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CLUSTERING AND THEMATIC MAPPING OF AI-BASED HUMAN RESOURCE MANAGEMENT PRACTICES: A BIBLIOMETRIC INVESTIGATION

Yıl 2025, Cilt: 20 Sayı: 1, 1 - 28, 01.07.2025
https://doi.org/10.54860/beyder.1604753

Öz

The growing significance of artificial intelligence has led to an increased focus on studying the impact of human-computer interaction within organizations. Researchers are paying more attention to this area every day. The goal of human resource management (HRM) departments in organizations is to recruit the most suitable employees for the right positions, effectively and efficiently assign these employees to their roles, and maintain a high quality of work life to attain a sustainable competitive advantage. In the post-Covid-19 era, the hybrid work environment has led to the widespread use of new technology-supported applications for efficient human resource management aligned with organizational goals. These applications aim to increase cost efficiency, excellence, and the quality of work life. This study investigates AI-based HRM practices and the relationships between AI and HRM concepts. The relationship between AI and HRM practices and these concepts was examined using clustering, network and factor analysis, and conceptual maps with the bibliometric method. Bibliometric data was analyzed using the WOS database and the R program. As a result of the examination of 1157 studies obtained from the WOS database, it was seen that the studies were collected in five clusters. These clusters: It consists of the development of AI tools, the acceptance of AI tools by the user, the use of AI tools in the field of HRM, decision making, and strategic dimension related to the future, and specifically in the field of medicine. As a result of the study, it is aimed to develop recommendations for theory and practitioners

