Derleme
BibTex RIS Kaynak Göster

İnsan Kaynakları Yönetiminde Endüstri 4.0 ve Yapay Zekâ’nın Etkisi

Yıl 2023, Cilt: 5 Sayı: 2 - ARALIK 2023 SAYISI, 143 - 166, 25.12.2023
https://doi.org/10.47898/ijeased.1306881

Öz

Günümüz piyasa koşullarında rekabetin önemi ortadadır. Kuruluşlar, rekabet gücünü arttırmak ve pazarda kalabilmek için doğru kaynağı doğru yatırıma yönlendirmek zorundadırlar. Bu bağlamda, İnsan Kaynakları Yönetimi (İKY) birimi de dijitalleşme evresine girmiş bulunmaktadır. İnsan kaynaklarında (İK) dijitalleşme evresi, yapay zekâ yardımı ile özellikle işe alım sürecinde önemli aşamalar kaydetmiştir. Kurum için değer kaybı yaratan bu evrede, yüzlerce hatta binlerce başvuru arasından adayların aranması, işe en uygun olanın seçilmesi ve uygun olanların kurum içinde açık pozisyonlara yerleştirilmesi; yapay zeka teknolojisi ile yapılan değerlendirmeler sonucunda maliyet ve zaman kaybı olmadan gerçekleştirilebilmektedir. Böylece, yapay zekâ yaklaşımı, işe alım sürecinde mülakatların hızlı ve daha az maliyetle yönetilmesi sağlamaktadır. Ayrıca, yapay zekâ İKY biriminin eğitim, oryantasyon, kariyer planlama gibi çeşitli faaliyetlerinin de verimli bir şekilde yerine getirilmesini sağlamıştır. Bu çalışma, Endüstri 4.0 ve yapay zekânın insan kaynakları yönetimindeki rolünü literatür araştırması yaparak incelemiştir.

