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

$54.97 plus tax (Refund Policy)

Buy Article:

Abstract:

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

DOI: http://dx.doi.org/10.1080/00036846.2014.904491

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

Publication date: July 23, 2014

More about this publication?
Related content

Share Content

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
X
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more