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Human Resources Analytics and Talent Management

In: Business Analytics and Decision Making in Practice

Author

Listed:
  • Rashmi Bezalwar

    (University of Surrey)

  • Deji Sotunde

    (University of Surrey)

Abstract

This study examines the impact of AI-enabled HR analytics on organizational performance, using a quantitative design with a sample of 165 h managers and employees from two MNC Indian IT companies as research subjects. The research utilizes a self-completion questionnaire to assess different dimensions of HR practices and organizational performance, with a focus on AI-enabled HR analytics. AI-driven HR analytics are not related to organizational performance; factor analysis reveals that workforce planning and workforce forecasting, components of AI-enhanced HR practices play an important role in determining organizational performance. These results demonstrate the subtlety of AI contribution to the HR processes by highlighting its interrelation, rather than a linear causality in the performance outcomes. The research highlights the role of AI-powered HR with analytics on the enhancement of organizational efficiency working with other HR processes, however, the low regression coefficient shows other unexplored factors are contributing to the organizational performance. This work extends the debate on the contribution of AI-based HR analytics in enhancing organizational outcomes by proposing a more intensive examination of HR subsystem data.

Suggested Citation

  • Rashmi Bezalwar & Deji Sotunde, 2024. "Human Resources Analytics and Talent Management," Lecture Notes in Operations Research, in: Ali Emrouznejad & Panagiotis D. Zervopoulos & Ilhan Ozturk & Dima Jamali & John Rice (ed.), Business Analytics and Decision Making in Practice, chapter 0, pages 307-324, Springer.
    • Handle: RePEc:spr:lnopch:978-3-031-61589-4_24
    DOI: 10.1007/978-3-031-61589-4_24
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