Kaynakça

  • Akça, C. (2023). Yetenek yönetiminde yapay zekâ uygulamaları, Ahi Evran Akademi, 4(1), 49-63.
  • Aksu, S. G., & Sürgevil, O. (2019). Competencies of the digital age: A view from the framework of employees, human resources specialists and managers. Journal of Business in The Digital Age, 2(2), 54-68.
  • Alkan. M. A. (2019). Makine öğrenimi nedir? https://www.endustri40.com/makine-ogrenimi-nedir/ (Date of Access: 20.07.2022)
  • Anayat, S. (2023). Human resources management after Industry 4.0: blending AI and HRM. In strategic human resource management in the hospitality industry: a digitalized economic paradigm. Hershey, PA: IGI Global.
  • Arda E. & Küçükkocaoğlu, G. (2021). Stock price predictions using artificial intelligence methods. Journal of Research in Economics, Politics & Finance, (6)2, pp.565-586.
  • Batur, C. & Diri, B. (2018). Identifying predictive genes for sequence classification using artificial immune recognition system. Int. J. Sci. Technol. 8(4), pp. 58–66.
  • Batur Dinler, Ö. & Aydın, N. (2020). An optimal feature parameter set based on gated recurrent unit recurrent neural networks for speech segment detection. Appl Sci. 10(4),1273,1-23.
  • Batur Dinler, Ö. & Batur Şahin, C. (2021). Prediction of phishing web sites with deep learning using WEKA environment. European Journal of Science and Technology. (24)24. pp.35-41.
  • Batur Şahin, C. (2021). Deep –Immune-Network model for vulnerable clone detection. Manchester Journal of Artificial Intelligence & Applied Sciences. Springer, (2)2, pp. 213-218.
  • Bayarçelik, E. B. (2020). Dijital dönüşümün insan kaynakları yönetimi üzerine etkileri. Dijital Dönüşüm ve Süreçler & Digital Transformation and Processes. İstanbul Gelişim Üniversitesi Yayınları.
  • Booth M. (2019). The next industrial revolution is upon us. Daresay. Retrieved from : https://daresay.co/2019/08/29/daresay-designing-for-industry-4-0/
  • Calfee, R. C., and Valencia, R. R. (1991). APA guide to preparing manuscripts for journal publication. Washington, DC: American Psychological Association.
  • Cerebro, (2018). Yapay zeka dokunuşu ile insan kaynakları. Indutry leading artificial intelligenceand machine learning blog. Retrieved from: https://medium.com/@cerebro.tech/yapay-zeka-dokunu%C5%9Fu-ile-i%CC%87nsan kaynaklar %C4%B1-152eebdc23a9
  • Chowdhury, S., Budhwar, P., Dey, P. K., Joel-Edgar, S., & Abadie, A. (2022). AI-employee collaboration and business performance: integrating knowledge-based view, socio-technical systems and organisational socialisation framework. Journal of Business Research, 144, 31-49.
  • Çiftçioğlu, B. A., Mutlu, M., & Katırcıoğlu, S. (2019). The relationship between Industry 4.0 and human resource management. Social Sciences Research Journal Bandırma Onyedi Eylül Üniversitesi (BANÜSAD), 2(1), 31-53.
  • Çiçek, Y., Uludağ, A. & Gülbandilar, E. (2022). Şeker pancarı üretiminde kullanılan yapay zekâ teknikleri. Journal of ESTUDAM Information. (3)2, pp. 54-59.
  • Dikel, S. & Öz, M. (2022). Artificial intelligence (AI) application in aquaculture. ISPEC 10th Internatıonal Conference on Agriculture, Animal Sciences and Rural Development.
  • Duncan, G. J., and Brooks-Gunn, J. (Eds.). (1997). Consequences of growing up poor. New York, NY: Russell Sage Foundation.
  • Eker, E., Kayri, M., Ekinci, S., and İzci, D. (2021). A new fusion of ASO with SA algorithm and its applications to MLP training and DC motor speed control. Arab J Sci Eng 46, 3889–3911 https://doi.org/10.1007/s13369-020-05228-5
  • Ertaş, A. (2023). Dijital insan kaynakları yönetimi. İstanbul, Efe Akademik Yayıncılık.
  • Gardner, M. W. and Dorling, S. R. (1998). Artificial neural networks (the multilayer perceptron) a review of applications in the atmospheric sciences. Atmospheric Environment, 32 (14), 2627–2636. doi:10.1016/S1352-2310(97)00447-0.
  • Gong, Y., Zhao M., Wang Q., & Lv Z. (2022). Design and interactive performance of human resource management system based on artificial intelligence. PLoS ONE 17(1): e0262398. https://doi.org/10.1371/journal.pone.0262398
  • Helfer, M. E., Kempe, R. S., and Krugman, R. D. (1997). The battered child (5th ed.). Chicago, IL: University of Chicago Press.
  • İbrahimağaoğlu, Ö. (2023). Elektronik insan kaynakları yönetimi ile ilgili bir yazın taraması. Balkan & Near Eastern Journal of Social Sciences (BNEJSS), 9(2), 82-91.
  • James, W. (1890). The principles of psychology. New York: Henry Holt and Company the Principles of Psychology.
  • Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making, Business Horizons, 61(4), 577-586.
  • Jawad, W. K. (2020). Design and implementation of e-human resource management system for IT Ccompany. Int J Found Comput S, 3(1), 1-6.
  • Karaboğa, T., & Karaboğa, H.A. (2022). İnsan kaynakları yönetiminde dijitalleşme: Bibliyometrik bir inceleme. Turkish Studies-Economy, 17(2), 343-364.
  • Kılıç Kırılmaz, S. & Ateş, Ç. (2021). İşe alımlarda yapay zekâ kullanımı: kavramsal bir değerlendirme. Journal of Business and Trade, 2 (1), 37-48.
