The Role of Science Artificial Intelligence for Trend of Digital HRM
DOI:
10.29303/jppipa.v10i12.9421Published:
2024-12-21Downloads
Abstract
The science in the world is moving very fast, and technological support is an important factor in the development of this increasingly fast-paced business world. There is something very promising when technology becomes a very reliable tool, as a substitute for the use of muscle-based or human labors. One of the technologies that greatly support the performance of business organizations is the use of digital technology in human resource governance. of these digital technologies, it is still focused on the use of artificial intelligence technology for integrative HR management. This research is a literature review of several articles related to machine learning. The review was conducted from some of the recent research efforts that utilize machine learning. Furthermore, this review is derived from multiple literacies and includes an attempt at problem solving efforts that are divided into section areas from the perspective of each AI category. AI can change the way the human resource management domain functions in an organization. It is making changes in all aspects of human resource management starting from human resource planning. Enormous data is available in human resource information systems (HRIS) available in organizations.
Keywords:
Artificial intelligent, HRM, ScienceReferences
Allal-Chérif, O., Aránega, A. Y., & Sánchez, R. C. (2021). Intelligent recruitment: How to identify, select, and retain talents from around the world using artificial intelligence. Technological Forecasting and Social Change, 169, 120822. https://doi.org/10.1016/j.techfore.2021.120822
Azah, & Atah, A.-S. (2021). Manpower, AI, robot, Re-imagining the Workforce. In Industry and Higher Education (pp. 1689–1699). https://www.theseus.fi/handle/10024/508853
Bakare, K. M. (2020). Impact of Human Resources Development on Economic Growth: An Appraisal. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3675605
Barišić, A. F., Rybacka Barišić, J., & Miloloža, I. (2021). Digital Transformation: Challenges for Human Resources Management. ENTRENOVA - Enterprise Research Innovation, 7(1), 365–375. https://doi.org/10.54820/gtfn9743
Chytiri, A.-P. (2019). Human Resource Managers’ Role in the Digital Era. SPOUDAI Journal of Economic and Business, 69(1), 62–72. https://dora.dmu.ac.uk/server/api/core/bitstreams/ea2d44b0-1211-4672-9c14-b594046a1ac1/content
FraiJ, J., & László, V. (2021). A literature review: artificial intelligence impact on the recruitment process. International Journal of Engineering and Management Sciences, 6(1), 108–119. https://doi.org/10.21791/IJEMS.2021.1.10
Hadiyatno, D., Susilowati, D., Moorcy, N. H., Arrywibowo, I., & Yuliani, T. (2023). Artificial Intelligence Model for Human Capital Management. Jurnal Penelitian Pendidikan IPA, 9(10), 8280–8286. https://doi.org/10.29303/jppipa.v9i10.5083
Jia, Q., Guo, Y., Li, R., Li, Y., & Chen, Y. (2018). A conceptual artificial intelligence application framework in human resource management. Proceedings of the International Conference on Electronic Business (ICEB), 106–114. https://aisel.aisnet.org/iceb2018/91/
Kumari, P. (2021). Role of Artificial Intelligence (AI. In Marketing Role of Artificial Intelligence (AI) in Marketing View project. August. https://doi.org/https://www.researchgate.net/publication/354200837
Mendel, J. M., & Bonissone, P. P. (2021). Critical thinking about explainable AI (XAI) for rule-based fuzzy systems. IEEE Transactions on Fuzzy Systems, 29(12), 3579–3593. https://doi.org/10.1109/TFUZZ.2021.3079503
Mirete-Ferrer, P. M., Garcia-Garcia, A., Baixauli-Soler, J. S., & Prats, M. A. (2022). A review on machine learning for asset management. Risks, 10(4), 84. https://doi.org/10.3390/risks10040084
Mosca, M. (2020). Digitalization of HRM: A study of success factors and consequences in the last decade [University of Twente]. https://purl.utwente.nl/essays/82872
OECD. (2021). Artificial Intelligence, Machine Learning and Big Data in Finance: Opportunities, Challenges, and Implications for Policy Makers. OECD Business and Finance Outlook 2020 : Sustainable and Resilient Finance., 1–72.
