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            <front>

                <journal-meta>
                                    <journal-id></journal-id>
            <journal-title-group>
                                                                                    <journal-title>Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi</journal-title>
            </journal-title-group>
                                        <issn pub-type="epub">1304-8899</issn>
                                                                                            <publisher>
                    <publisher-name>Cukurova University</publisher-name>
                </publisher>
                    </journal-meta>
                <article-meta>
                                        <article-id pub-id-type="doi">10.35379/cusosbil.1658222</article-id>
                                                                <article-categories>
                                            <subj-group  xml:lang="en">
                                                            <subject>Operations Research</subject>
                                                            <subject>Behaviour-Personality Assessment in Psychology</subject>
                                                    </subj-group>
                                            <subj-group  xml:lang="tr">
                                                            <subject>Yöneylem Araştırması</subject>
                                                            <subject>Psikolojide Davranış-Kişilik Değerlendirmesi</subject>
                                                    </subj-group>
                                    </article-categories>
                                                                                                                                                        <title-group>
                                                                                                                                                                                                <trans-title-group xml:lang="tr">
                                    <trans-title>ÇALIŞAN PERSPEKTİFİNDEN İŞLETMELERDE YAPAY ZEKÂ UYGULAMALARI: BİBLİYOMETRİK BİR ANALİZ</trans-title>
                                </trans-title-group>
                                                                                                                                                                                                <article-title>ARTIFICIAL INTELLIGENCE APPLICATIONS IN ORGANIZATIONS FROM AN EMPLOYEE PERSPECTIVE: A BIBLIOMETRIC ANALYSIS</article-title>
                                                                                                    </title-group>
            
                                                    <contrib-group content-type="authors">
                                                                        <contrib contrib-type="author">
                                                                    <contrib-id contrib-id-type="orcid">
                                        https://orcid.org/0000-0002-3872-2258</contrib-id>
                                                                <name>
                                    <surname>Durmuş</surname>
                                    <given-names>İbrahim</given-names>
                                </name>
                                                                    <aff>BAYBURT ÜNİVERSİTESİ</aff>
                                                            </contrib>
                                                                                </contrib-group>
                        
                                        <pub-date pub-type="pub" iso-8601-date="20260409">
                    <day>04</day>
                    <month>09</month>
                    <year>2026</year>
                </pub-date>
                                        <volume>35</volume>
                                                            
                        <history>
                                    <date date-type="received" iso-8601-date="20250314">
                        <day>03</day>
                        <month>14</month>
                        <year>2025</year>
                    </date>
                                                    <date date-type="accepted" iso-8601-date="20251121">
                        <day>11</day>
                        <month>21</month>
                        <year>2025</year>
                    </date>
                            </history>
                                        <permissions>
