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

Scherngell, Thomas; Barber, Michael J.

doi:10.1111/j.1435-5957.2008.00215.x

Cited by 177 publications

(157 citation statements)

References 40 publications

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“…see Costantini and Mazzanti, 2012;Kahouli and Maktouf, 2014). This equation has also been extensively used in the literature on research collaboration among European regions (see, for examples, Hoekman et al, 2009;Hoekman et al, 2010;Maggioni and Uberti, 2009;Ponds et al, 2007;Scherngell and Barber, 2009a;Scherngell and Barber, 2009b;Scherngell and Hu, 2010).…”

Section: Methodsmentioning

confidence: 99%

Proximity dimensions and scientific collaboration among academic institutions in Europe: The closer, the better?

2016

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ABSTRACT:The main objective of this paper is to examine the effect of various proximity dimensions (geographical, cognitive, institutional, organizational, social and economic) on academic scientific collaborations (SC). The data to capture SC consists of a set of co-authored articles published between 2006 and 2010 by universities located in EU-15, indexed by the Science Citation Index (SCI Expanded) of the ISI Web of Science database. We link this data to institution-level information provided by the EUMIDA dataset. Our final sample consists of 240,495 co-authored articles from 690 European universities that featured in both datasets. Additionally, we also retrieved data on regional R&D funding from Eurostat. Based on the gravital equation, we estimate several econometrics models using aggregated data from all disciplines as well as separated data for Chemistry & Chemical Engineering, Life Sciences and Physics & Astronomy. Our results provide evidence on the substantial role of geographical, cognitive, institutional, social and economic distance in shaping scientific collaboration, while the effect of organizational proximity seems to be weaker. Some differences on the relevance of these factors arise at discipline level.

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Section: Methodsmentioning

confidence: 99%

Proximity dimensions and scientific collaboration among academic institutions in Europe: The closer, the better?

2016

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“…However, key players of the regional innovation systems, such as universities and large knowledge-intensive firms do not only benefit from the local knowledge base, but increasingly are compelled to search for knowledge sources that are geographically located further away in order to keep pace in the global innovation competition (see, for example, Maggioni et al 2007, Scherngell and Barber 2009and 2011, Wanzenböck et al 2012. Such region-external knowledge sources are tapped via region-external research collaboration activities -for instance in the form of joint R&D projects, joint assignment of patents or joint conduction of scientific publications -and/or labour mobility.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Research Collaboration and Regional Knowledge Production in Europe

Hidas

Wolska

Fischer

et al. 2013

The Geography of Networks and R&D Collaborations

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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. Abstract. The focus of this study is on regional knowledge production in Europe, with special emphasis on the interplay between intra-and inter-regional research collaboration. The objective is to identify and measure effects of research collaboration on knowledge production at the level of European regions. We use a panel data spatial Durbin model (SDM) relationship for empirical testing. The European coverage is achieved using 228 NUTS-2 regions covering all pre-2007 EU member states except Cyprus, Greece and Malta. The dependent variable, regional knowledge production, is measured in terms of fractional patent counts at the regional level in the time period [2000][2001][2002][2003][2004][2005][2006][2007][2008], using patents applied at the European Patent Office (EPO). The independent variables include an agglomeration variable, reflecting intra-regional research collaboration, measured in terms of employment in knowledge intensive sectors, and a network variable, reflecting extra-regional research collaboration, measured in terms of a region´s collaboration activities in the EU Framework programmes (FPs), weighted by R&D expenditures in network partner regions. We implement a panel version of the standard SDM that controls for spatial autocorrelation as well as individual heterogeneity across regions, and allows for the estimation of spatial spillovers from neighbouring regions. The estimation results confirm the prevalence of agglomeration effects for regional knowledge production, and, by this, the importance of co-location of R&D actors. Furthermore, the study provides evidence that inter-regional R&D collaborations in the FPs significantly contribute to regional knowledge production. Up to now, there is only little empirical evidence on the local-global duality in knowledge creation at the regional level. In this study we take a regional perspective to address this question drawing on novel data sets providing information on project based networking activities in the The paper is organised as follows. Section 2 sheds some light on the theoretical background for the study, focusing on regional knowledge production and the importance of extra-regional research collaboration for gaining access to external knowledge sources. Section 3 outlines the econometric framework, specifying the empirical model in form of a panel version of the SDM relationship to be estimated. Section 4 comprises a detailed description of the empirical setting, presenting the ...

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“…These studies exhibit a high degree of variation in terms of scope, definition of nodes (organization or region) and methodological choice, but they all focus on explaining the determinants of bilateral 3 cooperation based on one-mode network representations (Autant-Bernard et.al., 2007;Paier and Scherngell, 2008;Scherngell and Barber, 2009;Lata and Scherngell, 2010;Broekel and Hartog, 2011).…”

Section: Introductionmentioning

confidence: 99%

Using Affiliation Networks to Study the Determinants of Multilateral Research Cooperation: Some Empirical Evidence from EU Framework Programs in Biotechnology

Hazir

Autant‐Bernard²

2012

SSRN Journal

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

Cited by 177 publications

References 40 publications

Proximity dimensions and scientific collaboration among academic institutions in Europe: The closer, the better?

Proximity dimensions and scientific collaboration among academic institutions in Europe: The closer, the better?

Research Collaboration and Regional Knowledge Production in Europe

Using Affiliation Networks to Study the Determinants of Multilateral Research Cooperation: Some Empirical Evidence from EU Framework Programs in Biotechnology

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