Originality and Innovation in AI-Generated Clothing: Purchase Intention of AGC-Interested Young Chinese Consumers Toward Independent Designer Brands

Generative artificial intelligence (GenAI) is reshaping fashion design by expanding creative possibilities and accelerating innovation. For independent designer brands, which rely on originality, distinctive aesthetics, and creative identity, GenAI offers opportunities to sustain innovation while raising concerns about authenticity and consumer trust. However, consumer responses toward AI-generated clothing (AGC) among AGC-interested young Chinese consumers remain underexplored. This study explores factors influencing their attitudes and purchase intention toward AGC. Drawing on a TPB–TCV-based integrated framework, this study develops an integrated model incorporating consumption value dimensions, perceived effort of the brand in design (PEBD), generative quality (GQ), and AI creativity (AIC). Based on 568 valid questionnaires, PLS-SEM was employed, with multi-group analysis as a supplementary analysis. The results show that attitude plays a key mediating role in explaining purchase intention. Specifically, PEBD and subjective norm significantly predict purchase intention, while PEBD also indirectly influences purchase intention through attitude. Emotional, epistemic, and social values, PEBD, GQ, and AIC significantly contribute to attitude formation, whereas only PEBD and subjective norm demonstrate significant direct effects on purchase intention. These findings provide managerial insights for independent designer brands seeking to apply GenAI while considering consumer perceptions of creativity, originality, and value in shaping AGC purchase intention.