• Energy Research

This paper provides a contribution to the international literature by applying regression tree methods to the analysis of the expected effects of the High Speed Rail project in Italy on the tourism market. This approach, as far as the author knows, has never been applied in this context. Tourism and transport information have been gathered for 99 Italian provinces during the 2006–2016 period. Tree-structured methods have been chosen as an application of regression models in which some explanatory variables are used as covariates to predict the dependent variable values on the basis of some decision rules. This approach establishes a casual effect between dependent and independent variables. The dependent variables chosen are the Italian and foreign tourists, and the number of overnights spent by Italians and foreigners. Among the independent variables are the presence of HSR, the presence of first-level airport hubs and the number of operating bases of low-cost airlines; among the attractiveness variables are the GDP, the number of attractions in a given province, the presence of the sea, the population and the percentage of unemployment. The main outcome of this study is that HSR affects the tourism market.

The objective of this manuscript is to understand whether the policies regarding tourism and transport affect positively citizens ‘trust in local institutions. A survey was employed to citizens of the metropolitan area of Naples (in Italy), aiming at capturing citizens’ perceptions with respect to the positive and negative impacts concerning tourism and transport related policies and the level of their engagement in the institutions ‘decisions for a sustainable development.