Factors Influencing Citizens’ Continuance Intention to Use Government Chatbots: An Empirical Study Based on Diffusion of Innovation Theory

Government chatbots are increasingly deployed to support digital public service delivery, yet their continued value depends on whether citizens with prior experience intend to use them again when a relevant public-service need arises. Drawing on Diffusion of Innovations (DOI) theory, this study examines factors associated with citizens’ continuance intention to use government chatbots by integrating five DOI constructs—relative advantage, compatibility, perceived complexity, trialability, and observability—with responsiveness and anthropomorphic design. Data were collected from 358 citizens with prior experience using government chatbots and analyzed using PLS-SEM. Responsiveness showed the strongest association with continuance intention, followed by anthropomorphic design and relative advantage, while perceived complexity was negatively associated. Trialability showed a weaker but statistically significant positive association, whereas compatibility and observability were not significantly associated. The model explains 62.4% of the variance in continuance intention. The findings suggest that reuse intention is more strongly associated with interaction quality and perceived functional benefits than with contextual fit or visibility of outcomes. Continuance intention refers to future-use intention reported by citizens with prior chatbot experience and does not represent observed continued use over time. Theoretically, the study extends DOI to a post-adoption government-chatbot context, while practically highlighting responsiveness and anthropomorphic design.