Employee’s Intentions to Use HR Analytics: Technology Acceptance Model with Job Relevance and Self-Efficacy

Abstract

The current examination aims to measure the determinants of adoption intentions of employees in the context of human resource analytics. In this view, a technology acceptance model was applied with four additional constructs namely, social influence, job relevance, self-efficacy and perceived enjoyment. The responses were collected from 345 service sector employees. Keeping in view the proposed relationships, partial least square structural equation modelling (PLS-SEM) was employed. It is found that perceived usefulness is significantly influenced by social influence and job relevance. However, the perceived enjoyment did not find significant with perceived ease of use. The present study has implications for theory, managers and international human resource managers. The novel contribution of this study is that it integrates job relevance, self-efficacy, social influence and perceived enjoyment to measure the adoption intentions of HR analytics.