Spurred on by the theory of network formation, and by the geography of innovation, traditional analyses on R&D cooperation face a deep renewal. This paper assesses the extent to which these renewals find an empirical validation. Based on the research projects submitted to the 6-super-th Framework Program of the European Union, a binary choice model is used in order to highlight the existence of network and spatial effects alongside other microeconomic determinants of cooperation. Our findings suggest that network effects are present, so that probability of collaboration is influenced by each individual's position within the network. Social distance thus seems to matter more than geographical distance. Copyright (c) 2007 the author(s). Journal compilation (c) 2007 RSAI.

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in SummaryIn this paper, we compare two different representations of Framework Programs as affiliation network: "One-mode networks"' and "Two-mode networks"'. The aim of this article is to show that the choice of the representation has an impact on the analysis of the networks and on the results of the analysis. In order to support our proposals, we present two forms of representation and different indicators used in the analysis. We study the network of the 6 th Framework Program using the two forms of representation. In particular, we show that the identification of the central nodes is sensitive to the chosen representation. Furthermore, the nodes forming the core of the network vary according to the representation. These differences of results are important as they can influence innovation policies.

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