Skip to main content
SpringerLink
Log in

Determinants of cross-regional R&D collaboration: some empirical evidence from Europe in biotechnology

  • Special Issue Paper
  • Published:
The Annals of Regional Science Aims and scope Submit manuscript

Abstract

In this study, we focus on the pattern of cross-regional R&D collaborations through which voluntary knowledge flows and accompanying spillovers might occur. Our aim is to investigate the processes that give rise to the observed network configuration in order to identify hampering factors of knowledge diffusion, with a particular interest in the role of geographical proximity and differences in territorial features. We make use of the data on project proposals submitted to the 7th Framework Programme in the field of biotechnology. We build a non-valued inter-regional R&D cooperation network among a set of European regions and study its formation through exponential random graph models (Frank and Strauss in J Am Stat Assoc 81(395):832–842, 1986; Wasserman and Pattison in Psychometrika 61(3):401–425, 1996). Besides the role played by absorptive capacities, the empirical results reveal that contiguity affects the pattern of cross-regional collaborations not only via edge formation among neighbours but also through a triadic closure process which links neighbouring regions to non-neighbours. Furthermore, triadic closure is found out to be in play among highly populated regions and regions including capital cities.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1

Similar content being viewed by others

Notes

  1. Communicative rationality is a term proposed by Habermas (1984). While the strategic rationality refers to the case where actors are driven by their own goals and they decide by anticipating the others decision; communicative rationality refers to the case where actors come together to reach a common understanding and coordinate their action.

  2. http://www.eurolio.eu/.

  3. Within the FP Collaborative projects, the EU distinguishes different types of projects according to the size, scope and internal organization of FP projects. FP collaboration projects can range therefore from small or medium-scale focused research actions to large-scale integrating projects. The definition of small or medium-scale focused research projects changes from topic to topic and bases on limits to the requested EC financial contribution (as an example, this limit might be 1-3 million euros for a small- to medium-scale projects in biotech, 6-9 million euros for large-scale projects).

  4. Overseas departments of France for instance (Guadeloupe, Martinique, French Guiana, Réunion), Canary Islands, Autonomous regions of Portugal consisting of volcanic islands (Madeira and Açores), etc.

  5. The process by which two direct neighbours of a node become direct neighbours.

  6. Estimations and goodness-of-fit analysis made using the PNet program (Wang et al. 2006).

  7. “At least three legal entities must participate, each of which must be established in a Member State or associated country, and no two of which may be established in the same Member State or associated country” (Regulation(EC) No 1906/2006; Article 5/(1), p.5).

  8. See Hazir (2014) for a detailed presentation of goodness-of-fit analysis in ERGM.

  9. This is not presented in Table 4, but all t-ratios for statistics included in the model are lower than 0.1.

  10. Due to changes in the themes and subthemes across different FPs we could not make use of information in earlier collaborations.

References

  • Acs ZJ, Audretsch DB, Feldman MP (1994) R&D spillovers and innovative activity. Manag Decis Econ 15(2):131–138

    Article  Google Scholar 

  • Almeida P, Kogut B (1999) Localization of knowledge and the mobility of engineers. Manag Sci 45(7): 905–917

  • Andersson M and Karlsson C (2005) Knowledge accessibility and regional economic growth. Working Paper Series in Economics and Institutions of Innovation from Royal Institute of Technology 40, CESIS-Centre of Excellence for Science and Innovation Studies

  • Anselin L, Varga A, Acs Z (2000) Geographical spillovers and university research: a spatial econometric perspective. Growth Change 31:501–515

    Article  Google Scholar 

  • Autant-Bernard C, Mangematin V, Massard N (2006) Creation of biotech SMEs in France: the role of local environment. Small Bus Econ J 26(2):173–187

    Article  Google Scholar 

  • Baldwin RE, Forslid R (2000) The core-periphery model and endogenous growth: stabilizing and de-stabilizing integration. Economica 67:307–324

    Article  Google Scholar 

  • Baldwin RE, Martin P, Ottaviano G (2001) Global economic divergence, trade and industrialisation: the geography of growth takeoffs. J Econ Growth 6:5–37

    Article  Google Scholar 

  • Beaudry C, Schiffauerova C (2011) Impacts of collaboration and network indicators on patent quality: the case of Canadian nanotechnology innovation. Eur Manag J 29(5):362–376

    Article  Google Scholar 

  • Besag J (1974) Spatial interaction and the statistical analysis of lattice systems. J R Stat Soc Series B (Methodol) 36(2):192–236

    Google Scholar 

  • Boschma RA (2005) Proximity and innovation: a critical assessment. Reg Stud 39(1):61–74

    Article  Google Scholar 

  • Camagni R, Pompili T (1990) Irreversible investment and internal evolution of firm networks: two case studies in the Lombardy region. In: Maillat D, Quévit M, Senn L, (eds) Réseaux dinnovation et Milieux Innovateurs: Un Pari Pour le Dévelopment Régional. Cambridge University Press, Cambridge, pp 235–258