                    <copyright-statement>Copyright © 2013, Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi</copyright-statement>
                    <copyright-year>2013</copyright-year>
                    <copyright-holder>Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi</copyright-holder>
                </permissions>
            
                                                                                                                                                <trans-abstract xml:lang="tr">
                            <p>Organizasyonlarda çalışan faaliyetlerinde, yapay zekâ veya uygulamalarının etkinliği günden güne artmıştır. Bu durum çalışanlara birtakım kolaylıklar sağlamasının yanında birçok endişeyi de beraberinde getirmiştir. Araştırmada çalışanlar ve yapay zekâ işbirliği ve çatışmalarını belirlemeye yönelik bir ihtiyaç doğmuştur. Bu açıdan araştırmada işletmeler düzeyinde çalışanlar ve yapay zekâ etkileşimine yönelik çıkarımlarda bulunulması amaçlanmıştır. Yapay zeka uygulamaları ve çalışanlara ilişkin literatür bilgilerine yer verilmiştir. WoS kullanılarak bibliyometrik analiz yöntemi uygulanmıştır. Bu araştırma, 1996-2024 yılları arasında yayımlanmış toplam 497 çalışmayı içeren bir uygulamayı kapsamaktadır. Yapay zekâ uygulamalarında yazarların en fazla vurguladığı anahtar kelimeler, yapay zekâ, makine öğrenme, yönetim, yapay, bilgi, öğrenme, derin öğrenme, zekâ, büyük veri, veri madenciliği, çalışan, insan kaynakları, makine, teknoloji, iş, bilgi yönetimi, performans ve yapay sinir ağı olarak sıralanmıştır. Analizde yapay zekâ, makine öğrenme, yönetim, veri madenciliği, dijital dönüşüm, analiz, teknoloji, çalışan, insan kaynakları, işbirliği, verimlilik, insan kaynakları yönetimi, büyük veri, performans, dijital teknolojiler kavramları birlikte güçlü ilişkiler ortaya koymuştur. Sonuçlar işletmelerde yapay zekâ kullanımının çalışanlar açısından birçok kavram ile ilişkili olduğunu göstermiştir. Araştırma yapay zekâ uygulamalarının çalışanlarla olan etkileşiminde öne çıkan kavramlar üzerinden, insan kaynakları yönetimi, işbirliği, performans ve dijital dönüşüm gibi alanlarda stratejik kararlar alınmasına yönelik önemli çıkarımlar sunmaktadır.</p></trans-abstract>
                                                                                                                                    <abstract><p>In organizational settings, the effectiveness of artificial intelligence (AI) and AI-based applications in employees&#039; activities continues to increase steadily over time. While this situation provides some conveniences to employees, it has also brought several concerns. Accordingly, a need has emerged to identify areas of collaboration and conflict between employees and AI. From this perspective, the present study aims to generate insights into employee–AI interactions at the organizational level. Literature on AI applications and their impact on employees is included. Bibliometric analysis was conducted using Web of Science (WoS) database. This research covers an application that includes a total of 497 studies published between 1996 and 2024. The keywords most emphasized by the authors in AI applications include artificial intelligence, machine learning, management, artificial, knowledge, learning, deep learning, intelligence, big data, data mining, employee, human resources, machine, technology, business, knowledge management, performance, and artificial neural networks. In the analysis, strong relationships between the concepts of artificial intelligence, machine learning, management, data mining, digital transformation, analysis, technology, employee, human resources, collaboration, productivity, human resource management, big data, performance, and digital technologies were revealed. Results have shown that the use of artificial intelligence in businesses is related to many concepts from the employees&#039; perspective. The research offers important implications for strategic decision-making in areas such as human resources management, collaboration, performance, and digital transformation, based on the concepts that emerge in the interaction of artificial intelligence applications with employees.</p></abstract>
                                                            
            
                                                                                                                                                <kwd-group>
                                                    <kwd>Employees</kwd>
                                                    <kwd>  Organizations</kwd>
                                                    <kwd>  Artificial Intelligence</kwd>
                                            </kwd-group>
                            
