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The adoption of AI virtual assistants in conversational commerce: The moderating role of digital literacy

Trịnh Hoàng Nam: Trường Đại học Ngân hàng Thành phố Hồ Chí Minh;
doi:10.62831/nckh.2026.153.v1

Abstract

This study clarifies the role of artificial intelligence (AI) technology characteristics and digital knowledge in shaping users’ attitudes and intentions toward using AI virtual assistants in conversational commerce. The findings demonstrate how technical attributes, including intelligence, vividness, and anthropomorphism, influence users’ psychological experiences and subsequently promote adoption behavior. The study also highlights digital knowledge as a critical moderating variable that explains differences in how users interpret and respond to technological cues. These results contribute to a deeper understanding of consumer behavior in the context of the growing prevalence of AI and provide design implications for e-commerce platforms.

Keywords
AI virtual assistant SOR conversational commerce intention to use

References

1.
Vecom (2024). Báo cáo chỉ số thương mại điện tử Việt Nam 2024. Truy cập tại https://drive.google.com/file/d/1gxbKNYlgW5GOu6M_ED68PgjKtGbi8JBS/view
2.
Ashfaq, M., Yun, J., Yu, S., & Loureiro, S. M. C. (2020). I, Chatbot: Modeling the determinants of users’ satisfaction and continuance intention of AI-powered service agents. Telematics and Informatics, 54, 101473.
3.
Ding, Y., & Najaf, M. (2024). Interactivity, humanness, and trust: a psychological approach to AI chatbot adoption in e-commerce. BMC Psychol, 12(1), 595.
4.
Dwivedi, Y. K., Balakrishnan, J., Baabdullah, A. M., & Das, R. (2023). Do chatbots establish “humanness” in the customer purchase journey? . Psychology & Marketing, 40(10), 2008–2037
5.
Esiyok, E., Gokcearslan, S., & Kucukergin, K. G. (2024). Acceptance of Educational Use of AI Chatbots in the Context of Self-Directed Learning with Technology and ICT Self-Efficacy of Undergraduate Students. International Journal of Human–Computer Interaction, 41(1), 641–650
6.
Fatima, J. K., Khan, M. I., & Bahmannia, S. (2024). Rapport with a chatbot? The underlying role of anthropomorphism in socio-cognitive perceptions of rapport and e-word of mouth. Journal of Retailing and Consumer Services, 77, 103666.
7.
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM) (3rd Ed.): Sage.
8.
Hong, J. W., Fischer, K., Kim, D., Cho, J. H., & Sun, Y. (2024). I Am Not Your Typical Chatbot: Hedonic and Utilitarian Evaluation of Open-Domain Chatbots. International Journal of Human–Computer Interaction, 41(14), 8963–8974
9.
Hu, X., Li, J., & Chen, Y. (2023). User motivations for AI chatbot adoption: A UGT perspective. Computers in Human Behavior, 141, 107650
10.
Jin, S. V., & Youn, S. (2022). Social Presence and Imagery Processing as Predictors of Chatbot Continuance Intention in Human-AI-Interaction. International Journal of Human–Computer Interaction, 39(9), 1874–1886.
11.
Kasilingam, D. L. (2020). Understanding the attitude and intention to use smartphone chatbots for shopping. Technology in Society(62), 101280
12.
Li, M., & Wang, R. (2023). Chatbots in e-commerce: The effect of chatbot language style on customers’ continuance usage intention and attitude toward brand. Journal of Retailing and Consumer Services, 71, 103209
13.
Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. Cambridge, MA: MIT Press.
14.
Meng, H., Lu, X., & Xu, J. (2025). The impact of chatbot response strategies and emojis usage on customers’ purchase intention. Behavioral Sciences, 15(2), 117
15.
Rahman, M. K., Ismail, N. A., Hossain, M. A., & Hossen, M. S. (2025). Students' mindset to adopt AI chatbots for effectiveness of online learning in higher education. Future Business Journal, 11(1), 30
16.
Sidlauskiene, J., Joye, Y., & Auruskeviciene, V. (2023). AI-based chatbots in conversational commerce and their effects on product and price perceptions. Electronic Markets, 33(1), 24.
17.
Zhu, Y., Zhang, R., Zou, Y., & Jin, D. (2023). Investigating customers’ responses to artificial intelligence chatbots in online travel agencies: the moderating role of product familiarity. Journal of Hospitality and Tourism Technology, 14(2), 208-224

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Section Quản trị - Quản lý
Issue Số 14 - Tháng 5 - 2026

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