Skip to main content
SpringerLink
Log in

Twenty-five years of science-industry collaboration: the emergence and evolution of policy-driven research networks across Europe

  • Published:
The Journal of Technology Transfer Aims and scope Submit manuscript

Abstract

This paper aims at examining the collaborative networks established during the seven Framework Programmes on Research and Technological Development (1984–2009). These networks are the result of self-organized partnering by different participating entities (industry, universities, research centers and technology users) in subsidized research joint ventures selected on a competitive basis under the thematic priorities and funding rules imposed by the European Union. Social network analysis tools are employed in order to describe and assess the architecture, and the dynamics of the networks that were developed in the context of each Framework Programme. Analysis of organizations’ positioning in the network space will show whether there are some pivotal actors with significant policy implications for knowledge and technology transfer. Last but not least, understanding how these network are formed and how they have evolved over time may provide useful policy implications for the design and structure of the current and future EU Programmes aimed at shaping and creating a unified European Research Area.

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
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Notes

  1. FP7 includes partial data up to the end of 2009. The database is being updated with the missing data and information on FP7as soon as they become available.

  2. Organizations receive a ranking in terms of their performance in each of the four centrality measures used. The synthetic index or centrality score is calculated using the sum of the four rankings. A smaller synthetic index indicates a more central organization in the network. The same methodology in terms of constructing the synthetic centrality index (but on the basis of two different centrality measures) is followed by Breschi and Malerba (2009)

  3. Independent-sample t tests that have been conducted to compare participants, participating countries and funding per project for subsequent FPs (e.g. FP1–FP2, FP2–FP3 etc.) confirmed statistically significant differences in these variables’ scores through time.

  4. Participation intensity represents the number of project participations per organization type.

  5. The percentage of organizations returning to FP7 from FP6 seems to have been doubled compared to that of returning entities to FP6 from FP5. However, the available interim FP7 data include just the first calls and should be considered with caution.

  6. Switzerland, Norway, Israel, Iceland and Liechtenstein.

  7. The total cross-country connections for each group, is the sum of intra-group (i.e. those developed between the different countries of the group) and intergroup links i.e. connections of the specific group to other country groups.

  8. Degree distributions following a power-law P(k) ~ k − γ with scaling exponent γ taking a value between 2.1 and 4 suggest ‘scale-free’ distributions of the relevant graphs (Barabàsi and Albert 1999).

  9. The top 1 % central actors’ subgroup was chosen arbitrarily. However their removal from the RJVs networks resulted in a significant drop of the giant component initial size. In addition these organizations accounted for a significant fraction of the total networks’ ties. We used different values than the one adopted (e.g. top 5 %) to check for robustness and the main results remained unaffected.

  10. The number of top 1 % central actors ranges from minimum 18 organizations in FP1 to maximum 199 in FP 5.

References

  • Arnold, E., Åström, T., Boekholt, P., Brown, N., Good, B., Holmberg, R., et al. (2008). Impacts of the Framework Programme in Sweden. Stockholm: VINNOVA.

    Google Scholar 

  • Barabàsi, A. L., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286, 509.

    Article  Google Scholar 

  • Barabàsi, A. L., Jeong, H., Neda, Z., Ravasz, E., Schubert, A., & Vicsek, T. (2002). Evolution of the social network of scientific collaborations. Physica A, 311(3–4), 590–614.

    Article  Google Scholar 

  • Barajas, A., Huergo, E., & Moreno L. (2011). Measuring the economic impact of research joint ventures supported by the EU Framework Programme. Journal of Technology Transfer. doi:10.1007/s10961-011-9222-y.

  • Barber, M., Krueger, A., Krueger, T., & Roediger-Schluga, T. (2006). The network of EU-funded collaborative R&D projects. Physical Review E, 73, 036132. (arXiv:physics/0509119).

    Article  Google Scholar 

  • Barker, K., & Cameron, H. (2004). European Union science and technology policy, RJV collaboration and competition policy. In Y. Caloghirou, N. S. Vonortas, & S. Ioannides (Eds.), European Collaboration in Research and Development: Business strategies and public policies. Cheltenham: Edward Elgar.

    Google Scholar 

  • Baum, J. A. C., Shipilov, A. V., & Rowley, T. J. (2003). Where do small worlds come from? Industrial and Corporate Change, 12(4), 697–725.

    Article  Google Scholar 

  • Bell, G. G. (2005). Clusters, networks and firm innovativeness. Strategic Management Journal, 26, 281–295.