                                                                                                        <kwd-group xml:lang="tr">
                                                    <kwd>Çalışanlar</kwd>
                                                    <kwd>  Organizasyonlar</kwd>
                                                    <kwd>  Yapay Zekâ.</kwd>
                                            </kwd-group>
                                                                                                                                    <funding-group specific-use="FundRef">
                    <award-group>
                                                    <funding-source>
                                <named-content content-type="funder_name">Destekleyen kurum yoktur</named-content>
                            </funding-source>
                                                                            <award-id>projeden türetilmemiştir</award-id>
                                            </award-group>
                </funding-group>
                                </article-meta>
    </front>
    <back>
                            <ref-list>
                                    <ref id="ref1">
                        <label>1</label>
                        <mixed-citation publication-type="journal">Abdullah, R., &amp; Fakieh, B. (2020). Health care employees’ perceptions of the use of artificial intelligence applications: Survey study. Journal of Medical Internet Research, 22(5), 1-8. http://dx.doi.org/10.2196/17620</mixed-citation>
                    </ref>
                                    <ref id="ref2">
                        <label>2</label>
                        <mixed-citation publication-type="journal">Akay, A. (2025). Environmental design in the age of AI: Bibliometric and thematic insights from a social sciences perspective. Çukurova Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 34, 452-473. https://doi.org/10.35379/cusosbil.1696548</mixed-citation>
                    </ref>
                                    <ref id="ref3">
                        <label>3</label>
                        <mixed-citation publication-type="journal">Al Husaeni, D.F., Widiaty, I., Mulyanti, B., Abdullah, A.G., Rıza, L.S., Suherman, A., &amp; Al Husaeni, D.N. (2025). Trends and impacts of artificial intelligence application in the development of computational thinking skills. Informatics in Education, 24(2), 261–298. http://dx.doi.org/10.15388/infedu.2025.14</mixed-citation>
                    </ref>
                                    <ref id="ref4">
                        <label>4</label>
                        <mixed-citation publication-type="journal">Aria, M., &amp; Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959-975. http://dx.doi.org/10.1016/j.joi.2017.08.007</mixed-citation>
                    </ref>
                                    <ref id="ref5">
                        <label>5</label>
                        <mixed-citation publication-type="journal">Arslan, A., Cooper, C., Khan, Z., Golgeci, I., &amp; Ali, I. (2022). Artificial intelligence and human workers interaction at team level: A conceptual assessment of the challenges and potential HRM strategies. International Journal of Manpower, 43(1), 75-88. http://dx.doi.org/10.1108/IJM-01-2021-0052</mixed-citation>
                    </ref>
                                    <ref id="ref6">
                        <label>6</label>
                        <mixed-citation publication-type="journal">Bankins, S., Ocampo, A.C., Marrone, M., Restubog, S.L.D., &amp; Woo, S.E. (2024).  A multilevel review of artificial intelligence in organizations: Implications for organizational behavior research and practice. Journal of Organizational Behavior, 45(2), 159-182. http://dx.doi.org/10.1002/job.2735</mixed-citation>
                    </ref>
                                    <ref id="ref7">
                        <label>7</label>
                        <mixed-citation publication-type="journal">Berigel, D.S., &amp; Şılbır, L. (2024). A bibliometric analysis of AI literacy: Trends, topics and future directions. Near East University Journal of Education Faculty (NEUJE), 7(1), 42-53.</mixed-citation>
                    </ref>
                                    <ref id="ref8">
                        <label>8</label>
                        <mixed-citation publication-type="journal">Bhargava, A., Bester, M., &amp; Bolton, L. (2021). Employees’ perceptions of the implementation of robotics, artificial intelligence, and automation (RAIA) on job satisfaction, job security, and employability. Journal of Technology in Behavioral Science, 6, 106–113. https://doi.org/10.1007/s41347-020-00153-8</mixed-citation>
