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Would an AI chatbot persuade you: An empirical answer from the elaboration likelihood model
Journal article

Would an AI chatbot persuade you: An empirical answer from the elaboration likelihood model

Qian Chen, Changqin Yin and Yeming Gong
Information Technology and People, Vol.38(2), pp.937-962
14/03/2025

Abstract

AI chatbot Recommendation adoption Elaboration likelihood model Trust Mind perception
Purpose This study investigates how artificial intelligence (AI) chatbots persuade customers to accept their recommendations in the online shopping context. Design/methodology/approach Drawing on the elaboration likelihood model, this study establishes a research model to reveal the antecedents and internal mechanisms of customers' adoption of AI chatbot recommendations. The authors tested the model with survey data from 530 AI chatbot users. Findings The results show that in the AI chatbot recommendation adoption process, central and peripheral cues significantly affected a customer's intention to adopt an AI chatbot's recommendation, and a customer's cognitive and emotional trust in the AI chatbot mediated the relationships. Moreover, a customer's mind perception of the AI chatbot, including perceived agency and perceived experience, moderated the central and peripheral paths, respectively. Originality/value This study has theoretical and practical implications for AI chatbot designers and provides management insights for practitioners to enhance a customer's intention to adopt an AI chatbot's recommendation.
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Collaboration types
Domestic collaboration
International collaboration
Citation topics
6 Social Sciences
6.3 Management
6.3.65 Consumer Behavior
Web of Science research areas
Information Science & Library Science
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