Artificial Intelligence (AI), which is quickly being incorporated into digital service ecosystems, has fundamentally transformed user decision-making processes. However, users often experience a paradox of selection due to information overload, as they are exposed to a vast number of book titles and diverse genres, which makes decision making more complex. To solve this problem, this study examines the effects of chatbot features conceptualized through perceived warmth and capability on users’ purchase intention in digital book platforms. It investigates the moderating function of trust in AI and the mediating role of cognitive and affective dimensions of user engagement based on an extended Stimulus–Organism–Response (S-O-R) theory, incorporating insights from the Stereotype Content Model (SCM). Respondents who had used chatbot features in digital book platforms completed a quantitative survey. The collected data were analyzed using mediation and moderated mediation analysis for hypothesis testing, while measurement model assessment was conducted to evaluate the reliability and validity of the constructs. This relationship is mediated by user engagement. However, the moderating effect of trust in AI is not statistically supported, indicating that the influence of chatbot features on engagement remains stable regardless of users’ trust levels. This research contributes to the corpus of knowledge on conversational commerce by demonstrating that customer behavior is significantly influenced by AI-driven interactions, with practical implications for designing chatbots as experiential rather than purely transactional tools.

Adam, M., Wessel, M., & Benlian, A. (2021). AI-based chatbots in customer service and their effects on user compliance. Electronic Markets, 31(2), 427-445.
Afroogh, S., Akbari, A., Malone, E., Kargar, M., & Alambeigi, H. (2024). Trust in AI: Progress, challenges, and future directions. Humanities and Social Sciences Communications, 11(1), 1568.
Al-Shafei, M. (2025). Navigating human-chatbot interactions: An investigation into factors influencing user satisfaction and engagement. International Journal of Human–Computer Interaction, 41(1), 411-428.
Asante, I. O., Jiang, Y., Hossin, A. M., & Luo, X. (2023). Optimization of consumer engagement with artificial intelligence elements on electronic commerce platforms. Journal of Electronic Commerce Research, 24(1), 7-28.
Chen, Q., Yin, C., & Gong, Y. (2025). Would an AI chatbot persuade you: An empirical answer from the elaboration likelihood model. Information Technology & People, 38(2), 937-962.
Cheng, Y.-M. (2026). Will customers buy financial products impulsively? AI-powered chatbots’ recommendations. Journal of Asia Business Studies, 20(3), 775-813.
Chivkula, A., & Pokhriyal, D. (2026). The role of AI-driven chatbots in enhancing sustainable customer service: A survey-based study on consumer perceptions. Journal of Innovation and Entrepreneurship, 15(1), 40.
Cho, K. A., & Seo, Y. H. (2024). Dual mediating effects of anxiety to use and acceptance attitude of artificial intelligence technology on the relationship between nursing students’ perception of and intention to use them: A descriptive study. BMC Nursing, 23(1), 212.
Choung, H., David, P., & Ross, A. (2023). Trust in AI and its role in the acceptance of AI technologies. International Journal of Human–Computer Interaction, 39(9), 1727-1739.
Dang, Q., & Li, G. (2026). Unveiling trust in AI: The interplay of antecedents, consequences, and cultural dynamics. AI & SOCIETY, 41(1), 669-692.
Deng, Z., & Yan, J. (2025). The effect of perceived warmth, competence, and social presence of ai-driven chatbots on consumers’ engagement and satisfaction. SAGE Open, 15(3), 21582440251365438.
Dwivedi, Y. K., Balakrishnan, J., Baabdullah, A. M., & Das, R. (2023). Do chatbots establish “humanness” in the customer purchase journey? An investigation through explanatory sequential design. Psychology & Marketing, 40(11), 2244-2271.
Fan, W. (2025). Optimization of multi-subject collaborative innovation path in value cocreation on multi-sided digital reading platforms: A platform ecosystem perspective. Science-Technology & Publication, 44(4), 94-102.
Fiske, S. T. (2018). Stereotype content: Warmth and competence endure. Current Directions in Psychological Science, 27(2), 67-73.
Frank, D.-A., Jacobsen, L. F., Søndergaard, H. A., & Otterbring, T. (2023). In companies we trust: Consumer adoption of artificial intelligence services and the role of trust in companies and AI autonomy. Information Technology & People, 36(8), 155-173.
Goi, M.-T., Kalidas, V., & Yunus, N. (2018). Mediating roles of emotion and experience in the stimulus-organism-response framework in higher education institutions. Journal of Marketing for Higher Education, 28(1), 90-112.
Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2-24.
Hayes, A. F. (2017). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach (2nd ed). The Guilford Press, 0(0), 391-504.
Hollebeek, L. D., Menidjel, C., Sarstedt, M., Jansson, J., & Urbonavicius, S. (2024). Engaging consumers through artificially intelligent technologies: Systematic review, conceptual model, and further research. Psychology & Marketing, 41(4), 880-898.
Huang, Y., & Gursoy, D. (2024). Customers’ online service encounter satisfaction with chatbots: Interaction effects of language style and decision-making journey stage. International Journal of Contemporary Hospitality Management, 36(12), 4074-4091.
Islam, A., & Chang, K. (2021). Real-time AI-based informational decision-making support system utilizing dynamic text sources. Applied Sciences, 11(13), 6237.
Kim, M. J., Lee, C.-K., & Jung, T. (2020). Exploring consumer behavior in virtual reality tourism using an extended stimulus-organism-response model. Journal of Travel Research, 59(1), 69-89.
