Consumer purchase behavior in livestreaming commerce: An investigation through the lens of the UTAUT2 model
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DOIhttp://dx.doi.org/10.21511/im.21(4).2025.18
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Article InfoVolume 21 2025, Issue #4, pp. 246-260
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Creative Commons Attribution 4.0 International License
Type of the article: Research Article
Abstract
The rapid growth of livestreaming commerce has transformed online retail in Asian markets, blending entertainment and shopping into an interactive and immersive experience. Despite its increasing prevalence, limited research has examined the determinants of purchase intention and actual buying behavior in emerging economies such as Vietnam. This study employs the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) to investigate the key factors influencing consumer behavior in livestreaming commerce. A structured online survey was administered to 520 Vietnamese consumers with prior experience purchasing through livestreaming channels. Data were collected using purposive sampling from e-commerce communities and social media networks between March and April 2025. Partial Least Squares Structural Equation Modelling (PLS-SEM) was applied to test the proposed model. The results reveal that Performance Expectancy (β = 0.441, p < 0.001) has the strongest positive effect on Purchase Intention, followed by Effort Expectancy (β = 0.215, p < 0.001), Hedonic Motivation (β = 0.140, p = 0.006), and Price Value (β = 0.103, p = 0.030). Social Influence (β = –0.045, p = 0.218) shows no significant effect, suggesting that livestream shopping decisions are driven more by perceived utility and enjoyment than by peer influence. Regarding Actual Purchase, Facilitating Conditions (β = 0.296, p < 0.001) and Habit (β = 0.320, p < 0.001) are significant predictors, while Purchase Intention (β = 0.017, p = 0.583) is not. These findings extend UTAUT2 to a consumer context and offer practical implications for enhancing engagement and conversion in Vietnam’s rapidly digitizing retail landscape.
Acknowledgment
The author wishes to express deep gratitude to all survey participants for their valuable time and contributions, which significantly enhanced the success of this study. The author also extends sincere thanks to the author’s university for the financial support that made this research possible. This research was funded by University of Finance – Marketing.
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JEL Classification (Paper profile tab)M31, L81, D83
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References50
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Tables4
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Figures2
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- Figure 1. The proposed model
- Figure 2. Structural model with standardized path coefficients
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- Table 1. Respondents’ characteristics
- Table 2. Indicators of reliability and convergent validity
- Table 3. Discriminant validity of the constructs
- Table 4. Hypotheses testing results
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- Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
- Brislin, R. W. (1980). Translation and content analysis of oral and written materials. In H. C. Triandis & J. W. Berry (Eds.), Handbook of cross-cultural psychology: Vol 2 Methodology (pp. 389-444). Boston: Allyn & Bacon.
- Cai, J., & Wohn, D. Y. (2019). Live streaming commerce: Uses and gratifications approach to understanding consumers’ motivations. In Proceedings of the 52nd Hawaii International Conference on System Sciences (pp. 2548-2557). Grand Wailea, Maui, HI: University of Hawai‘i at Mānoa.
- Cai, J., Wohn, D. Y., Mittal, A., & Sureshbabu, D. (2018). Utilitarian and hedonic motivations for live streaming shopping. In Proceedings of the 2018 ACM international conference on interactive experiences for TV and online video (pp. 81-88). NY: Association for Computing Machinery.
- Chandraa, M., Sukmaningsih, D. W., & Sriwardiningsih, E. (2024). The impact of live streaming on purchase intention in social commerce in Indonesia. Procedia Computer Science, 234, 987-995.
- Chandrruangphen, E., Assarut, N., & Sinthupinyo, S. (2022). The effects of live streaming attributes on consumer trust and shopping intentions for fashion clothing. Cogent Business & Management, 9(1), 2034238.
- Chen, C. C., & Lin, Y. C. (2018). What drives live-stream usage intention? The perspectives of flow, entertainment, social interaction, and endorsement. Telematics and Informatics, 35(1), 293-303.
- Chen, H., Chen, H., & Tian, X. (2022). The dual-process model of product information and habit in influencing consumers’ purchase intention: The role of live streaming features. Electronic Commerce Research and Applications, 53, 101150.