  • Carayol N, Roux P (2007) The strategic formation of inter-individual collaboration networks: empirical evidence from co-invention patterns. Annales d’Economie et de Statistiques 87–88:275–301

    Google Scholar 

  • Carlsson B, Stankiewicz R (1995) On the nature, function and composition of technological systems. In: Carlsson B (ed) Technological systems and economic performance: the case of factory automation. Kluwer, Dordrecht

    Google Scholar 

  • Cohen WM, Levinthal DA (1990) Absorptive capacity: a new perspective on learning and innovation. Admin Q 35(1), Special Issue: technology, organizations, and innovation, pp 128–152

  • Coleman JS (1988) Social capital in the creation of human capital. The American Journal of Sociology, 94, supplement: Organizations and Institutions: Sociological and Economic Approaches to the Analysis of Social Structure, pp 95–120

  • Cooke P, Uranga MG, Etxebarria G (1997) Regional innovation systems: institutional and organisational dimensions. Res Policy 26:475–491

    Article  Google Scholar 

  • Edquist C (1997) Systems of innovation: technology institutions and organizations. Pinter, London

    Google Scholar 

  • Feldman MP (1993) An examination of the geography of innovation. Ind Corp Change 2(3):451–470

  • Feldman MP, Florida R (1994) The geographic sources of innovation: technological infrastructure and product innovation in the United States. Ann Assoc Am Geogr 84(2):210–229

    Article  Google Scholar 

  • Frank O, Strauss D (1986) Markov Graphs. J Am Stat Assoc 81(395):832–842

    Article  Google Scholar 

  • Gelsing L (2010) Innovation and the development of industrial networks. In: Lundvall BA (ed) National systems of innovation: toward a theory of innovation and interactive learning. Anthem Press, London

    Google Scholar 

  • Gertler MS and Levitte YM (2005) Local nodes in global networks: the geography of knowledge flows in biotechnology innovation. Retrieved [18/07/2012] from Cornell University, School of Industrial and Labor Relations site: http://digitalcommons.ilr.cornell.edu/articles/122

  • Geyer CJ, Thompson EA (1992) Constrained Monte Carlo maximum likelihood for dependent data. J R Stat Soc Series B (Methodol) 54(3):657–699

    Google Scholar 

  • Habermas J (1984) The theory of communicative action, vol I. Beacon Press, Boston

    Google Scholar 

  • Hazir CS (2014) Spatial dynamics of knowledge networks. PhD Thesis, Université de Saint-Etienne

  • Hagedoorn J (2002) Inter-firm R&D partnerships: an overview of major trends and patterns since 1960. Res Policy 31:477–492

    Article  Google Scholar 

  • Hanneke S, Fu W, Xing EP (2010) Discrete temporal models of social networks. Electron J Stat 4:585–605

    Article  Google Scholar 

  • Hazir CS (2013) Multilateral R&D collaboration: an ERGM application on biotechnology. In: Scherngell T (ed) Advances in spatial science: the geography of networks and R&D collaborations. Springer, forthcoming

  • Hoekman J, Frenken K, van Oort F (2009) The geography of collaborative knowledge production in Europe. Ann Reg Sci 43(3):721–738

    Article  Google Scholar 

  • Hoekman J, Frenken K, Tijsen RJW (2010) Research collaboration at a distance: changing spatial patterns of scientific collaboration within Europe. Res Policy 39:662–673

    Article  Google Scholar 

  • Jackson MO, Wolinsky A (1996) A strategic model of social and economic networks. J Econ Theory 71:44–74

    Article  Google Scholar 

  • Jaffe BA, Trajtenberg M, Henderson R (1993) Geographic localization of knowledge spillovers as evidenced by patent citations. Q J Econ 108(3):577–598

    Article  Google Scholar 

  • Johnson C, Gilles R (2000) Spatial social networks. Rev Econ Des 5:273–299

    Google Scholar 

  • Knoben J, Oerlemans LAG (2006) Proximity and inter-organizational collaboration: a literature review. Int J Manag Rev 8(2):71–89

    Article  Google Scholar 

  • Krivitsky PN and Handcock MS (2010) A separable model for dynamic, networks. arXiv:1011.1937v1

  • Krivitsky PN (2012) Exponential-family random graph models for valued networks. Electron J Stat 6:1100–1128

    Article  Google Scholar 

  • Lane PJ, Lubatkin M (1998) Relative absorptive capacity and inter-organizational learning. Strateg Manag J 19:461–477

    Article  Google Scholar 

  • Lundvall BA (1992) National systems of innovation: towards a theory of innovation and interactive learning. Pinter, London

    Google Scholar 

  • Lundvall BA et al (2002) National systems of production. Innovation and competence building. Res Policy 31(2):213–231

    Article  Google Scholar 

  • Maillat D, Quévit M, Senn L (1993) Réseaux d’innovation et Milieux Innovateurs: Un Pari Pour le Développement Régional. GREMI, EDES, Neuchâtel, Switzerland