  • Korkmaz, Y. & Boyacı, A. (2022). A comprehensive Turkish accent/dialect recognition system using acoustic perceptual formants. Applied Acoustics 193,108761.
  • Kulkarni, Swatee B. and Che, X. (2019). Intelligent software tools for recruiting. Journal of International Technology and Information Management, 28 (2), Article 1. DOI: https://doi.org/10.58729/1941-6679.1398.
  • Kumari, P. Barani and Hemalatha, A. (2021). Perception towards artificial intelligence in human resources management practices - with reference to IT companies in chennai. IJRTE,8(4S3), 61-65.
  • Lauriola, I., Lavelli, A. & Aiolli, F. (2022). An introduction to deep learning in natural language processing: Models, techniques, and tools. Neurocomputing. (470). pp. 443-456.
  • Medium, (2018). Yapay zeka dokunuşu ile insan kaynakları”, https://medium.com/@cerebro.tech/yapay-zeka-dokunu%C5%9Fu-ile-i%CC%87nsan kaynaklar %C4%B1-152eebdc23a9 (Date of Access: 22.01.2022).
  • Ming, L. (2022). A deep learning-based framework for human resource recommendation. Hindawi, Wireless Communications and Mobile Computing, 2022(1), pp. 1-12 Doi:10.1155/2022/2377143
  • Murugesan, U., Subramanian, P., Srivastava, S. and Dwivedi, A. (2023) . A study of artificial intelligence impacts on human resource digitalization in Industry 4.0. Decision Analytics Journal, 7: 100249. ISSN 2772-6622.
  • Nawaz, N. (2020). Exploring artificial intelligence applications in human resource management. Journal of Management Information and Decision Sciences, 23(5), 552-563.
  • Necula, S. C., & Strîmbei, C. (2019). People analytics of semantic web human resource résumés for sustainable talent acquisition. Sustainability, 11(13), 3520.
  • Ning, J. (2022). Natural language processing technology used in artificial intelligence scene of law for human behavior. Hindawi, Wireless Communications and Mobile Computing, pp. 1-8. Doi: 10.1155/2022/6606588.
  • Ogoo Blog, (2017). Tofaş mobil intranetle iç iletişimde dijital dönüşüm, http://blog.ogoodigital.com/tofas-mobil-intranetle-ic-iletisimde-dijital-donusum/ (Date of Access: 15.11.2021).
  • O'Neil, J. M., and Egan, J. (1992). Men's and women's gender role journeys: A metaphor for healing, transition, and transformation. In B. R. Wainrib (Ed.), Gender issues across the life cycle (pp. 107-123). New York, NY: Springer.
  • Oruçoğlu, O. (2022). Endüstri 4.0'ın insan kaynakları yönetimi fonksiyonlarından işe alım'a etkileri. Ege Stratejik Araştırmalar Dergisi, 13(1), 57-84.
  • Onik, M. M. H., Miraz, M. H., & Kim, C. S. (2018, April). A recruitment and human resource management technique using Blockchain technology for Industry 4.0. In Proceedings of the Smart Cities Symposium (SCS-2018), Manama, Bahrain (pp. 11-16). IET.
  • Öğüt, A., Akgemci, T. & Demirsel, M. T. (2004). Stratejik insan kaynakları yönetimi bağlamında örgütlerde işgören motivasyonu süreci. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (12), 277-290.
  • Özçelik, A. O., Sadullah, Ö., & Uyargil, C. (2021). İnsan kaynakları yönetimi (İ.Ü.). İstanbul, Beta Yayınevi.
  • Pal, R., Shaikh, S., Satpute, S., & Bhagwat, S. (2022). Resume classification using various machine learning algorithms. In ITM Web of Conferences, 44: 03011, EDP Sciences.
  • Palos-Sánchez, P. R., Baena-Luna, P., Badicu, A., & Infante-Moro, J. C. (2022). Artificial intelligence and human resources management: A bibliometric analysis. Applied Artificial Intelligence, 36(1), 2145631.
  • Pan, Y., Froese, F., Liu, N., Hu, Y., & Ye, M. (2022). The adoption of artificial intelligence in employee recruitment: The influence of contextual factors. The International Journal of Human Resource Management, 33(6), 1125-1147.
  • Parsehyan, B. G. (2020). Digital transformation in human resources management: HR 4.0. Turkish Studies-Information Technologies and Applied Sciences, 15(2), 211-224.
  • Pereira, V., Hadjielias, E., Christofi, M., & 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), 100857.
  • Plath, S. (2000). The unabridged journals. K. V. Kukil (Ed.). New York, NY: Anchor. Laplace, P. S. (1951). A philosophical essay on probabilities. (F. W. Truscott and F. L. Emory, Trans.). New York, NY: Dover. (Original work published 1814).
  • Rahman, M. M., Mollik, M. F., Hasan, M., & Akter, M. (2022, December). Blockchain in human resource management to hire the right candidate. In 2022 4th International Conference on Sustainable Technologies for Industry 4.0 (STI).
  • Rykun, E. (2019). Artificial intelligence in HR management–what can we expect? The Boss Magazine. https://thebossmagazine.com/ai-hr-management/ [Google Scholar].
  • Qamar, Y., Agrawal, R. K., Samad, T. A., & Jabbour, C. J. C. (2021). When technology meets people: the interplay of artificial intelligence and human resource management. Journal of Enterprise Information Management, 34(5), 1339-1370.
