The Benefit–Sacrifice Trade-Off of AI-Powered Fashion Services: Effects on Perceived Value and Intention to Use

This study investigates the benefit–sacrifice trade-off of artificial intelligence (AI)-powered fashion services by examining how perceived benefits (usefulness, timeliness, enjoyment) and perceived sacrifices (technical effort, privacy risk, lack of personalization) shape consumers’ perceived value and intention to use, drawing on the Value-based Adoption Model (VAM). Survey data were collected from 420 Millennial and Generation Z (MZ) consumers with prior experience using online fashion platforms, and the measurement and structural models were evaluated using SPSS 25.0 and AMOS 25.0 through confirmatory factor analysis, structural equation modeling, mediation analysis, and multi-group analysis. The results show that timeliness and enjoyment significantly increased perceived value, whereas usefulness and enjoyment directly increased intention to use. Technical effort negatively affected both perceived value and intention to use, while privacy risk showed no significant effect. Unexpectedly, lack of personalization positively influenced intention to use, suggesting that young consumers favor exposure to broad market trends over restrictive, narrowly tailored recommendations. Perceived value mediated the effects of the benefit–sacrifice factors, and consumer trust moderated the value–intention relationship, strengthening it among high-trust consumers. By integrating VAM with a benefit–sacrifice trade-off perspective, this study offers theoretical and practical insights for designing effective AI-driven fashion commerce strategies.