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The potential of artificial intelligence in human resource management

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The growth of Artificial Intelligence (AI) technologies is revolutionizing Human Resource (HR) practices, offering new opportunities for organizations to optimize their operations and better support for their workforce in an era defined by technological advancement. In this context, the emergence of industry 5.0 highlights human-centricity, resilience, and sustainability, promoting collaboration between humans and technology. This article conducts a bibliometric analysis to explore the intersection of AI and Human Resources Management (HRM), highlighting trends, research directions, and the evolving landscape of this thematic. Through performance analysis, social structure assessment, and thematic evolution examination, this study identifies key themes, emerging topics, and research trends. The findings underscore the transformative potential of AI in reshaping HRM and organizational dynamics, calling for more research and strategic applications of AI technologies to foster adaptive strategies and informed decision-making in the era of industry 5.0.
Rocznik
Strony
153--170
Opis fizyczny
Bibliogr. 38 poz., fig., tab.
Twórcy
  • Abdelmalek Essaadi University, Faculty of Science and Technologies, Intelligent Automation and BioMedGenomics laboratory, Morocco
  • Abdelmalek Essaadi University, Faculty of Science and Technologies, Intelligent Automation and BioMedGenomics laboratory, Morocco
Bibliografia
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  • [2] Alcalde-Bezhold, G., Alcázar-Arroyo, R., Angoso-de-Guzmán, M., Arenas, M. D., Arias-Guillén, M., Arribas-Cobo, P., Díaz-Gómez, J. M., García-Maset, R., González-Parra, E., Hernández-Marrero, D., Herrero-Calvo, J. A., Maduell, F., Molina, P., Molina-Núñez, M., Otero-González, A., Pascual, J., Pereira-García, M., Pérez-García, R., Dolores Del Pino Y Pino, M., … De Sequera-Ortiz, P. (2021). Hemodialysis centers guide 2020. Nefrología (English Edition), 41, 1-77. https://doi.org/10.1016/S2013-2514(22)00042-6
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  • [5] Bouhsaien, L. (2024, May 24). Database BA. https://drive.google.com/drive/folders/1sr6nQoMI0Tyy5VEuK1vcMELVpMhlqAzk
  • [6] Bouhsaien, L., & Azmani, A. (2024). Burnout: A pervasive challenge threatening workplace well-being and organizational success. International Journal of Professional Business Review, 9(4), e04597. https://doi.org/10.26668/businessreview/2024.v9i4.4597
  • [7] Budhwar, P., Malik, A., De Silva, M. T. 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. https://doi.org/10.1080/09585192.2022.2035161
  • [8] Choudhury, P. (Raj), Foroughi, C., & Larson, B. (2021). Work‐from‐anywhere: The productivity effects of geographic flexibility. Strategic Management Journal, 42(4), 655–683. https://doi.org/10.1002/smj.3251
  • [9] 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. https://doi.org/10.1016/j.hrmr.2022.100899
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  • [11] Deepa, R., Sekar, S., Malik, A., Kumar, J., & Attri, R. (2024). Impact of AI-focussed technologies on social and technical competencies for HR managers – A systematic review and research agenda. Technological Forecasting and Social Change, 202, 123301. https://doi.org/10.1016/j.techfore.2024.123301
  • [12] Derviş, H. (2020). Bibliometric analysis using Bibliometrix an R Package. Journal of Scientometric Research, 8(3), 156–160. https://doi.org/10.5530/jscires.8.3.32
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  • [14] 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. https://doi.org/10.1016/j.jbusres.2021.04.070
  • [15] Fernandes França, T. J., São Mamede, H., Pereira Barroso, J. M., & Pereira Duarte Dos Santos, V. M. (2023). Artificial intelligence applied to potential assessment and talent identification in an organisational context. Heliyon, 9(4), e14694. https://doi.org/10.1016/j.heliyon.2023.e14694
  • [16] Foroudi, P., Akarsu, T. N., Marvi, R., & Balakrishnan, J. (2021). Intellectual evolution of social innovation: A bibliometric analysis and avenues for future research trends. Industrial Marketing Management, 93, 446–465. https://doi.org/10.1016/j.indmarman.2020.03.026
  • [17] Fosso Wamba, S., Bawack, R. E., Guthrie, C., Queiroz, M. M., & Carillo, K. D. A. (2021). Are we preparing for a good AI society? A bibliometric review and research agenda. Technological Forecasting and Social Change, 164, 120482. https://doi.org/10.1016/j.techfore.2020.120482
  • [18] Galán Hernández, J. J., Marín Díaz, G., & Galdón Salvador, J. L. (2024). Artificial Intelligence applied to human resources management: A bibliometric analysis. In Á. Rocha, C. Ferrás, J. Hochstetter Diez, & M. Diéguez Rebolledo (Eds.), Information Technology and Systems (Vol. 932, pp. 269–277). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-54235-0_25
  • [19] Garg, S., Sinha, S., Kar, A. K., & Mani, M. (2022). A review of machine learning applications in human resource management. International Journal of Productivity and Performance Management, 71(5), 1590–1610. https://doi.org/10.1108/IJPPM-08-2020-0427
  • [20] Gong, X., De Pessemier, T., Martens, L., & Joseph, W. (2019). Energy- and labor-aware flexible job shop scheduling under dynamic electricity pricing: A many-objective optimization investigation. Journal of Cleaner Production, 209, 1078–1094. https://doi.org/10.1016/j.jclepro.2018.10.289
  • [21] Guenole, N., & Feinzig, S. (2018). The business case for AI in HR. IBM Smarter Workforce Institute.
