Exploring the predictors of chatbot service quality

The ever-growing applications of AI-enabled agents in customer relationship management require a comprehensive understanding of customers’ perception of the services provided by chatbots, which is an underexplored research area so far. To fill this gap, this study draws on the literature on human-chatbot interaction to identify and test the main determinants of customers’ perception of the quality of chatbot services. To test our research model, data was collected from 529 re-spondents who had interacted with chatbots as part of their shopping experience and analysed using partial least squares-structural equation modelling. The analy-sis confirmed that a positive evaluation of service quality is predicted by service convenience, competence and functional congruity. Our study contributes to the literature on customer-chatbot interactions by providing insights into service qual-ity perception by customers in the context of chatbot services.