Visual Search in Fashion Retail: Linking Assortment Variety, Search Costs, and Experiential Benefits to Consumer Satisfaction

Fashion Visual Search (FVS), driven by AI technology, has transformed how consumers search for fashion products online, enabling image-based searches that replace traditional text-based methods. Despite these advancements, gaps in research persist regarding the strategic development of FVS to enhance consumer search experiences. Conducting an online experiment within a virtual mobile shopping environment, this study investigates how the assortment variety of FVS search results influences consumer satisfaction, mediated by search costs and experiential benefits related to information search values. The findings reveal that a lower assortment variety of FVS search results increases consumer satisfaction by reducing search costs, particularly among highly fashion-involved consumers. Conversely, a higher assortment variety enhances consumer satisfaction through improved experiential benefits, consistently across different levels of fashion involvement. By exploring these dynamics, this research provides insights into optimizing FVS for enhanced consumer experiences and effective deployment in digital retail strategies.