  • Qin, C., Zhu, H., Xu, T., Zhu, C., Ma, C., Chen, E., & Xiong, H. (2020). An enhanced neural network approach to person-job fit in talent recruitment. ACM Transactions on Information Systems (TOIS), 38(2), 1-33.
  • Samarasinghe, K. R., & Medis, A. (2020). Artificial intelligence based strategic human resource management (AISHRM) for industry 4.0. Global Journal of Management and Business Research, 20(2), 7-13.
  • Saridakis, G., Lai, Y., & Cooper, C. L. (2017). Exploring the relationship between HRM and firm performance: A meta-analysis of longitudinal studies. Human Resource Management Review, 27(1), 87-96.
  • Seyidzadə, J. (2023). Dijital dönüşümün insan kaynakları yönetiminde rolü: İşletmelerde dijital İKY uygulamaları üzerine bir Araştırma. Turan-Sam, 15 (Sp. Issue), 170-179.
  • Soleimani, M., Intezari, A., & Taskin, N. (2021, April). Cognitive biases in developing biased artificial intelligence recruitment system. Proceedings of the 54th Hawaii International Conference on System Sciences, Hawaii, USA.
  • Suseno, Y., Chang, C., Hudik, M., & Fang, E. S. (2022). Beliefs, anxiety and change readiness for artificial intelligence adoption among human resource managers: the moderating role of high-performance work systems. The InTernaTIonal Journal of human resource managemenT, 33(6), 1209-1236.
  • Şekeroğlu, S. ve Özer, K. (2019). The effect of technology and artificial intelligence in human resources management. In book: Dijital dönüşüm ve kooperatifler, Chapter:17, 185-192.
  • Şendoğdu, A. A. (2020). The inevitability of new expansions in human resource management in the context of robotic resource management in the Industry 4.0 revolution. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 34(1), 141-161.
  • Şengüler, H. & İnel, M. N. (2021) An empirical study based on artificial intelligence for determining brand value based on financial data. Sosyoekonomi, (30)53, 395-424.
  • Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial ıntelligence in human resources management: Challenges and a path forward. California Management Review, 61(4), 15-42.
  • Tewari, I. & Pant, M. (2020, December). Artificial intelligence reshaping human resource management: a review. IEEE International Conference on Advent Trends in Multidisciplinary Research and Innovation (ICATMRI),1-4.
  • Tiwari, P., Pandey, R., Garg, V., & Singhal, A. (2021, January). Application of artificial intelligence in human resource management practices. 2021 11th International Conference on Cloud Computing, Data Science & Engineering (Confluence). Noida, India.
  • Thite, M. (2018). Future directions in electronic /dijital HRM, in: e-HRM (1st ed.). Taylor and Francis. Retrieved from:https://www.perlego.com/book/2193324/ehrm-digital-approaches-directions-applications-pdf.
  • Toprak, M., Doğukan, Ö., & Çalışkan, S. (2022). Yapay zekâ kullanımı ve insan kaynakları yönetimi. Uluslararası Eşitlik Politikası Dergisi, 2(2), 76-103.
  • Tripathi, R. T. and Singh, P. K. (2017, March). A study on innovative practices in digital human resource management. National Seminar On Digital Transformation Of Business İn India: Opportunities And Challenges, Dehradun, Ims Unison University Publisher, Uttarakhand.
  • Uğur, A. & Güner, A. (2017). Sakarya üniversitesi çalışma ekonomisi ve endüstri ilişkileri seçme yazılar, 1. Sakarya, Sakarya Yayıncılık.
  • Uğurlu, H. Ü. A., & Doğan, A.(2023). İnsan kaynakları yönetiminde dijital dönüşüm ve dijitalleşen işe alım işlevi. Kocaeli Üniversitesi Sosyal Bilimler Dergisi, 1(45), 1-16.
  • Ullah, A., Şahin, C. B., Dinler, Ö. B., Khan, M. H., & Aznaoui, H. (2021). Heart disease prediction using various machines learning approach. J Cardiovasc. Dis. Res.,12(3), 379-391.
  • Wiener, P. P. (19731974). Dictionary of the history of ideas: studiesof selected pivotal ideas. New York, NY: Scribner's.
  • Wei, G., & Jin, Y. (2021). Human resource management model based on three-layer BP neural network and machine learning. Journal of Intelligent & Fuzzy Systems, 40(2), 2289-2300.
  • Van Noordt, C., & Misuraca, G. (2022). Artificial intelligence for the public sector: results of landscaping the use of AI in government across the European Union. Government Information Quarterly, 39(3), 101714.
  • Vorontis, D., Christofi, M., Pereira, V., & Tarba, S. (2021). Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review. The International Journal of Human Resource Management 33(3), 1-30, Doi:10.1080/09585192.2020.1871398.
  • Yawalkar, V.V. (2019). A Study of artificial intelligence and its role in human resource management. International Journal of Research and Analytical Reviews(IJRAR), (6)2, pp.20-24.
  • Yılmaz, C., & Yılmaz, T. (2023). Endüstri 4.0’ın insan kaynakları yönetimine etkisi: İKY 4.0. Hak İş Uluslararası Emek ve Toplum Dergisi, 12(32), 11-28.
  • Zhu H, and Usman, M. (2021). Research on human resource recommendation algorithm based on machine learning. Sci. Program, 2021 (2021). doi: https://doi.org/10.1155/2021/8387277

