Abstract:

[Purpose/Significance] Artificial intelligence is profoundly transforming library services worldwide, making it essential to understand the factors influencing librarians' AI adoption intentions for promoting smart library development. Unlike previous studies that primarily focused on general technology adoption in commercial settings, this research specifically targets academic librarians in Chinese universities who face unique professional challenges and institutional constraints in the digital transformation era. This study aims to identify key determinants of AI adoption intention among academic librarians, providing theoretical foundations and practical guidance for optimizing library AI service systems. The research contributes to the existing literature by constructing an integrated framework that combines individual-level perceptions with organizational and environmental factors to explain technology adoption behavior in the academic library context. [Method/Process] Drawing upon the Technology Acceptance Model (TAM) and Technology-Organization-Environment (TOE) framework, this study constructs an integrated theoretical model encompassing three dimensions: individual perceptions (perceived usefulness and perceived ease of use), organizational factors (organizational readiness and management support), and environmental factors (external environment). Six research hypotheses were proposed based on the theoretical framework. A questionnaire survey was conducted among academic librarians from various types of higher education institutions across 12 provinces in China during November 2025. A total of 177 valid responses were collected from research universities, teaching-oriented universities, and vocational colleges, with an effective response rate of 84.7%. The measurement items were adapted from validated scales and underwent rigorous translation and back-translation procedures. Partial Least Squares Structural Equation Modeling (PLS-SEM) was employed for measurement model assessment, structural model evaluation, hypothesis testing, and mediation effect analysis. [Results/Conclusions] The findings reveal that perceived usefulness exerts the strongest influence on AI adoption intention (β=0.447, p<0.001), followed by the external environment (β=0.354, p<0.001) and perceived ease of use (β=0.234, p<0.001). Contrary to theoretical expectations, organizational readiness (β=-0.099, p=0.075) and management support (β=0.034, p=0.593) showed no significant effects on adoption intention. The mediation analysis demonstrates that perceived ease of use influences adoption intention both directly (β=0.234) and indirectly through perceived usefulness (β=0.205, t=5.450, p<0.001), with the indirect effect accounting for 46.7% of the total effect. The integrated model explains 62.6% of variance in adoption intention, demonstrating substantial explanatory power. These findings suggest that during the early stage of AI technology adoption in Chinese academic libraries, individual-level perceptions and external competitive pressures predominate over organizational factors. This pattern may be attributed to the fact that librarians currently access AI technologies primarily through personal exploration using publicly available tools rather than through organizational deployment. The study provides differentiated practical recommendations for universities at different development stages and suggests future research directions including longitudinal designs and cross-cultural comparisons.

Key words: artificial intelligence, technology adoption, academic libraries, technology acceptance model, TOE framework