Mapping Smart Regions. An Exploratory Approach
The paper presents the results of an exploratory approach aimed at extending the ranking procedures normally used in studying the socioeconomics determinants of smart growth at the regional level. Most of these studies adopt a methodological procedure which essentially consists of the following st...
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Università di Napoli Federico II
2014-05-01
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doaj-0017252a921f4458a53e0cb1d346d5ea2020-11-25T03:50:08ZengUniversità di Napoli Federico IITeMA: Journal of Land Use, Mobility and Environment1970-98891970-98702014-05-010010.6092/1970-9870/25111617Mapping Smart Regions. An Exploratory ApproachSylvie Occelli0Alessandro Sciullo1IRES- Istituto di Ricerche Economico Sociali del Piemonte, Via Nizza 18, 10125 Turin, ItalyIRES- Istituto di Ricerche Economico Sociali del Piemonte, Via Nizza 18, 10125 Turin, ItalyThe paper presents the results of an exploratory approach aimed at extending the ranking procedures normally used in studying the socioeconomics determinants of smart growth at the regional level. Most of these studies adopt a methodological procedure which essentially consists of the following steps: a) identification of the pertinent elementary indicators according to the study objectives; b) data selection and processing; c) combination of the elementary indicators by multivariate statistical techniques aimed at obtaining a robust synthetic index to rank the observation units. In the procedure a relational dimension is mainly subsumed in the system oriented perspective adopted in selecting the indicators which would best represent the system determinants depending on the goals of the analysis (step a). In order to get deeper insights into the smartness profile of the European regions, this study makes an effort to account of the relational dimension also in steps b and c of the procedure. The novelties of the proposed approach are twofold. First, by computing region-to-region distances associated with the selected indicators it extends the conventional ranking procedure (step c). Second, it uses a relational database (step b), dealing with the regional participation to the FP7-ICT project, to modify the distances and investigate its impact on the interpretation of the regional positioning. The main results of this exercise seem to suggest that regional collaborations would have a positive role in regional convergence process. By providing an opportunity to get contacts with the areas endowed with a comparatively more robust smartness profile, regions may have a chance to enhance their own smartness profile.http://www.tema.unina.it/index.php/tema/article/view/2511Regional smart growthRegion-to-region distancesRegional collaborationRegional performance indices |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Sylvie Occelli Alessandro Sciullo |
spellingShingle |
Sylvie Occelli Alessandro Sciullo Mapping Smart Regions. An Exploratory Approach TeMA: Journal of Land Use, Mobility and Environment Regional smart growth Region-to-region distances Regional collaboration Regional performance indices |
author_facet |
Sylvie Occelli Alessandro Sciullo |
author_sort |
Sylvie Occelli |
title |
Mapping Smart Regions. An Exploratory Approach |
title_short |
Mapping Smart Regions. An Exploratory Approach |
title_full |
Mapping Smart Regions. An Exploratory Approach |
title_fullStr |
Mapping Smart Regions. An Exploratory Approach |
title_full_unstemmed |
Mapping Smart Regions. An Exploratory Approach |
title_sort |
mapping smart regions. an exploratory approach |
publisher |
Università di Napoli Federico II |
series |
TeMA: Journal of Land Use, Mobility and Environment |
issn |
1970-9889 1970-9870 |
publishDate |
2014-05-01 |
description |
The paper presents the results of an exploratory approach aimed at extending the ranking procedures normally used in studying the socioeconomics determinants of smart growth at the regional level. Most of these studies adopt a methodological procedure which essentially consists of the following steps: a) identification of the pertinent elementary indicators according to the study objectives; b) data selection and processing; c) combination of the elementary indicators by multivariate statistical techniques aimed at obtaining a robust synthetic index to rank the observation units. In the procedure a relational dimension is mainly subsumed in the system oriented perspective adopted in selecting the indicators which would best represent the system determinants depending on the goals of the analysis (step a). In order to get deeper insights into the smartness profile of the European regions, this study makes an effort to account of the relational dimension also in steps b and c of the procedure. The novelties of the proposed approach are twofold. First, by computing region-to-region distances associated with the selected indicators it extends the conventional ranking procedure (step c). Second, it uses a relational database (step b), dealing with the regional participation to the FP7-ICT project, to modify the distances and investigate its impact on the interpretation of the regional positioning. The main results of this exercise seem to suggest that regional collaborations would have a positive role in regional convergence process. By providing an opportunity to get contacts with the areas endowed with a comparatively more robust smartness profile, regions may have a chance to enhance their own smartness profile. |
topic |
Regional smart growth Region-to-region distances Regional collaboration Regional performance indices |
url |
http://www.tema.unina.it/index.php/tema/article/view/2511 |
work_keys_str_mv |
AT sylvieoccelli mappingsmartregionsanexploratoryapproach AT alessandrosciullo mappingsmartregionsanexploratoryapproach |
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1724492142966996992 |