Social Network Usage, Fear of Missing Out, AR-AI Virtual Try-On Attitudes, and Online Purchase Intention: A Systematic Evidence Review and Meta-Analysis
Main Article Content
Abstract
Objective: This review synthesises evidence concerning four relationships: social network usage and online purchase intention; FoMO and online purchase intention; social network usage and FoMO; and AR-AI VTO-related attitudes/experiences and online purchase intention, with particular attention to students and young digital consumers.
Methods: PRISMA 2020 principles were used to structure the review. Peer-reviewed, web-accessible empirical studies were screened for conceptual relevance and quantitative information. Pearson correlations were extracted where directly reported and conceptually comparable. A random-effects meta-analysis was conducted for the FoMO–purchase-intention relationship using five independent samples with directly extractable correlations. Published meta-analytic evidence was used to contextualise the social-media-use–FoMO relationship. AR-AI VTO evidence was synthesised narratively because the available studies used non-equivalent constructs and SEM coefficients rather than a common correlation.
Results: Five independent samples (total N = 1148) provided directly extractable FoMO–purchase-intention correlations ranging from r = .24 to .70. The random-effects pooled association was r = 0.41, 95% CI [0.20, 0.59], with substantial heterogeneity (Q = 64.92, df = 4, I² = 93.8%, τ² = 0.067). A separate published meta-analysis of social-media use and FoMO included 65 studies and 70 independent effect sizes and reported significant heterogeneity. Student-specific primary evidence included a 2,058-student international sample showing positive correlations between two forms of social-media use and purchase intention, and a 2025 Danang student study linking FoMO with purchase intention through psychological pathways.
Conclusion: FoMO is positively associated with purchase intention in the directly extractable consumer evidence, but the high heterogeneity and differences in populations and purchase contexts limit causal or student-specific generalisation. AR-AI VTO findings support its relevance to purchase intention, but a common quantitative effect should not be manufactured from heterogeneous SEM models.