Antecedents and consequences of chatbot initial trust

Abstract

Purpose Artificial intelligence chatbots are shifting the nature of online services by revolutionizing the interactions of service providers with consumers. Thus, this study aims to explore the antecedents (e.g. compatibility, perceived ease of use, performance expectancy and social influence) and consequences (e.g. chatbot usage intention and customer engagement) of chatbot initial trust. Design/methodology/approach A sample of 184 responses was collected in Lebanon using a questionnaire and analyzed using structural equation modeling (SEM) by AMOS 24. Findings The results revealed that except for performance expectancy, all the other three factors (compatibility, perceived ease of use and social influence) significantly boost customers’ initial trust toward chatbots. Further, initial trust in chatbots enhances the intention to use chatbots and encourages customer engagement. Research limitations/implications The study provides insights into some variables influencing initial chatbot trust. Future studies could extend the model by adding other variables (e.g. customer experience and attitude), in addition to exploring the dark side of artificial intelligence chatbots. Practical implications This study suggests key insights for marketing managers on how to build chatbot initial trust, which, in turn, will lead to an increase in customers’ interactions with the brand. Originality/value The current study marks substantial contributions to the artificial intelligence marketing literature by proposing and testing a novel conceptual model that examines for the first time the factors that impact chatbot initial trust and the key outcomes of the latter.