Understanding the Design Personalization of Fashion Products Using Computational Design Methods: Practical Insights into Consumer Perceptions

Abstract This paper explores user perceptions of the design personalization of fashion products using a computational design method from the designer’s point of view. As for the research methodology, ten participants were asked to design textile patterns for their own fashion clutch bags by using a design personalization tool developed using Generative Design Methods (GDM), one of the computational design methods for personalizing product design. Subsequently, in-depth interviews were conducted to collect consumer thoughts on the aforementioned design personalization experience. Their central cognitive nodes were analyzed based on the means-end chain (MEC) model. The hierarchical value analysis results of the MEC model showed core linkages among the attributes, consequences, and values levels that participants perceived prominently for a given design personalization experience. The primary cognitive paths for consumers mainly focused on hedonic values and satisfaction as a destination, triggered by inspiring and fun design experiences, as well as solving design problems for non-professionals provided by GDM-based design personalization processes. This study’s findings can provide practical insights and guidance for designers and service planners to understand how their ideas can be placed in the consumer market while planning and designing digital design personalization services.