The Effect of Industry 4.0 and Artificial Intelligence on Human Resource Management

Yıl 2023, Cilt: 5 Sayı: 2 - ARALIK 2023 SAYISI, 143 - 166, 25.12.2023
https://doi.org/10.47898/ijeased.1306881

Öz

In today's market conditions, the importance of competition is obvious. Organizations must direct the right resources to the right investment to increase their competitive power and stay in the market. In this respect, the Human Resource Management (HRM) unit has also entered the digitalization phase. The digitalization phase in Human Resources (HR) has made significant progress, particularly in the recruitment process, with the help of Artificial Intelligence (AI). During this phase that creates a loss of value for the organization, searching for candidates among hundreds or even thousands of applications, selecting the most suitable one for the job, and placing the suitable ones in open positions within the institution; As a result of the evaluations made with artificial intelligence technology, it can be carried out without loss of cost and time. Thus, the AI approach ensures that interviews are managed quickly and with less cost in the recruitment process. Furthermore, AI enables the efficient fulfillment of various activities of the HRM unit, such as training, orientation, and career planning. The present study attempts to explain the impact of Industry 4.0 and AI on human resource management processes as a result of a literature review. This study, examined the role of Industry 4.0 and artificial intelligence in human resources management by making a literature review.

Kaynakça

  • Akça, C. (2023). Yetenek yönetiminde yapay zekâ uygulamaları, Ahi Evran Akademi, 4(1), 49-63.
  • Aksu, S. G., & Sürgevil, O. (2019). Competencies of the digital age: A view from the framework of employees, human resources specialists and managers. Journal of Business in The Digital Age, 2(2), 54-68.
  • Alkan. M. A. (2019). Makine öğrenimi nedir? https://www.endustri40.com/makine-ogrenimi-nedir/ (Date of Access: 20.07.2022)
  • Anayat, S. (2023). Human resources management after Industry 4.0: blending AI and HRM. In strategic human resource management in the hospitality industry: a digitalized economic paradigm. Hershey, PA: IGI Global.
  • Arda E. & Küçükkocaoğlu, G. (2021). Stock price predictions using artificial intelligence methods. Journal of Research in Economics, Politics & Finance, (6)2, pp.565-586.
  • Batur, C. & Diri, B. (2018). Identifying predictive genes for sequence classification using artificial immune recognition system. Int. J. Sci. Technol. 8(4), pp. 58–66.
  • Batur Dinler, Ö. & Aydın, N. (2020). An optimal feature parameter set based on gated recurrent unit recurrent neural networks for speech segment detection. Appl Sci. 10(4),1273,1-23.
  • Batur Dinler, Ö. & Batur Şahin, C. (2021). Prediction of phishing web sites with deep learning using WEKA environment. European Journal of Science and Technology. (24)24. pp.35-41.
  • Batur Şahin, C. (2021). Deep –Immune-Network model for vulnerable clone detection. Manchester Journal of Artificial Intelligence & Applied Sciences. Springer, (2)2, pp. 213-218.
  • Bayarçelik, E. B. (2020). Dijital dönüşümün insan kaynakları yönetimi üzerine etkileri. Dijital Dönüşüm ve Süreçler & Digital Transformation and Processes. İstanbul Gelişim Üniversitesi Yayınları.
  • Booth M. (2019). The next industrial revolution is upon us. Daresay. Retrieved from : https://daresay.co/2019/08/29/daresay-designing-for-industry-4-0/
  • Calfee, R. C., and Valencia, R. R. (1991). APA guide to preparing manuscripts for journal publication. Washington, DC: American Psychological Association.
  • Cerebro, (2018). Yapay zeka dokunuşu ile insan kaynakları. Indutry leading artificial intelligenceand machine learning blog. Retrieved from: https://medium.com/@cerebro.tech/yapay-zeka-dokunu%C5%9Fu-ile-i%CC%87nsan kaynaklar %C4%B1-152eebdc23a9
  • Chowdhury, S., Budhwar, P., Dey, P. K., Joel-Edgar, S., & Abadie, A. (2022). AI-employee collaboration and business performance: integrating knowledge-based view, socio-technical systems and organisational socialisation framework. Journal of Business Research, 144, 31-49.