                    </ref>
                                    <ref id="ref9">
                        <label>9</label>
                        <mixed-citation publication-type="journal">Brougham, D., &amp; Haar, J. (2018). Smart Technology, Artificial Intelligence, Robotics, and Algorithms (STARA): Employees’ perceptions of our future workplace. Journal of Management &amp; Organization, 24(2), 239–257. http://dx.doi.org/10.1017/jmo.2016.55</mixed-citation>
                    </ref>
                                    <ref id="ref10">
                        <label>10</label>
                        <mixed-citation publication-type="journal">Budhwar, P., Malik, A., Silva, M.T.T., &amp; Thevisuthan, P. (2022). Artificial intelligence – challenges and opportunities for international HRM: a review and research agenda. The International Journal of Human Resource Management, 33(6), 1065-1097. https://doi.org/10.1080/09585192.2022.2035161</mixed-citation>
                    </ref>
                                    <ref id="ref11">
                        <label>11</label>
                        <mixed-citation publication-type="journal">Chang, P-C., Zhang, W., Cai, Q., &amp; Guo, H. (2024). Does AI-driven technostress promote or hinder employees’ artificial intelligence adoption ıntention? A moderated mediation model of affective reactions and technical self-efficacy. Psychology Research and Behavior Management, 17, 413-427. https://doi.org/10.2147/PRBM.S441444</mixed-citation>
                    </ref>
                                    <ref id="ref12">
                        <label>12</label>
                        <mixed-citation publication-type="journal">Chiu, Y-T., Zhu, Y-Q., &amp; Corbett, J. (2021). In the hearts and minds of employees: A model of pre-adoptive appraisal toward artificial intelligence in organizations. International Journal of Information Management, 60, 1-16. https://doi.org/10.1016/j.ijinfomgt.2021.102379</mixed-citation>
                    </ref>
                                    <ref id="ref13">
                        <label>13</label>
                        <mixed-citation publication-type="journal">Cobo, M.J., López-Herrera, A.G., Herrera-Viedma, E., &amp; Herrera F. (2011). An approach for detecting, quantifying, and visualizing the evolution of a research field: A practical application to the Fuzzy Sets Theory field. Journal of Informetrics, 5, 146–166. http://dx.doi.org/10.1016/j.joi.2010.10.002</mixed-citation>
                    </ref>
                                    <ref id="ref14">
                        <label>14</label>
                        <mixed-citation publication-type="journal">Cobo, M.J., Martinez, M.A., Gutierrez-Salcedo, M., Fujita, H., &amp; Herrera-Viedma, E. (2015). 25 years at Knowledge-Based Systems: A bibliometric analysis. Knowledge-Based Systems, 80, 3–13. http://dx.doi.org/10.1016/j.knosys.2014.12.035</mixed-citation>
                    </ref>
                                    <ref id="ref15">
                        <label>15</label>
                        <mixed-citation publication-type="journal">Cramarenco, R.E., Burcă-Voicu, M.I., &amp; Dabija, D-C. (2023). The impact of artificial intelligence (AI) on employees’ skills and well-being in global labor markets: A systematic review. Oeconomia Copernicana, 14(3), 731–767. http://dx.doi.org/10.24136/oc.2023.022</mixed-citation>
                    </ref>
                                    <ref id="ref16">
                        <label>16</label>
                        <mixed-citation publication-type="journal">Dabbous, A., Barakat, K.A., &amp; Sayegh, M.M. (2022). Enabling organizational use of artificial intelligence: an employee perspective. Journal of Asia Business Studies, 16(2), 245-266. http://dx.doi.org/10.1108/JABS-09-2020-0372</mixed-citation>
                    </ref>
                                    <ref id="ref17">
                        <label>17</label>
                        <mixed-citation publication-type="journal">Esen, D. (2023). Artificial intelligence and employee behaviour: A bibliometric analysis. Uluslararası Akademik Birikim Dergisi, 6, 109-124. http://dx.doi.org/10.5281/zenodo.10003975</mixed-citation>
                    </ref>
                                    <ref id="ref18">
                        <label>18</label>
                        <mixed-citation publication-type="journal">Giering, O., Fedorets, A., Adriaans, J., &amp; Kirchner, S. (2021) Artificial intelligence in Germany: Employees often unaware they are working with AI-based systems, DIW Weekly Report, ISSN 2568-7697, Deutsches Institut für Wirtschaftsforschung (DIW), Berlin, 11(48), 369-375. https://doi.org/10.18723/diw_dwr:2021-48-1</mixed-citation>
