An interesting measure for equitable and sustainable well-being has been proposed recently by the National Institute of Statistics in Italy and the National Council for Economy and Labour. It is called BES (from the Italian Benessere Equo e Sostenibile). A set of indicators, partitioned into several domains and themes, is used for measuring the BES. Taking into account prior knowledge of both the structure of this set of indicators and the relationships among them, the paper proposes a hierarchical composite model for measuring and modeling the BES of the Italian provinces. This hierarchical model allows us to synthesize individual indicators into single indexes in order to construct composite indicators at a global and a partial level. Moreover, we analyze the relationships among the different domains and themes as well as the effects of these on equitable and sustainable well-being, in order to search for strongly influential factors. In order to estimate the parameters of the model, we use both Partial Least Squares path modeling and a new method, called Quantile Composite-based path modeling. In particular, Partial Least Squares path modeling is used to estimate average effects in the network of relationships between variables, while with Quantile Composite-based path modeling we investigate whether the magnitude of these effects changes across different parts of the variable distributions, providing a more complete picture and uncovering specific local leveraging factors for improvement. A final ranking of the Italian provinces, according to the BES composite indicator, is also provided at the national level and for different geographic areas of Italy
Association Rules are one of the most widespread data mining\ud
tools because they can be easily mined, even from very huge database, and they provide valuable information for many application fields such as marketing, credit scoring, business, etc. The counterpart is that a massive effort is required (due to the large number of rules usually mined) in order to make actionable the retained knowledge. In this framework vizualization tools become essential to have a deep insight into the association\ud
structures and interactive features have to be exploited for\ud
highlighting the most relevant and meaningful rules
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