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The quality and availability of labour is essential for the economic performance of clusters. The availability of labour in clusters is superior compared to locations outside clusters, because labour is more mobile in clusters, education services in clusters are better and employees in clusters have a higher willingness to invest in specific skills. These effects arise 'spontaneously', as a result of 'market forces'. Apart, from these effects, in some clusters, firms and governments also actively aim to improve the quality of the labour pool in the cluster. Clusters differ in the extent to which relevant stakeholders manage to invest in the quality of the labour pool. Thus, superior 'organising capacity' is a potential source of competitive advantage of a cluster vis-à-vis other clusters. This paper presents an analysis of these efforts of firms and governments to improve the quality of the labour force in three seaport clusters. The concept of a 'training and education regime' is used to analyse efforts of firms and governments to improve the labour pool. The results of three case studies of port clusters lead to a number of conclusions. First, the assumption that the quality of training and education regime differs substantially per cluster is validated. Second, the presence of a 'regime manager' adds to the quality of Rotterdam's training and education regime. Such an organisation may be effective across countries and clusters. Finally, the presence of leader firms, willing to invest in training and education improves an education regime.

The article describes the idea of cluster formation with particular emphasis on creative industry clusters. In first part the concept and the basic definitions of creative clusters were presented. The second part of the article is devoted to experiences in establishing creative clusters in Poland, which in reality are not significant (five formed clusters and 13 cluster initiatives countrywide).

Cover -- Half Title -- Dedication -- Title Page -- Copyright Page -- Table of Contents -- List of Tables -- List of Figures -- List of Abbreviations -- List of Contributors -- Preface -- 1 Industrial Clustering in India: Local Dynamics and the Global Debate -- 2 An Italian Model and an Indian Reality: Searching for a Way-Out of Deteriorating Sweatshop Conditions -- 3 Flexible Accumulation and Labour Markets: Case of the Tiruppur Knitwear Cluster -- 4 Industrial Clusters and Labour in Rural Areas: The Brick Kiln Industry in Three States -- 5 Competition and Response in Small Firm Clusters: Two Cases from Gujarat -- 6 Organizational Forms, Technological Change and Income Generation: Handloom and Conch Shell Product Clusters in West Bengal -- 7 Variations on the Classical Model: Forms of Cooperation in Leather Clusters of Palar Valley, Tamil Nadu -- 8 Industrial Clustering and Cooperation: The Kanpur Saddlery Cluster -- 9 Flexible Specialization for Rural Industries? A Study of the Bamboo and Rattan Subsector -- 10 The Silver Filigree Cluster in Cuttack, Orissa: What Ails It? -- 11 Handicrafts and 'Cluster Development Approach': The Hand Block Printed Textiles Cluster of Jaipur -- 12 Transforming Artisans to Entrepreneurs through Group Enterprise: The Footwear Cluster of Athani, Karnataka -- 13 Classifying Small Enterprise Clusters: A Conceptual Enquiry in Ahmedabad -- Index

AbstractThe modifiable areal unit problem (MAUP) is seldom accounted for in economic geography cluster studies. This issue is particularly problematic as clusters play such a central role in regional development policy. In this study, we tested for the appearance of the MAUP when examining workplace category clusters over three different administrative scales in Stockholm County, Sweden. The measures used were the standardised ratio, global autocorrelation, and local autocorrelation. We discovered not only that the appearance of clusters depended on the administrative unit scale but also that the location of the clusters, based on the local indicator of spatial association, fluctuated wildly over the various administrative scales. Thus, our conclusion was that the robustness and validity of workplace category clusters should always be challenged if the MAUP has not been taken into account, or at least tested for.

Seaports can be meaningfully analysed with a cluster perspective. In this perspective, seaports are regarded as concentrations of economic activity related to the arrival and service of ships and cargoes at ports. This perspective has two main advantages: first, it draws attention to forces of agglomeration and disagglomeration in seaports. Some seaports are able to become concentrations of logistics activities, commercial centres, 'information hubs' and 'shipping hubs', while others do not attract such activities. The cluster perspective allows for an analysis of such processes of agglomeration. Second, the cluster perspective enriches existing theories on governance in seaports. The analysis of governance in seaports has mostly been limited to the role of the port authority. Notwithstanding the central role of port authorities in ports (port clusters), we argue that a port authority is one 'arrangement' to improve the governance in clusters, but not the only 'arrangement'. Other arrangements include the formation of associations, the development of public-private partnerships and the use of networks. The literature on governance in clusters provides a broad analytical framework. This framework has implications for analysing the important and complex issue of the role of port authorities in seaports. In this paper, we deal in depth with the issue of cluster governance in seaports and illustrate our approach to cluster governance with an analysis of the port of Rotterdam.

Intro -- Contents -- Preface -- About the Authors -- Abbreviations -- Chapter 1 Competition, Competition Policy, and Growth -- Competition and Growth -- Product Market Regulation and Economic Performance -- Competition Policy -- Conclusion -- Notes -- References -- Chapter 2 Competitiveness and Its Indicators -- Elements of Competitiveness -- Defining Competitiveness -- Price Indicators of Competitiveness -- Nonprice Indicators of Competitiveness -- Doing Business: Measuring Business Regulations -- Conclusion -- Notes -- References -- Chapter 3 National Competitiveness -- Defining National Competitiveness -- Competitiveness Rankings -- Conclusion -- Notes -- References -- Chapter 4 Innovation Policy for Competitiveness -- Innovation: Definition and Measurements -- Innovation, Growth, and Competitiveness -- Policies for Innovation -- How Can Government Help? -- Conclusion -- Notes -- References -- Chapter 5 Competitiveness and Clusters -- Background to Clusters -- Cluster Initiatives -- Policy Implications -- Conclusion -- Notes -- References -- Box -- Box 2.1 Price and Nonprice Indicators of Competitiveness: The Case of Armenia -- Figures -- Figure 1.1 Markups in Manufacturing and Nonmanufacturing -- Figure 1.2 The Tree Structure of the Economy-wide PMR Indicator -- Figure 1.3 PMR in Accession and OECD Countries, Aggregate Level, 2008 -- Figure 1.4 Decomposition of PMR in Accession Countries, 2008 -- Figure 2.1 Business Environment Quality: The Diamond -- Figure 2.2 The Three Pillars of Trade Competitiveness -- Figure 2.3 Outcomes and Determinants of Competitiveness -- Figure B2.1.1 Armenia's Share of World Exports -- Figure B2.1.2 Nominal and Real Effective Exchange Rates for Armenia -- Figure B2.1.3 GDP Dynamics and Global Competitiveness Rankings for Armenia -- Figure 2.4 The 12 Pillars of Competitiveness.

"Clusters and Regional Development" published on by Oxford University Press.

ABSTRACT  The tendency of firms to cluster within a region has been observed for quite some time. However, it is only over the past two decades that business researchers have focused much attention on clusters, particularly in terms of their entrepreneurial and innovative characteristics and potential. At the same time, regional developers around the world have put much effort in promoting the formation of clusters. A gap in such efforts is an understanding of the differences among types of clusters. This article draws a distinction between two generic types of clusters: technology‐based and industry‐focused. Using the resource‐based view as the organizing framework, we argue that the two generic cluster types create very different regional resource profiles over time, accumulating resources in a different manner, cultivating different capabilities, and deriving different sources of regional advantage. As concluded in the study, these differences are likely to have implications for firms located in the regions as well as for economic developers and public policy officials charged with developing cluster strategies.