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 < 0.001), perceived behavioral control (β = -0.371, p < 0.001), attitude (β = -0.339, p < 0.001), and subjective norms (β = -0.451, p < 0.001), and it was also associated with behavioral intention through multiple indirect pathways. Multi-group analysis showed that the association between perceived ease of use and perceived usefulness was stronger among professionals with low AI familiarity, while the remaining paths remained stable across groups. AI adoption intention in hospital HRM appears to involve more than rational evaluations of usefulness and ease of use. Emotional states, such as technology anxiety, also play a role. Reducing technology anxiety and improving ease of use for users with lower AI familiarity are therefore important steps for promoting AI adoption intention. These findings highlight the value of addressing emotional factors alongside cognitive beliefs when introducing AI tools in healthcare organizations.