Benchmark Value-added Chains and Regional Clusters in R&D-intensive Industries
Reinhold Kosfeld, Mirko Titze
International Regional Science Review,
Nr. 5,
2017
Abstract
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.
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Actors and Interactions – Identifying the Role of Industrial Clusters for Regional Production and Knowledge Generation Activities
Mirko Titze, Matthias Brachert, Alexander Kubis
Growth and Change,
Nr. 2,
2014
Abstract
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.
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The Identification of Industrial Clusters – Methodical Aspects in a Multidimensional Framework for Cluster Identification
Mirko Titze, Matthias Brachert, Alexander Kubis
Abstract
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.
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Industry Specialization, Diversity and the Efficiency of Regional Innovation Systems
Michael Fritsch, Viktor Slavtchev
Determinants of Innovative Behaviour,
2008
Abstract
Innovation processes are characterized by a pronounced division of labor between actors. Two types of externality may arise from such interactions. On the one hand, a close location of actors affiliated to the same industry may stimulate innovation (MAR externalities). On the other hand, new ideas may be born by the exchange of heterogeneous and complementary knowledge between actors, which belong to different industries (Jacobs’ externalities). We test the impact of both MAR as well as Jacobs’ externalities on innovative performance at the regional level. The results suggest an inverted u-shaped relationship between regional specialization in certain industries and innovative performance. Further key determinants of the regional innovative performance are private sector R&D and university-industry collaboration.
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Industry Specialization, Diversity and the Efficiency of Regional Innovation Systems
Michael Fritsch, Viktor Slavtchev
Jena Economic Research Papers, Nr. 2007-018,
Nr. 18,
2007
Abstract
Innovation processes are characterized by a pronounced division of labor between actors. Two types of externality may arise from such interactions. On the one hand, a close location of actors affiliated to the same industry may stimulate innovation (MAR externalities). On the other hand, new ideas may be born by the exchange of heterogeneous and complementary knowledge between actors, which belong to different industries (Jacobs’ externalities). We test the impact of both MAR as well as Jacobs’ externalities on innovative performance at the regional level. The results suggest an inverted u-shaped relationship between regional specialization in certain industries and innovative performance. Further key determinants of the regional innovative performance are private sector R&D and university-industry collaboration.
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What Determines the Efficiency of Regional Innovation Systems?
Michael Fritsch, Viktor Slavtchev
Jena Economic Research Papers, Nr. 2007-006,
Nr. 6,
2007
Abstract
We assess the efficiency of regional innovation systems (RIS) in Germany by means of a knowledge production function. This function relates private sector research and development (R&D) activity in a region to the number of inventions that have been registered by residents of that region. Different measures and estimation approaches lead to rather similar assessments. We find that both spillovers within the private sector as well as from universities and other public research institutions have a positive effect on the efficiency of private sector R&D in the respective region. It is not the mere presence and size of public research institutions, but rather the intensity of interactions between private and public sector R&D that leads to high RIS efficiency. We find that relationship between the diversity of a regions’ industry structure and the efficiency of its innovation system is inversely u-shaped. Regions dominated by large establishments tend to be less efficient than regions with a lower average establishment size.
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