and OUT (supporting H5). This finding is as expected because, as noted by Van Yperen et al. (2016), EROW influences the scope of existing free­dom, independence and discretion of people in scheduling their job functions and in establishing relevant procedures to follow in implementing the allocated roles. Finally, as regards the mediating roles of EMW and EROW in the CJC–OUT relationship, the results showed that both of these variables acted as mediators thus sup­porting H6 and H7, respectively. This finding is in line with Wegman et al. (2018), who noted that the psycho­logical states of CJC lead to EROW and EMW that can increase internal work motivation, work quality and per­formance, and work satisfaction, and reduce absenteeism and staff turnover levels. 6 Concluding Remarks 6.1 Theoretical and practical implications The current study has many implications for theo­ry and practice. From the theoretical perspective, a wide range of studies have tested the direct relationship between CJC and OUT, but there is a comparative lack of research on the indirect relationship between these two variables. Therefore, the current study makes an important contribu­tion to the literature by offering evidence to show that two mediating variables (ERW and EROW) have a productive impact on this relationship. Thus, this finding makes it more convenient for researchers to introduce other medi­ators to examine similar relationships and to build models to test those relationships in the future. A second theoret­ical contribution in this study is that the model proposed was proved statistically. So, it would be a helpful tool for researchers who may investigate and predict such relation­ships within different sectors to gain knowledge on some vital theoretical and practical implications that could en­hance organizational outcomes. In short, such work could provide more evidence about the positive impact of CJC, EROW, and EMW on OUT. Furthermore, this research ex­amined the mediating role of EROW and EMW between CJC and OUT. The result showed that CJC has a reason­able positive direct and indirect impact on OUT, as indi­cated by remarkable positive relationships within the re­search model. Therefore, these findings underline the need for more exploration of these issues in this under-exploited research area. From a practical perspective, this study’s findings are relevant to human resource managers, line managers, and administrators in organizations in the Northern Cy­prus hotel sector. The varying mediation of EROW and EMW in the attainment of CJC implies a need to adopt distinct human resource management systems to capitalise on the different knowledge and capabilities possessed by employees, which could lead to the attainment of differ­ent outcomes of work. By adopting this approach, human resource managers and other administrators of the North­ern Cyprus hotel sector would be able to identify the stra­tegic contributions of each of their various departments; this would then guide them in the implementation of CJC for the appropriate personal work outcomes. Also, as the direct and indirect impact of CJC was found to have a substantial influence on OUT, the market environment in which the Northern Cyprus hotel sector operates should be given priority. Hence, it is recommended that the Northern Cyprus hotel sector organizations review their policies re­garding the role of CJC in OUT. Part of this would include the job design strategies that appreciate and increase a job role’s motivational potential. This is done by prioritizing job rotation, job enlargement, enrichment, and simplifica­tion. Through this, the employees would be more motivat­ed to adopt a set of skills in their job positions instead of doing a single thing repeatedly. The findings of this study behove the top management of these organizations to de­velop new job designs that consider EROW and EMW. These two variables can play a vital role in gaining superi­or employee and business performance benefits. However, as it is not easy to make and implement such design in a developing economy, building a national strategy within Northern Cyprus could encourage the hotel sector to alter their tourism curriculum to smooth this process. For the line managers, the outcome of this report is applicable in ensuring that they can successfully evaluate the job and provide better engagement to preferable link the different departments by integrating their core job characteristics with an organization’s objectives. In particular, this is done by working collaboratively with employees to create an appropriate phenomenon and situation for all stakehold­ers and eventually increase engagement and productivity. Hence, the line managers would approach their job func­tions by facilitating and recognizing today’s working and equally developing future-based jobs. 6.2 Research limitations When considering the above findings, it is also im­portant to evaluate the limitations of this study. The