The use of chatbots has rapidly increased worldwide. However, research exploring the factors that influence user satisfaction and continuance intention, particularly in the banking sector, remains limited. This study aims to address this gap by examining the roles of confirmation, anthropomorphism, virtual flow experience (VFE) and trust in artificial intelligence (AI) within the expectation-confirmation model framework.
A survey questionnaire was designed and administered to a sample of 437 Indians, recruited through purposive and snowball sampling. partial least squares-structural equation modeling was employed to verify the research model.
The findings reveal that confirmation and anthropomorphism significantly influence user satisfaction, which in turn drives continuance intention. Contrary to expectations, VFE did not show a significant effect on user satisfaction with banking chatbots. This study further establishes that trust in AI moderates the relationship between satisfaction and continuance intention.
By identifying the key antecedents of satisfaction and continuance intention, this research enriches the existing literature on chatbots and offers actionable insights for banks to enhance user continuance intention to use chatbots. In addition, the study highlights the potential of VFE as a critical area for future exploration to optimize chatbot success.