Kim, W. B., & Hur, H. J. (2024). What makes people feel empathy for AI chatbots? Assessing the role of competence and warmth. International Journal of Human–Computer Interaction, 40(17), 4674-4687.
Kuranga, M. B., Bale, H., Olaoti, R. M., Muraina, S. A., & Abiola, A. B. (2026). The impact of AI-powered chatbots on user engagement and information seeking behavior in Nigerian university libraries. African Research Reports, 2(1), 69-78.
Laato, S., Islam, A. N., Farooq, A., & Dhir, A. (2020). Unusual purchasing behavior during the early stages of the COVID-19 pandemic: The stimulus-organism-response approach. Journal of Retailing and Consumer Services, 57(0), 102224.
Lee, C., & Cha, K. (2025). Toward the dynamic relationship between AI transparency and trust in AI: A case study on ChatGPT. International Journal of Human–Computer Interaction, 41(13), 8086-8103.
Lee, C.-H., & Wu, J. J. (2017). Consumer online flow experience: The relationship between utilitarian and hedonic value, satisfaction and unplanned purchase. Industrial Management & Data Systems, 117(10), 2452-2467.
Lee, J., & Lee, J.-N. (2015). How purchase intention consummates purchase behaviour: The stochastic nature of product valuation in electronic commerce. Behaviour & Information Technology, 34(1), 57-68.
Li, J., Wu, L., Qi, J., Zhang, Y., Wu, Z., & Hu, S. (2023). Determinants affecting consumer trust in communication with AI chatbots: The moderating effect of privacy concerns. Journal of Organizational and End User Computing (JOEUC), 35(1), 1-24.
Li, X., Zhou, Y., Wong, Y. D., Wang, X., & Yuen, K. F. (2021). What influences panic buying behaviour? A model based on dual-system theory and stimulus-organism-response framework. International Journal of Disaster Risk Reduction, 64(0), 102484.
Marjerison, R. K., Zhang, Y., & Zheng, H. (2022). AI in e-commerce: Application of the use and gratification model to the acceptance of chatbots. Sustainability, 14(21), 14270.
McKee, K. R., Bai, X., & Fiske, S. T. (2023). Humans perceive warmth and competence in artificial intelligence. iScience, 26(8), 11.
McKee, K. R., Bai, X., & Fiske, S. T. (2024). Warmth and competence in human-agent cooperation. Autonomous Agents and Multi-Agent Systems, 38(1), 23.
Nazir, S., Khadim, S., Asadullah, M. A., & Syed, N. (2023). Exploring the influence of artificial intelligence technology on consumer repurchase intention: The mediation and moderation approach. Technology in Society, 72(0), 102190.
Ng, S. W. T., & Zhang, R. (2025). Trust in AI chatbots: A systematic review. Telematics and Informatics, 97(0), 102240.
Ng, W., Hao, F., & Zhang, C. (2026). From function to relation: Exploring the dual influences of warmth and competence on generative artificial intelligence services in the hospitality industry. Journal of Hospitality & Tourism Research, 50(1), 36-49.
Pereira, M. L., de La Martinière Petroll, M., Soares, J. C., Matos, C. A. d., & Hernani-Merino, M. (2023). Impulse buying behaviour in omnichannel retail: An approach through the stimulus-organism-response theory. International Journal of Retail & Distribution Management, 51(1), 39-58.
Podsakoff, P. M., MacKenzie, S. B., Lee, J.-Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5), 879.
Rahevar, M., & Darji, S. (2024). The adoption of AI-driven chatbots into a recommendation for e-commerce systems to targeted customer in the selection of product. International Journal of Management, Economics and Commerce, 1(2), 128-137.
Riswanto, A. L., Ha, S., Lee, S., & Kwon, M. (2024). Online reviews meet visual attention: A study on consumer patterns in advertising, analyzing customer satisfaction, visual engagement, and purchase intention. Journal of Theoretical and Applied Electronic Commerce Research, 19(4), 3102-3122.
Rozenkowska, K. (2023). Theory of planned behavior in consumer behavior research: A systematic literature review. International Journal of Consumer Studies, 47(6), 2670-2700.
Sindhu, P., & Bharti, K. (2024). Influence of chatbots on purchase intention in social commerce. Behaviour & Information Technology, 43(2), 331-352.
Sun, H., Steinkrauss, R., Wieling, M., & De Bot, K. (2018). Individual differences in very young Chinese children’s English vocabulary breadth and semantic depth: Internal and external factors. International Journal of Bilingual Education and Bilingualism, 21(4), 405-425.
Tan, R., Li, Y., Huang, Q., & Liu, H. (2025). Enhancing customer service chatbot effectiveness: The effect of dyadic communication traits on customer purchase intention. Journal of the Association for Information Systems, 26(3), 799-831.
Vieira, V. A. (2013). Stimuli–organism-response framework: A meta-analytic review in the store environment. Journal of Business Research, 66(9), 1420-1426.
Xie, C., Wang, Y., & Cheng, Y. (2024). Does artificial intelligence satisfy you? A meta-analysis of user gratification and user satisfaction with AI-powered chatbots. International Journal of Human–Computer Interaction, 40(3), 613-623.
Yang, S., Xie, W., Chen, Y., Li, Y., Jiang, H., & Zhou, W. (2025). Warmth or competence? Understanding voice shopping intentions from human-AI interaction perspective. Electronic Commerce Research, 25(6), 4625-4654.