    Google Scholar 

  • Morrison A et al (2011) When do global pipelines enhance knowledge diffusion in clusters? Papers in Evolutionary Economic Geography 11.05, Utrecht University Urban and Regional Research Centre

  • Owen-Smith J, Powell WW (2004) Knowledge networks as channels and conduits: the effects of spillovers in the boston biotechnology community. Organ Sci 15(1):5–21

    Article  Google Scholar 

  • Pattison P, Robins G (2002) Neighborhood-based models for social networks. Sociol Methodol 32:301–337

    Article  Google Scholar 

  • Powell WW, Koput KW, Smith-Doerr L (1996) Inter-organizational collaboration and the locus of innovation: networks of learning in biotechnology. Admin Sci Q 41(1):116–145

    Article  Google Scholar 

  • Powell WW et al (2005) Network dynamics and field evolution: the growth of inter-organizational collaboration in the life sciences. Am J Sociol 110(4):1132–1205

    Article  Google Scholar 

  • Quévit M (1993) Réseaux de Partenariats Technologiques et Milieux Innovateurs. In: Maillat D, Quévit M, Senn L (eds) Réseaux d’innovation et Milieux Innovateurs: Un Pari Pour le Dévelopment Régional. GREMI, EDES, Neuchâtel, Switzerland

    Google Scholar 

  • Regulation (EC) No 1906/2006 of the European Parliament and of the Council of 18 December 2006 laying down the rules for the participation of undertakings, research centres and universities in actions under the Seventh Framework Programme and for the dissemination of research results (2007–2013)

  • Robins G et al (2007) An introduction to exponential random graph (p*) models for social networks. Social Netw 29:173–191

    Article  Google Scholar 

  • Scherngell T, Barber MJ (2009) Spatial interaction modelling of cross-region R&D collaborations: empirical evidence from the 5th EU framework program. Pap Reg Sci 88(3):531–546

    Article  Google Scholar 

  • Scherngell T, Lata R (2013) Towards an integrated European research area? Findings from eigenvector spatially filtered spatial interaction models using European framework programme data. Pap Reg Sci 92(3):555–577

    Google Scholar 

  • Schiffauerova A, Beaudry C (2012) Collaboration spaces in canadian biotechnology: a search for gatekeepers. J Eng Technol Manag 29(2):281–306

    Article  Google Scholar 

  • Snijders TAB (2002) Markov chain Monte Carlo estimation of exponential random graph models. J Social Struct 3(2)

  • Straus D, Ikeda M (1990) Pseudolikelihood estimation for social networks. J Am Stat Assoc 85(409): 204–212

  • Walker G et al (1997) Social capital, structural holes and formation of an industry network. Organ Sci 8(2):109–125

    Article  Google Scholar 

  • Wang P et al (2006) PNet: a program for the simulation and estimation of exponential random graph models. School of Behaviour Science, University of Melbourne. URL http://www.sna.unimelb.edu.au/pnet/pnet.html

  • Wang P et al (2009) Exponential random graph (p*) models for affiliation networks. Social Netw 31:12–25

    Article  Google Scholar 

  • Wang P, Pattison P, Robins G (2012) Exponential random graph model specifications for bipartite networks—a dependence hierarchy. Social Networks. doi:10.1016/j.socnet.2011.12.004

  • Wasserman S, Pattison P (1996) Logit models and logistic regression for social networks: I. An introduction to markov graphs and p*. Psychometrika 61(3):401–425

    Article  Google Scholar 

  • Wuchty S, Jones BF, Uzzi B (2007) The increasing dominance of teams in production of knowledge. Science 316:1036–1039

    Article  Google Scholar 

Download references

Acknowledgments

This research has received funding from the European Community’s Seventh Framework Programme under Grant Agreement No. 266834 and also supported by the Programme FOuille de Reseaux d’Innovation (FORI- S752FORI1R) funded by Saint-Etienne Metropole, LHC, GATE-LSE , Eurolio (january 2011-october 2014). We would also like to thank Prof. Stefano Usai for his cooperation in obtaining the contiguity matrix. The usual disclaimer applies.

Author information

Authors and Affiliations

  1. Université de Lyon, 69007 , Lyon, France

    Cilem Selin Hazir & Corinne Autant-Bernard

  2. CNRS, GATE Lyon Saint-Étienne, 69130 , Ecully, France

    Cilem Selin Hazir & Corinne Autant-Bernard

  3. Université Jean Monnet, 42000 , Saint-Étienne, France

    Cilem Selin Hazir & Corinne Autant-Bernard

Authors
  1. Cilem Selin Hazir
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Corinne Autant-Bernard
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Cilem Selin Hazir.

Appendix

Appendix

See Table 5.

Table 5 Variable definitions
Full size table

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Hazir, C.S., Autant-Bernard, C. Determinants of cross-regional R&D collaboration: some empirical evidence from Europe in biotechnology. Ann Reg Sci 53, 369–393 (2014). https://doi.org/10.1007/s00168-014-0606-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00168-014-0606-4

JEL Classification

Search

Navigation