Vlog information characteristics and audience involvement on check-in intention at instagrammable tourist places

Travel vlogs serve as vital vehicles for constructing and promoting instagrammable tourist destinations. Drawing on Interaction Ritual Chain theory and the elaboration likelihood model (ELM), this study investigates how multimodal information attributes of travel vlogs, together with audience involvement, jointly shape viewers’ check-in intentions. Multimodal data analyses yield four observations: rich scene diversity and natural visual cues strengthen visual attractiveness; natural dialogue and authentic human voices can cultivate affinity; properly timed background music enhances the immersive experience; and vloggers’ targeted replies to viewer questions significantly raise audience interactivity and willingness to engage. Second, necessary condition analysis reveals that perceived similarity, which operates through the peripheral route of ELM, acts as a necessary condition for vlog viewers to develop check-in intention, exhibiting both a significant bottleneck effect and incremental influence on check-in intention. Third, four configuration paths are identified by fuzzy set qualitative comparative analysis: emotional resonance, rational analysis, information-driven with vloggers’ impact, and content guidance with perceived similarity. These reveal diverse mechanisms that collectively shape viewers’ intention to check in at instagrammable tourist places.