Despite the growing adoption of Virtual Fitting Room (VFR) technology, further investigation is needed to understand the acceptance of digital technologies among users with physical disabilities. Existing studies have provided limited insight into the behavioural responses of individuals with physical disabilities after using VFR. Therefore, this study aims to develop a VFR acceptance model to examine the behavioural intention to use VFR among individuals with physical disabilities living in mainland China and Taiwan. Three psychological factors—perceived fun, self-efficacy, and perceived convenience—were integrated into the Technology Acceptance Model (TAM) to explore their influence on users’ potential intention to adopt VFR. Questionnaire data were collected from 427 individuals with physical disabilities living in these two regions. Structural equation modelling was employed to test the research model and evaluate ten proposed hypotheses. The results indicate that perceived fun positively influences both users’ attitudes toward using VFR and their behavioural intention to use it. Self-efficacy directly and positively affects perceived usefulness, while perceived convenience has a significant positive effect on perceived ease of use. This study extends TAM by constructing a VFR acceptance model tailored to individuals with physical disabilities, enriching the theoretical understanding of VFR usage behaviour in this population. The findings offer valuable implications for future research and provide guidance for the design, development, and marketing of digital technology–assisted products for individuals with physical disabilities.
Exploring key psychological factors influencing virtual fitting room adoption among individuals with physical disabilities
Xin-Zhu Li,Wen-Hung Chao,Xin Kang,Chen Han,Yan-Fen Pang,Xen-Xuan Ji,Zhao-Hua Zhu,Hongguang Zhao,Xiao-Xia Bai
Published 2026 in Scientific Reports
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- Publication year
2026
- Venue
Scientific Reports
- Publication date
2026-02-02
- Fields of study
Medicine, Psychology
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Semantic Scholar
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