The Impact of Service Quality of Generative AI Chatbots on Intention to Continue Using

Abstract

Generative artificial intelligence (AI) has transformed chatbot interactions with users. This study explores how service quality in generative AI chatbots affects users' intention to continue using. This study examines how information appropriateness, security, interactivity, and reliability affect perceived usefulness, satisfaction, and usage intention. In empirical research, statistical analysis of 295 valid survey responses show that information appropriateness, interactivity, and service reliability significantly affect perceived usefulness, while interactivity and service reliability also impact user satisfaction. Furthermore, perceived usefulness and satisfaction are key mediating variables in shaping user attitudes towards generative AI chatbots, which in turn affect their continuance intention. The empirical results highlight the importance of information appropriateness, interactivity, and service reliability in enhancing both perceived usefulness and satisfaction. Moreover, these findings provide valuable insights and empirical evidence for academic and practical applications in generative AI chatbots.