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Harnessing the Power of Algorithmic Human Resource Management and Human Resource Strategic Decision-Making for Achieving Organizational Success: An Empirical Analysis

Author

Listed:
  • Mahmoud Abdulhadi Alabdali

    (Business Administration Department, Faculty of Economics and Administration, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Sami A. Khan

    (Department of Human Resource Management, Faculty of Economics and Administration, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Muhammad Zafar Yaqub

    (Business Administration Department, Faculty of Economics and Administration, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Mohammed Awad Alshahrani

    (Business Administration Department, Faculty of Economics and Administration, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

Abstract

This study examines the role of using algorithmic human resource management (HRM) to make strategic decisions concerning firms’ human resource (HR) activities. This study develops a scale to measure algorithmic HRM usage in its first phase. In the second phase, it is found that algorithmic HRM usage significantly impacts strategic HR decision-making, which helps and enables firms to create a competitive advantage. Utilizing the authors’ LinkedIn profiles, 234 participants were included in the fieldwork. Collected data were analyzed by applying partial least squares structure equation modeling (PLS-SEM). The mediating roles of HR strategic decision-making and HR digital maturity as moderators in enabling the impact of algorithmic HRM on the firm’s competitive advantage have been corroborated. This study finds a strong relationship between algorithmic HRM usage and competitive advantage, a significant relationship between algorithmic HRM usage and strategic HR decision-making, and a significant relationship between strategic HR decision-making and competitive advantage. The moderating role of HR digital maturity was insignificant in this research, paving the way for future research. This research, the model, and its findings contribute to the theory and implicate the practicality of algorithmic HRM. It is one of few papers addressing algorithmic HRM usage in a transitioning economy like Saudi Arabia.

Suggested Citation

  • Mahmoud Abdulhadi Alabdali & Sami A. Khan & Muhammad Zafar Yaqub & Mohammed Awad Alshahrani, 2024. "Harnessing the Power of Algorithmic Human Resource Management and Human Resource Strategic Decision-Making for Achieving Organizational Success: An Empirical Analysis," Sustainability, MDPI, vol. 16(11), pages 1-30, June.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:11:p:4854-:d:1410099
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    References listed on IDEAS

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