DOI: 10.11118/978-80-7701-025-2-0272
THE ALGORITHM EFFECT: HOW AI-DRIVEN TRAVEL PLANNING FUELS OVERTOURISM
- Emil Drápela
- Department of Geography, Faculty of Science, Humanities and Education, Technical University of Liberec, Czechia
Artificial intelligence (AI) is increasingly shaping tourist decision-making through recommendation systems embedded in travel platforms, search engines, and conversational AI models. This study examines how AI-generated travel recommendations contribute to overtourism by reinforcing the popularity of crowded destinations. Using an experimental approach, various GPT models were prompted to suggest travel destinations within selected regions of the Czech Republic. The results revealed a strong bias toward well-established tourist hotspots, many already experiencing overtourism-related challenges. Lesser-known locations, which could serve as alternative destinations to distribute tourist flows more evenly, were rarely recommended. These findings suggest that AI-driven travel planning, rather than diversifying visitor distribution, may amplify existing tourism imbalances by favouring destinations with high digital visibility and historical popularity. This study highlights the need for more responsible AI design in tourism applications to promote sustainable travel behaviours and mitigate overtourism.
Klíčová slova: AI-Driven Travel Recommendations, GPT Models in Tourism, overtourism, data-driven travel choices, tourism sustainability
stránky: 272-276, Publikováno: 2025, online: 2025
Reference
- Bryndin, E. (2019). Practical development of creative life-saving artificial intelligence. Communications, 7(2), 31. https://doi.org/10.11648/j.com.20190702.11
Přejít k původnímu zdroji... - Choe, Y. and Kim, H. (2021). Risk perception and visit intention on olympic destination: symmetric and asymmetric approaches. Journal of Vacation Marketing, 27(3), 314-329. https://doi.org/10.1177/1356766721995983
Přejít k původnímu zdroji... - Dias, Ã. et al. (2021). Selecting lifestyle entrepreneurship recovery strategies: a response to the covid-19 pandemic. Tourism and Hospitality Research, 22(1), 115-121. https://doi.org/10.1177/1467358421990724
Přejít k původnímu zdroji... - Drápela, E. (2023). Geoheritage and overtourism: a case study from sandstone rock cities in the Czech Republic. Geological Society Special Publication, 530(1), 257 - 275. https://doi.org/10.1144/SP530-2022-102
Přejít k původnímu zdroji... - Rahman, M. et al. (2021). Effect of covid-19 pandemic on tourist travel risk and management perceptions. Plos One, 16(9), e0256486. https://doi.org/10.1371/journal.pone.0256486
Přejít k původnímu zdroji... - Ramli, T. et al. (2023). Artificial intelligence as object of intellectual property in indonesian law. The Journal of World Intellectual Property, 26(2), 142-154. https://doi.org/10.1111/jwip.12264
Přejít k původnímu zdroji... - Tang, R. et al. (2022). Artificial intelligence in intensive care medicine: bibliometric analysis. Journal of Medical Internet Research, 24(11), e42185. https://doi.org/10.2196/42185
Přejít k původnímu zdroji... - Zheng, Y. et al. (2023). Designing human-centered ai to prevent medication dispensing errors: focus group study with pharmacists. Jmir Formative Research, 7, e51921. https://doi.org/10.2196/51921
Přejít k původnímu zdroji...

