Competitive Advantage Analysis: A Novel Method for Industrial Clusters Identification

By Stejskal, Jan; Hajek, Petr | Journal of Business Economics and Management, April 2012 | Go to article overview

Competitive Advantage Analysis: A Novel Method for Industrial Clusters Identification


Stejskal, Jan, Hajek, Petr, Journal of Business Economics and Management


1. Introduction

The changes in global economy, which is very often named "knowledge based economy", are not a direct cause for the geographical concentration of firms. The economic world of today is stiring priorities toward innovation, an outcome of network cooperation and the commutation of social capital within this network. In the global world, based on highly developed communication and transport technologies, the meaning of spatial proximity is socially determined (Bojar 2007).

Regional policy has been recognized as a policy which contributes to competitiveness. Regions are recognized as actors which make political and economic decisions, and whose local knowledge can be harnessed to improve the performance of world economy. Research and innovation represent the drivers of productivity and growth. As a result, they are the engines of regional development (Skokan 2008; Ginevicius 2010).

In recent years, it is possible to identify a significant shift in the "paradigm" of regional development (see Bachtler, Yuill 2001; Karlsson 2008). The traditional approach to regional development was undertaken by central governments using different subsidies for firms, infrastructure, and the location of public sector activities. In part, this has been superseded by a "contemporary" approach, characterised by decentralised intervention based on integrated regional development plans and strategies, designed and delivered by the partnerships of regional and local actors (see Table 1). There are four characteristics of these contemporary approaches in regional development. First, they have a broad sphere of action, covering a range of policy sectors: infrastructure, business development, human resources, tourism, environmental, etc. Second, the national policy versions tend to encompass economic development in all regions, not just those designated for regional policy purposes which exhibit the biggest regional disparities. Third, they tend to take a pro-active approach to development, with a multi-annual programme of measures targeted at the business environment and soft infrastructure. Lastly, they have a distinctive approach to policy implementation which is collectively negotiated, led by regional authorities and involving a wide range of partners from the local government, the voluntary sector, business, and social communities.

In this context, new theories of regional development came to the fore, especially those concerned with industrial milieux (Storper 1995; Camagni 1995) and the role of clusters, systems of innovation, and networks (Porter 1998b; Cooke 2002; Maier 2007; Stejskal 2007; Karlsson 2008; Hajkova, Hajek 2009; Nowicka-Skowron, Pachura 2010; Pachura 2010, and others). It was recognized that competitive advantage increasingly improved the ability and capacity of regions to facilitate the generation, acquisition, control, and application of knowledge and information, in the interests of innovation and marketing. Many economists and policy makers highlight regions as key sites of innovation and competitiveness in the globalising economy. Thus, regional innovation systems (Cooke et al. 1997; Braczyk et al. 1998; Hajkova, Hajek 2011) are seen as an increasingly important policy framework for long-term realization of innovation based regional development strategies, including clusters (Skokan 2008).

In our previous research, we developed the method of competitive advantage analysis (Stejskal, Hajek 2008; Stejskal 2009). In this paper, we extend this method by using hierarchical multi-block principal component analysis in order to capture and model the relations between the selected factors of industrial clusters development.

This paper is structured as follows. First, clusters will be introduced as a phenomenon of the contemporary regional policy conception. Second, industrial clusters identification methods will be characterised. These methods are used with the intention not to waste the public finances provided for cluster birth and existing subsidies. …

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