Integrating technology anxiety into the TPB-TAM framework to examine AI adoption intention in hospital HRM: a study of Chinese healthcare professionals

Artificial intelligence (AI) can empower healthcare professionals to make data-driven decisions and streamline administrative tasks in hospital human resource management (HRM). However, it is vital to understand their perceptions towards AI for seamless implementation in practice. Therefore, the study aimed to assess the role of technology anxiety within an integrated framework combining the Technology Acceptance Model (TAM) and the Theory of Planned Behavior (TPB) to better understand adoption intentions in this high-stakes context.

A cross-sectional survey was conducted among 547 healthcare professionals working in hospitals across China. Data were analyzed using structural equation modeling, including confirmatory factor analysis, path analysis, and bootstrap mediation testing. Multi-group structural equation modeling was also used to compare healthcare professionals with different levels of AI familiarity.

The integrated model explained 49.4% of the variance in behavioral intention, and all twelve hypothesized paths were statistically significant. Technology anxiety was negatively associated with perceived ease of use (β = -0.553, p