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The AI Revolution in Virtual Try-Ons: A Means-End Chain Model Perspective
Ju-Young M Kang1, Ji Young Lee2, Dooyoung Choi3
1Department of Family and Consumer Sciences, University of Hawai'i at Mānoa, Honolulu, HI 96822, USA.
Behavioral Sciences (Basel, Switzerland)
|July 28, 2026
Summary
Artificial intelligence-driven virtual try-on (AI VTO) enhances customer loyalty by improving value equity. Perceived quality factors like customization positively influence AI VTO value, boosting satisfaction and repeat purchases.
Area of Science:
- * Consumer behavior research
- * Human-computer interaction
- * Retail technology adoption
Background:
- * Leading brands are adopting AI VTO technology to enhance customer experience and operational efficiency.
- * AI VTO aims to reduce returns and increase conversion rates, repeat purchases, and customer loyalty.
- * Understanding the influence of perceived quality on user value and loyalty is crucial for AI VTO implementation.
Purpose of the Study:
- * To examine how perceived quality factors of AI VTO influence user value equity and loyalty.
- * To investigate the moderating effects of clothing-self relationship and appearance concern on AI VTO user experience.
- * To validate the applicability of the Means-End Chain model in the AI VTO context.
Main Methods:
- * Data collected from 509 U.S. online apparel shoppers via a consumer panel.
- * Structural equation modeling (SEM) and multigroup analysis employed for data analysis.
- * Analysis based on the Means-End Chain model framework.
Main Results:
- * Pragmatic quality, hedonic quality, and customization positively impact AI VTO value equity.
- * Value equity positively influences satisfaction, leading to increased repurchase and brand loyalty.
- * The impact of value equity on satisfaction is stronger for users with higher clothing-self connection.
Conclusions:
- * AI VTO quality attributes significantly shape user value equity, satisfaction, and loyalty.
- * The Means-End Chain model effectively explains the quality-value-satisfaction-loyalty chain in AI VTO.
- * Findings identify key AI VTO features influencing user assessment and behavioral outcomes.
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