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Erschienen in: Social Indicators Research 3/2018

31.12.2016

A Measure of Well-Being Across the Italian Urban Areas: An Integrated DEA-Entropy Approach

verfasst von: Eugenia Nissi, Annalina Sarra

Erschienen in: Social Indicators Research | Ausgabe 3/2018

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Abstract

In recent years, there has been an increasing proliferation of initiatives focusing on the concept of quality of life and well-being. At the centre of these studies there is the recognizing that the GDP offers only a partial perspective of factors affecting people’s lives. Following this line of the research, this paper is aimed at computing the well-being efficiencies of a sample of Italian Province capital cities, using a methodological approach that combines data envelopment analysis (DEA) with Shannon’s entropy formula. To avoid subjectivity in choosing a representative set of variables that proxy the phenomenon under study, we rely on the theoretical framework adopted by the Italian National Institute of Statistics (ISTAT) within the equitable and sustainable well-being (BES) project. The dashboard of indicators included in the analysis are related to the Ur-BES initiative, promoted by ISTAT to implement the BES framework at cities level. In a first step of the analysis, an immediate focus on separate dimensions of urban well-being is obtained by summarizing the plurality of available indicators through the building of composite indices. Next, the adopted integrated DEA–Shannon entropy approach has permitted to increase the discriminatory power of DEA procedure and attain a more reliable profiling of Italian Province capital cities well-being efficiencies. The results show a marked duality between the Northern and Southern cities, highlighting important differences in many aspects of human and ecosystem well-being.

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1
Anyway, for each dimension, it has been checked if there was a certain redundancy between elementary indicators to be summarized with a few number of factors. For the majority of well-being dimensions, the results of Kaiser–Mayer–Olkin (KMO) index indicate a poor sampling adequacy for factor analysis.
 
2
The number of all different combinations of unitary input and output subsets from S is \(K = (2^{s} - 1)\).
 
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Metadaten
Titel
A Measure of Well-Being Across the Italian Urban Areas: An Integrated DEA-Entropy Approach
verfasst von
Eugenia Nissi
Annalina Sarra
Publikationsdatum
31.12.2016
Verlag
Springer Netherlands
Erschienen in
Social Indicators Research / Ausgabe 3/2018
Print ISSN: 0303-8300
Elektronische ISSN: 1573-0921
DOI
https://doi.org/10.1007/s11205-016-1535-7

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