Spatial interaction modelling of cross-region R&D collaborations: empirical evidence from the 5th EU framework programme

By Thomas Scherngell, Michael J. Barber. 2009

253 citations recorded by the source corpus.

The focus of this study is on cross-region R&D collaborations in Europe. We use data on collaborative R&D projects funded by the 5th EU Framework Programme (FP5). The objective is to identify separation effects - such as geographical or technological effects - on the constitution of cross-region collaborative R&D activities within a Poisson spatial interaction modelling framework. The results provide striking evidence that geographical factors are important determinants of cross-region collaboration intensities, but the effect of technological proximity is stronger. R&D collaborations occur most often between organizations that are located close to each other in technological space. Copyright (c) 2009 the author(s). Journal compilation (c) 2009 RSAI.

Subfields: Economics and Econometrics, Strategy and Management

View Paper: https://www.semanticscholar.org/paper/0ad8394b436c04acc6b228a704bff83286524173

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Citations in the corpus

Distinct spatial characteristics of industrial and public research collaborations: evidence from the fifth EU Framework Programme (2010, methodology): “As in Scherngell and Barber (2009), we adopt a Poisson spatial interaction modelling perspective to estimate the separation effects for crossregion industry and public research networks.”
Networks of innovators within and across borders. Evidence from patent data (2013, background): “…for a negative effect of physical distance and country borders on the likelihood of collaboration (Ponds et al., 2007; Maggioni and Uberti, 2007; Scherngell and Barber, 2009; Frenken et al., 2009b; Hoekman et al., 2009, 2010; Scherngell and Barber, 2011; Scherngell and Hu, 2011; Scherngell and…”
Acquisition of European research funds and its effect on international scientific collaboration. (2013, methodology): “Scherngell and Barber (2009, 2010) have studied the importance of spatial and other impediments for collaboration within the fifth FP and conclude that – despite the intended European character – the number of links between organisations in the fifth FP funding scheme tends to decay with…”
Determinants of Collaboration in European R&D Networks: Empirical Evidence from a Discrete Choice Model (2011, background): “While Scherngell and Barber (2009, 2010) use regions as units of analysis, we focus on individual organizations and adopt a discrete choice modelling perspective that provides a suitable analytical framework to address the objective of the current study.”