Benchmark Value-added Chains and Regional Clusters in R&D-intensive Industries
International Regional Science Review,
Although the phase of euphoria seems to be over, policy makers and regional agencies have maintained their interest in cluster policy. Modern cluster theory provides reasons for positive external effects that may accrue from interaction in a group of proximate enterprises operating in common and related fields. Although there has been some progress in locating clusters, in most cases only limited knowledge on the geographical extent of regional clusters has been established. In the present article, we present a hybrid approach to cluster identification. Dominant buyer–supplier relationships are derived by qualitative input–output analysis from national input–output tables, and potential regional clusters are identified by spatial scanning. This procedure is employed to identify clusters of German research and development-intensive industries. A sensitivity analysis reveals good robustness properties of the hybrid approach with respect to variations in the quantitative cluster composition.
Actors and Interactions – Identifying the Role of Industrial Clusters for Regional Production and Knowledge Generation Activities
Growth and Change,
This paper contributes to the empirical literature on systematic methodologies for the identification of industrial clusters. It combines a measure of spatial concentration, qualitative input–output analysis, and a knowledge interaction matrix to identify the production and knowledge generation activities of industrial clusters in the Federal State of Saxony in Germany. It describes the spatial allocation of the industrial clusters, identifies potentials for value chain industry clusters, and relates the production activities to the activities of knowledge generation in Saxony. It finds only a small overlap in the production activities of industrial clusters and general knowledge generation activities in the region, mainly driven by the high-tech industrial cluster in the semiconductor industry. Furthermore, the approach makes clear that a sole focus on production activities for industrial cluster analysis limits the identification of innovative actors.
The Identification of Regional Industrial Clusters Using Qualitative Input-Output Analysis (QIOA)
The 'cluster theory' has become one of the main concepts promoting regional competitiveness, innovation, and growth. As most empirical applications focus on measures of concentration of one industrial branch in order to identify regional clusters, the appropriate analysis of specific vertical relations is developing in this discussion. This paper tries to identify interrelated sectors via national input-output tables with the help of minimal flow analysis (MFA). The regionalization of these national industry templates is carried out with the allocation of branch-specific production values on regional employment. As a result, the paper shows concentrations of vertical clusters in only 27 of 439 German Nomenclature des Unite´s Territoriales Statistiques (NUTS)-3 regions.
The Identification of Industrial Clusters – Methodical Aspects in a Multidimensional Framework for Cluster Identification
IWH Discussion Papers,
We use a combination of measures of spatial concentration, qualitative input-output analysis and innovation interaction matrices to identify the horizontal and vertical dimension of industrial clusters in Saxony in 2005. We describe the spatial allocation of the industrial clusters and show possibilities of vertical interaction of clusters based on intermediate goods flows. With the help of region and sector-specific knowledge interaction matrices we are able to show that a sole focus on intermediate goods flows limits the identification of innovative actors in industrial clusters, as knowledge flows and intermediate goods flows do not show any major overlaps.
Die Identifikation horizontaler und vertikaler industrieller Clusterstrukturen in Deutschland – Ein neues Verfahren und erste empirische Ergebnisse
Raumforschung und Raumordnung,
. If regional development agencies assume the cluster concept to be an adequate framework to promote regional growth and competitiveness, it is necessary to identify industrial clusters in a comprehensive manner. Previous studies used a diversity of methods starting with specific regional case studies, input-output methods and different concentration measures. This article presents a new instrument in empirical cluster research – the Qualitative Input-Output Analysis –, which offers the possibility to identify industrial cluster in conjunction with concentration measures. Especially, this method allows the combination of an identified critical mass of regional firms with the necessity of interaction of these firms within an input-output framework. Applying this method to Germany’s “Arbeitsmarktregionen” we find that 103 “Arbeitsmarkregionen“ show first signs of horizontal industrial clusters, while only 28 regions are able to attract vertical industrial clusters. 139 “Arbeitsmarktregionen” did not show signs of industrial clusters according to the research design.
The Identification of Regional Industrial Clusters Using Qualitative Input-Output Analysis
IWH Discussion Papers,
The ‘cluster theory’ has become one of the main concepts promoting regional competitiveness, innovation, and growth. As most studies focus on measures of concentration of one industrial branch in order to identify regional clusters, the appropriate analysis of specific vertical relations within a value-adding chain is developing in this discussion. This paper tries to identify interrelated sectors via national input-output tables with the help of Minimal Flow Analysis by Schnabl (1994). The regionalization of these national industry templates is carried out with the allocation of branch-specific production values on regional employment. As a result, the paper shows concentrations of vertical clusters in only 27 of 439 German NUTS-3 regions.