The use of synthetic data in tourism
• Large language models can support stimuli evaluation. • Synthetic data suits early research such as pretests; avoid it for main studies. • Prompt-tuning and fine-tuning improve large language model's responses.
Authors
- Susanne Adler (ORCID: https://orcid.org/0000-0002-3211-6871)
- Caroline Lancelot Miltgen (ORCID: https://orcid.org/0000-0001-7170-1451)
- Marko Sarstedt (ORCID: https://orcid.org/0000-0002-5424-4268)
- Giampaolo Viglia (ORCID: https://orcid.org/0000-0001-8521-4988)
Institutions
- Audencia Business School (FR)
- Babeș-Bolyai University (RO)
- University of Aosta Valley (IT)
- University of Portsmouth (GB)
- Ludwig-Maximilians-Universität München (DE)
Publication Details
- Journal
- Annals of Tourism Research
- Published
- 2024-08-09
- DOI
- https://doi.org/10.1016/j.annals.2024.103819
- Citations
- 15
- Primary Topic
- Topic Modeling
- Type
- article
- Field-Weighted Citation Impact
- 5.21