From Feeds to Footsteps: How Museum-Generated Instagram Content Drives Visit Intention through Information Quality and Service Responsiveness, A PLS-SEM Study of Museum Sonobudoyo

Abstract

Museums increasingly rely on Instagram as a low-cost channel to communicate with prospective visitors, yet little quantitative evidence links museum-generated content (MGC) on Instagram to actual visit intention through intervening perceptual mechanisms. Grounded in the Stimulus-Organism-Response (S-O-R) framework, this study examined how MGC shapes visit intention (VI) toward Museum Sonobudoyo through the mediating roles of perceived information quality (IQ) and customer service responsiveness (CS). Data were collected from 155 respondents who follow the museum's official Instagram account and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with sample bootstrapping. The measurement model was assessed for internal consistency, convergent validity, and discriminant validity, while the structural model was tested for path significance, coefficient of determination (R2), and effect size (f2). Results show that MGC significantly predicts both IQ (β = 0.53, p < .001) and CS (β = 0.58, p < .001). IQ significantly predicts VI (β = 0.19, p < .05), whereas the direct effects of CS and MGC on VI were not statistically significant, indicating that information quality operates as the principal mediating pathway. The model explains 28.0%, 34.2%, and 14.9% of the variance in IQ, CS, and VI, respectively. Findings extend S-O-R theory to heritage-marketing contexts and offer practical guidance for museums seeking to convert Instagram engagement into physical visitation