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...

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Bibliographic Details
Published inJournal of travel research
Main Authors Xiong, Xiling, Wong, IpKin Anthony, Huang, GuoQiong Ivanka, Peng, Yixuan
Format Journal Article
LanguageEnglish
Published 05.09.2024
Online AccessGet full text
ISSN0047-2875
1552-6763
DOI10.1177/00472875241275945

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Summary: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.
ISSN:0047-2875
1552-6763
DOI:10.1177/00472875241275945