When Generative AI Is Reported as a Leading Travel Information Source: Rank-Sensitive Associations with Completed-Trip Portfolios and Implications for Sustainable Destination Governance
Generative artificial intelligence (GenAI) is reshaping travel information search, but binary use measures may obscure whether it is a leading or merely listed source. This exploratory study examines rank-sensitive associations between GenAI source position and completed-trip outcomes in the 2024 Seoul Foreign Tourist Survey. Among 2669 respondents with valid ranked online source data and complete covariates, 23 ranked GenAI first or second, 37 ranked it third, and 2609 did not report it. The primary leading-versus-no-GenAI contrast used pairwise overlap weighting, 4999 propensity-score-refitted bootstrap replications, and explicit common support restriction. Leading-GenAI respondents had a higher exploratory portfolio expansion summary (adjusted difference = 0.26 SD, 95% CI [0.03, 0.50]) and a lower iconic/heritage visitation index (−0.36 SD, 95% CI [−0.54, −0.16]). Destination evaluation was lower in direction (−0.34 SD), but its interval included zero (95% CI [−0.72, 0.02]). Support-restricted estimates were nearly identical. Component results indicated greater spending breadth, not higher total spending; communication satisfaction did not differ. Any-rank and third-rank comparisons did not reproduce the pattern, and ordinal rank trends were imprecise. These exploratory observational findings apply to a covariate-overlap population and suggest that reported source position may matter for completed-trip portfolio composition, without establishing a universal, dose–response, causal, or destination-sustainability effect.
Authors
- Jungwon Lee (ORCID: https://orcid.org/0000-0002-3621-0179)
- Cheong Dong Kim
Institutions
- Dongyang University (KR)
- Cultural Heritage Administration (KR)
Publication Details
- Journal
- Sustainability
- Published
- 2026-09-01
- DOI
- https://doi.org/10.3390/su18178955
- Primary Topic
- AI in Service Interactions
- Type
- article
- Field-Weighted Citation Impact
- 0.00