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Learning from Clusters

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Cover of 'Learning from Clusters'

Table of Contents

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    Book Overview
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    Chapter 1 Clustering, Learning and Regional Development
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    Chapter 2 A Systematic Perspective on Local Development
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    Chapter 3 Cluster Dynamics
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    Chapter 4 Embedded Local Growth: A Theory Taken too Far?
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    Chapter 5 Beyond the Learning Region: The Dialectics of Innovation and Culture in Territorial Development
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    Chapter 6 Economic Development, Institutions and Trust
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    Chapter 7 Social Capital and Regional Development: An Empirical Analysis of the Third Italy
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    Chapter 8 Regional Innovation Systems, Varieties of Capitalism and Non-Local Relations: Challenges from the Globalising Economy
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    Chapter 9 Delirious Rotterdam: The Formation of an Innovative Cluster of Architectural Firms
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    Chapter 10 Competitiveness in Regional Clusters. The Case of Océ's ‘Knowledge Industry Clustering’ Project
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    Chapter 11 Urban Milieux: From Theory to Empirical Findings
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    Chapter 12 The Spatial Clustering of Knowledge-Intensive Services: Computing Services in the Netherlands
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    Chapter 13 Dynamic Information Externalities and Employment Growth in the Netherlands
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    Chapter 14 New Regional Economics: About Virtual Agglomeration Effects
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    Chapter 15 'Old’ and ‘New’ Economy and Services
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    Chapter 16 Economic Capabilities and Strategic Clusters: New Perspectives for National and Regional Economic Policy
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    Chapter 17 Further Learning from Clusters
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Title
Learning from Clusters
Published by
Springer Netherlands, March 2006
DOI 10.1007/1-4020-3679-5
ISBNs
978-1-4020-3671-2, 978-1-4020-3679-8
Editors

Boschma, Ron A., Kloosterman, Robert C.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 30%
Student > Doctoral Student 2 20%
Student > Ph. D. Student 2 20%
Unknown 3 30%
Readers by discipline Count As %
Social Sciences 3 30%
Business, Management and Accounting 1 10%
Economics, Econometrics and Finance 1 10%
Engineering 1 10%
Unknown 4 40%