  • Çiftçioğlu, B. A., Mutlu, M., & Katırcıoğlu, S. (2019). The relationship between Industry 4.0 and human resource management. Social Sciences Research Journal Bandırma Onyedi Eylül Üniversitesi (BANÜSAD), 2(1), 31-53.
  • Çiçek, Y., Uludağ, A. & Gülbandilar, E. (2022). Şeker pancarı üretiminde kullanılan yapay zekâ teknikleri. Journal of ESTUDAM Information. (3)2, pp. 54-59.
  • Dikel, S. & Öz, M. (2022). Artificial intelligence (AI) application in aquaculture. ISPEC 10th Internatıonal Conference on Agriculture, Animal Sciences and Rural Development.
  • Duncan, G. J., and Brooks-Gunn, J. (Eds.). (1997). Consequences of growing up poor. New York, NY: Russell Sage Foundation.
  • Eker, E., Kayri, M., Ekinci, S., and İzci, D. (2021). A new fusion of ASO with SA algorithm and its applications to MLP training and DC motor speed control. Arab J Sci Eng 46, 3889–3911 https://doi.org/10.1007/s13369-020-05228-5
  • Ertaş, A. (2023). Dijital insan kaynakları yönetimi. İstanbul, Efe Akademik Yayıncılık.
  • Gardner, M. W. and Dorling, S. R. (1998). Artificial neural networks (the multilayer perceptron) a review of applications in the atmospheric sciences. Atmospheric Environment, 32 (14), 2627–2636. doi:10.1016/S1352-2310(97)00447-0.
  • Gong, Y., Zhao M., Wang Q., & Lv Z. (2022). Design and interactive performance of human resource management system based on artificial intelligence. PLoS ONE 17(1): e0262398. https://doi.org/10.1371/journal.pone.0262398
  • Helfer, M. E., Kempe, R. S., and Krugman, R. D. (1997). The battered child (5th ed.). Chicago, IL: University of Chicago Press.
  • İbrahimağaoğlu, Ö. (2023). Elektronik insan kaynakları yönetimi ile ilgili bir yazın taraması. Balkan & Near Eastern Journal of Social Sciences (BNEJSS), 9(2), 82-91.
  • James, W. (1890). The principles of psychology. New York: Henry Holt and Company the Principles of Psychology.
  • Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making, Business Horizons, 61(4), 577-586.
  • Jawad, W. K. (2020). Design and implementation of e-human resource management system for IT Ccompany. Int J Found Comput S, 3(1), 1-6.
  • Karaboğa, T., & Karaboğa, H.A. (2022). İnsan kaynakları yönetiminde dijitalleşme: Bibliyometrik bir inceleme. Turkish Studies-Economy, 17(2), 343-364.
  • Kılıç Kırılmaz, S. & Ateş, Ç. (2021). İşe alımlarda yapay zekâ kullanımı: kavramsal bir değerlendirme. Journal of Business and Trade, 2 (1), 37-48.
  • Korkmaz, Y. & Boyacı, A. (2022). A comprehensive Turkish accent/dialect recognition system using acoustic perceptual formants. Applied Acoustics 193,108761.
  • Kulkarni, Swatee B. and Che, X. (2019). Intelligent software tools for recruiting. Journal of International Technology and Information Management, 28 (2), Article 1. DOI: https://doi.org/10.58729/1941-6679.1398.
  • Kumari, P. Barani and Hemalatha, A. (2021). Perception towards artificial intelligence in human resources management practices - with reference to IT companies in chennai. IJRTE,8(4S3), 61-65.
  • Lauriola, I., Lavelli, A. & Aiolli, F. (2022). An introduction to deep learning in natural language processing: Models, techniques, and tools. Neurocomputing. (470). pp. 443-456.
  • Medium, (2018). Yapay zeka dokunuşu ile insan kaynakları”, https://medium.com/@cerebro.tech/yapay-zeka-dokunu%C5%9Fu-ile-i%CC%87nsan kaynaklar %C4%B1-152eebdc23a9 (Date of Access: 22.01.2022).
  • Ming, L. (2022). A deep learning-based framework for human resource recommendation. Hindawi, Wireless Communications and Mobile Computing, 2022(1), pp. 1-12 Doi:10.1155/2022/2377143
  • Murugesan, U., Subramanian, P., Srivastava, S. and Dwivedi, A. (2023) . A study of artificial intelligence impacts on human resource digitalization in Industry 4.0. Decision Analytics Journal, 7: 100249. ISSN 2772-6622.
  • Nawaz, N. (2020). Exploring artificial intelligence applications in human resource management. Journal of Management Information and Decision Sciences, 23(5), 552-563.
  • Necula, S. C., & Strîmbei, C. (2019). People analytics of semantic web human resource résumés for sustainable talent acquisition. Sustainability, 11(13), 3520.
  • Ning, J. (2022). Natural language processing technology used in artificial intelligence scene of law for human behavior. Hindawi, Wireless Communications and Mobile Computing, pp. 1-8. Doi: 10.1155/2022/6606588.
