Abstract:
The Italian government has devised a strategy for those municipalities further away from poles of services (trains, hospitals, and schools), defined as inner areas, for the European programming period 2014-2020. The main trend of characterising these areas has been depopulation being higher than the national average due to migration (to poles), lower birth rate, and aging population. This phenomenon brought a serious lack of public services and losses in the labor market. The abandonment of the young workforce was accompanied by the abandonment of the land with degradation of the landscape and greater hydrogeological risks. This thesis concentrates on those areas, in the insular regions of Italy, which are defined by the strategy as peripheral and ultra-peripheral, namely those which were more heavily affected. The approach used to study the involved municipalities will be building the economic, socio-demographic, and environmental indicators to assess their sustainability. The analysis, to highlight the underlying relationship between indicators, will be conducted through the application of Rough Set theory. The advantage of choosing this data mining method is that it does not require any statistical assumption on data distribution or any structure collecting data, which ensures the description of pattern present in the data. After assessing how condition attributes (the indicators above mention) connect to the decision attribute (sustainability), a set of rules will be generated, which will help the decision-makers to determine the right policy to apply to act against the given trend.
