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Is agritourism eco-friendly? A comparison between agritourisms and other farms in Italy using farm accountancy data network dataset

This paper presents the results of research regarding the environmental performances of Italian farms with agritourism compared with farms without agritourism. In Italy, agritourism is considered an agricultural activity and can only be performed by a farmer. Moreover, Italian national legislation f...

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Detalles Bibliográficos
Autores principales: Mastronardi, Luigi, Giaccio, Vincenzo, Giannelli, Agostino, Scardera, Alfonso
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4627998/
https://www.ncbi.nlm.nih.gov/pubmed/26543725
http://dx.doi.org/10.1186/s40064-015-1353-4
Descripción
Sumario:This paper presents the results of research regarding the environmental performances of Italian farms with agritourism compared with farms without agritourism. In Italy, agritourism is considered an agricultural activity and can only be performed by a farmer. Moreover, Italian national legislation forces the farmer to dedicate himself mainly to traditional farming, rather than to tourism activities. For this reason, environmental performances have been highlighted by analyzing only features and production systems of the farms. By utilizing the most frequent indicators used in studies regarding sustainability, the authors show how Italian agritourisms tend to develop more environmentally friendly agricultural methods, which have a positive impact on biodiversity, landscape and natural resources. The empirical analysis is based on the Italian FADN (Farm Accountancy Data Network) dataset. The European FADN was created to represent farms’ technical and economic operation in the European Union and on which it drafts the agricultural and rural policies. The dichotomous structure of the dependent variable (presence or absence of agritourism at the farm) has a propensity for an assessment method based on Binary Response Model Regression. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40064-015-1353-4) contains supplementary material, which is available to authorized users.