Mitze, Timo and Strotebeck, Falk (2017): Modeling interregional research collaborations in German biotechnology using industry directory data: A quantitative social network analysis.
Preview |
PDF
MPRA_paper_83392.pdf Download (1MB) | Preview |
Abstract
We use industry directory data as a novel source of information to model the strength of interregional research collaboration in German biotechnology. Specifically, we gather data on the number of research collaborations for biotech actors listed in the BIOCOM Year and Address book and aggregate this information to the level of German NUTS3 regions. This allows us to set up a modeling framework that treats individual regions as nodes of the biotech research network. We then specify the collaboration activity between regional nodes as a function of research and economic capacities at the regional level, the geographical proximity between regions, and policy variables. Our results show that the strength of interregional research collaboration can be related to both node properties and the relationship between nodes. As such, we find that modern locational factors are positively correlated with the extent of interregional research collaboration, while geographical distance is found to be an impediment to collaboration. The results further show that the pursuit of network and cluster policies in the biotech sector, particularly through collaborative R&D funding, is positively related to the strength of the interregional collaboration activity.
Item Type: | MPRA Paper |
---|---|
Original Title: | Modeling interregional research collaborations in German biotechnology using industry directory data: A quantitative social network analysis |
Language: | English |
Keywords: | Biotechnology, research collaboration, cluster policy, social network analysis, count data |
Subjects: | C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables > C21 - Cross-Sectional Models ; Spatial Models ; Treatment Effect Models ; Quantile Regressions L - Industrial Organization > L6 - Industry Studies: Manufacturing > L65 - Chemicals ; Rubber ; Drugs ; Biotechnology O - Economic Development, Innovation, Technological Change, and Growth > O3 - Innovation ; Research and Development ; Technological Change ; Intellectual Property Rights > O38 - Government Policy R - Urban, Rural, Regional, Real Estate, and Transportation Economics > R3 - Real Estate Markets, Spatial Production Analysis, and Firm Location > R38 - Government Policy |
Item ID: | 83392 |
Depositing User: | Dr. Timo Mitze |
Date Deposited: | 22 Dec 2017 04:32 |
Last Modified: | 01 Oct 2019 18:21 |
References: | Alecke, B.; Alsleben, C.; Scharr, F.; Untiedt, G. (2006): Are there really high-tech clusters? The geographic concentration of German manufacturing industries and its determinants, in: Annals of Regional Science, 40(1): 19-42. Anselin, L. (1988): Spatial Econometrics: Methods and Models, Kluwer: Dordrecht. Balconi, M.; Breschi, S.; Lissoni, F. (2004): Networks of inventors and the role of academia: an ex-ploration of Italian patent data, in: Research Policy, 33(1): 127‐145. Baptista, R.; Swann, G. (1998): Do firms in clusters innovate more?, in: Research Policy, 27(5): 525-540. Barabási, A.; Albert, R. (1999): Emergence of scaling in random networks, in: Science, 386(15): 509-512. Bathelt, H.; Malmberg, A.; & Maskell, P. (2004): Clusters and knowledge: Local buzz, global pipe-lines and the process of knowledge creation, in: Progress in Human Geography, 28: 31–56. BIOCOM AG (2005): BioTechnologie – Das Jahr- und Adressbuch 2005, Mietzsch, A. (Ed.), 19. Jahrgang, Berlin. BIOCOM AG (2009): BioTechnologie – Das Jahr- und Adressbuch 2005, Mietzsch, A. (Ed.), 23. Jahrgang, Berlin. BMBF (2010): Ideas. Innovation. Prosperity. High-Tech Strategy 2020 for Germany, Bundesministerium für Bildung und Forschung (BMBF): Bonn und Berlin. Boschma, R. (2005): Proximity and innovation: A critical assessment, in: Regional Studies, 39(1): 61-74. Breschi, S.; Lissoni, F. (2009): Mobility of skilled workers and co-invention networks: an anatomy of localized knowledge flows, in: Journal