Leveraging user-generated content (UGC) in pre-travel behavior: A PLS-SEM and necessary conditions analysis (NCA) approach

Abstract

Online review reading is almost ritualistic before making any purchases. Building on social cognition theory, uses and gratification theory, and stimulus organism response theory, this study explores user-generated content (UGC) attributes affecting intentions to travel via a mediating variable (destination image). Using partial least squares structural equation modeling (PLS-SEM) analysis and necessary conditions analysis (NCA) on responses ( N = 392) collected online in India, the findings reveal that the perceived novelty of content (PNC) and perceived value of content (PVC) positively influence destination image and behavioral intention. Destination image mediates the relationship between PNC, PVC, and content users’ behavioral intentions. Perceived reliability of content (PRC) positively affects behavioral intention. The findings suggest that adequate PNC, PRC, and PVC levels are necessary to enhance destination image and generate intention to travel. This study contributes to the UGC literature and provides recommendations for stakeholders to improve user experience and enhance destination image perception.