Fashioning the Future with AI: Technology Acceptance and Expectation Confirmation of Integrated Design Platforms in Chinese Fashion Design Education
Xinjie Huang, Zhicheng Wang, Jixu Hao, Hangyu Zheng, Rongrong Cui · Systems · 2025
Due to the limitations of general-purpose generative artificial intelligence (GenAI) platforms in meeting the needs of fashion design, AI-based integrated fashion design platforms (AIIFDP) have emerged as a more suitable solution. As the next generation of designers, fashion design students play a pivotal role in shaping the optimization and promotion of AIIFDP. However, research on their continuance intention toward such platforms remains limited. This study constructs an integrated model by combining the Unified Theory of Acceptance and Use of Technology (UTAUT) with the Expectation-Confirmation Model (ECM), and extending it with variables such as personal innovativeness, habit, and perceived intelligence. Using a multi-stage SEM-ANN analysis, the study empirically analyzed data from 486 questionnaires completed by fashion design students in China. The results suggest that satisfaction is the most significant positive factor influencing continuance intention. Moreover, performance expectancy, social influence, perceived intelligence, and habit also exert significant effects. This study broadens the segmented perspective on the application of GenAI in design education and validates the applicability of the extended UTAUT-ECM model in the context of AIIFDP. It also provides theoretical foundations and multi-level strategic recommendations for optimizing AIIFDP products and guiding their integration into educational practices.