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Purpose The purpose of this study is to investigate the influence of AI chatbots on consumer behavior in e-commerce, specifically focusing on how dialogic chatbot communication affects consumers' willingness to accept chatbot decisions. The study aims to uncover the underlying factors and processes driving consumers' intention to adopt AI chatbot decisions, utilizing social exchange theory (SET) as a theoretical framework. Design/methodology/approach This research employs a quantitative approach, utilizing survey responses from 445 respondents. The study develops a research model based on SET principles to explore the relationship between dialogic chatbot communication, AI-tech trust and intention to adopt chatbot decisions. The proposed research model was analyzed using the structural equation modeling technique. Findings The findings of the study indicate significant relationships between dialogic chatbot communication conversational tone and responsiveness, AI-tech trust and intention to adopt chatbot decisions. Specifically, dialogic chatbot communication conversational tone and responsiveness are found to positively influence AI-tech trust, which in turn positively affects consumers' intention to adopt chatbot decisions. Additionally, the study reveals the moderation role of perceived self-threat, which weakens the link between AI-tech trust and intention to adopt chatbot decisions. Originality/value This study contributes to the existing literature by offering insights into the impact of AI chatbots on consumer behavior in e-commerce environments, particularly in the context of Chinese consumers. By employing SET as a theoretical framework, the study provides a novel perspective on the underlying mechanisms driving consumers' willingness to accept AI chatbot decisions. Furthermore, the examination of perceived self-threat as a moderating factor adds originality to the research, offering a nuanced understanding of the dynamics involved in AI–chatbot interactions.
Zhang et al. (Thu,) studied this question.