Podgorodnichenko, N., Edgar, F., & McAndrew, I. (2020). The role of HRM in developing sustainable organizations: Contemporary challenges and contradictions. Human Resource Management Review, 30(3), 100685. https://doi.org/10.1016/j.hrmr.2019.04.001
Prakash, N., Krishna, G., & Mores, G. (2019). Digitalization of HRM practice in the present scenario. International Journal of Research in Management Studies, 4(1), 1–5. https://www.ijrms.com/olvolume4issue1/NBhanuPrakash-GandhamSriRamaKrishna-GSamuelMores-1.pdf
Qamar, Y., Agrawal, R. K., Samad, T. A., & Chiappetta Jabbour, C. J. (2021). When technology meets people: the interplay of artificial intelligence and human resource management. Journal of Enterprise Information Management, 34(5), 1339–1370. https://doi.org/10.1108/jeim-11-2020-0436
Sakka, F., El Maknouzi, M. E. H., & Sadok, H. (2022). Human resource management in the era of artificial intelligence: future HR work practices, anticipated skill set, financial and legal implications. Academy of Strategic Management Journal, 21, 1–14. https://shorturl.at/dACQ4
Sanyaolu, E., & Atsaboghena, R. (2022). Role of Artificial Intelligence in Human Resource Management: Overview of its benefits and challenges. ResearchGate, December, 1–8. https://shorturl.asia/q69R7
Siregar, H., Setiawan, W., & Dirgantari, P. D. (2020). Isu Proses Bisnis Berbasis Artificial Intelligence untuk Menyosong Era Industri 4.0. Jurnal Bisnis Strategi, 29(2), 89–100. https://doi.org/10.14710/jbs.29.2.89-100
Smids, J., Nyholm, S., & Berkers, H. (2020). Robots in the workplace: a threat to—or opportunity for—meaningful work? Philosophy & Technology, 33(3), 503–522. https://doi.org/10.1007/s13347-019-00377-4
Stone, M., Aravopoulou, E., Ekinci, Y., Evans, G., Hobbs, M., Labib, A., Laughlin, P., Machtynger, J., & Machtynger, L. (2020). Artificial intelligence (AI) in strategic marketing decision-making: a research agenda. The Bottom Line, 33(2), 183–200. https://doi.org/10.1108/BL-03-2020-0022
Strohmeier, S. (2020). Digital human resource management: A conceptual clarification. German Journal of Human Resource Management, 34(3), 345–365. https://doi.org/10.1177/2397002220921131
Subagio, H., & Sitepu, R. (2023). Reading Big Data by Machine Learning: The Used of Computer Science for Human Life. Jurnal Penelitian Pendidikan IPA, 9(10), 8588–8593. https://doi.org/10.29303/jppipa.v9i10.4752
Sugiharto, B., Simanungkalit, R. V, Siregar, I., & Andriani, M. (2023). Artificial Intelligence (AI) Architecture for Integrated Smart Digital Banking System. Jurnal Penelitian Pendidikan IPA, 9(10), 876–882. https://doi.org/10.29303/jppipa.v9i10.4645
Van Giffen, B., Herhausen, D., & Fahse, T. (2022). Overcoming the pitfalls and perils of algorithms: A classification of machine learning biases and mitigation methods. Journal of Business Research, 144, 93–106. https://doi.org/10.1016/j.jbusres.2022.01.076
Varadaraj, D. A., & Al Wadi, D. B. M. (2021). A Study on Contribution of Digital Human Resource Management towards Organizational Performance. The International Journal of Management Science and Business Administration, 7(5), 43–51. https://doi.org/10.18775/ijmsba.1849-5664-5419.2014.75.1004
Vardarlier, P. (2020). Digital transformation of human resource management: digital applications and strategic tools in HRM. Digital Business Strategies in Blockchain Ecosystems: Transformational Design and Future of Global Business, 239–264. https://doi.org/10.1007/978-3-030-29739-8_11
Vishwanath, B., & Vaddepalli, S. (2023). The Future of Work: Implications of Artificial Intelligence on Hr Practices. Journal of Propulsion Technology, 44(3), 1711–1724. https://shorturl.asia/egkOU
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. https://doi.org/10.4324/9781003377085-7
Zhang, Q. T., Li, B., & Xie, D. (2022). Alternative Data and Artificial Intelligence Techniques. Palgrave Studies in Risk and Insurance. https://doi.org/10.1007/978-3-031-11612-4
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