AI-Based Recommendation System, FOMO, and Online Impulse Buying Behavior: An S-O-R Perspective

Abstract

This study examines how AI-based recommendation system features influence online impulse buying behavior through the mediating role of fear of missing out (FOMO), based on the Stimulus-Organism-Response (S-O-R) framework. Using data from 365 online shoppers analyzed with PLS-SEM, four system attributes: accuracy, diversity, portability, and visual appeal were tested as stimuli affecting consumer responses. The structural and mediation analyses revealed that portability (β = 0.161, p < 0.001) and visual appeal (β = 0.238, p <0.01) significantly enhanced FOMO, which in turn increased impulse buying behavior (β = 0.350, p < 0.001). In contrast, accuracy (β = –0.101, p < 0.05) showed a negative effect, and diversity (β = 0.089, p = 0.051) showed no significant impact. FOMO fully mediated the relationships between portability, visual appeal, and impulse buying, confirming its central emotional role. Theoretically, the findings extend the S-O-R framework to AI-driven shopping environments by emphasizing emotional rather than purely functional system effects. Practically, enhancing visual appeal and portability can effectively boost user engagement, but ethical considerations are crucial to avoid excessive psychological influence.