Loading article...
Loading article...
Stream/Area:
-
Subject:
-
Paper ID:
IJSREM64406
Volume:
10 |
5 |
May 2026
Pages:
1-4
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
School Of Architecture Planning And Design
Sanjeev Agrawal Global Educational [SAGE] University, Bhopal
School Of Architecture Planning And Design
Sanjeev Agrawal Global Educational [SAGE] University, Bhopal
School Of Architecture Planning And Design
Sanjeev Agrawal Global Educational [SAGE] University, Bhopal
The integration of Artificial Intelligence (AI) and virtual try-on technologies has significantly transformed the online fashion retail landscape by enhancing personalization and consumer engagement. Despite these advancements, concerns regarding the accuracy of virtual clothing representations continue to affect consumer satisfaction and trust. This conceptual paper examines the role of virtual clothing accuracy as a critical determinant of consumer satisfaction in the context of AI styling recommendations. Drawing on established theoretical perspectives, including Expectation- Confirmation Theory and the Technology Acceptance Model, the study proposes a conceptual framework that links virtual clothing accuracy with consumer satisfaction through the mechanism of AI recommendation quality and consumer trust. The paper argues that accurate visualization of clothing attributes such as fit, color, and texture reduces uncertainty, aligns consumer expectations with actual product outcomes, and enhances the perceived usefulness of AI-driven recommendations. By integrating technological and behavioral perspectives, this study contributes to the growing literature on AI in fashion retail and highlights the importance of accuracy as a psychological enabler of positive consumer experiences.
KEYWORDS
This study highlights that accuracy is not merely a technical attribute but a critical psychological determinant that shapes consumer perceptions and trust. Accurate virtual representations reduce uncertainty and enhance the perceived usefulness of AI recommendations. Improving virtual clothing accuracy emerges as a key priority for ensuring the success and long-term adoption of AI-enabled fashion platforms.
Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351–370. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51–90. Huang, M. H., & Rust, R. T. (2021). Artificial intelligence in service. Journal of Service Research, 24(1), 3–21. Javornik, A. (2016). ‘It’s an illusion, but it looks real!’ Consumer responses to augmented reality applications. Journal of Marketing Management, 32(9–10), 987–1011. Mustak, M., Salminen, J., Plé, L., & Wirtz, J. (2021). Artificial intelligence in marketing. Journal of Business Research, 124, 389–404. Poushneh, A., & Vasquez-Parraga, A. Z. (2017). Discernible impact of augmented reality on retail customer experience. Journal of Retailing and Consumer Services, 34, 229–234. Venkatesh, V., et al. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425–478.
Publication Date
6/1/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
Documents
Article Views
0
Total views since publication
PDF Downloads
8
Total downloads since publication
Geographic Reach
5
Digital Preservation: This article is permanently archived on Zenodo and complies with all data preservation standards across major indexing platforms.
Plagiarism Screening
This manuscript has been checked for plagiarism using TurnitinPlagiarismChecker software.
Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
Related research in the same subject area
Loading similar articles...