The Role of Augmented Reality (AR) in Online Fashion Shopping on Gen Z Customers’ Purchase Intention in Can Tho City
Year: 2026
Type: conference-paper
Study design: Observational Study
Abstract: This study attempts to explore the drivers of Generation Z consumers’ online purchase intention toward fashion products in Can Tho City, Vietnam, by considering the mechanisms for creating value using augmented reality (AR) shopping experiences. Based on the Stimulus–Organism–Response (S–O–R) theory and technology acceptance literature, the theoretical model proposed identifies interactivity and informativeness as technological stimuli that influence internal evaluations regarding utilitarian value, hedonic value, and ease of use, which eventually affect attitude and online purchase intention. To test the proposed hypotheses, data have been gathered from 755 Generation Z customers and analyzed using partial least squares structural equation modeling (PLS-SEM). Results show that informativeness has greater impacts on utilitarian value, hedonic value, and ease of use than interactivity. Additionally, hedonic value and utilitarian value positively contribute to attitude toward AR, and attitude is identified as the strongest driver of purchase intention. From these findings, we can conclude that the fashion industry should consider the proactive application of augmented reality as a primary value-creation tool. Enhancing the informativeness of augmented reality is crucial. Offering realistic product visualisation, precise size and colour comparisons, comprehensive descriptions, and integrated user feedback can markedly diminish ambiguity and enhance perceived utilitarian value. Enhancing AR interactivity and system usability is essential for promoting both hedonic pleasure and user-friendliness. Seamless virtual try-on capabilities, rapid system responsiveness, and an intuitive interface design can augment emotional connection and foster a more immersive shopping experience.
Institution: FPT University
Language: English
Subfield: Information Systems and Management
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7214729205