(Created page with " == Abstract == This paper provides a contribution to the international literature by applying regression tree methods to the analysis of the expected effects of the High Spe...") |
m (Scipediacontent moved page Draft Content 886918363 to Pagliara et al 2020a) |
(No difference)
|
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&ndash
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.
Document type: Article
The different versions of the original document can be found in:
under the license https://creativecommons.org/licenses/by/4.0/
Published on 01/01/2020
Volume 2020, 2020
DOI: 10.3390/su12030910
Licence: Other
Are you one of the authors of this document?