                    </ref>
                                    <ref id="ref19">
                        <label>19</label>
                        <mixed-citation publication-type="journal">Guedes, T.A. (2023). Thematic analysis on ethical concepts of artificial intelligence in business: A systematic review and research agenda. International Journal of Business Marketing and Management (IJBMM), 8(6), 54-66.</mixed-citation>
                    </ref>
                                    <ref id="ref20">
                        <label>20</label>
                        <mixed-citation publication-type="journal">Howard, J. (2019). Artificial intelligence: Implications for the future of work. American Journal of Industrial Medicine, 62, 917-926. https://doi.org/10.1002/ajim.23037</mixed-citation>
                    </ref>
                                    <ref id="ref21">
                        <label>21</label>
                        <mixed-citation publication-type="journal">Huang, M-H., &amp; Rust, R.T. (2018). Artificial intelligence in service. Journal of Service Research, 21(2), 155-172.  https://doi.org/10.1177/1094670517752459</mixed-citation>
                    </ref>
                                    <ref id="ref22">
                        <label>22</label>
                        <mixed-citation publication-type="journal">Hughes, C., Robert, L., Frady, K., &amp; Arroyos, A., (2019), Artificial Intelligence, Employee Engagement, Fairness, and Job Outcomes, Managing Technology and Middle- and Low-skilled Employees (The Changing Context of Managing People), Emerald Publishing Limited, 61-68. https://doi.org/10.1108/978-1-78973-077-720191005</mixed-citation>
                    </ref>
                                    <ref id="ref23">
                        <label>23</label>
                        <mixed-citation publication-type="journal">Jaiswal, A., Arun, C.J., &amp; Varma, A. (2022). Rebooting employees: Upskilling for artificial intelligence in multinational corporations. The International Journal of Human Resource Management, 33(6), 1179-1208. https://doi.org/10.1080/09585192.2021.1891114</mixed-citation>
                    </ref>
                                    <ref id="ref24">
                        <label>24</label>
                        <mixed-citation publication-type="journal">Jerdea, I-L. (2025). Artificial intelligence for product innovation: A bibliometric analysis. Proceedings of the International Conference on Business Excellence, 19(1), 3538-3552. https://doi.org/10.2478/picbe-2025-0270</mixed-citation>
                    </ref>
                                    <ref id="ref25">
                        <label>25</label>
                        <mixed-citation publication-type="journal">Kądzielawski, G. (2023). The state of development of artificial intelligence in polish industry: opinions of employees. International Journal of Contemporary Management, 59(1), 12-25. https://doi.org/10.2478/ijcm-2022-0015</mixed-citation>
                    </ref>
                                    <ref id="ref26">
                        <label>26</label>
                        <mixed-citation publication-type="journal">Kazim, S.I.H., Afzal, M.F., Gondal, S., Ashraf, M.U., &amp; Umair, M. (2024). Evaluating the impact of artificial intelligence on employee engagement and performance in Pakistan. Journal of Excellence in Social Sciences, 3(1), 30-42.</mixed-citation>
                    </ref>
                                    <ref id="ref27">
                        <label>27</label>
                        <mixed-citation publication-type="journal">Khanfar, A.A., Mavi, R.K., Iranmanesh, M., &amp; Gengatharen, D. (2024). Determinants of artificial intelligence adoption: Research themes and future directions. Information Technology and Management, 1-22. https://doi.org/10.1007/s10799-024-00435-0</mixed-citation>
                    </ref>
                                    <ref id="ref28">
                        <label>28</label>
                        <mixed-citation publication-type="journal">Kılınç, E. (2023). Bibliometrics analysis of studies carried out in Scopus database in the field of artificial intelligence in businesses. Uluslararası Yönetim akademisi Dergisi, 6(4), 1185-1198. https://doi.org/10.33712/mana.1380858</mixed-citation>
                    </ref>
                                    <ref id="ref29">
                        <label>29</label>
