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54th Congress of the European Regional Science Association: "Regional development & globalisation: Best practices", 26-29 August 2014, St. Petersburg, Russia
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.
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