AI-Enhanced strategies to ensure new sustainable destination tourism trends among the 27 European Union Member States

Abstract

The United Nations 2030 Agenda defines the priorities and aspirations for global development based on seventeen ambitious sustainable development goals encompassing economic, environmental, and social dimensions. Tourism plays a vital role in the list of actions for the people and the planet. While the tourism industry drives economic growth, its environmental and social impact is equally high. Sustainable tourism aims to reduce the damage caused by the tourism industry, protect communities, and guarantee the industry’s long-term future. These changes require tourists’ collective and concerted effort. The question arises whether tourists are willing to be more demanding about sustainability when looking for a destination. This study uses artificial intelligence to classify a new trend in European citizens’ search for sustainable destinations and to generate intelligent recommendations. Using data from the Flash Eurobarometer 499, we use a tree-based algorithm, random forest, to obtain intelligent citizens classification systems supported by machine learning. The classification system explores the predisposition of citizens to contribute to the three pillars of sustainability when choosing a destination to visit based on gender, age, and the region of living. We found that European citizens place little emphasis on the social sustainability pillar. While they care about preserving the environment, this competes with the cultural offerings and availability of activities at the destination. Additionally, we found that the willingness to contribute to the three pillars of sustainability varies by gender, age, and European region.