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Artificial Intelligence Models and Employee Lifecycle Management: A Systematic Literature Review

Author

Listed:
  • Nosratabadi Saeed

    (Doctoral School of Economic and Regional Sciences, Hungarian University of Agriculture and Life Sciences, Gödöllő, Hungary)

  • Zahed Roya Khayer

    (Department of Management, Faculty of Administrative Sciences and Economics, University of Isfahan, Isfahan, Iran)

  • Ponkratov Vadim Vitalievich

    (Department of Public Finance, Financial University under the Government of the Russian Federation, Moscow, Russian Federation)

  • Kostyrin Evgeniy Vyacheslavovich

    (Department of Finances, Bauman Moscow State Technical University, Moscow, Russian Federation)

Abstract

Background and purpose: The use of artificial intelligence (AI) models for data-driven decision-making in different stages of employee lifecycle (EL) management is increasing. However, there is no comprehensive study that addresses contributions of AI in EL management. Therefore, the main goal of this study was to address this theoretical gap and determine the contribution of AI models to EL management.

Suggested Citation

  • Nosratabadi Saeed & Zahed Roya Khayer & Ponkratov Vadim Vitalievich & Kostyrin Evgeniy Vyacheslavovich, 2022. "Artificial Intelligence Models and Employee Lifecycle Management: A Systematic Literature Review," Organizacija, Sciendo, vol. 55(3), pages 181-198, August.
    • Handle: RePEc:vrs:organi:v:55:y:2022:i:3:p:181-198:n:1
    DOI: 10.2478/orga-2022-0012
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    References listed on IDEAS

    as
    1. Nosratabadi, Saeed & Mosavi, Amir & Duan, Puhong & Ghamisi, Pedram & Filip, Ferdinand & Band, Shahab S. & Reuter, Uwe & Gama, Joao & Gandomi, Amir H., 2020. "Data science in economics: comprehensive review of advanced machine learning and deep learning methods," MetaArXiv haf2v, Center for Open Science.
    2. Saeed Nosratabadi & Sina Ardabili & Zoltan Lakner & Csaba Mako & Amir Mosavi, 2021. "Prediction of Food Production Using Machine Learning Algorithms of Multilayer Perceptron and ANFIS," Agriculture, MDPI, vol. 11(5), pages 1-13, May.
    3. Saeed Nosratabadi & Sina Ardabili & Zoltan Lakner & Csaba Mako & Amir Mosavi, 2021. "Prediction of Food Production Using Machine Learning Algorithms of Multilayer Perceptron and ANFIS," Papers 2104.14286, arXiv.org.
    4. Olan, Femi & Ogiemwonyi Arakpogun, Emmanuel & Suklan, Jana & Nakpodia, Franklin & Damij, Nadja & Jayawickrama, Uchitha, 2022. "Artificial intelligence and knowledge sharing: Contributing factors to organizational performance," Journal of Business Research, Elsevier, vol. 145(C), pages 605-615.
    Full references (including those not matched with items on IDEAS)

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