Kaynakça

  • Acemoglu, D., & Restrepo, P. (2020). Robots and jobs: Evidence from US labor markets. Journal of political economy, 128(6), 2188-2244.
  • Aşkun, V. (2024). Yapay Zekâ ve Otomasyon Çağında Eşitlik ve Refah: Daron Acemoğlu’nun Görüşlerine Dayalı Bir İnceleme. Bozok Sosyal Bilimler Dergisi, 3(2), 137-160.
  • Berg, A., Buffie, E. F., & Zanna, L. F. (2018). Should we fear the robot revolution?(The correct answer is yes). Journal of Monetary Economics, 97, 117-148.
  • Budhwar, P., Malik, A., De Silva, M. T., & 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.
  • Cheng, J., & Zeng, J. (2023). Shaping AI’s future? China in global AI governance. Journal of Contemporary China, 32(143), 794-810.
  • Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2023). Unlocking the value of artificial intelligence in human resource management through AI capability framework. Human resource management review, 33(1), 100899.
  • Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of business research, 133, 285-296.
  • Dutta, D., & Mishra, S. K. (2024). Artificial intelligence-based virtual assistant and employee engagement: an empirical investigation. Personnel Review.
  • Egghe, L. (2006). “Theory and practice of the G-index”. Scientometrics, vol. 69, no. 1, pp. 131–152).
  • Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation?. Technological forecasting and social change, 114, 254-280.
  • Hirsch, J. E. (2005). “An Index to Quantify an Individual’s Scientific Research Output.” Proceedings of the National Academy of Sciences - PNAS 102.46 (2005): 16569–16572.
  • Hofeditz, L., Clausen, S., Rieß, A., Mirbabaie, M., & Stieglitz, S. (2022). Applying XAI to an AI-based system for candidate management to mitigate bias and discrimination in hiring. Electronic Markets, 32(4), 2207-2233.
  • Insch, G. S., Green, K. Y., & Franz, D. (2024). Navigating management changes in the post-COVID era: suggestions for adapting to the new dynamic work landscape. Development and Learning in Organizations: An International Journal, 38(3), 7-10.
  • Kaushal, N., Kaurav, R. P. S., Sivathanu, B., & Kaushik, N. (2023). Artificial intelligence and HRM: identifying future research Agenda using systematic literature review and bibliometric analysis. Management Review Quarterly, 73(2), 455-493.
  • Kosmyna, N., Hauptmann, E., Yuan, Y. T., Situ, J., Liao, X. H., Beresnitzky, A. V., ... & Maes, P. (2025). Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task. arXiv preprint arXiv:2506.08872.
  • Lawler, J. J., & Elliot, R. (1996). Artificial Intelligence in HRM: An Experimental Study of an Expert System. Journal of Management, 22(1), 85-111. https://doi.org/10.1177/014920639602200104
  • Malin, C. D., Fleiß, J., Seeber, I., Kubicek, B., Kupfer, C., & Thalmann, S. (2024). The application of AI in digital HRM–an experiment on human decision-making in personnel selection. Business Process Management Journal.
  • Nawaz, N., Arunachalam, H., Pathi, B. K., & Gajenderan, V. (2024). The adoption of artificial intelligence in human resources management practices. International Journal of Information Management Data Insights, 4(1), 100208.
  • Newby, G. B., Greenberg, J., & Jones, P. (2003). Open source software development and Lotka's law: bibliometric patterns in programming. Journal of the American Society for information science and technology, 54(2), 169-178.
  • Ouyang, D., He, B., Ghorbani, A., Yuan, N., Ebinger, J., Langlotz, C. P., ... & Zou, J. Y. (2020). Video-based AI for beat-to-beat assessment of cardiac function. Nature, 580(7802), 252-256.
  • Öztürk, O., Kocaman, R., & Kanbach, D. K. (2024). How to design bibliometric research: an overview and a framework proposal. Review of managerial science, 18(11), 3333-3361.
  • Pan, Y., & Froese, F. J. (2023). An interdisciplinary review of AI and HRM: Challenges and future directions. Human resource management review, 33(1), 100924.
  • Reuters, (2025). China's top universities expand enrolment to beef up capabilities in AI, strategic areas, Erişim 17.06.2025, https://www.reuters.com/world/china/chinas-top-universities-expand-enrolment-beef-up-capabilities-ai-strategic-areas-2025-03-10/?utm_source=chatgpt.com Sadullah, Ö., Uyargil, C., Acar, A. C., Özçelik, O. A., Dündar, G., Ataay, İ. D., ... & Tüzüner, L. (2015). İnsan kaynakları yönetimi.(7. Baskı). İstanbul: Beta Yayınları.
  • Siccardi, S., & Villa, V. (2022). Trends in Adopting BIM, IoT and DT for Facility Management: A Scientometric Analysis and Keyword Co-Occurrence Network Review. Buildings, 13(1), 15.
  • Strohmeier, S., Piazza, F. (2015). Artificial Intelligence Techniques in Human Resource Management—A Conceptual Exploration. In: Kahraman, C., Çevik Onar, S. (eds) Intelligent Techniques in Engineering Management. Intelligent Systems Reference Library, vol 87. Springer, Cham. https://doi.org/10.1007/978-3-319-17906-3_7
  • Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial intelligence in human resources management: Challenges and a path forward. California Management Review, 61(4), 15-42.
  • Toffler, A. (1996). Üçüncü Dalga, çev. Ali Seden, Altın Kitaplar Yayınevi, İstanbul.
  • Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., & Trichina, E. (2023). Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review. Artificial intelligence and international HRM, 172-201.

YAPAY ZEKA TABANLI İNSAN KAYNAKLARI YÖNETİMİ UYGULAMALARININ KÜMELENMESİ VE TEMATİK HARİTALANMASI: BIBLİYOMETRİK BİR ARAŞTIRMA

Yıl 2025, Cilt: 20 Sayı: 1, 1 - 28, 01.07.2025
https://doi.org/10.54860/beyder.1604753

