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When ChatGPT Gives Incorrect Answers: The Impact of Inaccurate Information by Generative AI on Tourism Decision-Making
Open accessAbstract
This study investigates how inaccurate information provided by ChatGPT impacts travelers’ acceptance of recommendations. Six experiments were conducted based on the accessibility-diagnosticity framework. These examined the moderating role of the prominence and type of incorrect information and their effects on decision-making. The results show that participants perceived more accuracy and trustworthiness, leading to stronger intentions to visit when incorrect information was absent. However, there was a decline in their intentions to visit when incorrect information was present and more prominent or in the same domain. This effect diminished when multiple domains were involved or when participants were focused on the initial task. The research highlights that both the prominence and type of incorrect information are boundary conditions and provides insights into AI applications in tourism. Furthermore, it offers practical implications for online travel agencies in terms of user interface and user experience design planning.
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“Finally, AI-generated misinformation influences attitudes and decisions (Kim et al. 2023; Spitale et al. 2023).”
From Generative AI and misinformation: a scoping review of the role of generative AI in the generation, detection, mitigation, and impact of misinformation (2026) · cites this paper as Kim et al. 2023
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“Kim et al. (2025) found that when ChatGPT provided incorrect recommendations, users were less likely to rely on the GenAI tools and less inclined to act on its advice.”
From Perceived Search Overload, Generative AI Credibility, and Comparative Usefulness: A Channel Complementarity Approach to Health Information Seeking (2025) · cites this paper as Kim et al., 2025
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Metadata
- Authors
- Kim, J. H., Kim, J., Park, J., Kim, C., Jhang, J., & King, B.
- Affiliations
- Kyung Hee University (KR)
- Peking University (CN)
- Ritsumeikan University (JP)
- University of Central Arkansas (US)
- Texas A&M University (US)
- Corresponding author
- Kim, Jeong Hyun
- Venue
- Journal of Travel Research
- Publisher
- SAGE Publications
- Published
- 2023-11-29
- Volume
- 64
- Issue
- 1
- Pages
- 51-73
- ISSN
- 0047-2875 (ISSN-L)
- 1552-6763
- OpenAlex
- W4389201667
- Cited by
- 202
- References
- 90
- Citations by year
- 2026: 82 · 2025: 91 · 2024: 29
- FWCI
- 19.04
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Travel Research (publishedVersion)
- Topics
- Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
- Social Sciences › Business, Management and Accounting › Tourism, Leisure and Hospitality Management › Diverse Aspects of Tourism Research
- Social Sciences › Business, Management and Accounting › Marketing › Digital Marketing and Social Media
- Keywords
- ChatGPT, generative AI, incorrect information, tourist decision-making, recommendation acceptance, trustworthiness, visit intention, online travel agencies, user interface design, user experience design
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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