  • Ogoo Blog, (2017). Tofaş mobil intranetle iç iletişimde dijital dönüşüm, http://blog.ogoodigital.com/tofas-mobil-intranetle-ic-iletisimde-dijital-donusum/ (Date of Access: 15.11.2021).
  • O'Neil, J. M., and Egan, J. (1992). Men's and women's gender role journeys: A metaphor for healing, transition, and transformation. In B. R. Wainrib (Ed.), Gender issues across the life cycle (pp. 107-123). New York, NY: Springer.
  • Oruçoğlu, O. (2022). Endüstri 4.0'ın insan kaynakları yönetimi fonksiyonlarından işe alım'a etkileri. Ege Stratejik Araştırmalar Dergisi, 13(1), 57-84.
  • Onik, M. M. H., Miraz, M. H., & Kim, C. S. (2018, April). A recruitment and human resource management technique using Blockchain technology for Industry 4.0. In Proceedings of the Smart Cities Symposium (SCS-2018), Manama, Bahrain (pp. 11-16). IET.
  • Öğüt, A., Akgemci, T. & Demirsel, M. T. (2004). Stratejik insan kaynakları yönetimi bağlamında örgütlerde işgören motivasyonu süreci. Selçuk Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, (12), 277-290.
  • Özçelik, A. O., Sadullah, Ö., & Uyargil, C. (2021). İnsan kaynakları yönetimi (İ.Ü.). İstanbul, Beta Yayınevi.
  • Pal, R., Shaikh, S., Satpute, S., & Bhagwat, S. (2022). Resume classification using various machine learning algorithms. In ITM Web of Conferences, 44: 03011, EDP Sciences.
  • Palos-Sánchez, P. R., Baena-Luna, P., Badicu, A., & Infante-Moro, J. C. (2022). Artificial intelligence and human resources management: A bibliometric analysis. Applied Artificial Intelligence, 36(1), 2145631.
  • Pan, Y., Froese, F., Liu, N., Hu, Y., & Ye, M. (2022). The adoption of artificial intelligence in employee recruitment: The influence of contextual factors. The International Journal of Human Resource Management, 33(6), 1125-1147.
  • Parsehyan, B. G. (2020). Digital transformation in human resources management: HR 4.0. Turkish Studies-Information Technologies and Applied Sciences, 15(2), 211-224.
  • Pereira, V., Hadjielias, E., Christofi, M., & 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), 100857.
  • Plath, S. (2000). The unabridged journals. K. V. Kukil (Ed.). New York, NY: Anchor. Laplace, P. S. (1951). A philosophical essay on probabilities. (F. W. Truscott and F. L. Emory, Trans.). New York, NY: Dover. (Original work published 1814).
  • Rahman, M. M., Mollik, M. F., Hasan, M., & Akter, M. (2022, December). Blockchain in human resource management to hire the right candidate. In 2022 4th International Conference on Sustainable Technologies for Industry 4.0 (STI).
  • Rykun, E. (2019). Artificial intelligence in HR management–what can we expect? The Boss Magazine. https://thebossmagazine.com/ai-hr-management/ [Google Scholar].
  • Qamar, Y., Agrawal, R. K., Samad, T. A., & Jabbour, C. J. C. (2021). When technology meets people: the interplay of artificial intelligence and human resource management. Journal of Enterprise Information Management, 34(5), 1339-1370.
  • Qin, C., Zhu, H., Xu, T., Zhu, C., Ma, C., Chen, E., & Xiong, H. (2020). An enhanced neural network approach to person-job fit in talent recruitment. ACM Transactions on Information Systems (TOIS), 38(2), 1-33.
  • Samarasinghe, K. R., & Medis, A. (2020). Artificial intelligence based strategic human resource management (AISHRM) for industry 4.0. Global Journal of Management and Business Research, 20(2), 7-13.
  • Saridakis, G., Lai, Y., & Cooper, C. L. (2017). Exploring the relationship between HRM and firm performance: A meta-analysis of longitudinal studies. Human Resource Management Review, 27(1), 87-96.
  • Seyidzadə, J. (2023). Dijital dönüşümün insan kaynakları yönetiminde rolü: İşletmelerde dijital İKY uygulamaları üzerine bir Araştırma. Turan-Sam, 15 (Sp. Issue), 170-179.
  • Soleimani, M., Intezari, A., & Taskin, N. (2021, April). Cognitive biases in developing biased artificial intelligence recruitment system. Proceedings of the 54th Hawaii International Conference on System Sciences, Hawaii, USA.
  • Suseno, Y., Chang, C., Hudik, M., & Fang, E. S. (2022). Beliefs, anxiety and change readiness for artificial intelligence adoption among human resource managers: the moderating role of high-performance work systems. The InTernaTIonal Journal of human resource managemenT, 33(6), 1209-1236.