first limitation involved the utilization of direct and indirect effect measurements based on specific calculations for the variables. Secondly, a questionnaire survey was used to ac­quire data to evaluate the impacts of the different variables on each other. The questionnaire was used as a subjective measurement. Different scholars make an assumption that the different measures are appropriate in regard to social science studies. Hence, as a best practice in the future, re­searchers should focus on using different measurements to assess the relationships among the different variables. Nevertheless, the best practice would have been to adopt this questionnaire form in conjunction with objec­tive measurements. This would have then led to more ro­bust outcomes in line with the convergent and discriminate validity (Rojas and Widiger, 2014). Finally, based on the literature reviewed for this study, it is evident that a limit­ed number of sources have examined the effect of CJC on EMW and that they have done so in from the perspective of the senior administration of organizations. Hence, as a future best practice, researchers could opt to explore dif­ferent concepts of CJC. Moreover, this study was cross-sectional. By focusing on the Northern Cyprus Hotel Sector, this research in­volved sourcing data from the population at one specific point on time. In this cross-sectional study, multiple var­iables at a particular point of time. Hence, this limitation is that the analysis was not causal or relational but only used to evaluate the relationship of CJC and OUT. Still, there is a comparative lack of research on the indirect re­lationship between these two variables. Hence, it is not possible to understand what would happen in the future in the Northern Cyprus hotel sector in the areas of ELW, CJC, and OUT. 6.3 Originality/value The research model developed for this study provides some valuable insights for job design because it shows that the utilisation of suitable mediators can help in the attainment of successful outcomes of work in the North­ern Cyprus hotel sector. Thus, the results of the study are valuable not only for researchers, but also human resource managers and executives in tourism who wish to develop job design practices to stay ahead of the competition in a hyper-competitive business environment. This research data was gathered from 3- to 5-stars hotels operating in Northern Cyprus. There is a possibility that data collected from such sectors or countries may yield different findings. Therefore, there is a need to prove these research results in other developing/developed countries’ contexts to be sure that the effects of sector or country do not confound with existing findings. Acknowledgment This paper was financially supported by the Palestine Technical University – Kadoorie and the authors would like to express their gratitude for this funding. References 1Received: 15th September 2021; revised: 13th April 2022; accepted: 23th July 2022 Figure 1: Conceptual research model Table 1: Results of the measurement model. Reflective Constructs Construct Items Code Item Loading CR AVE Core job characteristics The results of my efforts are clearly visible and identifiable. TI1 0.787 0.916 0.553 I make significant contributions to the final product or service. TI2 0.756 The job provides me with the chance to completely finish the pieces of work I began. TI3 0.812 The work is likely to significantly affect the lives and the well-being of other people. TS1 0.838 This job is one where a lot of other people can be affected by how well the work gets done. TS2 0.777 The job itself is very significant or important in the broader scheme of things. TS3 0.758 The job requires me to do many different things at work, using a variety of skills and talents. TV1 0.753 The job requires me to use a number of complex or high-level skills. TV2 0.707 The job is not too simple or repetitive. TV3 0.752 Experienced meaningful­ness of work The work I do in this job is very meaningful to me. EMW1 0.835 0.889 0.668 Most people in this job feel that the work is beneficial or vital. EMW2 0.880 Most people in this job feel there is a great deal of personal meaning in the work they do. EMW3 0.810 Most people in this job find the work very meaningful. EMW4 0.736 Experienced responsibility for outcomes of work It is vital in this job for me to care very much about whether or not the work gets done right. EROW1 0.836 0.911 0.673 I feel a very high degree of personal responsibility for the work I do in this job. EROW2 0.824 Most people doing this job feel that whether or not the job gets done right is clearly their own responsibility. EROW3 0.777 Most people doing this job feel a great deal of personal responsibility for the work they do. EROW4 0.814 Whether or not this job gets done right is clearly my responsibility. EROW5 0.848 Personal work outcomes I feel a great sense of personal satisfaction when I do this job well. HIWM1 0.832 