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What Drives Regional Cooperative Behavior in German Biotechnology? Embedding Social Network Analysis in a Regression Framework

  • Timo Mitze

    ()

  • Falk Strotebeck

We analyse the determinants of network formation in German’s biotechnology sector combining elements from social network analysis (SNA) and a regression framework for count data. For the latter we adopt a regional innovation system perspective, we estimate the number of total and interregional R&D collaborations of local biotech actors in the year 2005 as a function of region’s innovation and economic context as well as a set of policy related variables. The inclusion of policy instruments in the regression approach allows us to answer the question to what extent R&D-based cluster policies such as the well-known BioRegio contest (BRC) shape the formation of the German biotech network. We use the region’s degree centrality, a standard measure in SNA, as outcome variable. Our results show that policy indicators such as the volume of public funding for collaborative R&D are positively correlated with the region’s total and interregional number of R&D cooperations. However, besides this direct funding effect no further advantages such as image effects etc. are found. Regarding the role of factors defining the regional innovation system, we observe that the number of biotech patent applications, the share of regional hightech start-ups and the population density are positively linked to the region’s degree centrality.

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Paper provided by European Regional Science Association in its series ERSA conference papers with number ersa12p629.

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Date of creation: Oct 2012
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Handle: RePEc:wiw:wiwrsa:ersa12p629
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  1. Patuelli, Roberto & Grimpe, Christoph, 2008. "Knowledge Production in Nanomaterials: An Application of Spatial Filtering to Regional Systems of Innovation," ZEW Discussion Papers 08-064, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
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  4. Uwe Cantner & Holger Graf, 2003. "Cooperation and Specialization in German Technology Regions," Jenaer Schriften zur Wirtschaftswissenschaft 04/2003, Friedrich-Schiller-Universität Jena, Wirtschaftswissenschaftliche Fakultät.
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  6. Dirk Engel & Oliver Heneric, 2005. "Biotechnologie-Gründungen im Ruhrgebiet – Eine vergleichende Analyse," RWI Materialien, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, pages 33, December.
  7. Cassi, Lorenzo & Plunket, Anne, 2010. "The determinants of co-inventor tie formation: proximity and network dynamics," MPRA Paper 27303, University Library of Munich, Germany.
  8. Mario A. Maggioni & Mario Nosvelli & Teodora Erika Uberti, 2007. "Space versus networks in the geography of innovation: A European analysis," Papers in Regional Science, Wiley Blackwell, vol. 86(3), pages 471-493, 08.
  9. Wagner, Alfred, 1891. "Marshall's Principles of Economics," History of Economic Thought Articles, McMaster University Archive for the History of Economic Thought, vol. 5, pages 319-338.
  10. Dirk Fornahl & Tom Broekel & Ron Boschma, 2010. "What drives patent performance of German biotech firms? The impact of R&D subsidies, knowledge networks and their location," Papers in Evolutionary Economic Geography (PEEG) 1009, Utrecht University, Section of Economic Geography, revised Aug 2010.
  11. Vuong, Quang H, 1989. "Likelihood Ratio Tests for Model Selection and Non-nested Hypotheses," Econometrica, Econometric Society, vol. 57(2), pages 307-33, March.
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