A new approach to the identification of regional clusters: hierarchical clustering on principal components
Year: 2014
Type: 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.
Source: Applied Economics
Authors: M. Argüelles, C. Benavides, I. Fernández
Institution: Universidad de Oviedo
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W1992936231