Closing the intention–behavior gap: the role of ai-enabled personalization in promoting sustainable fashion consumption among vietnamese youth

Abstract

The growing environmental impact of the fashion industry has driven attention toward sustainable consumption behaviors, particularly among digitally active young consumers. Despite rising awareness, a persistent intention–behavior gap hampers sustainable fashion adoption, especially in emerging markets like Vietnam. This study investigates the role of artificial intelligence-enabled personalization (AIP) in bridging the persistent intention–behavior gap in sustainable fashion consumption (SFC) among Vietnamese Generation Y and Z consumers. Despite increasing awareness of sustainability, actual consumer behavior in developing markets remains inconsistent with pro-environmental intentions due to informational and cognitive barriers. Drawing upon Stimulus–Response (S–R) theory and the Theory of Planned Behavior (TPB), this study conceptualizes AIP as an external digital stimulus that enhances both sustainable fashion consumption intention (SFCI) and behavior (SFCB). A cross-sectional survey was conducted with 260 Vietnamese online fashion consumers aged 18–40, and data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results reveal that AIP significantly and positively influences both SFCI and SFCB. Furthermore, SFCI mediates the relationship between AIP and SFCB, supporting the theorized dual-pathway model. These findings validate AIP as a technological intervention that can directly trigger behavioral change and also operate indirectly by enhancing pro-sustainability intentions. This research highlights the potential of AI-driven strategies in advancing sustainable consumption goals in emerging digital economies. Research purpose: To examine whether artificial intelligence-enabled personalization (AIP) enhances sustainable fashion consumption intention (SFCI) and behavior (SFCB), and whether SFCI mediates this relationship among Vietnamese youth. Research motivation: Despite growing environmental awareness, a significant intention–behavior gap persists in sustainable fashion consumption in Vietnam. Prior research has rarely examined the potential of AI tools, particularly AIP, as a solution in emerging market contexts. Research design, approach, and method: A quantitative, cross-sectional survey design using a non-probability convenience sample of 260 Gen Y and Z Vietnamese consumers. Data were analyzed using PLS-SEM to assess measurement and structural models. Main findings: AIP positively influences both SFCI and SFCB. SFCI also significantly mediates the relationship between AIP and SFCB, confirming the proposed dual-pathway mechanism. Practical/managerial implications: E-commerce platforms and fashion retailers should optimize AIP systems to enhance sustainability perceptions, simplify green decision-making, and use social proof to encourage eco-friendly purchases.