Generative Adversarial Networks in Fashion Retailing and Customer Purchase Intention: An Extension of Theory of Consumption Value

Abstract

The emergence of generative adversarial networks (GANs) in marketing, a component of artificial intelligence (AI) technology, has the potential to influence customer behaviour in a variety of ways. In various contexts, the theory of consumption value (TCV) has elucidated customer behaviour. Few studies have applied TCV to GAN in marketing, particularly in fashion retailing. To close the gap, this study extends TCV to GAN-fashion retailing. A mixed research approach began with a 12-participant explorative focus group discussion to identify factors and develop the questionnaire. Second, we conducted a stratified random sampling-based cross-sectional survey and distributed the questionnaire to 258 diverse respondents. Analytical methods included structural equation modelling. It is discovered that decision-intelligent infrastructure (representing functional value) was a major driver of purchase intention in the GAN-fashion retailing context. This study has also found contradictory results and also discussed the reasons behind them. Overall, this has contributed in both the theoretical area, by extending the TCV framework in GAN-fashion retailing, and the managerial area, by making some suggestions. Also, it has opened up many new avenues for future study in the GAN-fashion retailing context.