AI-DRIVEN HRM AND EMPLOYEE INNOVATIVE BEHAVIOR THROUGH WORK ENGAGEMENT AND CREATIVE SELF-EFFICACY

Yixuan Li; Arti Pandey

doi:10.29040/ijebar.v10i2.20109

AI-DRIVEN HRM AND EMPLOYEE INNOVATIVE BEHAVIOR THROUGH WORK ENGAGEMENT AND CREATIVE SELF-EFFICACY

Authors

Yixuan Li International College, Rajamangala University of Technology Krungthep, Thailand
Arti Pandey International College, Rajamangala University of Technology Krungthep, Thailand

DOI:

https://doi.org/10.29040/ijebar.v10i2.20109

Abstract

Abstract− The rapid advancement of artificial intelligence technology has accelerated the popularization of AI- Driven HRM among modern corporate organizations. Current academic literature predominantly concentrates on the efficiency advantages brought by this new-type human resource management model. Few scholarly works have further discussed how it influences employee Innovative behavior from the perspective of individual internal psychological mechanisms. Grounding on Self-Determination Theory (SDT), this study carries out quantitative questionnaire research targeting staff members from five Internet enterprises located in Zhengzhou City. The empirical results generated by PLS-SEM statistical analysis demonstrate that AI- Driven HRM can positively predict employee adaptability and employee Innovative behavior in the workplace, and adaptability presents a prominent mediating effect between the above two research variables. This research enriches the practical application scenarios of Self-Determination Theory in the intelligent human resource management field. It also offers feasible empirical references for enterprises to optimize internal innovative performance via the implementation of AI- Driven HRM.

Keywords: AI-Driven HRM; Employee Innovative Behavior; Work Engagement; Creative Self-Efficacy; Adaptability

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Published

2026-06-21

How to Cite

Li, Y., & Pandey, A. (2026). AI-DRIVEN HRM AND EMPLOYEE INNOVATIVE BEHAVIOR THROUGH WORK ENGAGEMENT AND CREATIVE SELF-EFFICACY. International Journal of Economics, Business and Accounting Research (IJEBAR), 10(2). https://doi.org/10.29040/ijebar.v10i2.20109

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Issue

Vol. 10 No. 2 (2026): IJEBAR: Vol. 10, Issue 2, June 2026

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Articles

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