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How AI chatbots shape satisfactory experiences: A combined perspective of competence expansion and emotional extension

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  • Hao, Riyan
  • Li, Chunqing

Abstract

To explore the formation mechanism of consumers' experiences with AI chatbots, this study, grounded in the assemblage theory, focuses on the centrality of “interaction.” We selected AI chatbot conversational quality as the antecedent, with perceived chatbot competence/warmth, consumer creative self-efficacy, and rapport as mediators. Structural equation modeling and fuzzy-set qualitative comparative analysis (fsQCA) set qualitative comparative analysis were employed to test the theoretical model. The research results indicate that AI chatbot conversation quality and its various dimensions positively promote consumers' experiences with AI chatbots. The competence expansion path represented by “perceived competence - creative self-efficacy” and the emotional extension path represented by “perceived warmth - rapport” each play a chain mediation role in this process. The results of fsQCA support these findings and identify different antecedent configurations for enhancing consumers' experiences with AI chatbots. Moreover, they demonstrate the significant role of emotional factors in shaping a satisfying consumers' experience with AI chatbots over both short and long-time spans. The conclusions offer practical guidance for improving chatbot services and advancing human-chatbot interaction.

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  • Hao, Riyan & Li, Chunqing, 2025. "How AI chatbots shape satisfactory experiences: A combined perspective of competence expansion and emotional extension," Technological Forecasting and Social Change, Elsevier, vol. 212(C).
    • Handle: RePEc:eee:tefoso:v:212:y:2025:i:c:s0040162525000101
    DOI: 10.1016/j.techfore.2025.123979
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