THE ALGORITHM EFFECT: HOW AI-DRIVEN TRAVEL PLANNING FUELS OVERTOURISM

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24510%2F25%3A00013976" target="_blank" >RIV/46747885:24510/25:00013976 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.mendelu.cz/pdfs/doi/9900/08/5700.pdf" target="_blank" >https://doi.mendelu.cz/pdfs/doi/9900/08/5700.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

THE ALGORITHM EFFECT: HOW AI-DRIVEN TRAVEL PLANNING FUELS OVERTOURISM

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

THE ALGORITHM EFFECT: HOW AI-DRIVEN TRAVEL PLANNING FUELS OVERTOURISM

Popis výsledku anglicky

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.

Druh

O - Ostatní výsledky

CEP obor

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OECD FORD obor

50701 - Cultural and economic geography

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů