The effects of interactions with generative AI-powered virtual streamers on purchase intention and purchasing behavior on TikTok
Published: October 16, 2026
Abstract
The growth of livestream commerce has accelerated the adoption of generative AI-powered virtual streamers on platforms such as TikTok. Drawing on the Stimulus-Organism-Response (S-O-R) framework, this study examines the effects of interactions with virtual streamers on purchase intention and purchasing behavior, while also considering the roles of social presence and perceived value. Data collected from 319 TikTok users in Vietnam were analyzed using partial least squares structural equation modeling (PLS-SEM). The results show that both social interaction and product interaction positively influence social presence and perceived value. In turn, social presence and perceived value positively affect purchase intention, which subsequently has a positive effect on purchasing behavior. The findings provide managerial implications for businesses seeking to deploy generative AI-powered virtual streamers to enhance customer experience and improve business performance on TikTok.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
2.
Cao, Y., & Wang, F. (2025). Generative AI streamers in action: A source credibility perspective. International Journal of Advertising, 1-34.
3.
Chang, Y., Wang, H., & Guo, Z. (2025). Artificial intelligence in live streaming: How can virtual streamers bring more sales? Journal of Retailing and Consumer Services, 84, 104247.
4.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
5.
Hair, J. F., Jr., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial least squares structural equation modeling (PLS-SEM) using R: A workbook. Springer.
6.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43, 115-135.
7.
Hossain, M. A., Kalam, A., Nuruzzaman, M., & Kim, M. (2023). The power of live-streaming in consumers’ purchasing decision. SAGE Open, 13(4), 1-18.
8.
Kemp, S. (2025). Digital 2026: Vietnam. DataReportal. https://datareportal.com
9.
Liu, H., Zhang, P., Cheng, H., Hasan, N., & Chiong, R. (2025). Impact of AI-generated virtual streamer interaction on consumer purchase intention: A focus on social presence and perceived value. Journal of Retailing and Consumer Services, 85, 104290.
10.
Mehrabian, A., & Russell, J. A. (1974). An approach to environmental psychology. MIT Press.
11.
Tang, X., & Wang, Z. (2026). Anthropomorphic design of virtual streamers in live streaming: A double-edged sword effect on consumers’ acceptance intention. Journal of Consumer Behaviour, 25(5), 2321-2341.
12.
VECOM (2025). Báo cáo chỉ số thương mại điện tử Việt Nam 2025. Hiệp hội Thương mại điện tử Việt Nam. https://vecom.vn
13.
Wang, L., Yeap, J. A. L, Liu, J., & Li, Z. (2026). From avatars to algorithms: Virtual streamers and AI-enabled consumer behavior in live streaming commerce-a systematic review. Journal of Theoretical and Applied Electronic Commerce Research, 21(2), 57.
14.
Xu, B., Dastane, O., Aw, E. C. X., & Jha, S. (2025). The future of live-streaming commerce: Understanding the role of AI-powered virtual streamers. Asia Pacific Journal of Marketing and Logistics, 37(5), 1175-1196.
15.
Zhang, X., Shi, Y., Li, T., Guan, Y., & Cui, X. (2024). How do virtual AI streamers influence viewers’ livestream shopping behavior? The effects of persuasive factors and the mediating role of arousal. Information Systems Frontiers, 26(5), 1803-1834.
16.
Zhou, T., & Li, S. (2025). Examining consumer impulsive purchase intention in virtual AI streaming: A S-O-R perspective. Journal of Theoretical and Applied Electronic Commerce Research, 20(3), 204.
