How do Artificial Intelligence Chatbots Affect Customer Purchase? Uncovering the Dual Pathways of Anthropomorphism on Service Evaluation

Yang Li (), Zhenghua Gan () and Bowen Zheng ()
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Yang Li: Hefei University of Technology
Zhenghua Gan: Hefei University of Technology
Bowen Zheng: Central South University

Information Systems Frontiers, 2025, vol. 27, issue 1, No 15, 283-300

Abstract: Abstract Although chatbots are increasingly deployed in customer service to reduce the burden of human labor and sometimes replace human employees in online shopping, there remains the challenge of ensuring consumers’ service evaluation and purchase decisions after chatbot service. Anthropomorphism, referring to human-like traits exhibited by non-human entities, is considered a key principle to facilitate customers’ positive evaluation of chatbot service and purchase decisions. However, equipping chatbots with anthropomorphism should be planned and rolled out cautiously because it could be both advantages to building customer trust and disadvantages for increasing customer overload. To understand how customers process and react to chatbot anthropomorphism, this study applied Wixom and Todd’s model and social information processing theory which guide this study to examine how object-based social beliefs (i.e., chatbot warmth and chatbot competence) of anthropomorphic chatbot influence service evaluation and customer purchase by generating behavioral beliefs (i.e., trust in chatbot and chatbot overload). The research model was examined with a “lab–in–the–field” experiment of 212 samples and two scenario-based experiments of 124 samples and 232 samples. The results showed that chatbot warmth and competence had significant effects on trust in chatbot and chatbot overload. Trust in chatbot and chatbot overload further significantly impact service evaluation and then customer purchase. Implications for theory and practice are discussed.

Keywords: Chatbot; Anthropomorphism; Trust; ICT–related overload; Service evaluation (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s10796-023-10438-x

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