Clusters, Learning, and Regional Development: Theory and Cases

  • Roel RuttenEmail author
  • Dessy Irawati
Part of the Advances in Spatial Science book series (ADVSPATIAL)


The economy today is more globalized than ever before in the history of mankind. While the limits of electronic communication are continuously pushed beyond new horizons, globalization can only be expected to increase further (Friedman 2005). Paradoxically, perhaps, the economy is at the same time increasingly an economy of regions (Morgan 2004; Scott and Storper 2003). Obviously, there are stark contrasts between regions that have successfully linked up to the global economy and those that have not. Which begs the question why some regions perform better than others in the global economy? True to Porter’s (1990) adage that not nations (or regions) compete but companies, and given the fact that successful companies are often embedded in strong regional clusters of companies (Dupuy and Torre 2006; Spencer et al. 2010), the question is more accurately rephrased as: why do some clusters perform better than others? The answer to this question must be sought along two related but distinct lines of inquiry. First of all the characteristics of clusters are important with regard to their success or failure in the global economy. Secondly, the characteristics of the region wherein a cluster is embedded must be considered. This chapter addresses both lines of inquiry based on the assumption that economic performance is fundamentally driven by innovation, learning, and knowledge creation. Therefore, the degree in which a cluster is successful in creating new knowledge and converting the outcomes of that process into innovations is of crucial importance for the understanding of the economic performance of that cluster. Similarly, the degree in which a region offers a favorable social and institutional environment for learning and innovation offers an important explanation for the economic performance of its companies.


Social Capital Gross Domestic Product Knowledge Spillover Knowledge Creation Cluster Scheme 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Tilburg School of Social and Behavioural SciencesTilburg UniversityTilburgThe Netherlands
  2. 2.Sondervick CollegeVeldhovenThe Netherlands

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