of Economic Geography, 9: 439-468. Broekel, T.; Brenner, T. (2011): Regional factors and innovativeness: an empirical analysis of four German industries, in: Annals of Regional Science, 47: 169-194. Broekel, T. (2015): Do cooperative R&D subsidies stimulate regional innovation efficiency? Evidence from Germany, in: Regional Studies, 49(7): 1087-1111. Broekel, T.; Fornahl, D.; Morrison, A. (2015): Another cluster premium: Innovation subsidies and R&D collaboration networks, in: Research Policy, 44(8): 1431–1444. Cantner, U.; Graf, H. (2004): Cooperation and Specialization in German Technology Regions, in: Journal of Evolutionary Economics, 14(5): 543-562. Cantner, U.; Graf, H.; Töpfer, S. (2015): Structural dynamics of innovation networks in German Leading-Edge Clusters, Jena Economic Research Papers No. 2015-26. Chun, Y.; Griffith, D. (2010): Modelling network autocorrelation in Space-Time Migration Flow Data: An Eigenvector Spatial Filtering Approach, in: Annals of the Association of American Geographers, 101(3): 523-536. Cohen, W.; Levinthal, D. (1990): Absorptive capacity: a new perspective on learning and innovation, in: Administrative Science Quarterly, 35: 128-152. Cooke, P.; De Laurentis, C.; Tödtling, F.; Trippl, M. (2007): Regional Knowledge Economies – Markets, Clusters and Innovation, Edward Elgar Publishing: Cheltenham. Dohse, D. (2007): Cluster-Based Technology Policy – The German Experience, in: Industry and Innovation, 14(1): 69-94. Dolfsma, W.; Seo, D. (2013): Government policy and technological innovation a suggested typology, in: Technovation, 33: 173-179. Engel, D.; Heneric, O. (2005): Biotechnologiegründungen im Ruhrgebiet - Eine vergleichende Analyse, RWI: Materialien, Heft 21, RWI: Essen. Engel, D.; Mitze, T.; Patuelli, R.; Reinkowski, J. (2013): Does cluster policy trigger R&D activity? Evidence from German biotech contests, in: European Planning Studies, 21(11): 1735-1759. Ernst & Young (2005): Kräfte der Evolution. Deutscher Biotechnologie-Report 2005, Ernst & Young AG Wirtschaftsprüfungsgesellschaft: Mannheim. Falck, O.; Heblich, S.; Kipar, S. (2010): Industrial innovation: Direct evidence from a cluster-oriented policy, in: Regional Science and Urban Economics, 40(6): 574-582. Fornahl, D.; Broekel, T.; Boschma, R. (2011): What drives patent performance in German biotech firms? The impact of R&D subsidies, knowledge networks and their location, in: Papers in Regional Science, 90(2): 395-418. Freeman, L. C. (1978/79): Centrality in Social Networks – Conceptual Clarification, in: Social networks, 1(3): 215-239. Fritsch, M.; Kudic, M. (2016): Preferential Attachment and Pattern Formation in R&D Networks – Plausible explanation or just a widespread myth?, Jena Economic Research Papers No. 2016-005. Gertler, M.; Levitte, Y. (2005): Local Nodes in Global Networks: The Geography of Knowledge Flows in Biotechnology Innovation, in: Industry and Innovation, 12(4): 487-507. Griffith, D. (2003): Spatial Autocorrelation and Spatial Filtering. Berlin. Grimpe, C.; Patuelli, R. (2011): Regional Knowledge Production in Nanomaterials: A Spatial Filtering Approach, in: Annals of Regional Science, 46(3): 519-541. Hazir, C.; Autant-Bernard, C. (2014): Determinants of cross-regional R&D collaboration: some empirical evidence from Europe in biotechnology, in: Annals of Regional Science, 53(2): 369-393. Jaffe, B.; Trajtenberg, M.; Henderson, R. (1993): Geographic localization of knowledge spillovers as evidenced by patent citations, in: Quarterly Journal of Economics, 108(3): 577-598. Kang, K.N.; Park, H. (2012): Influence of government R&D support and inter-firm collaborations on innovation in Korean biotechnology SMEs, in: Technovation, 32: 68-78. Kesteloot, K.; Veugelers, R. (1995): Stable R&D Cooperations with Spillovers, in: Journal of Economics and Management Strategy, 4(4): 651-672. Knoke, D.; Yang, S. (2008): Social Network Analysis, 2. edition, Sage: Thousand Oaks. Lecocq, C. (2010): Technological Performance of Regions (and Firms). The Case of Biotechnology, PhD thesis, Faculty of Business and Economics, Katholieke Universiteit