Should the chatbot “save itself” or “be helped by others”? The influence of service recovery types on consumer perceptions of recovery satisfaction

• This study divides the service recovery types into chatbot self-recovery and human-involved recovery. • Based on social response theory, this study expands the exploration of the causes of consumer service recovery satisfaction. • This study introduced the level of chatbot intelligence as a moderating variable into the research of chatbot service failure. The application of artificial intelligence is considered essential to adapt to a new cycle of industrial transformation and technological advancements in many fields and industries. The extensive use of artificial intelligence technology is expected to improve the level and quality of services provided by companies adopting these methods. In this study, we propose a novel approach to self-recovery by chatbot systems after service failures based on social response theory. Moreover, we explore differences in consumer perceptions of different service recovery types and their impact on recovery satisfaction, and discusses whether the intelligence of the computational agent also has an effect. We present the results of three scenario-based experiments, which demonstrate the positive effect of chatbot self-recovery on consumer satisfaction, and show the mediating paths of service recovery types in terms of perceived functional value and privacy risks as well as the boundary condition of the level of robot intelligence. This work expands the range of applications of chatbots in the service industry and provides a new framework for the governance of artificial intelligence.