Öz

Yapay zekânın artan önemiyle birlikte insan-bilgisayar etkileşiminin örgütler açısından etki ve sonuçlarının incelenmesi her geçen gün daha fazla ölçüde araştırmacıların ilgisini çekmektedir. Örgütlerin İKY birimlerinin amacı, doğru işlere doğru elemanları bularak, bu elemanları en etkin ve verimli bir biçimde işe kanalize ederek, iş-yaşam kalitesini de temin edip sürdürülebilir bir rekabet avantajı sağlamaya çalışmaktır. Covid-19 sonrası dönemde iyice yaygınlaşan hibrit çalışma çevresinde, örgüt hedefleri doğrultusunda insan kaynaklarının verimli şekilde yönetimi, maliyet etkinliği, mükemmellik ve çalışma yaşamının kalitesinin arttırılması için birtakım teknoloji destekli yeni uygulamalar kullanılmaya başlamıştır. Buna göre bu çalışmanın amacı YZ temelli İKY uygulamalarını ve YZ ve İKY kavramları arasındaki ilişkileri incelemektedir. YZ ve İKY uygulamaları ve bu kavramlar arasındaki ilişki bibliyometrik yöntemle kümeleme, ağ ve faktör analizleri ve kavramsal haritalar aracılığıyla incelenmeye çalışılmıştır. Bibliyometrik verilerin analiz edilmesinde WOS veri tabanı ve R programından yararlanılmıştır. WOS veri tabanından elde edilen 1157 çalışmanın incelenmesi sonucunda çalışmaların beş kümede toplandığı görülmüştür. Bu kümeler; YZ araçlarının geliştirilmesi, YZ araçlarının kullanıcı tarafından kabulü, YZ araçlarının İKY alanında kullanımı, gelecekle ilgili karar verme ve stratejik boyut ve spesifik olarak tıp alanında kullanımından oluşmaktadır. Çalışmanın sonucunda teori ve uygulayıcılar açısından öneriler geliştirilmesi hedeflenmektedir.

