Adoption of HR analytics for future-proof decision making: role of attitude toward artificial intelligence as a moderator
International Journal of Organizational Analysis
ISSN: 1934-8835
Article publication date: 6 September 2024
Abstract
Purpose
This study aims to investigate the relationship between the adoption of human resource (HR) analytics and managerial decision-making (DM), with attitude toward artificial intelligence (AI) as a potential moderator.
Design/methodology/approach
This study was conducted in three phases. In Phase I, a comprehensive scale to measure the “Adoption of HR analytics” was conceptualized and developed. In Phase II, the scale was validated and operationalized. Finally, in Phase III, a survey of 377 managers was conducted, and a conceptual model was validated using structural equation modeling.
Findings
This study reveals that the adoption of HR analytics (HRA) and a positive attitude toward AI significantly influence DM. The findings suggest that the structural factors play the most important role in the adoption of HRA, followed by individual factors, value and system support.
Practical implications
These findings hold valuable implications for managers seeking integration of HRA and AI within organizational systems and processes. HR practitioners can evaluate their organization’s readiness for HRA, enabling them to build a future-proof workforce with the necessary skills. It can help managers make the adoption of AI-enabled HRA a reality. The study also helps to remove inhibitions and concerns of HR managers and employees related to AI.
Originality/value
This paper addresses the methodological, practical knowledge and evidence gap in the area of adoption of HRA and DM. It sheds light on the “future of work” in HR, highlighting a potential shift toward human-AI collaboration.
Keywords
Citation
Arora, S., Chaudhary, P. and Singh, R.K. (2024), "Adoption of HR analytics for future-proof decision making: role of attitude toward artificial intelligence as a moderator", International Journal of Organizational Analysis, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJOA-03-2024-4392
Publisher
:Emerald Publishing Limited
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