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European Cluster Networks ? Insights from 7th EU Framework Program

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  • Mirko Titze

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  • Matthias Brachert

Abstract

The EU Framework Programme (FP) belongs to the most important instruments promoting transnational collaborative R&D projects in Europe. Its main objective is to initiate cross-border complementarities in order to exploit knowledge resources and to conduct large scale research. Within the EU FPs the applicants are free to choose partners from all over Europe. The key question of our paper is: Which determinants affect the emergence of intra- and interregional collaborations within EU Framework Programmes? One might assume that geographical factors do not matter since trade barriers have been eliminated in the Single European Market. Though, there is a controversial debate on the importance of geographical proximity for the exchange of knowledge. Our paper relies on two theoretical concepts. First, we apply the global cluster networks conception developed by Bathelt and Li (2013). Within this concept it is argued that clustered organizations are more likely to set up collaborative R&D efforts with other similar clustered organizations to keep up with wider industry developments. Conversely, non-cluster organizations are less likely to get integrated cluster destinations. Second, we tie in with the proximity debate discussed in Boschma (2005). According to this concept geographical proximity addresses only one facet. Beyond physical distance other forms of proximity are existent such as social, cognitive, organisational and institutional proximity. It is argued that physical distance is neither a necessary nor a sufficient condition for interactive learning processes. Though, it may facilitate the other dimensions of proximity. In line with these strands of research we investigate the determinants of the number of cross-region collaborations within EU FPs. The analysis is focused on regional level (NUTS 2). Moreover, we differentiate between two technology fields, biotechnology and aerospace. In doing so, we are capable to capture technology specific characteristics. We apply a spatial interaction modelling framework that bases on a gravity type (Scherngell and Barber 2009). The empirical analysis is carried out using a negative binomial specification. We found evidence that geographical factors still matter ? but technological proximity seems to be more importantly. Moreover, we prove that the mere size in terms of employment and establishments is not necessarily required to establish cross-region collaborations. Also small actors have been chosen as partners in collaborative R&D networks across Europe.

Suggested Citation

  • Mirko Titze & Matthias Brachert, 2014. "European Cluster Networks ? Insights from 7th EU Framework Program," ERSA conference papers ersa14p552, European Regional Science Association.
  • Handle: RePEc:wiw:wiwrsa:ersa14p552
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    References listed on IDEAS

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    1. Mario Maggioni & Teodora Erika Uberti & Stefano Usai, 2011. "Treating Patents as Relational Data: Knowledge Transfers and Spillovers across Italian Provinces," Industry and Innovation, Taylor & Francis Journals, vol. 18(1), pages 39-67.
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    4. Thomas Scherngell & Michael J. Barber, 2009. "Spatial interaction modelling of cross‐region R&D collaborations: empirical evidence from the 5th EU framework programme," Papers in Regional Science, Wiley Blackwell, vol. 88(3), pages 531-546, August.
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    6. Rolf Sternberg & Timo Litzenberger, 2004. "Regional clusters in Germany--their geography and their relevance for entrepreneurial activities," European Planning Studies, Taylor & Francis Journals, vol. 12(6), pages 767-791, September.
    7. Ron Boschma, 2005. "Proximity and Innovation: A Critical Assessment," Regional Studies, Taylor & Francis Journals, vol. 39(1), pages 61-74.
    8. Thomas Scherngell & Michael Barber, 2011. "Distinct spatial characteristics of industrial and public research collaborations: evidence from the fifth EU Framework Programme," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 46(2), pages 247-266, April.
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    1. Lucian-Florin Onișor, 2015. "Marketing and Business Development between Idea, Scientific Discovery and Innovation," International Conference on Marketing and Business Development Journal, The Bucharest University of Economic Studies, vol. 1(1), pages 29-39, July.

    More about this item

    JEL classification:

    • D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
    • L14 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Transactional Relationships; Contracts and Reputation
    • R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
    • R15 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Econometric and Input-Output Models; Other Methods

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