Determinants of Consumer Acceptance of AI-Powered Virtual Try-On Technology in Online Fashion Commerce: An Extended Technology Acceptance Model Approach
DOI:
https://doi.org/10.63901/ijebam.v4i3.181Keywords:
artificial intelligence , virtual try-on, technology acceptance model , purchase intentionAbstract
AI-powered virtual try-on technology has emerged as an innovative solution to enhance online fashion shopping experiences. This study aims to examine consumer acceptance of virtual try-on technology by extending the Technology Acceptance Model (TAM) with perceived realism, perceived enjoyment, and trust. A quantitative approach was conducted using data from 500 respondents selected through purposive sampling. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS 3.0. The results indicate that perceived realism significantly influences perceived usefulness and trust. Moreover, perceived enjoyment and perceived usefulness positively affect attitude toward virtual try-on, while attitude and trust significantly influence purchase intention. This study emphasizes the importance of realistic, enjoyable, and trustworthy AI-based shopping experiences in increasing consumer adoption of virtual try-on technology.
References
Alameri, S.A.S. et al. (2026) “Consumer Acceptance of AI-Supported Circular Fashion Services: A Technology Acceptance Perspective,” in K. Mouloudj and L. Arantes (eds.) Ethical Consumption and Responsible Innovation in Fashion Through AI. IGI Global Scientific Publishing, pp. 35–58. Available at: https://doi.org/10.4018/979-8-3373-7200-6.ch002.
Baber, R., Baber, P. and Narula, S. (2026) “Driving AR Experience to Purchase Intention: Examining the Role of Users’ Immersiveness, Perceived Innovativeness and Engagement in Virtual Try-On,” International Journal of Consumer Studies, 50(2), p. e70185. Available at: https://doi.org/10.1111/ijcs.70185.
Daguimol, C. (2023) ZALORA LEADSTHEWAYINAI-DRIVEN FASHION E-COMMERCE IN SOUTHEAST ASIA. Singapore. Available at: ZALORA LEADSTHEWAYINAI-DRIVEN FASHION E-COMMERCE IN SOUTHEAST ASIA.
Davis, F.D. (1989) “Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology,” MIS Quarterly, 13(3), pp. 319–340. Available at: https://doi.org/10.2307/249008.
Davis Jr, F.D. (1986) A technology acceptance model for empirically testing new end-user information systems : theory and results. Massachusetts Institute of Technology. Available at: https://dspace.mit.edu/handle/1721.1/15192.
ElSayad, G. and Mamdouh, H. (2026) “The Power of AI in Retail E-Commerce: What Drives Online Customer Word-of-Mouth Intention Toward AI-Powered Shopping Applications?,” International Journal of Human–Computer Interaction, 42(1), pp. 567–579. Available at: https://doi.org/10.1080/10447318.2025.2508910.
Farid, A.F. and Pawar, K.M. (2026) “CONSUMER ACCEPTANCE OF AI-POWERED VIRTUAL TRY-ON TECHNOLOGY: A MULTI-PLATFORM COMPARATIVE ANALYSIS USING TECHNOLOGY ACCEPTANCE AND EXTENDED SELF THEORY,” International Journal of Research in Science and Technology, 13(2), pp. 43–52. Available at: https://doi.org/10.64151/PSGCARE-29.
Google (no date) “Formulir online untuk mendapatkan insight dengan cepat.” Google. Available at: https://workspace.google.com/products/forms/.
Hair Jr., J.F. et al. (2021) Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R: A Workbook. 1st ed. Cham: Springer Cham. Available at: https://doi.org/10.1007/978-3-030-80519-7.
Hair Jr, J.F. et al. (2021) A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). 3rd ed. Thousand Oaks: SAGE Publications, Inc. Available at: https://uk.sagepub.com/en-gb/eur/a-primer-on-partial-least-squares-structural-equation-modeling-pls-sem/book270548.
Haran, K.R. et al. (2026) “Virtual try-on technology in fashion retail employing augmented reality,” International Journal of Fashion Design, Technology and Education, pp. 1–14. Available at: https://doi.org/10.1080/17543266.2026.2683393.
Haryono, S. (2016) Metode SEM Untuk Penelitian Manajemen dengan AMOS LISREL PLS. Bekasi: PT. Intermedia Personalia Utama.
Hien, N.N. et al. (2026) “Determinants of AI-Integrated E-Commerce Acceptance: The Roles of Personal Innovativeness, Self-Efficacy, Compatibility, and Curiosity,” Human Behavior and Emerging Technologies, 2026(1), p. 5689688. Available at: https://doi.org/10.1155/hbe2/5689688.
Kamaliah, A. (2025) Belanja Baju Langsung Coba Pakai “Coba Virtual Shopee”, Gini Caranya, detikInet. Available at: https://inet.detik.com/cyberlife/d-8195744/belanja-baju-langsung-coba-pakai-coba-virtual-shopee-gini-caranya (Accessed: March 21, 2026).
Khalid, L. and Gong, W. (2026) “Exploring AI in fashion: a review of aesthetics, personalization, virtual try-on, and forecasting,” Multimedia Systems, 32(3), p. 167. Available at: https://doi.org/10.1007/s00530-026-02232-x.
Kim, S. et al. (2026) “Understanding User Experience with Virtual Try-On and Design Implications for Online Fashion Shopping,” in Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems. New York, NY, USA: Association for Computing Machinery (CHI ’26). Available at: https://doi.org/10.1145/3772318.3791811.
Mishra, S., Saxena, G. and Jain, S. (2025) “Does AR-driven virtual try-on technology inspire luxury consumers: a mixed-method study,” Industrial Management & Data Systems, 126(5), pp. 1555–1579. Available at: https://doi.org/10.1108/IMDS-02-2025-0141.
Rambe, A.S. (2017) Zalora Liris Fitur Pencarian Visual Menggunakan AI, Lapak Teknologi. Available at: https://rambe.blog.uma.ac.id/2017/12/14/zalora-liris-fitur-pencarian-visual-menggunakan-ai/ (Accessed: March 8, 2026).
Sony and Suresh, R. (2026) “Impact of Virtual Try-On Features on Purchase Intention in Online Apparel Shopping,” International Journal of Advances in Business and Management Research (IJABMR), 3(3), pp. 37–49. Available at: https://doi.org/10.62674/ijabmr.2026.v3i03.004.
Venkatesh, V. et al. (2003) “User Acceptance of Information Technology: Toward a Unified View,” MIS Quarterly, 27(3), pp. 425–478. Available at: https://doi.org/10.2307/30036540.
Venkatesh, V. and Davis, F.D. (2000) “Theoretical extension of the Technology Acceptance Model: Four longitudinal field studies,” Management Science, 46(2), pp. 169–332. Available at: https://doi.org/10.1287/mnsc.46.2.186.11926.
Wu, D. et al. (2026) “Decoding developments and novel research pathways in e-commerce and livestreaming commerce through the lens of the technology acceptance theory: a bibliometric analysis,” Journal of Business Analytics, 9(1), pp. 43–64. Available at: https://doi.org/10.1080/2573234X.2025.2517139.
Zhang, Y. and Liu, C. (2026) “AI-Driven Consumer Research in Fashion: A Systematic and Bibliometric Review (2022–2025) and Future Research Agenda,” Journal of Theoretical and Applied Electronic Commerce Research, p. 74. Available at: https://doi.org/10.3390/jtaer21030074.
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