Analyzing the Influence of UTAUT2 Constructs and E-Commerce Usage Frequency on Gen Z's Purchase Intention Toward AR Virtual Try-On Shade Filters
DOI:
https://doi.org/10.55606/ijemr.v4i3.545Keywords:
Augmented Reality (AR), E-commerce, Purchase Intention, UTAUT2, Gen ZAbstract
The rapid growth of Indonesia’s beauty and e-commerce industries has fueled the adoption of Augmented Reality (AR) virtual try-on (VTO) shade filters, particularly for makeup products such as lipstick and foundation. These tools enable users to visualize products before purchasing, addressing a major challenge in online beauty shopping. While Gen Z consumers are highly active in digital environments, research on how AR VTO shade features influence their buying decisions remains limited. This study applies the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) to examine the impact of each UTAUT2 construct on purchase intention among Indonesian Gen Z consumers when using AR try-on shade filters on e-commerce platforms. It also investigates whether e-commerce usage frequency moderates these effects. A quantitative method was employed, with data collected from 260 female Gen Z respondents and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Findings reveal that all seven UTAUT2 constructs—Performance Expectancy, Effort Expectancy, Social Influence, Facilitating Conditions, Hedonic Motivation, Price Value, and Habit—significantly influence purchase intention, with Habit emerging as the strongest predictor. Moreover, e-commerce usage frequency was found to moderate these relationships. Among frequent users, the effects of Performance Expectancy, Facilitating Conditions, Hedonic Motivation, and Price Value on purchase intention were stronger, while the influence of Effort Expectancy, Social Influence, and Habit was weaker. The results confirm that UTAUT2 effectively explains AR adoption in e-commerce beauty contexts. The study suggests that businesses should tailor AR strategies according to users’ e-commerce experience levels to enhance engagement, strengthen purchase intentions, and optimize the effectiveness of AR integration. Such adjustments can help e-commerce platforms provide more personalized and immersive shopping experiences, ultimately boosting customer satisfaction and sales performance.
References
Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Williams, M. D. (2016). Consumer adoption of mobile banking in Jordan: Examining the role of usefulness, ease of use, trust and self-efficacy. Journal of Enterprise Information Management, 29(1), 118–139. https://doi.org/10.1108/JEIM-04-2015-0035
Childers, T. L., Carr, C. L., Peck, J., & Carson, S. (2001). Hedonic and utilitarian motivations for online retail shopping be-havior. Journal of Retailing, 77(4), 511–535. https://doi.org/10.1016/S0022-4359(01)00056-2
Choi, H., Kim, Y., & Kim, J. (2020). Understanding the use of augmented reality in shopping contexts: A uses and gratifica-tions perspective. Computers in Human Behavior, 107, 106274. https://doi.org/10.1016/j.chb.2020.106274
Chung, N., Han, H., & Joun, Y. (2015). Tourists' intention to visit a destination: The role of augmented reality (AR) application for heritage site. Computers in Human Behavior, 50, 588–599. https://doi.org/10.1016/j.chb.2015.02.068
Cocosila, M., & Igonor, A. (2015). How important is the "social" in social networking? A perceived value empirical investi-gation. Information Technology & People, 28(2), 366–382. https://doi.org/10.1108/ITP-03-2014-0055
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008
Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the unified theory of ac-ceptance and use of technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers, 21(3), 719–734. https://doi.org/10.1007/s10796-017-9774-y
Gao, L., & Bai, X. (2014). A unified perspective on the factors influencing consumer acceptance of internet of things technology. Asia Pacific Journal of Marketing and Logistics, 26(2), 211–231. https://doi.org/10.1108/APJML-06-2013-0061
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 Publications. https://doi.org/10.1007/978-3-030-80519-7
Jung, J., & tom Dieck, M. C. (2017). Augmented reality and virtual reality: New drivers for fashion retail? In Augmented reality and virtual reality (pp. 183–194). Springer. https://doi.org/10.1007/978-3-319-64027-3
Kock, N. (2020). WarpPLS user manual: Version 7.0. ScriptWarp Systems.
Kotler, P., & Keller, K. L. (2022). Marketing management (16th ed.). Pearson Education.
Lim, S. S., & Dubinsky, J. M. (2005). The theory of planned behavior and intentions to purchase counterfeit merchandise: The moderating effects of ethical beliefs. Journal of Business Ethics, 60(2), 115–124. https://doi.org/10.1007/s10551-004-7370-9
Lu, J., Yu, C.-S., Liu, C., & Yao, J. E. (2003). Technology acceptance model for wireless Internet. Internet Research, 13(3), 206–222. https://doi.org/10.1108/10662240310478222
McLean, G., & Wilson, A. (2019). Shopping in the digital world: Examining customer engagement through augmented reality mobile applications. Computers in Human Behavior, 101, 210–224. https://doi.org/10.1016/j.chb.2019.07.002
Pantano, E., Rese, A., & Baier, D. (2017). Enhancing the online decision-making process by using augmented reality: A two country comparison of youth markets. Journal of Retailing and Consumer Services, 38, 81–95. https://doi.org/10.1016/j.jretconser.2017.05.011
Scholz, J., & Duffy, K. (2018). We ARe at home: How augmented reality reshapes mobile marketing and consumer-brand relationships. Journal of Retailing and Consumer Services, 44, 11–23. https://doi.org/10.1016/j.jretconser.2018.05.004
Smink, A. R., Frowijn, L., van Reijmersdal, E. A., van Noort, G., & Neijens, P. C. (2020). Try online before you buy: How does shopping with augmented reality affect brand responses and personal data disclosure? Journal of Interactive Marketing, 52, 31–45. https://doi.org/10.1016/j.intmar.2020.04.001
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 (UTAUT2). MIS Quarterly, 36(1), 157–178. https://doi.org/10.2307/41410412
Yim, M. Y. C., Chu, S. C., & Sauer, P. L. (2017). Is augmented reality technology an effective tool for e-commerce? An interactivity and vividness perspective. Journal of Interactive Marketing, 39, 89–103. https://doi.org/10.1016/j.intmar.2017.04.001
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