Exploring Chinese Millennials’ Purchase Intentions for Clothing with AI-Generated Patterns from Premium Fashion Brands: An Integration of the Theory of Planned Behavior and Perceived Value Perspective - Xinjie Huang; Chuanlan Liu; Jiayao Wang; Jingjing Zheng (Journal of Theoretical and Applied Electronic Commerce Research)
Premium fashion brands are increasingly adopting Generative Artificial Intelligence (GenAI) to reduce costs and enhance creativity. However, consumers have mixed perceptions of clothing with AI-generated patterns (CAGPs) launched by premium fashion brands, especially in online shopping contexts where consumers cannot examine physical products firsthand. This study integrates the Theory of Planned Behavior (TPB) with Customer Perceived Value (CPV) to investigate Chinese Millennials’ attitudes and purchase intentions toward online purchases of CAGPs launched by premium fashion brands. Using a purposive sampling approach, the study collected 471 valid responses from Chinese Millennials. Structural equation modeling (SEM) was then employed to test the proposed model and hypotheses. The results reveal that perceived brand design effort and perceived price value are primary drivers of purchase intention for CAGPs from premium fashion brands, while perceived aesthetic value significantly shapes consumer attitudes. The subjective norm and attitude positively influence purchase intention. This study sheds light on the roles of aesthetic, emotional, monetary and social factors in driving purchase intention, offering practical suggestions for premium brands’ product design and marketing strategies.