The United Nations approved, in September 2015, the Sustainable Development Agenda and the related 17 goals to be achieved by 2030. Individual Italian regions are, also, called upon to contribute to the achievement of these goals. Sustainable tourism, defined as a form of tourism that respects the resources on which the very future of the sector depends, has been attributed to the functions of renewing the cultural pride of the host communities, empowering local communities, and protecting biodiversity. The objective of this work is to have the analysis of the environmental impacts that the tourism sector produces are explored. Often the development of this sector is useful for facilitating growth in less developed areas, but the effects on the environment are not considered. The available data will be analyzed at a provincial level through multivariate statistical methodologies (Totally Fuzzy and Relative method) and density-based spatial clustering methods (DBSCAN), which allow identifying contiguous areas with high levels of sustainable tourism. These aspects should guide the way for the distribution of resources and investments, as currently, not all Italian regions start from the same conditions.

Statistics for the Environment: Tourism and Sustainability in Italy

Antonucci L.
2025-01-01

Abstract

The United Nations approved, in September 2015, the Sustainable Development Agenda and the related 17 goals to be achieved by 2030. Individual Italian regions are, also, called upon to contribute to the achievement of these goals. Sustainable tourism, defined as a form of tourism that respects the resources on which the very future of the sector depends, has been attributed to the functions of renewing the cultural pride of the host communities, empowering local communities, and protecting biodiversity. The objective of this work is to have the analysis of the environmental impacts that the tourism sector produces are explored. Often the development of this sector is useful for facilitating growth in less developed areas, but the effects on the environment are not considered. The available data will be analyzed at a provincial level through multivariate statistical methodologies (Totally Fuzzy and Relative method) and density-based spatial clustering methods (DBSCAN), which allow identifying contiguous areas with high levels of sustainable tourism. These aspects should guide the way for the distribution of resources and investments, as currently, not all Italian regions start from the same conditions.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11369/476265
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