                        <mixed-citation publication-type="journal">Kong, H., Yuan, Y., Baruch, Y., Bu, N., Jiang, X., &amp; Wang, K. (2021). Influences of artificial intelligence (AI) awareness on career competency and job burnout. International Journal of Contemporary Hospitality Management, 33(2), 717-734. https://doi.org/10.1108/IJCHM-07-2020-0789</mixed-citation>
                    </ref>
                                    <ref id="ref30">
                        <label>30</label>
                        <mixed-citation publication-type="journal">Kong, H., Jiang, X., Zhou, X., Baumi T., Li, J., &amp; Yu, J. (2024). Influence of artificial intelligence (AI) perception on career resilience and informal learning. Tourism Review, 79(1), 219-233. https://doi.org/10.1108/TR-10-2022-0521</mixed-citation>
                    </ref>
                                    <ref id="ref31">
                        <label>31</label>
                        <mixed-citation publication-type="journal">Łapi´nska, J., Escher, I., Górka, J., Sudolska, A., &amp; Brzustewicz, P. (2021). Employees’ trust in artificial intelligence in companies: The case of energy and chemical industries in Poland. Energies, 14, 1-20. https://doi.org/10.3390/en14071942
 
Li, W., Qin, X., Yam, K.C., Deng, H., Chen, C., Dong, X., Jiang, L., &amp; Tang, W. (2024a). Embracing artificial intelligence (AI) with job crafting: Exploring trickle-down effect and employees’ outcomes. Tourism Management, 104, 1-18. https://doi.org/10.1016/j.tourman.2024.104935</mixed-citation>
                    </ref>
                                    <ref id="ref32">
                        <label>32</label>
                        <mixed-citation publication-type="journal">Li, Y., Song, Y., Sun, Y., &amp; Zeng, M. (2024b). When do employees learn from artificial intelligence? The moderating effects of perceived enjoyment and task-related complexity. Technology in Society, 77, 1-15. https://doi.org/10.1016/j.techsoc.2024.102518</mixed-citation>
                    </ref>
                                    <ref id="ref33">
                        <label>33</label>
                        <mixed-citation publication-type="journal">Lichtenthaler, U. (2020). Extremes of acceptance: employee attitudes toward artificial intelligence. Journal of Business Strategy, 41(5), 39-45. https://doi.org/10.1108/JBS-12-2018-0204</mixed-citation>
                    </ref>
                                    <ref id="ref34">
                        <label>34</label>
                        <mixed-citation publication-type="journal">Moral-Muñoz, Jose A., Herrera-Viedma, E., Santisteban-Espejo, A., &amp; Cobo, M.J. (2020). Software tools for conducting bibliometric analysis in science: An up-to-date review. El Profesional de la Información, 29(1), 1-20. https://doi.org/10.3145/epi.2020.ene.03</mixed-citation>
                    </ref>
                                    <ref id="ref35">
                        <label>35</label>
                        <mixed-citation publication-type="journal">Nawaz, N., Arunachalam, H., Pathi, B.K., &amp; Gajenderan, V. (2024). The adoption of artificial intelligence in human resources management practices. International Journal of Information Management Data Insights, 4, 1-11. https://doi.org/10.1016/j.jjimei.2023.100208</mixed-citation>
                    </ref>
                                    <ref id="ref36">
                        <label>36</label>
                        <mixed-citation publication-type="journal">Öztırak, M. (2023). A study on the impact of artificial intelligence anxiety on the innovation-oriented behaviours of employees. Optimum Journal of Economics and Management Sciences, 10(2), 267-286. https://doi.org/10.17541/optimum.1255576</mixed-citation>
                    </ref>
                                    <ref id="ref37">
                        <label>37</label>
                        <mixed-citation publication-type="journal">Pektaş, T. (2024). The impact of artificial intelligence anxiety on employees: A comprehensive review of psychological and organizational dynamics. International Journal of Education Technology and Scientific Researches, 9(26), 194-206. http://dx.doi.org/10.35826/ijetsar.733</mixed-citation>
                    </ref>
                                    <ref id="ref38">
                        <label>38</label>
                        <mixed-citation publication-type="journal">Pereira, V., Hadjielias, E., Christofi, M., &amp; Vrontis, D. (2023). A systematic literature review on the impact of artificial intelligence on workplace outcomes: A multi-process perspective. Human Resource Management Review, 33, 1-22. https://doi.org/10.1016/j.hrmr.2021.100857</mixed-citation>
                    </ref>
                                    <ref id="ref39">
