Sustainability, Vol. 17, Pages 11200: AI Transparency and Sustainable Travel Under Climate Risk: A Geographical Perspective on Trust, Spatial Decision-Making, and Rural Destination Resilience

Fuente: Sustainability - Revista científica (MDPI)
Sustainability, Vol. 17, Pages 11200: AI Transparency and Sustainable Travel Under Climate Risk: A Geographical Perspective on Trust, Spatial Decision-Making, and Rural Destination Resilience
Sustainability doi: 10.3390/su172411200
Authors:
Aleksandra Vujko
Darjan Karabašević
Aleksa Panić
Martina Arsić
Vuk Mirčetić

Tourism is a key spatial process linking human mobility, resource consumption, and environmental change. Despite growing awareness of climate risks, sustainable travel behavior often remains inconsistent with pro-environmental attitudes, reflecting the persistent attitude–behavior gap. This study examines how psychological factors—sustainability motives, ecological identity, and climate attitudes—interact with artificial intelligence (AI) transparency to shape travel decisions with spatial and environmental consequences. Using survey data from 1795 leisure travelers and a discrete-choice experiment simulating hotel booking scenarios, the study shows that ecological identity and climate attitudes reinforce sustainability motives and intentions, while transparent AI recommendations enhance perceived clarity, data visibility, and reliability. These transparency effects amplify the influence of eco-scores on revealed spatial preferences, with trust mediating the relationship between transparency and sustainable choices. Conceptually, the study integrates psychological and technological perspectives within a geographical framework of human–environment interaction and extends this lens to rural destinations, where travel decisions directly affect cultural landscapes and climate-sensitive ecosystems. Practically, the findings demonstrate that transparent AI systems can guide spatial redistribution of tourist flows, mitigate destination-level climate pressures, and support equitable resource management in sustainable tourism planning. These mechanisms are particularly relevant for rural areas and traditional cultural landscapes facing heightened vulnerability to climate stress, depopulation, and uneven visitation patterns. Transparent and trustworthy AI can thus convert environmental awareness into spatially sustainable behavior, contributing to more resilient and balanced tourism geographies.