- Chen, X., Shen, J., & Wei, S. (2023). What reduces product uncertainty in live streaming e-commerce? From a signal consistency perspective. Journal of Retailing and Consumer Services, 74, 103441.
- Chin, W. W., & Newsted, P. R. (1999). Structural equation modeling analysis with small samples using partial least squares. In R. H. Hoyle (Ed.), Statistical strategies for small sample research (pp. 307-341). Thousand Oaks, CA: Sage Publications.
- Cốc cốc (2024). 2023 và những xu hướng mới của người tiêu dùng Việt [2023 and new trends of Vietnamese consumers].
- Dodds, W. B., Monroe, K. B., & Grewal, D. (1991). Effects of price, brand, and store information on buyers’ product evaluations. Journal of Marketing Research, 28(3), 307-319.
- Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
- Guo, J., Li, Y., Xu, Y., & Zeng, K. (2021). How live streaming features impact consumers’ purchase intention in the context of cross-border E-commerce? A research based on SOR theory. Frontiers in Psychology, 12, 767876.
- Hair, J. F., Sarstedt, M., Ringle, C. M., & Gudergan, S. P. (2017). Advanced Issues in Partial Least Squares Structural Equation Modeling. SAGE Publications.
- Hong, W. X., & Hoo, W. C. (2022). A study on purchase intention of agricultural produce on Shopee live-streaming in Malaysia. International Journal of E-Services and Mobile Applications, 14(1), 1-13.
- Hu, M., & Chaudhry, S. S. (2020). Enhancing consumer engagement in ecommerce live streaming via relational bonds. Internet Research, 30(3), 1019-1041.
- Huang, Y., & Suo, L. (2021). Factors affecting Chinese consumers’ impulse buying decision of live streaming E-commerce. Asian Social Science, 17(5), 16-32.
- Katz, E., Blumler, J. G., & Gurevitch, M. (1973). Uses and Gratifications Research. Public Opinion Quarterly, 37(4), 509-523.
- Khánh Anh. (2019). Cuộc đua livestream của các sàn thương mại điện tử [Livestream race of e-commerce platforms]. VnExpress.
- Lee, C. H., & Chen, C. W. (2021). Impulse buying behaviors in live streaming commerce based on the stimulus-organismresponse framework. Information, 12(6), 241.
- Li, L., Kang, K., Zhao, A., & Feng, Y. (2023). The impact of social presence and facilitation factors on online consumers’ impulse buying in live shopping–celebrity endorsement as a moderating factor. Information Technology & People, 36(6), 2611-2631.
- Li, Z., Wang, Y., Cianfrone, B. A., Guo, Z., Liu, B., Zhang, J., & Shi, C. (2025). Impact of scene features of e-commerce live streaming on consumers’ flow and purchase intentions of sporting goods. Behavioral Sciences, 15(2), 238.
- Lim, Y. J., Osman, A., Salahuddin, S. N., Romle, A. R., & Abdullah, S. (2016). Factors influencing online shopping behavior: the mediating role of purchase intention. Procedia Economics and Finance, 35, 401-410.
- Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How Habit Limits the Predictive Power of Intention: The Case of Information Systems Continuance. MIS Quarterly, 31(4), 705-737.
- Limna, P., Kraiwanit, T., & Jangjarat, K. (2023). Adopting the technology acceptance model (TAM) to explore online purchase intention via Facebook live streaming: Empirical evidence from Bangkok, Thailand. ASEAN Journal of Management & Innovation, 10(1), 1-13.
- Lin, S. C., Tseng, H. T., Shirazi, F., Hajli, N., & Tsai, P. T. (2022). Exploring factors influencing impulse buying in live streaming shopping: a stimulus-organism-response (SOR) perspective. Asia Pacific Journal of Marketing and Logistics (ahead-of-print).
- Liu, D., & Yu, J. (2022). Impact of perceived diagnosticity on live streams and consumer purchase intention: Streamer type, product type, and brand awareness as moderators. Information Technology and Management, 25(3), 219-232.