                        <label>39</label>
                        <mixed-citation publication-type="journal">Pillai, R., Ghanghorkar, Y., Sivathabu, B., Algharabat, R., &amp; Rana, N.P. (2024). Adoption of artificial intelligence (AI) based employee experience (EEX) chatbots. Information Technology &amp; People, 37(1), 449-478. https://doi.org/10.1108/ITP-04-2022-0287</mixed-citation>
                    </ref>
                                    <ref id="ref40">
                        <label>40</label>
                        <mixed-citation publication-type="journal">Prentice, C., Lopes, S.D., &amp; Wang, X. (2020a). Emotional intelligence or artificial intelligence– an employee perspective. Journal of Hospitality Marketing &amp; Management, 29(4), 377-403. https://doi.org/10.1080/19368623.2019.1647124</mixed-citation>
                    </ref>
                                    <ref id="ref41">
                        <label>41</label>
                        <mixed-citation publication-type="journal">Prentice, C., Lopes, S.D., &amp; Wang, X. (2020b). The impact of artificial intelligence and employee service quality on customer satisfaction and loyalty. Journal of Hospitality Marketing &amp; Management, 29(7), 739-756. https://doi.org/10.1080/19368623.2020.1722304</mixed-citation>
                    </ref>
                                    <ref id="ref42">
                        <label>42</label>
                        <mixed-citation publication-type="journal">Presbitero, A., &amp; Teng-Calleja, M. (2023). Job attitudes and career behaviors relating to employees’ perceived incorporation of artificial intelligence in the workplace: A career self-management perspective. Personnel Review, 52(4), 1169-1187. https://doi.org/10.1108/PR-02-2021-0103</mixed-citation>
                    </ref>
                                    <ref id="ref43">
                        <label>43</label>
                        <mixed-citation publication-type="journal">Ramachandran, K.K., Mary, A.A.S., Hawladar, S., Asokk, D., Bhaskar, B., &amp; Pitroda, J.R. (2022). Machine learning and role of artificial intelligence in optimizing work performance and employee behavior. Materials Today: Proceedings, 51, 2327-2331. https://doi.org/10.1016/j.matpr.2021.11.544</mixed-citation>
                    </ref>
                                    <ref id="ref44">
                        <label>44</label>
                        <mixed-citation publication-type="journal">Rao, S., Chitranshi, J., &amp; Punjabi, N. (2020). Role of artificial intelligence in employee engagement and retention. Journal of Applied Management-Jidnyasa, 12(2), 42-60.</mixed-citation>
                    </ref>
                                    <ref id="ref45">
                        <label>45</label>
                        <mixed-citation publication-type="journal">Rožman, M., Oreški, D., &amp; Tominc, P. (2023). Artificial-intelligence-supported reduction of employees’ workload to increase the company’s performance in today’s VUCA environment. Sustainability, 15, 1-21. https://doi.org/10.3390/su15065019</mixed-citation>
                    </ref>
                                    <ref id="ref46">
                        <label>46</label>
                        <mixed-citation publication-type="journal">Sağbaş, M., &amp; Kılınç, S. (2024). Artificial intelligence in business management: A bibliometric analysis. Sinop Üniversitesi Sosyal Bilimler Dergisi, 8, 504-531. https://doi.org/10.30561/sinopusd.1561011</mixed-citation>
                    </ref>
                                    <ref id="ref47">
                        <label>47</label>
                        <mixed-citation publication-type="journal">Sekaki, Y., Ziane, H., &amp; Khazzar, A. (2025). Artificial intelligence in management studies (2021–2025): A bibliometric mapping of themes, trends, and global contributions. International Journal of Accounting, Finance, Auditing, Management and Economics, 6(9), 62–80.</mixed-citation>
                    </ref>
                                    <ref id="ref48">
                        <label>48</label>
                        <mixed-citation publication-type="journal">Sharma, S., &amp; Saxena, P. (2024). Role of emotional and artificial intelligence in employee performance: A perspective from the Indian Service Industry. Abhigyan, 42(1) 43–56. https://doi.org/10.1177/09702385241233078</mixed-citation>
                    </ref>
                                    <ref id="ref49">
                        <label>49</label>