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  • [23] Kong, H., Yuan, Y., Baruch, Y., Bu, N., Jiang, X., & 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
  • [24] Laviola, F., Cucari, N., & Novic, H. (2024). Artificial intelligence in personal development from cradle to grave: A comprehensive review of HRD literature. Sinergie Italian Journal of Management, 42(1), 121–163. https://doi.org/10.7433/s123.2024.06
  • [25] Moral-Muñoz, J. A., Herrera-Viedma, E., Santisteban-Espejo, A., & Cobo, M. J. (2020). Software tools for conducting bibliometric analysis in science: An up-to-date review. El Profesional de La Información, 29(1). https://doi.org/10.3145/epi.2020.ene.03
  • [26] Morgan, N., & Pritchard, A. (2019). Gender matters in hospitality. International Journal of Hospitality Management, 76, 38–44. https://doi.org/10.1016/j.ijhm.2018.06.008
  • [27] Mumu, J. R., Tahmid, T., & Azad, Md. A. K. (2021). Job satisfaction and intention to quit: A bibliometric review of work-family conflict and research agenda. Applied Nursing Research, 59, 151334. https://doi.org/10.1016/j.apnr.2020.151334
  • [28] Ortega-Cotto, N., Bhuyan, R., LaGrand, C., & Caldwell, C. (2022). Strategic human resource management – distinguishing between the urgent and the important. Business and Management Research, 12(1), 1. https://doi.org/10.5430/bmr.v12n1p1
  • [29] 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. https://doi.org/10.1080/08839514.2022.2145631
  • [30] Pedraja-Rejas, L., Rodríguez-Ponce, E., & Muñoz-Fritis, C. (2022). Human resource management and performance in Ibero-America: Bibliometric analysis of scientific production. Cuadernos de Gestión, 22(2), 123–137. https://doi.org/10.5295/cdg.211569lp
  • [31] Pejic-Bach, M., Bertoncel, T., Meško, M., & Krstić, Ž. (2020). Text mining of industry 4.0 job advertisements. International Journal of Information Management, 50, 416–431. https://doi.org/10.1016/j.ijinfomgt.2019.07.014
  • [32] Ryu, J., Seo, J., Jebelli, H., & Lee, S. (2019). Automated action recognition using an accelerometer-embedded wristband-type activity Tracker. Journal of Construction Engineering and Management, 145(1), 04018114. https://doi.org/10.1061/(ASCE)CO.1943-7862.0001579
  • [33] 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. https://doi.org/10.1177/0008125619867910
  • [34] Tong, S., Jia, N., Luo, X., & Fang, Z. (2021). The Janus face of Artificial Intelligence feedback: Deployment versus disclosure effects on employee performance. Strategic Management Journal, 42(9), 1600–1631. https://doi.org/10.1002/smj.3322
  • [35] Torres-Salazar, E., Cruzado-Yesquén, K., Alvarez-Vasquez, H., Saavedra-Ruíz, J., Castañeda-Hipólito, M., Gastiaburú-Morales, S., Barandiarán-Gamarra, J., Vásquez-Coronado, M., & Alviz-Meza, A. (2024). A bibliometric study with statistical patterns of industry 4.0 on business management in the decade. Journal of Physics: Conference Series, 2726(1), 012009. https://doi.org/10.1088/1742-6596/2726/1/012009
  • [36] Toumia, O., & Zouari, F. (2024). Artificial Intelligence and venture capital decision-making: In R. Sharma, K. Mehta, & P. Yu (Eds.), Advances in Business Strategy and Competitive Advantage (pp. 16–38). IGI Global. https://doi.org/10.4018/979-8-3693-1326-8.ch002
  • [37] Vlačić, B., Corbo, L., Costa E Silva, S., & Dabić, M. (2021). The evolving role of Artificial Intelligence in marketing: A review and research agenda. Journal of Business Research, 128, 187–203. https://doi.org/10.1016/j.jbusres.2021.01.055
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Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki (2025).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-22040b6b-fb5c-4471-b759-fed581dc529d
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