Distinct spatial characteristics of industrial and public research collaborations: evidence from the fifth EU Framework Programme

By Thomas Scherngell, Michael J. Barber. 2010

207 citations recorded by the source corpus.

This study compares the spatial characteristics of industrial R&D networks to those of public research R&D networks (i.e. universities and research organisations). The objective is to measure the impact of geographical separation effects on the constitution of cross-region R&D collaborations for both types of collaboration. We use data on joint research projects funded by the fifth European Framework Programme (FP) to proxy cross-region collaborative activities. The study area is composed of 255 NUTS-2 regions that cover the EU-25 member states (excluding Malta and Cyprus) as well as Norway and Switzerland. We adopt spatial interaction models to analyse how the variation of cross-region industry and public research networks is affected by geography. The results of the spatial analysis provide evidence that geographical factors significantly affect patterns of industrial R&D collaboration, while in the public research sector effects of geography are much smaller. However, the results show that technological distance is the most important factor for both industry and public research cooperative activities.

Subfields: Economics and Econometrics, Political Science and International Relations

View Paper: https://www.semanticscholar.org/paper/67e76460e4ab9edc6ee0c7a2293532601dad13c4

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Citations in the corpus

Determinants of Collaboration in European R&D Networks: Empirical Evidence from a Discrete Choice Model (2011, background): “Within a spatial interaction modelling framework, Scherngell and Barber ( 2010 ) identify differing geographical collaboration patterns for firms and public research.”
Industry 4.0: national and regional comparative advantages in key enabling technologies (2018, background): “As suggested in Scherngell and Barber (2011), the eigenvector is particularly useful in the analysis of regional networks and stems from the idea that while having many connections ensures that a region can exert influence and is able to access knowledge, it is also arguable that not all…”
Networks of innovators within and across borders. Evidence from patent data (2013, background): “…variable techdist that measures the technological distance between regions in a given year (Peri, 2005; Maggioni and Uberti, 2007; Paci and Usai, 2009; Hoekman et al., 2010; Scherngell and Barber, 2009, 2011; Scherngell and Hu, 2011; Scherngell and Lata, 2012; Miguèlez and Moreno, 2013).”