This study examines the impact of AI agent service quality on users’ continuance intention by integrating the Information Systems Success Model (ISSM), the Value-based Adoption Model (VAM), and the Expectation–Confirmation Model (ECM). Based on the proposed research model, an empirical analysis was conducted using structural equation modeling. The results indicate that service quality dimensions significantly influence perceived benefits, perceived value, and user satisfaction, which in turn positively affect continuance intention. In particular, user perception variables play a critical mediating role in post-adoption behavior. These findings suggest that AI agent services should shift from a technology-centered approach toward a user experience–oriented strategy. This study contributes to the literature by extending traditional information systems models to the context of AI agent services and provides practical implications for the design and management of AI-based services.
Park et al. (Tue,) studied this question.