Leuven. Ma, Z.; Lee, Y. (2008): Patent application and technological collaboration in inventive activities: 1980–2005, in: Technovation, 28(6): 379-390. Maggioni, M.; Nosvelli, N.; Uberti, T. (2007): Space versus networks in the geography of innovation: European analysis, in: Papers in Regional Science, 86(3): 471-493. Martin, P.; Mayer, T.; Mayneris, F. (2011): Public Support to Clusters: A Firm Level Study of French ‘Local Productive Systems, in: Regional Science and Urban Economics, 41(2): 108–123. Maskell, P.; Bathelt, H.; Malmberg, A. (2006): Building global knowledge pipelines: The role of temporary clusters, in: European Planning Studies, 14(8): 997-1013. McCann, P. (2013): Modern urban and regional economics. 2nd edition, Oxford University Press. Mwalili, S.; Lesaffre, E.; Declerck, D. (2008): The zero-inflated negative binomial regression model with correction for misclassification: an example in caries research, in: Statistical Methods in Medical Research, 17: 123-139. OECD (2010): Science, Technology and Industry Scoreboard 2009, OECD: Paris. Ó hUallancháin, B.; Lee, D.S. (2014): Urban centers and networks of co-invention in American biotechnology, in: Annals of Regional Science, 52: 799–823. Paci, R.; Marrocu, E.; Usai, S. (2014): The complementary effects of proximity dimensions on knowledge spillovers, in: Spatial Economic Analysis, 9(1): 9-30. Patuelli, R.; Schanne, N.; Griffith, D.; Nijkamp, P. (2012): Persistence of Regional Unemployment: Application of a Spatial Filtering Approach to Local Labour Markets in Germany, in: Journal of Regional Science, 52(2): 300–323. Quintana-Garcia, C.; Benavides-Velasco, C. (2004): Cooperation, competition and innovative capability: a panel data of European dedicated biotechnological firms, in: Technovation, 24: 927-938. Rose, A. (2004): Do we really know that the WTO increases trade?, in: American Economic Review, 94(1): 98-114. RWI, SG, Joanneum Research und Friedrich-Schiller Universität Jena (2014): Begleitende Evaluierung des Förderinstruments „Spitzencluster-Wettbewerb“ des BMBF: Abschlussbericht. RWI Projektberichte, available at: http://www.rwi-essen.de/publikationen/rwi-projektberichte/ (last accessed: 18.01.2017). Scherngell, T.; Barber, M. (2009): Spatial interaction modelling of cross-region R&D collaborations: empirical evidence from the 5th EU framework programme, in: Papers in Regional Science, 88(3): 531-546. Schweitzer, F.; Fagiolo, G.; Sornette, D.; Vega-Redondo, F.; Vespignani, A.; White, D. (2009): Eco-nomic Networks: The New Challenges, in: Science, 325: 422-425. Statistisches Bundesamt (2005): Unternehmen der Biotechnologie in Deutschland. Ergebnisse der Wiederholungsbefragung 2004, Statistisches Bundesamt: Wiesbaden. Ter Wal, A. (2014): The dynamics of the inventor network in German biotechnology: geographic proximity versus triadic closure, in: Journal of Economic Geography, 14(3): 589-620. Uyarra, E.; Ramlogan, R. (2012): The Effects of Cluster Policy on Innovation. Compendium of Evidence on the Effectiveness of Innovation Policy Intervention. Working paper, Manchester Institute of Innovation Research, Manchester Business School, University of Manchester. Veugelers, R. (1998): Collaboration in R&D: an assessment of theoretical and empirical findings, in: De Economist, 146(3): 419-443. Vuong, Q. (1989): Likelihood ratio tests for model selection and non-nested hypotheses, in: Econometrica, 57: 307-333. Wanzenböck, I.; Scherngell, T.; Brenner, T. (2014): Embeddedness of region in European knowledge networks: a comparative analysis of inter-regional R&D collaborations, co-patents and co-publications, in: Annals of Regional Science, 53(2): 337-368. Wanzenböck, I.; Scherngell, T.; Lata, R. (2015): Embeddedness of European regions in the European Union-funded research and development (R&D) network: A spatial econometric perspective, in: Regional Studies, 49(10): 1685-1705. Zeng, S.X; Xie, X.M.; Tam, C.M. (2010): Relationship between cooperation networks and innovation performance of SMEs, in: Technovation, 30: 181-194. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/83392 |