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Regional Cohesion: Effectiveness of Network Structures: Contributions to Economics

Autor Piotr Pachura
en Limba Engleză Paperback – mar 2012
This book presents an interdisciplinary analysis of EU regional cohesion based on a network and clusters approach. The author explores the question if and how the presence of network structures supports the effectiveness of transformation in EU regions, in particular with a focus on non-pecuniary factors of regional growth. For a theoretical foundation of the topic, characteristics of a networking economy as well as the determinants of EU policies on regional development and innovation are examined and discussed. The empirical analysis at the core of this work presents and makes use of interdisciplinary methodological tools such as Data Envelopment Analysis (DEA), K-means models and self-organizing maps.
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Specificații

ISBN-13: 9783790828092
ISBN-10: 3790828092
Pagini: 132
Ilustrații: IX, 120 p. 31 illus.
Dimensiuni: 155 x 235 x 7 mm
Greutate: 0.2 kg
Ediția:2010
Editura: Physica-Verlag HD
Colecția Physica
Seria Contributions to Economics

Locul publicării:Heidelberg, Germany

Public țintă

Research

Cuprins

– Thesis and Research Methodology.- Clustering and Networking in Regional Policy.- Cluster and Network Approach in Regional Development.- Regional Disparities in EU.- Regional Clustering Based on Efficiency and Networking Models.

Textul de pe ultima copertă

This book presents an interdisciplinary analysis of EU regional cohesion based on a network and clusters approach. The author explores the question if and how the presence of network structures supports the effectiveness of transformation in EU regions, in particular with a focus on non-pecuniary factors of regional growth. For a theoretical foundation of the topic, characteristics of a networking economy as well as the determinants of EU policies on regional development and innovation are examined and discussed. The empirical analysis at the core of this work presents and makes use of interdisciplinary methodological tools such as Data Envelopment Analysis (DEA), K-means models and self-organizing maps.

Caracteristici

Includes supplementary material: sn.pub/extras