Author
Listed:
- Meenal Arora
- Anshika Prakash
- Amit Mittal
- Swati Singh
Abstract
Purpose - This study aimed to evaluate the factors that determine an individual's decision to adopt human resources (HR) analytics. This study attempts to extend Unified Theory of Acceptance and Use of Technology - 2 (UTAUT2) to identify the lag rate in adoption. Design/methodology/approach - Responses were obtained from 387 HR employees of the Banking Financial Services and Insurance (BFSI) sector in metropolitan cities of India through nonprobabilistic purposive sampling. The analysis was performed through hierarchical regression, structural equation modeling and moderation of resistance to change. Findings - The results suggest that performance expectancy, hedonic motivation and data availability are endorsed by proponents of the intention to adopt HR analytics. In contrast, effort expectancy, social influence, quantitative self-efficacy and habits did not influence behavioral intention (BI). Additionally, the actual use behavior (UB) of HR analytics was determined by BI and facilitating conditions. Furthermore, the moderating effect of resistance to change is explored. Practical implications - This study makes a significant contribution to the literature on the adoption of HR analytics. By appropriately concentrating on the adoption intention of HR analytics, organizations can intensify healthy employee relationships, thus encouraging the actual usage of HR analytics. Originality/value - This study formulates a conceptual framework for the adoption of HR analytics that can be used by top management to formulate strategies for the implementation of HR analytics. Moreover, this study aimed to expand UTAUT2, emphasizing the concept of data availability and quantitative self-efficacy and examining the moderating role of resistance to change in the relationship between BI and UB.
Suggested Citation
Meenal Arora & Anshika Prakash & Amit Mittal & Swati Singh, 2022.
"Moderating role of resistance to change in the actual adoption of HR analytics in the Indian banking and financial services industry,"
Evidence-based HRM, Emerald Group Publishing Limited, vol. 11(3), pages 253-270, September.
Handle:
RePEc:eme:ebhrmp:ebhrm-12-2021-0249
DOI: 10.1108/EBHRM-12-2021-0249
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