0.918 0.588 I feel good and happy when I discover that I have performed poorly on this job. HIWM2 0.827 My own feelings generally are affected very much one way or the other by how well I do in this job. HIWM3 0.820 My opinion of myself goes up when I do this job well. HIWM4 0.766 The overall quality of the supervision I receive in my work. HQWP1 0.731 I feel I should personally take the credit or blame for the results of my work in doing this job. HQWP2 0.771 I often have trouble figuring out whether I’m doing well or poorly in this job. HQWP3 0.785 Most people doing this job feel good or happy when they find that they have per­formed the work well. HQWP4 0.758 Note: CJC: Core job characteristics; OUT: Personal work outcomes; EROW: Experienced responsibility for outcomes of work; EMW: Ex­perience meanengfullness of work; TI: Task identity; TS: Task significance; TV: Task variety; HIW: High internal work motivation; HQW: High-quality work performance. Table 2: Fornell–Larcker criterion Constructs Core job characteristics Experienced meaningfulness of work Experienced responsibility for outcomes of work Personal work outcomes Core job char­acteristics 0.779       Experienced meaningful­ness of work 0.748 0.856     Experienced responsibility for outcomes of work 0.743 0.824 0.890   Personal work outcomes 0.734 0.793 0.814 0.767 Figure 2: Measurement model Table 3: Results of hypothesis testing of direct relationships Path (ß) Std. error T-value P-value Result Core job characteristics . Experienced meaningful­ness of work 0.743 0.027 27.960 0.000 Supported Core job characteristics . Experienced responsibility for outcomes of work 0.743 0.029 25.511 0.000 Supported Core job characteristics . Personal work outcomes 0.325 0.051 6.394 0.000 Supported Experienced meaningful­ness of work. Personal work outcomes 0.241 0.058 4.128 0.000 Supported Experienced responsibility for outcomes of work . 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Malek Bakheet Elayan: Assistant Professor and the Specialist of Human Resources Development at Business Administration Department, The Institute of Public Administration (IPA), The Kingdom of Saudi Arabia, Riyadh. His work focuses on Human Resources Development and Management courses. He has participated as Session Chair & Presenter in “7th International Conference on Economics, Finance & Management Outlooks, Asian Research Development Wing, Research interests: HRM-Development Practices, E-HRM and Contemporary Business topics. Lamar Abu Hajleh: Graduated from Near East University- Northern Cyprus. Her work focuses on the management field in general especially; risk management, financial management, and monetary institutions research. Kljucne znacilnosti delovnega mesta in osebni delovni rezultati: posredniška vloga kriticnih psiholoških stanj: empiricni dokazi iz hotelskega sektorja Severnega Cipra Ozadje in namen: Namen te študije je raziskati razmerje med kljucnimi znacilnostmi delovnega mesta (CJC) in osebnimi delovnimi rezultati (OUT), pa tudi vlogo izkustvenene smiselnosti dela (EMW) in izkustvene odgovornosti za rezultate dela ( EROW) pri posredovanju odnosa CJC–OUT. Natancneje, ta študija proucuje ucinkovitost CJC pri izboljšanju EMW in EROW ter osvetli vlogi EMW in EROW pri povecanju OUT zaposlenih v hotelskem sektorju Severnega Cipra. Metodologija: Študija uporablja kvantitativni pristop za zbiranje in analizo podatkov 420 zaposlenih v hotelskem sektorju Severnega Cipra. Tehnika delnih najmanjših kvadratov (PLS) z uporabo Smart-PLS je bila uporabljena za testiranje neposrednih odnosov znotraj raziskovalnega modela in analizo posrednih ucinkov. Rezultati: Analiza je razkrila mocno podporo smiselnosti dela in izkustveno odgovornost za rezultate dela, ki deluje­jo kot delni posredniki v razmerju med temeljnimi znacilnostmi dela in osebnimi delovnimi rezultati. Poleg tega je bilo ugotovljeno, da imajo kljucne znacilnosti dela razumno neposreden ucinek na osebne delovne rezultate, izkustveno smiselnost dela in izkustveno odgovornost za rezultate dela. Zakljucek: Študija kaže na pomen vkljucitve izkustvene smiselnosti dela in izkustvene odgovornosti za rezultate dela kot posredniških spremenljivk za boljše razumevanje razmerja med kljucnimi znacilnostmi dela in osebnimi de­lovnimi izidi. Vkljucenih je vec teoreticnih in prakticnih implikacij, ki temeljijo na rezultatih te študije. Ugotavljamo, da bi najvišjemu vodstvu v hotelskem sektorju koristilo preoblikovanje delovnega mesta, ker imajo kljucne znacilnosti delovnega mesta pozitiven ucinek na delovne rezultate. 