                        <mixed-citation publication-type="journal">Shi, Y., Blainey, S., Sun, C., &amp; Jing, P. (2020). A literature review on accessibility using bibliometric analysis techniques. Journal of Transport Geography, 87, 1-12. https://doi.org/10.1016/j.jtrangeo.2020.102810</mixed-citation>
                    </ref>
                                    <ref id="ref50">
                        <label>50</label>
                        <mixed-citation publication-type="journal">Strich, F., Mayer, A-S., &amp; Fiedler, M. (2021). What do I do in a world of artificial intelligence? Investigating the impact of substitutive decision-making AI systems on employees’ professional role identity. Journal of the Association for Information Systems, 22(2), 304-324. https://doi.org/10.17705/1jais.00663</mixed-citation>
                    </ref>
                                    <ref id="ref51">
                        <label>51</label>
                        <mixed-citation publication-type="journal">Sunman, G. (2025). Artificial intelligence in management: Bibliometric analysis. Politik Ekonomik Kuram, 9(2), 723-739. https://doi.org/10.30586/pek.1637141</mixed-citation>
                    </ref>
                                    <ref id="ref52">
                        <label>52</label>
                        <mixed-citation publication-type="journal">Tong, S., Jia, N., Luo, X., &amp; Fang, Z. (2021). The Janus face of artificial intelligence feedback: Deployment versus disclosure effects on employee performance. Strategic Management Journal, 42, 1600-1631. https://doi.org/10.1002/smj.3322</mixed-citation>
                    </ref>
                                    <ref id="ref53">
                        <label>53</label>
                        <mixed-citation publication-type="journal">Wassan, S., Gulati, K., Pallathadka, H., Suhail, B., Kuhar, P., &amp; Gupta, A. (2021). How artificial intelligence transforms the experience of employees. Turkish Journal of Computer and Mathematics Education, 12(10), 7116-7135.</mixed-citation>
                    </ref>
                                    <ref id="ref54">
                        <label>54</label>
                        <mixed-citation publication-type="journal">Vergara, D., Bosque, A., Lampropoulos, G., &amp; Fernández-Arias, p. (2025). Trends and applications of artificial intelligence in project management. Electronics, 14, 1-18. https://doi.org/10.3390/electronics14040800</mixed-citation>
                    </ref>
                                    <ref id="ref55">
                        <label>55</label>
                        <mixed-citation publication-type="journal">Verma, S., &amp; Singh, V. (2022). Impact of artificial intelligence-enabled job characteristics and perceived substitution crisis on innovative work behavior of employees from high-tech firms. Computers in Human Behavior, 131, 1-9. https://doi.org/10.1016/j.chb.2022.107215</mixed-citation>
                    </ref>
                                    <ref id="ref56">
                        <label>56</label>
                        <mixed-citation publication-type="journal">Virontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., &amp; Trichina, E. (2022). Artificial intelligence, robotics, advanced technologies and human resource management: A systematic review. The International Journal of Human Resource Management, 33(6), 1237-1266. https://doi.org/10.1080/09585192.2020.1871398</mixed-citation>
                    </ref>
                                    <ref id="ref57">
                        <label>57</label>
                        <mixed-citation publication-type="journal">Yawalkar, M.V.V. (2019). A study of artificial intelligence and its role in human resource management. International Journal of Research and Analytical Reviews (IJRAR), 6(1), 20-24.</mixed-citation>
                    </ref>
                                    <ref id="ref58">
                        <label>58</label>
                        <mixed-citation publication-type="journal">Yu, L., &amp; Li, Y. (2022). Artificial intelligence decision-making transparency and employees’ trust: The parallel multiple mediating effect of effectiveness and discomfort. Behavioral Sciences, 12, 1-17. https://doi.org/10.3390/bs12050127</mixed-citation>
                    </ref>
                                    <ref id="ref59">
                        <label>59</label>
                        <mixed-citation publication-type="journal">Zhu, Y-Q., Corbett, J.U., &amp; Chiu, Y-T. (2021). Understanding employees’ responses to artificial intelligence. Organizational Dynamics, 50, 1-10. https://doi.org/10.1016/j.orgdyn.2020.100786</mixed-citation>
                    </ref>
                            </ref-list>
                    </back>
    </article>
