Making virtual real: User-informed design priorities in the physicalization of AI-generated clothing

Abstract

Amid growing efforts to showcase design capability and meet young users’ demand for novel identities, fashion brands are increasingly engaging in the physicalization of AI-generated virtual clothing. This study explores how Chinese Generation Z users evaluate and prioritize the design outcomes of physicalized AI-generated virtual clothing (PAGVC) from a multidimensional perspective. The study adopted a mixed-methods approach. First, a literature review and semi-structured interviews were conducted to identify relevant user-informed design attributes. Then, a questionnaire was developed and tested, collecting 631 valid responses from Chinese Generation Z. Factor analysis revealed nine key factors, and entropy weighting determined the relative importance of each. Findings show that “Brand Design Performance” ranked highest, followed by “Design Rationality”, “Actual Wearability”, and “Creativity”. Based on these, the study proposes design optimization strategies. This study provides a data-driven, designer-oriented user perception–feedback framework to support efficient decision-making by designers and fashion brands in the design of PAGVC.