Understanding AI virtual try-on adoption and continuance: a multi-study approach

This study examines consumer behavior toward AI-powered virtual try-on platforms in beauty and fashion e-commerce using a dual-phase, mixed-method U&G framework. A qualitative phase (n = 15) supported candidate construct seeding, followed by a two-wave, temporally separated SEM survey design (T1 = 380; T2 = 347) to reduce common method bias. The first phase (T1) examines initial adoption intentions, revealing that convenience, entertainment, and perceived personalization positively drive usage intention, while enjoyment negatively moderates personalization due to hedonic expectation saturation – where highly entertained users emphasize exploratory self-presentation and cognitive fluency over outcome-driven personalization. The second phase (T2) investigates post-adoption continuance behavior, showing that information seeking, appearance enhancement, and social influence positively drive continuance intention, moderated by trust in AI output, forming a reinforcing AI-trust loop. This study refines U&G by incorporating hedonic saturation and AI-trust reinforcement, offering both theoretical and practical insights for immersive retail design in emerging digital markets.