Kaynakça

  • Acemoglu, D., & Restrepo, P. (2020). Robots and jobs: Evidence from US labor markets. Journal of political economy, 128(6), 2188-2244.
  • Aşkun, V. (2024). Yapay Zekâ ve Otomasyon Çağında Eşitlik ve Refah: Daron Acemoğlu’nun Görüşlerine Dayalı Bir İnceleme. Bozok Sosyal Bilimler Dergisi, 3(2), 137-160.
  • Berg, A., Buffie, E. F., & Zanna, L. F. (2018). Should we fear the robot revolution?(The correct answer is yes). Journal of Monetary Economics, 97, 117-148.
  • Budhwar, P., Malik, A., De Silva, M. T., & 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.
  • Cheng, J., & Zeng, J. (2023). Shaping AI’s future? China in global AI governance. Journal of Contemporary China, 32(143), 794-810.
  • Chowdhury, S., Dey, P., Joel-Edgar, S., Bhattacharya, S., Rodriguez-Espindola, O., Abadie, A., & Truong, L. (2023). Unlocking the value of artificial intelligence in human resource management through AI capability framework. Human resource management review, 33(1), 100899.
  • Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of business research, 133, 285-296.
  • Dutta, D., & Mishra, S. K. (2024). Artificial intelligence-based virtual assistant and employee engagement: an empirical investigation. Personnel Review.
  • Egghe, L. (2006). “Theory and practice of the G-index”. Scientometrics, vol. 69, no. 1, pp. 131–152).
  • Frey, C. B., & Osborne, M. A. (2017). The future of employment: How susceptible are jobs to computerisation?. Technological forecasting and social change, 114, 254-280.
  • Hirsch, J. E. (2005). “An Index to Quantify an Individual’s Scientific Research Output.” Proceedings of the National Academy of Sciences - PNAS 102.46 (2005): 16569–16572.
  • Hofeditz, L., Clausen, S., Rieß, A., Mirbabaie, M., & Stieglitz, S. (2022). Applying XAI to an AI-based system for candidate management to mitigate bias and discrimination in hiring. Electronic Markets, 32(4), 2207-2233.
  • Insch, G. S., Green, K. Y., & Franz, D. (2024). Navigating management changes in the post-COVID era: suggestions for adapting to the new dynamic work landscape. Development and Learning in Organizations: An International Journal, 38(3), 7-10.
  • Kaushal, N., Kaurav, R. P. S., Sivathanu, B., & Kaushik, N. (2023). Artificial intelligence and HRM: identifying future research Agenda using systematic literature review and bibliometric analysis. Management Review Quarterly, 73(2), 455-493.
  • Kosmyna, N., Hauptmann, E., Yuan, Y. T., Situ, J., Liao, X. H., Beresnitzky, A. V., ... & Maes, P. (2025). Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task. arXiv preprint arXiv:2506.08872.
  • Lawler, J. J., & Elliot, R. (1996). Artificial Intelligence in HRM: An Experimental Study of an Expert System. Journal of Management, 22(1), 85-111. https://doi.org/10.1177/014920639602200104
  • Malin, C. D., Fleiß, J., Seeber, I., Kubicek, B., Kupfer, C., & Thalmann, S. (2024). The application of AI in digital HRM–an experiment on human decision-making in personnel selection. Business Process Management Journal.
  • Nawaz, N., Arunachalam, H., Pathi, B. K., & Gajenderan, V. (2024). The adoption of artificial intelligence in human resources management practices. International Journal of Information Management Data Insights, 4(1), 100208.
  • Newby, G. B., Greenberg, J., & Jones, P. (2003). Open source software development and Lotka's law: bibliometric patterns in programming. Journal of the American Society for information science and technology, 54(2), 169-178.
  • Ouyang, D., He, B., Ghorbani, A., Yuan, N., Ebinger, J., Langlotz, C. P., ... & Zou, J. Y. (2020). Video-based AI for beat-to-beat assessment of cardiac function. Nature, 580(7802), 252-256.
  • Öztürk, O., Kocaman, R., & Kanbach, D. K. (2024). How to design bibliometric research: an overview and a framework proposal. Review of managerial science, 18(11), 3333-3361.
  • Pan, Y., & Froese, F. J. (2023). An interdisciplinary review of AI and HRM: Challenges and future directions. Human resource management review, 33(1), 100924.
  • Reuters, (2025). China's top universities expand enrolment to beef up capabilities in AI, strategic areas, Erişim 17.06.2025, https://www.reuters.com/world/china/chinas-top-universities-expand-enrolment-beef-up-capabilities-ai-strategic-areas-2025-03-10/?utm_source=chatgpt.com Sadullah, Ö., Uyargil, C., Acar, A. C., Özçelik, O. A., Dündar, G., Ataay, İ. D., ... & Tüzüner, L. (2015). İnsan kaynakları yönetimi.(7. Baskı). İstanbul: Beta Yayınları.
  • Siccardi, S., & Villa, V. (2022). Trends in Adopting BIM, IoT and DT for Facility Management: A Scientometric Analysis and Keyword Co-Occurrence Network Review. Buildings, 13(1), 15.
  • Strohmeier, S., Piazza, F. (2015). Artificial Intelligence Techniques in Human Resource Management—A Conceptual Exploration. In: Kahraman, C., Çevik Onar, S. (eds) Intelligent Techniques in Engineering Management. Intelligent Systems Reference Library, vol 87. Springer, Cham. https://doi.org/10.1007/978-3-319-17906-3_7
  • Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial intelligence in human resources management: Challenges and a path forward. California Management Review, 61(4), 15-42.
  • Toffler, A. (1996). Üçüncü Dalga, çev. Ali Seden, Altın Kitaplar Yayınevi, İstanbul.
  • Vrontis, D., Christofi, M., Pereira, V., Tarba, S., Makrides, A., & Trichina, E. (2023). Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review. Artificial intelligence and international HRM, 172-201.
Toplam 28 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular İstihdam
Bölüm Makaleler
Yazarlar

Meryem Aybas 0000-0001-6133-7238

Erken Görünüm Tarihi 29 Haziran 2025
Yayımlanma Tarihi 1 Temmuz 2025
Gönderilme Tarihi 12 Ocak 2025
Kabul Tarihi 20 Haziran 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 20 Sayı: 1

Kaynak Göster

APA Aybas, M. (2025). YAPAY ZEKA TABANLI İNSAN KAYNAKLARI YÖNETİMİ UYGULAMALARININ KÜMELENMESİ VE TEMATİK HARİTALANMASI: BIBLİYOMETRİK BİR ARAŞTIRMA. Bilgi Ekonomisi ve Yönetimi Dergisi, 20(1), 1-28. https://doi.org/10.54860/beyder.1604753