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Determinants of cross-regional R&D collaboration: some empirical evidence from Europe in biotechnology

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  • Cilem Hazir
  • Corinne Autant-Bernard

Abstract

In this study, we focus on the pattern of cross-regional R&D collaborations through which voluntary knowledge flows and accompanying spillovers might occur. Our aim is to investigate the processes that give rise to the observed network configuration in order to identify hampering factors of knowledge diffusion, with a particular interest in the role of geographical proximity and differences in territorial features. We make use of the data on project proposals submitted to the 7th Framework Programme in the field of biotechnology. We build a non-valued inter-regional R&D cooperation network among a set of European regions and study its formation through exponential random graph models (Frank and Strauss in J Am Stat Assoc 81(395):832–842, 1986 ; Wasserman and Pattison in Psychometrika 61(3):401–425, 1996 ). Besides the role played by absorptive capacities, the empirical results reveal that contiguity affects the pattern of cross-regional collaborations not only via edge formation among neighbours but also through a triadic closure process which links neighbouring regions to non-neighbours. Furthermore, triadic closure is found out to be in play among highly populated regions and regions including capital cities. Copyright Springer-Verlag Berlin Heidelberg 2014

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  • Cilem Hazir & Corinne Autant-Bernard, 2014. "Determinants of cross-regional R&D collaboration: some empirical evidence from Europe in biotechnology," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 53(2), pages 369-393, September.
    • Handle: RePEc:spr:anresc:v:53:y:2014:i:2:p:369-393
    DOI: 10.1007/s00168-014-0606-4
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    Citations

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    Cited by:

    1. Lorenzo CASSI & Emilie-Pauline GALLIÉ & Agénor LAHATTE & Valérie MERINDOL, 2018. "Scientific network centrality of European regions: the role of territorial resources," Region et Developpement, Region et Developpement, LEAD, Universite du Sud - Toulon Var, vol. 47, pages 5-26.
    2. Hermans, Frans, 2021. "The contribution of statistical network models to the study of clusters and their evolution," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 100(2), pages 379-403.
    3. Lili Wang & Xianwen Wang & Niels J. Philipsen, 2017. "Network structure of scientific collaborations between China and the EU member states," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 765-781, November.
    4. Lili Yuan & Yanni Hao & Minglu Li & Chunbing Bao & Jianping Li & Dengsheng Wu, 2018. "Who are the international research collaboration partners for China? A novel data perspective based on NSFC grants," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 401-422, July.
    5. Luigi Aldieri & Gennaro Guida & Maxim Kotsemir & Concetto Paolo Vinci, 2019. "An investigation of impact of research collaboration on academic performance in Italy," Quality & Quantity: International Journal of Methodology, Springer, vol. 53(4), pages 2003-2040, July.
    6. Mitze, Timo & Strotebeck, Falk, 2019. "Determining factors of interregional research collaboration in Germany's biotech network: Capacity, proximity, policy?," Technovation, Elsevier, vol. 80, pages 40-53.
    7. Gergő Tóth & Sándor Juhász & Zoltán Elekes & Balázs Lengyel, 2021. "Repeated collaboration of inventors across European regions," European Planning Studies, Taylor & Francis Journals, vol. 29(12), pages 2252-2272, December.
    8. Mitze, Timo & Strotebeck, Falk, 2017. "Modeling interregional research collaborations in German biotechnology using industry directory data: A quantitative social network analysis," MPRA Paper 83392, University Library of Munich, Germany.
    9. Cilem Selin Hazir & James Lesage & Corinne Autant-Bernard, 2014. "The Role of R&D Collaboration Networks on Regional Innovation Performance," Working Papers halshs-01073031, HAL.
    10. Luqi Li & Ben Derudder & Wei Shen & Xiang Kong, 2022. "Exploring the dynamics of the disaggregated intercity corporate network in the Yangtze River Delta, China: a relational event approach," Journal of Geographical Systems, Springer, vol. 24(1), pages 115-140, January.

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    Keywords

    L14; O31; O38;
    All these keywords.

    JEL classification:

    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy

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