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A new approach to the identification of regional clusters: hierarchical clustering on principal components

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This study focuses on the identification of regional business clusters as a primary step in the design and implementation of cluster-based development strategies. A methodology that has not been used previously to identify clusters is applied to data on inter-industry linkages from the input–output table of a region in northern Spain. The first advantage of this approach, hierarchical clustering on principal components (HCPC), over the use of factorial analysis alone, is that it involves the application of objective clustering techniques to the principal components analysis results, which leads to a better cluster solution. A second advantage is derived from using a mixed algorithm for the clustering process – a combination of the Ward’s classification method with the K-means algorithm – which improves the robustness of the final results.

Keywords: C39; O18; R15; cluster analysis; hierarchical clustering; multivariate statistics; regional clusters

Document Type: Research Article


Affiliations: Department of Applied Economics, University of Oviedo, 33006, Oviedo, Spain

Publication date: July 23, 2014

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