  • Şekeroğlu, S. ve Özer, K. (2019). The effect of technology and artificial intelligence in human resources management. In book: Dijital dönüşüm ve kooperatifler, Chapter:17, 185-192.
  • Şendoğdu, A. A. (2020). The inevitability of new expansions in human resource management in the context of robotic resource management in the Industry 4.0 revolution. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 34(1), 141-161.
  • Şengüler, H. & İnel, M. N. (2021) An empirical study based on artificial intelligence for determining brand value based on financial data. Sosyoekonomi, (30)53, 395-424.
  • Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial ıntelligence in human resources management: Challenges and a path forward. California Management Review, 61(4), 15-42.
  • Tewari, I. & Pant, M. (2020, December). Artificial intelligence reshaping human resource management: a review. IEEE International Conference on Advent Trends in Multidisciplinary Research and Innovation (ICATMRI),1-4.
  • Tiwari, P., Pandey, R., Garg, V., & Singhal, A. (2021, January). Application of artificial intelligence in human resource management practices. 2021 11th International Conference on Cloud Computing, Data Science & Engineering (Confluence). Noida, India.
  • Thite, M. (2018). Future directions in electronic /dijital HRM, in: e-HRM (1st ed.). Taylor and Francis. Retrieved from:https://www.perlego.com/book/2193324/ehrm-digital-approaches-directions-applications-pdf.
  • Toprak, M., Doğukan, Ö., & Çalışkan, S. (2022). Yapay zekâ kullanımı ve insan kaynakları yönetimi. Uluslararası Eşitlik Politikası Dergisi, 2(2), 76-103.
  • Tripathi, R. T. and Singh, P. K. (2017, March). A study on innovative practices in digital human resource management. National Seminar On Digital Transformation Of Business İn India: Opportunities And Challenges, Dehradun, Ims Unison University Publisher, Uttarakhand.
  • Uğur, A. & Güner, A. (2017). Sakarya üniversitesi çalışma ekonomisi ve endüstri ilişkileri seçme yazılar, 1. Sakarya, Sakarya Yayıncılık.
  • Uğurlu, H. Ü. A., & Doğan, A.(2023). İnsan kaynakları yönetiminde dijital dönüşüm ve dijitalleşen işe alım işlevi. Kocaeli Üniversitesi Sosyal Bilimler Dergisi, 1(45), 1-16.
  • Ullah, A., Şahin, C. B., Dinler, Ö. B., Khan, M. H., & Aznaoui, H. (2021). Heart disease prediction using various machines learning approach. J Cardiovasc. Dis. Res.,12(3), 379-391.
  • Wiener, P. P. (19731974). Dictionary of the history of ideas: studiesof selected pivotal ideas. New York, NY: Scribner's.
  • Wei, G., & Jin, Y. (2021). Human resource management model based on three-layer BP neural network and machine learning. Journal of Intelligent & Fuzzy Systems, 40(2), 2289-2300.
  • Van Noordt, C., & Misuraca, G. (2022). Artificial intelligence for the public sector: results of landscaping the use of AI in government across the European Union. Government Information Quarterly, 39(3), 101714.
  • Vorontis, D., Christofi, M., Pereira, V., & Tarba, S. (2021). Artificial intelligence, robotics, advanced technologies and human resource management: a systematic review. The International Journal of Human Resource Management 33(3), 1-30, Doi:10.1080/09585192.2020.1871398.
  • Yawalkar, V.V. (2019). A Study of artificial intelligence and its role in human resource management. International Journal of Research and Analytical Reviews(IJRAR), (6)2, pp.20-24.
  • Yılmaz, C., & Yılmaz, T. (2023). Endüstri 4.0’ın insan kaynakları yönetimine etkisi: İKY 4.0. Hak İş Uluslararası Emek ve Toplum Dergisi, 12(32), 11-28.
  • Zhu H, and Usman, M. (2021). Research on human resource recommendation algorithm based on machine learning. Sci. Program, 2021 (2021). doi: https://doi.org/10.1155/2021/8387277
Toplam 79 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yapay Zeka
Bölüm Makaleler / Articles
Yazarlar

Abdurrahim Bulut 0000-0003-0737-9394

Özlem Batur Dinler 0000-0002-2955-6761

Erken Görünüm Tarihi 20 Ağustos 2023
Yayımlanma Tarihi 25 Aralık 2023
Gönderilme Tarihi 30 Mayıs 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 5 Sayı: 2 - ARALIK 2023 SAYISI

Kaynak Göster

APA Bulut, A., & Batur Dinler, Ö. (2023). The Effect of Industry 4.0 and Artificial Intelligence on Human Resource Management. Uluslararası Doğu Anadolu Fen Mühendislik Ve Tasarım Dergisi, 5(2), 143-166. https://doi.org/10.47898/ijeased.1306881