Research on user behavior of traditional Chinese medicine therapeutic smart clothing

Abstract Smart clothing, as a cutting-edge artificial intelligence product integrating fashion and technology, demonstrates substantial market potential. However, smart clothing featuring traditional Chinese medicine (TCM) therapeutic functions has yet to achieve widespread adoption, with notably low usage frequency and short application cycles among users. To address this challenge, this study constructs a theoretical model of user behavior for TCM therapeutic smart clothing by integrating the Technology acceptance model, theory of planned behavior, and perceived risk (PR) theory. A multi-stage research design was adopted. A structured questionnaire based on established scales yielded 567 valid online responses (response rate: 97.7%), providing empirical support. Descriptive statistics and cluster analysis explored sample characteristics and group differences. Confirmatory factor analysis assessed measurement reliability and validity, while structural equation modeling tested hypothesized relationships. Additionally, hierarchical regression and simple slope analysis examined the moderating effect of user technology literacy (UTL). Results showed that perceived ease of use (PEOU) and perceived usefulness significantly enhanced user stickiness, which positively influenced usage behavior. PR negatively affected stickiness, and UTL moderated the link between PEOU and stickiness. Notably, perceived behavioral control and perceived cost did not show significant effects, suggesting users prioritize functional benefits and health outcomes over controllability and economic concerns. This study integrates theoretical and empirical analysis to quantify key behavioral factors, offering insights for product design, marketing, and user experience optimization in TCM therapeutic smart clothing.