Attitudes and Purchase Intentions for Smart Clothing

Abstract

This research extends the technology acceptance model with apparel design attributes and examines factors influencing consumers’ attitudes and purchase intentions of smart clothing, specifically, solar-powered clothing. A random sample of college students and faculty ( N = 720) participated in this study. Results from structural equation modeling reveal that perceived usefulness is the strongest predictor of attitude and purchase intention. Perceived compatibility is the strongest predictor of perceived usefulness, and along with perceived comfort, it determines perceptions of usefulness, ease of use, and performance risk. Perceived performance risk, aesthetic attributes, and environmental concern are significant predictors of attitude. This research validates the technology acceptance model in explaining new technology adoption in clothing and confirms the importance of multiple dimensions of smart clothing. Retailers can emphasize the shift from a technical concern to a user-centered one by highlighting utilitarian aspects of clothing and providing compatible and aesthetically appealing design features that interconnects functionality, expressiveness, and aesthetics (FEA) consumer needs.