Abstract
Augmented reality (AR) has promised the evolution of traditional shopping by satisfying consumers' needs for customization via advanced technology. However, existing studies have largely overlooked the customization process in AR retailing. By contextualizing affordance theory, this study endeavors to not only identify the novel customization affordances but also unveil the underlying mechanism determining different types of customer involvement and purchase decision. Importantly, this study carefully designed a three-stage hybrid research approach to address the complexity of consumers' decision-making in an emerging phenomenon. Integrating qualitative interviews, an SEM-based research model, and artificial neural network (ANN) analysis. The research results identified six customization affordances (i.e., selectivity, measurement, locality, controllability, responsiveness, and personalization) and unveiled a causal relationship among affordances, involvement, and purchase intention in the research model, enabling us to rank the importance of customization affordances in terms of their predictive power. This research offers a prominent methodological paradigm by demonstrating the contextualization of affordance theory in exploring the customization process in AR retailing using a mixed-method design. The research implications also advance the understanding of the paramount role played by customization affordance in shaping consumers' involvement and behaviors in AR retailing.
Published Version
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