Generative artificial intelligence for sustainable tourism : alleviating cognitive overload to foster well-being and eco-responsible behavior
Overview & Synopsis
The rise of AI-driven technologies, particularly generative AI (GenAI) like ChatGPT, is transforming customer service in hospitality and tourism sectors. These systems enhance user experiences by offering real-time, personalized support and 24/7 assistance. Yet, as sustainability becomes a key factor in travel decisions, consumers increasingly face information overload due to the abundance of eco-friendly options. This study examines how GenAI can alleviate this cognitive strain in sustainability-focused tourism contexts. Across two experiments (i.e., one on trip planning and another on on-site shopping), the findings show that more advanced GenAI tools significantly reduce information overload, improving decision-making and thus enhancing user perceptions of trust which in turn trust increases both well-being and behavioral intentions to use GenAI tools. On the other hand, the reduction of perceived decision risk increases behavioral intentions to use GenAI tools. In particular, by simplifying access to and comparison of eco-certified travel and shopping options, GenAI encourages more environmentally responsible consumer behavior.
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Document Information
| Document Title | Generative artificial intelligence for sustainable tourism : alleviating cognitive overload to foster well-being and eco-responsible behavior |
|---|---|
| Author / Organization | Lars Meyer-Waarden, Julien Cloarec, Manon Ferreira |
| Subject & Discipline | Multidisciplinary Academic Open Research |
| Categories | Science & Mathematics |
| Publication Year | 2026 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
HAL Open Science
(hal.science)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-250214 |
| Original Source Link | Visit Source Page on hal.science » |