- Luo, X., Lim, W. M., Cheah, J. H., Lim, X. J., & Dwivedi, Y. K. (2025). Live streaming commerce: a review and research agenda. Journal of Computer Information Systems, 65(3), 376-399.
- Ma, L., Gao, S., & Zhang, X. (2022). How to use live streaming to improve consumer purchase intentions: evidence from China. Sustainability, 14(2), 1-20.
- Ma, Y. (2023). Effects of interactivity affordance on user stickiness in livestream shopping: identification and gratification as mediators. Heliyon, 9(1), 1-18.
- Morwitz, V. G., Steckel, J. H., & Gupta, A. (2007). When do purchase intentions predict sales?. International Journal of Forecasting, 23(3), 347-364.
- Ngo, T. T. A., Bui, C. T., Chau, H. K. L., & Tran, N. P. N. (2023). The effects of social media live streaming commerce on Vietnamese Generation Z consumers’ purchase intention. Innovative Marketing, 19(4), 269-283.
- Nguyen, B. V., Hoang, H. Q., Truong, L. N. T., & Nguyen, N. T. B. (2024). Impulse buying behavior in livestream on Tiktok platform: Role of streamer attractiveness, social presence and sales promotion. VNUHCM Journal of Economics-Law and Management, 8(2), 5229-5242.
- Nuraisah, S., Nadlifatin, R., Subriadi, A. P., & Gumasing, M. J. J. (2024). Live streaming commerce is considered as shoppertaiment: A systematic literature review. Procedia Computer Science, 234, 1020-1028.
- Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), 101-134.
- Peña-García, N., Gil-Saura, I., Rodríguez-Orejuela, A., & Siqueira-Junior, J. R. (2020). Purchase intention and purchase behavior online: A cross-cultural approach. Heliyon, 6(6), 1-11.
- Qing, X. (2025). Live streamers impact on consumer purchase intention: exploring social presence trust and innovation acceptance. Innovation: The European Journal of Social Science Research, 1-31.
- Shareef, M. A., Baabdullah, A., Dutta, S., Kumar, V., & Dwivedi, Y. K. (2018). Consumer adoption of mobile banking services: An empirical examination of factors according to adoption stages. Journal of Retailing and Consumer Services, 43, 54-67.
- Sheeran, P., & Webb, T. L. (2016). The intention–behavior gap. Social and Personality Psychology Compass, 10(9), 503-518.
- Tamilmani, K., Rana, N. P., & Dwivedi, Y. K. (2021). Consumer acceptance and use of information technology: A meta-analytic evaluation of UTAUT2. Information Systems Frontiers, 23(4), 987-1005.
- Venkatesh, V., Thong, J. Y. L., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178.
- Venkatesh, V., Thong, J. Y., & Xu, X. (2016). Unified theory of acceptance and use of technology: A synthesis and the road ahead. Journal of the Association for Information Systems, 17(5), 328-376.
- Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly, 27(3), 425-478.
- Weber, R. (2012). Evaluating and Developing Theories in the Information Systems Discipline. Journal of the Association for Information Systems, 13(1), 1-30.
- Wongkitrungrueng, A., & Assarut, N. (2020) The Role of Live Streaming in Building Consumer Trust and Engagement with Social Commerce Sellers. Journal of Business Research, 117, 543-556.
- Xu, X., Wu, J.-H., & Li, Q. (2020). What drives consumer shopping behavior in live streaming commerce? Journal of Electronic Commerce Research, 21(3), 144-167.
- Yang, G., Chaiyasoonthorn, W., & Chaveesuk, S. (2024). Exploring the influence of live streaming on consumer purchase intention: A structural equation modeling approach in the Chinese E-commerce sector. Acta Psychologica, 249, 1-10.
- Zhang, N. (2023). Product presentation in the live-streaming context: The effect of consumer perceived product value and time pressure on consumer’s purchase intention. Frontiers in Psychology, 14, 1-12.
- Zhou, R., & Tong, L. (2022). A study on the influencing factors of consumers’ purchase intention during livestreaming e-commerce: the mediating effect of emotion. Frontiers in Psychology, 13, 1-15.


