Do Diasporas Affect Regional Knowledge Transfer within Host Countries? A Panel Analysis of German R&D Collaborations
Lutz Schneider, Alexander Kubis, Mirko Titze
Regional Studies,
No. 1,
2019
Abstract
Interactive regional learning involving various actors is considered a precondition for successful innovations and, hence, for regional development. Diasporas as non-native ethnic groups are regarded as beneficial since they enrich the creative class by broadening the cultural base and introducing new routines. Using data on research and development (R&D) collaboration projects, the analysis provides tentative evidence that the size of diasporas positively affects the region’s share of outward R&D linkages enabling the exchange of knowledge. The empirical analysis further confirms that these interactions mainly occur between regions hosting the same diasporas, pointing to a positive effect of ethnic proximity rather than ethnic diversity.
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R&D Collaborations and the Role of Proximity
Philipp Marek, Mirko Titze, Clemens Fuhrmeister,
Regional Studies,
No. 12,
2017
Abstract
R&D collaborations and the role of proximity. Regional Studies. This paper explores the impact of proximity measures on knowledge exchange measured by granted research and development (R&D) collaboration projects in German NUTS-3 regions. The results are obtained from a spatial interaction model including eigenvector spatial filters. Not only geographical but also other forms of proximity (technological, organizational and institutional) have a significant influence on the emergence of collaborations. Furthermore, the results suggest interdependences between proximity measures. Nevertheless, the analysis does not show that other forms of proximity may compensate for missing geographical proximity. The results indicate that (subsidized) collaborative innovation activities tend to cluster.
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Benchmark Value-added Chains and Regional Clusters in R&D-intensive Industries
Reinhold Kosfeld, Mirko Titze
International Regional Science Review,
No. 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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Does Proximity Matter in the Choice of Partners in Collaborative R&D Projects? – An Empirical Analysis of Granted Projects in Germany
Mirko Titze, Philipp Marek, , Clemens Fuhrmeister
IWH Discussion Papers,
No. 12,
2014
Abstract
This paper contributes to the discussion on the importance of physical distance in the emergence of cross-region collaborative Research and Development (R&D) interactions. The proximity theory, and its extensions, is used as a theoretical framework. A spatial interaction model for count data was implemented for the empirical analysis of German data from the period from 2005 to 2010. The results show that all tested proximity measurements (geographical, cognitive, social and institutional proximity) have a significant positive influence on collaboration intensity. The proximity paradox, however, cannot be confirmed for geographical, social and institutional proximity, but for cognitive proximity.
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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,
No. 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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