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Na zacetku prispevka, takoj za naslovom, naj bo povzetek (izvlecek) dolžine naj­vec 250 besed, kljucne besede, v koncni – sprejeti verziji clanka pa na koncu prispevka tudi kratek strokovni življenjepis vsakega od avtorjev (do 10 vrstic) in letnica rojstva (zaradi vnosa podatkov v knjižnicni informacijski sistem COBISS, v reviji letnica ne bo objavljena). Na prvi strani besedila naj bodo napisani le naslov prispevka, imena in (poštni in elektronski) naslovi avtorjev clanka, po možnosti tudi telefonska številka enega od avtorjev. Da bi za­gotovili anonimnost recenziranja, naj se imena av­torjev ne pojavljajo v besedilu prispevka. Na koncu clanka, za življenjepisi, naj bo slovenski prevod naslova, povzetka in kljucnih besed. Clanek naj bo razclenjen v oštevilcena poglavja. Naslovi clanka, poglavij in podpoglavij naj bodo napisani z malimi crkami, da so razvidne kratice. Slike in tabele v elektronski obliki vkljucite kar v besedilo. Besedilu so lahko priložene slike in/ali ta­bele na papirju v obliki pripravljeni za preslikavo. V tem primeru naj bo vsaka slika na posebnem listu, oštevilcene naj bodo z arabskimi številkami, v bese­dilu naj bo oznaceno, kam približno je treba uvrstiti sliko: na tem mestu naj bo številka slike/tabele in njen podnapis. Slike bomo praviloma pomanjšali in jih vstavili v clanek. Upoštevajte, da morajo biti oznake in besedila na vseh slikah dovolj velika, da bodo citljiva tudi pri velikosti slike, kot bo obja­vljena v reviji. Vse slike naj bodo crno-bele z be­lim ozadjem; barvnih slik v tiskani verziji revije ne moremo objaviti, barve so vidne le v spletni verziji. Clanki morajo biti pred objavo v Organizaciji lekto­rirani. Koncno verzijo mora lektorirati naravni go­vorec oz. lektor s primerljivim znanjem anglešcine. Podrobna navodila avtorjem za pisanje in oblikova­nje clankov so na https://sciendo.com/journal/orga - for Authors. Predložene prispevke pregledata in ocenita najmanj dva recenzenta. Na osnovi mnenj in predlogov re­cenzentov uredniški odbor ali urednik sprejmejo prispevek, zahtevajo manjše ali vecje popravke in dopolnitve ali ga zavrnejo. Ce urednik oziroma re­cenzenti predlagajo vecje popravke, se dopolnjeni prispevek praviloma pošlje v ponovno recenzijo. Clanke za objavo lahko predložite preko spletnega mesta http://organizacija.fov.uni-mb.si. Za nadalj­nje informacije in pojasnila se lahko obrnete na ure­dništvo Organizacije (organizacija@um.si ali joze.zupancic@um.si). Naslov uredništva: Univerza v Mariboru, Fakulteta za organizacijske vede Kidriceva cesta 55a 4000 Kranj Faks: 04-2374-299 Tel.: 04-2374-245 Prva slovenska revija za organizacijska in kadrovska raziskovanja in prakso. Revijo sofinancira Javna agencija za raziskovalno dejavnost Republike Slovenije. Ponatis in razmnoževanje deloma ali v celoti brez pisnega dovoljenja nista dovoljena. Izdajatelj: Univerza v Mariboru, Fakulteta za organizacijske vede Kranj, Založba MODERNA ORGANIZACIJA, Kidriceva cesta 55a, KRANJ, telefon: 04 23 74 200, telefax: 04 23 74 299, E-pošta: organizaija@um.si. Uredništvo revije: Kidriceva cesta 55a, 4000 Kranj, narocniški oddelek: 04 23 74 295. Letna narocnina: za pravne osebe za prvi naroceni izvod 51,47 EUR, drugi naroceni izvod 41,38 EUR, vsak nadaljnji 36,33 EUR, za posameznike 25,23 EUR. Cena posamezne številke je 9,08 EUR. Na leto izidejo 4 številke. Tisk: Tiskarna Koštomaj d.o.o. Naklada 200 izvodov. Organizacija is covered by the following services: Cabell’s Directory, CEJSH (The Central European Journal of Social Sciences and Humanities), Celdes, Clarivate Analytics - Emerging Sources Citation Index (ESCI), CNPIEC, Die Elektronische Zeitschriftenbibliothek, DOAJ, EBSCO - TOC Premier, EBSCO Discovery Service, ECONIS, Ergonomics Abstracts, ERIH PLUS, Google Scholar, Inspec, International Abstracts in Operations Research, J-Gate, Microsoft Academic Search, Naviga (Softweco), Primo Central (ExLibris), ProQuest - Advanced Polymers Abstracts, ProQuest - Aluminium Industry Abstracts, ProQuest - Ceramic Abstracts/World Ceramics Abstracts, ProQuest - Composites Industry Abstracts, ProQuest - Computer and Information Systems Abstracts, ProQuest - Corrosion Abstracts, ProQuest - Electronics and Communications Abstracts, ProQuest - Engineered Materials Abstracts, ProQuest - Mechanical & Transportation Engineering Abstracts, ProQuest - METADEX (Metals Abstracts), ProQuest - Sociological Abstracts, ProQuest - Solid State and Superconductivity Abstracts, Research Papers in Economics (RePEc), SCOPUS, Summon (Serials Solutions/ProQuest), TDOne (TDNet), TEMA Technik und Management, WorldCat (OCLC) CONTENTS - 3/2022 181 199 214 228 Saeed NOSRATABADI, Roya Khayer ZAHED, Vadim Vitalievich PONKRATOV, Evgeniy Vyacheslavovich KOSTYRIN Artificial Intelligence Models and Employee Lifecycle Management: A Systematic Literature Review Hasan TUTAR, Teymur SARKHANOV Tracing Management Fashions in Selected Indices: A Descriptive Statistical Study Sohrab GHANIZADEH, Farzad Sattari ARDABILI, Mohammad KHEIRANDISH, Eshagh RASOULI, Mohammad HASSANZADEH Psychological Capital and Organizational Performance: The Mediating Role of Organizational Ambidexterity Mohammad SLEIMI, Malek Bakheet ELAYAN, Lamar ABU HAJLEH Core Job Characteristics and Personal Work Outcomes: The Mediating Role of Critical Psychological States: Empirical Evidence from Northern Cyprus Hotel Sector