Understanding AI-Generated Experiments in Tourism: Replications Using GPT Simulations

The present work explores whether the generative pre-trained transformers (GPT) can complement empirical research in tourism as the GPT extends beyond commercial applications. In particular, we utilized OpenAI’s Python API to interact with the GPT-3.5-turbo. Using GPT as a special subject, we coined AI-generative study (AGS) to validate key findings of 16 scenario-based experiments published in leading journals of tourism and hospitality in two studies. This research contributes to the literature by delineating a new methodology that opens a forum for discussion on alternative means of conducting tourism research. Future studies could also utilize GPT and the ability of generative AI for tourism research in terms of pilot-/pre-testing and cross-validation. In conclusion, we recommend that GPT-generated results should serve primarily as preliminary findings and must be corroborated by data from actual human participants, thus providing converging evidence to support the corresponding research conclusions.

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Publication Details

Journal
Journal of Travel Research
Published
2024-09-05
DOI
https://doi.org/10.1177/00472875241275945
Citations
23
Primary Topic
Explainable Artificial Intelligence (XAI)
Type
article
Field-Weighted Citation Impact
7.99

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article

Understanding AI-Generated Experiments in Tourism: Replications Using GPT Simulations

Xiling Xiong, IpKin Anthony Wong, GuoQiong Ivanka Huang, Yixuan Peng
23 citations
Journal of Travel Research
Explainable Artificial Intelligence (XAI)
7.99
article

Understanding AI-Generated Experiments in Tourism: Replications Using GPT Simulations

Xiling Xiong, IpKin Anthony Wong, GuoQiong Ivanka Huang, Yixuan Peng
article en
23 citations

Abstract

The present work explores whether the generative pre-trained transformers (GPT) can complement empirical research in tourism as the GPT extends beyond commercial applications. In particular, we utilized OpenAI’s Python API to interact with the GPT-3.5-turbo. Using GPT as a special subject, we coined AI-generative study (AGS) to validate key findings of 16 scenario-based experiments published in leading journals of tourism and hospitality in two studies. This research contributes to the literature by delineating a new methodology that opens a forum for discussion on alternative means of conducting tourism research. Future studies could also utilize GPT and the ability of generative AI for tourism research in terms of pilot-/pre-testing and cross-validation. In conclusion, we recommend that GPT-generated results should serve primarily as preliminary findings and must be corroborated by data from actual human participants, thus providing converging evidence to support the corresponding research conclusions.

Journal of Travel ResearchVol. 64(8)
Hong Kong Polytechnic University (HK), University of Macau (MO), Southwestern University of Finance and Economics (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 2%
Explainable Artificial Intelligence (XAI)
7.99
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