Balancing trust and distrust in generative AI chatbot adoption: a case study from China

Generative AI (GAI) chatbots are increasingly pivotal in transforming customer interactions across various industries, particularly in enhancing consumers’ experience and operational efficiency in e-commerce. Drawing on dual factor theory, the study examines how consumer trust and distrust beliefs in GAI chatbots influence consumer satisfaction and continued use. The study’s research framework is examined through collecting online data from Chinese consumers. The results indicate that perceived anthropomorphism, transparency, and efficiency positively influence consumers’ trust beliefs. Meanwhile, privacy concerns and emotional detachment positively influence consumers’ distrust beliefs. Consumer satisfaction and continued intention are positively influenced by trust and negatively influenced by distrust. Further, consumer satisfaction positively impacts continued intention. Finally, consumers’ IT knowledge positively moderates the relationship between consumers’ satisfaction and continued intention to use GAI chatbots. Several theoretical and practical implications reveal the need to make GAI chatbots more humanlike and responsive, as well as address consumers’ concerns to establish trust.