Italian urban tourism predictions using the holiday Climate Index

The tourism sector is a source of sustenance for local communities, a driver of fiscal revenues and a way to connect local sites to international guests. Its dependence on climate change exposes it to chronic risks such as slowly varying climate patterns. In this paper, we predicted tourism intensity (as the number of beds per square kilometres) according to three Representative Concentration Pathways (RCP) at the municipal level in Italy: 2.6, 4.5 and 8.5. We first estimated a statistical model of tourism intensity using the Holiday Climate Index (HCI) and other drivers. Then, we used the prediction of beds per Km2 to infer changes between 2004 and 2050 according to each RCP scenario of the HCI. We find complex heterogeneous patterns in exposure and a moderate positive effect in the RCP2.6 scenario. However, delayed (RCP4.5) or no climate policy at all (RCP8.5) scenarios present dire consequences for the tourism sector.

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Publication Details

Journal
Tourism Economics
Published
2024-08-26
DOI
https://doi.org/10.1177/13548166241277858
Citations
7
Primary Topic
Diverse Aspects of Tourism Research
Type
article
Field-Weighted Citation Impact
7.92

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article

Italian urban tourism predictions using the holiday Climate Index

Simone Borghesi, Matteo Mazzarano, Giulia Galluccio
7 citations
Tourism Economics
Diverse Aspects of Tourism Research
7.92
article

Italian urban tourism predictions using the holiday Climate Index

Simone Borghesi, Matteo Mazzarano, Giulia Galluccio
article en
7 citations

Abstract

The tourism sector is a source of sustenance for local communities, a driver of fiscal revenues and a way to connect local sites to international guests. Its dependence on climate change exposes it to chronic risks such as slowly varying climate patterns. In this paper, we predicted tourism intensity (as the number of beds per square kilometres) according to three Representative Concentration Pathways (RCP) at the municipal level in Italy: 2.6, 4.5 and 8.5. We first estimated a statistical model of tourism intensity using the Holiday Climate Index (HCI) and other drivers. Then, we used the prediction of beds per Km2 to infer changes between 2004 and 2050 according to each RCP scenario of the HCI. We find complex heterogeneous patterns in exposure and a moderate positive effect in the RCP2.6 scenario. However, delayed (RCP4.5) or no climate policy at all (RCP8.5) scenarios present dire consequences for the tourism sector.

Tourism EconomicsVol. 31(4)
University of Siena (IT), CMCC Foundation - Euro-Mediterranean Center on Climate Change (IT), European University Institute (IT)
Ministero dell'Università e della Ricerca
Climate action
Openalex Percentile: Top 3%
Diverse Aspects of Tourism Research
7.92
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