How personal anticipations and perceived gratifications influence continuous use intention toward AI-driven chatbots? Moderating roles of perceived innovativeness and active involvement

In recent years, AI-driven chatbots have evolved into a transformative technological paradigm, deeply embedded in domains including retail, customer service, healthcare, and education. This study endeavors to unveil the psychological and behavioral mechanisms by which AI-driven chatbots influence users' continuous use intention. Leveraging an integrated theoretical framework, the study employs a partial least squares-structural equation modeling (PLS-SEM) approach. A valid sample comprising 581 AI-driven chatbot users was amassed via an online research methodology, meticulously scrutinizing their continuous use intention. Obtained findings substantiate a positive association between personal anticipations and perceived innovativeness, alongside affirming the positive correlation between perceived gratifications and active involvement. Both perceived innovativeness and active involvement positively influence continuous use intention toward AI-driven chatbots. These findings not only advance the understanding of user continuous use intention toward AI-driven chatbots from a novel theoretical perspective but also provide practitioners with pragmatic approaches to strategically develop AI-driven chatbots and sustain user engagement in the contemporary human-AI interaction environment.