Title: Economic development strategies and methods for identifying leading industries and industrial clusters
Authors: Thomas J. Webster
Addresses: Lubin School of Business, Pace University, One Pace Plaza, New York, NY 10038, USA
Abstract: This paper reviews several popular economic development strategies and discusses the practical problem of identifying leading industries and innovation clusters for government regulatory and financial support. Although there is no substitute for in-depth industry-by-industry analysis, several statistical techniques are available that can assist in the identification process, including principal component analysis, k-means clustering, hierarchical clustering, medoid partitioning and fuzzy clustering. The Republic of Indonesia is used as a case study to illustrate the strengths and weakness of each of these procedures.
Keywords: economic development; export-led growth; fuzzy clustering; hierarchical clustering; Indonesia; innovation clusters; k-means clustering; leading industries; medoid partitioning; principal component analysis; PCA; exports; industrial clusters.
International Journal of Economics and Business Research, 2013 Vol.5 No.1, pp.55 - 74
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 08 Nov 2012 *