Abstract:

[Purpose/Significance] With the rapid integration of generative artificial intelligence into library services, user trust in information has begun to exhibit a new pattern characterized by high usage, low certainty, and increased reliance on institutional guarantees. Existing studies on online credibility, artificial intelligence generated content (AIGC) applications and library innovation have mostly examined either technical performance, information literacy, or governance issues in isolation. Few have systematically analyzed how specific AIGC features, user capabilities and the institutional environment of libraries jointly shape multi dimensional user trust. This study focuses on AIGC supported services in public and academic libraries and constructs a comprehensive analytical framework linking technological signals, user ability and library based institutional mediation to the formation of cognitive, emotional and behavioral trust. The paper contributes to the refinement of trust theory in digital information environments by providing empirical evidence from a large-scale sample in China. It also offers actionable insights for libraries seeking to deploy AIGC while maintaining or enhancing their role as trusted public knowledge institutions. [Method/Process] The study is grounded in classic research on cognitive authority and online credibility, and combined with recent work on AIGC, knowledge services, information literacy and library governance. It conceptualizes user trust as a three dimensional construct comprising cognitive, emotional and behavioral components. AIGC related technological features are operationalized along three axes: perceived content quality, generation transparency and interactivity. User capability is measured through standardized digital literacy tests and indicators of professional background, while the library environment is captured by the presence of institutional arrangements such as usage guidelines, staff verification, result labelling and risk reminders. Data were collected through a large-scale questionnaire survey in ten public and academic libraries in Henan Province, yielding 2 347 valid responses. After data cleaning and reliability and validity checks, the study employed a combination of structural equation modelling, two stage least squares estimation, threshold regression, spatial autoregressive models, dynamic panel system GMM estimation, quantile regression and finite mixture models. This sequential strategy allowed for simultaneous identification of structural paths, endogenous relationships, non linear and moderating effects, spatial spillovers and temporal dependence, as well as heterogeneous trust formation patterns across user groups. [Results/Conclusions] The findings confirm that user trust in AIGC enabled library services is best understood as a three dimensional structure, in which cognitive trust influences emotional trust, and both jointly shape behavioral trust. Content quality and generation transparency exert strong and robust positive effects on cognitive trust, while interactivity mainly enhances emotional trust and indirectly affects behavioral intentions. Digital literacy and professional background introduce clear threshold and amplification effects: when user capability is below certain levels, improvements in content quality and transparency have limited impact on trust, but above these thresholds the marginal effects increase markedly. Library level institutional arrangements, including human review, explicit labelling and standardized usage rules, not only raise overall trust levels, but also significantly strengthen the effects of technological signals, sometimes to a degree comparable with individual level capability factors. Spatial and dynamic analyses show that trust exhibits both spillover and path dependence: practices in one library can influence neighbouring institutions through user mobility and word of mouth, and positive or negative experiences accumulate into longer term evaluations. The study suggests that libraries should treat trust building as a core design objective when introducing AIGC, embed transparency and quality signals into interfaces and metadata, establish robust verification and correction workflows, and provide differentiated services for users with different literacy levels and professional backgrounds. The limitations include the concentration of data in one province and the use of primarily macro-level instruments for identifying causation. Future research could extend the framework to cross regional and cross type libraries, compare specific functional scenarios such as reference services and reading promotion, and further integrate trust analysis with broader issues of library governance, literacy education and responsibility allocation in AIGC ecosystems.

Key words: AIGC, information trust, library services, technological signals, digital literacy, institutional intermediation