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Erschienen in: Social Indicators Research 2/2020

09.10.2019 | Original Research

A Spatial Composite Indicator for Human and Ecosystem Well-Being in the Italian Urban Areas

verfasst von: Annalina Sarra, Eugenia Nissi

Erschienen in: Social Indicators Research | Ausgabe 2/2020

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Abstract

The concept of well-being has evolved over the last decades and a multidisciplinary literature has acknowledged the multidimensional nature of this phenomenon that encompasses different key dimensions. To give concise measure of well-being, methodologies based on composite indices assume relevance, for their capability to summarize the multidimensional issues, rank the units and provide interesting analysis tools. This paper intends to make a contribution to the efforts of assessing human and ecosystem well-being in the Italian urban areas, by appreciating the spatial dimension of the elementary indicators involved in the building process of the composite indicator. To this end, we derive a set of local weights reflecting the spatial variability of data through the Geographically Weighted PCA. Then, the analysis proceeds by employing a unitary-input DEA model, also known as Benefit of Doubt approach, as a benchmarking tool for constructing a spatial composite indicator to evaluate the well-being in the Italian urban areas. In such way, we can take local peculiarities into account and identify the best performing cities to follow as examples of good administrative practices for promoting urban well-being. The approach followed in this specific study is applied empirically with data from the Urban ‘Equitable and Sustainable Well-Being” (Ur-Bes) project, proposed by ISTAT.

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1
We adopted a min–max transformation in a continuous scale from 70 (minimum) to 130 (maximum), which represents the range of each indicator over the given time period.
 
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Metadaten
Titel
A Spatial Composite Indicator for Human and Ecosystem Well-Being in the Italian Urban Areas
verfasst von
Annalina Sarra
Eugenia Nissi
Publikationsdatum
09.10.2019
Verlag
Springer Netherlands
Erschienen in
Social Indicators Research / Ausgabe 2/2020
Print ISSN: 0303-8300
Elektronische ISSN: 1573-0921
DOI
https://doi.org/10.1007/s11205-019-02203-y

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