A data-driven SEM-PLS model of tourist satisfaction and revisit intention: The role of social media analytics and service quality in digital tourism

Abstract

This study develops a data-driven model to examine the determinants of tourist satisfaction and revisit intention by integrating social media analytics and service quality factors within a digital tourism context. The rapid growth of big data generated through social media platforms has transformed how tourists perceive destinations, evaluate experiences, and make revisit decisions. However, limited studies have incorporated social media-driven variables into structural behavioral models in tourism research. This research proposes a comprehensive framework that includes brand image based on local wisdom, product quality, social media analytics, attitude, experience, and perceived risk as key predictors of tourist satisfaction and revisit intention. Data were collected from 160 domestic and international tourists visiting Belimbing Tourism Village, Bali, using a purposive sampling technique. The proposed model was analyzed using Structural Equation Modeling with Partial Least Squares (SEM-PLS), which is well-suited for predictive and complex data-driven analysis. The findings reveal that social media analytics, brand image, and product quality have significant positive effects on both tourist satisfaction and revisit intention, highlighting the critical role of digital engagement and online content in shaping tourist behavior. Attitude significantly influences satisfaction but does not directly affect revisit intention, while experience and perceived risk show no significant effects. Satisfaction is found to be a strong predictor of revisit intention and partially mediates the relationships between key antecedents and behavioral outcomes. This study contributes to the literature by integrating big data perspectives into tourism behavior modeling and demonstrates how social media-derived insights can enhance predictive accuracy in tourism analytics. Practically, the results suggest that tourism managers should leverage social media data, digital engagement metrics, and data-driven marketing strategies to strengthen destination competitiveness and foster sustainable revisit behavior.