Rethinking Information Quality: How Trust in ChatGPT Shapes Destination Visit Intentions

The present study examines the role of ChatGPT as a travel advisor in influencing tourists’ decision-making in regard to destination visit intentions. Grounded in the Information Systems Success (ISS) model, this study explores three primary relationships: (1) the effect of information quality on users’ trust in ChatGPT’s travel recommendations, (2) the impact of trust in ChatGPT’s travel recommendations on destination visit intentions, and (3) the moderating role of destination images in the relationship between information quality and trust. This research employed a quantitative research design, collecting data from 528 Indonesian ChatGPT users. The findings show that information quality does not significantly shape users’ trust in ChatGPT’s travel advice, contradicting the classical ISS-Model prediction. In contrast, trust in ChatGPT’s travel recommendations exerts a significant positive effect on destination visit intentions, and the destination image fails to moderate the information–quality–trust link. This study provides practical guidance for Destination Management Organizations (DMOs), travel agencies, and policymakers seeking to optimize AI-driven tourism marketing by focusing on interactive storytelling and personalized engagement rather than solely focusing on information quality.