Exploring administrative staff’s acceptance of generative AI in Chinese vocational colleges: A UTAUT-guided thematic study

As Generative Artificial Intelligence (GenAI) technologies reshape institutional processes, higher vocational colleges are increasingly exploring their potential in administrative management. Guided by the Unified Theory of Acceptance and Use of Technology (UTAUT), this qualitative study examines how administrative personnel perceive and accept GenAI in vocational college administration. In-depth, semi-structured interviews were conducted with 16 administrative staff from three vocational colleges in Henan Province, China. Data were analyzed using ATLAS.ti-assisted thematic analysis through a hybrid deductive–inductive coding strategy. A deductive seed codebook was developed based on the four UTAUT constructs, while inductive coding captured emergent themes. To enhance analytical rigor, two coders independently analyzed five transcripts, achieving an inter-coder agreement of Cohen’s κ = 0.84. Thematic saturation was reached after the 13th interview, with no new themes emerging from the subsequent sessions. The findings largely corroborate the relevance of the four core UTAUT constructs, performance expectancy, effort expectancy, social influence, and facilitating conditions, in explaining GenAI acceptance among administrative staff. Participants recognized GenAI’s potential to improve operational efficiency, decision-making, service responsiveness, and workflow standardization. However, they also expressed concerns regarding technical complexity, resources limitations, policy ambiguity, data privacy, accountability, and job security. These findings suggest several GenAI-specific contextual factors, including governance readiness, perceived trustworthiness and controllability, institutional digital maturity, and ethical safeguards. The study provides an exploratory, context-specific application of UTAUT to vocational college administration and offers practical guidance for GenAI training, governance, and responsible implementation.