Bridging The Green Gap with Fashiontech: How AI-Driven Styling Apps Enhance Sustainable Fashion Consumption

This study investigates how AI-driven FashionTech applications influence sustainable fashion consumption within the Stimulus–Organism–Response (S–O–R) framework. While digital styling tools are increasingly embedded in consumers' shopping journeys, their role in shaping sustainability-related knowledge and behavior remains underexplored. Analyzing a large-scale secondary dataset of 7,174 global consumers, a structural equation model (SEM) was estimated to test the effects of two technology stimuli—app usage and visual search features—on environmental knowledge and subsequent behavioral outcomes. Results show that both app use and visual search significantly increase sustainability knowledge (β = 0.07, p < 0.001). Knowledge, in turn, enhances consumers' willingness to pay a premium for sustainable fashion (β = 0.05, p < 0.001). App use also directly increases willingness to pay (β = 0.12, p < 0.001) and reduces overall shopping frequency (β = –0.05, p < 0.001), indicating a shift toward more conscious consumption. Visual search does not significantly influence shopping frequency (β = –0.01, n.s.), suggesting that its role is primarily cognitive. The study contributes to digital consumer behavior literature by demonstrating that AI-enabled fashion tools can generate meaningful but incremental progress toward sustainable consumption.