    Article  Google Scholar 

  • Borgatti, S. P., & Everett, M. G. (2006). A graph-theoretic framework for classifying centrality measures. Social Networks, 28(4), 466–484.

    Article  Google Scholar 

  • Breschi, S., & Cusmano, L. (2004). Unveiling the texture of a European Research Area: Emergence of oligarchic networks under EU Framework Programmes. International Journal of Technology Management, 27(8), 747–772.

    Article  Google Scholar 

  • Breschi, S., & Malerba, F. (2009). ERA and the role of networks. In H. Delanghe, U. Muldur, & L. Soete (Eds.), European Science and Technology Policy: Towards integration or fragmentation. Cheltenham: Edward Elgar.

    Google Scholar 

  • Caloghirou, Y., Ioannides, S., & Vonortas, N. S. (2004). Research joint ventures: A survey in theoretical literature. In Y. Caloghirou, N. S. Vonortas, & S. Ioannides (Eds.), European Collaboration in Research and Development: Business strategies and public policies. Cheltenham: Edward Elgar.

    Google Scholar 

  • Colombo, M. G., Grilli, L., Murtinu, S., Piscitello, L., & Piva, E. (2009). Effects of international R&D alliances on the performance of high-tech start-ups: A longitudinal analysis. Strategic Entrepreneurship Journal, 3, 348–370.

    Article  Google Scholar 

  • Cowan, R. (2005). Network models of innovation and knowledge diffusion. In S. Breschi & F. Malerba (Eds.), Clusters, networks and innovation. New York: Oxford University Press.

    Google Scholar 

  • Cowan, R., & Jonard, N. (2003). The dynamics of collective invention. Journal of Economic Behavior & Organization, 52, 513–532.

    Article  Google Scholar 

  • Delanghe, H., Sloan, B., & Muldur, U. (2009). Transnational collaboration in public research funding and publicly supported research in Europe. In H. Delanghe, U. Muldur, & L. Soete (Eds.), European Science and Technology Policy: Towards integration or fragmentation. Cheltenham: Edward Elgar.

    Chapter  Google Scholar 

  • Dosi, G., Llerena, P., & Labini, M. S. (2006). The relationships between science, technologies and their industrial exploitation: An illustration through the myths and realities of the so-called ‘European Paradox’. Research Policy, 35(10), 1450–1464.

    Article  Google Scholar 

  • European Commission. (1997). Five-year assessment of the European Community RTD Framework Programmes. Brussels: Report of the Independent Expert Panel and Commission Comments.

    Google Scholar 

  • European Commission. (2002). The European Research Area: Providing new momentum. Brussels: Communication to the Commission.

    Google Scholar 

  • European Commission. (2009). Evaluation of the Sixth Framework Programme for research and technological development 2002–2006. Brussels: Report of the Expert Group.

    Google Scholar 

  • Freeman, L. C. (1979). Centrality in social networks: I. Conceptual clarification. Social Networks, 1, 215–239.

    Article  Google Scholar 

  • Knoke, D., & Kuklinski, J. L. (1982). Network analysis. Newbury Park: Sage.

    Google Scholar 

  • Luukkonen, T. (1998). The difficulties in assessing impact of EU framework programmes. Research Policy, 27(6), 599–610.

    Article  Google Scholar 

  • Luukkonen, T. (2001). Old and new strategic roles for the European Union Framework Programmes. Science and Public Policy, 28(3), 205–218.

    Article  Google Scholar 

  • Luukkonen, T. (2002). Technology and market orientation in company participation in the EU framework programme. Research Policy, 31(3), 1459–1466.

    Article  Google Scholar 

  • Marin, P., & Siotis, G. (2008). Public policies towards research joint venture: Institutional design and participants characteristics. Research Policy, 37, 1057–1065.

    Article  Google Scholar 

  • Mitsos, A. (2007). The EU research policy. In N. Maravegias & M. Tsinisizelis (Eds.), The New European Union: Organization and policies. Athens: Themelio Editions. (in Greek).

    Google Scholar 

  • Muldur, U., Convers, F., Delanghe, H., Dratwa, J., Heimberger, D., Sloan, B., et al. (2006). Building on experience: Learning lessons from past framework programmes. In U. Muldur, F. Corvers, H. Delanghe, J. Dratwa, D. Heimberger, B. Sloan, & S. Vanslembrouck (Eds.), A new deal for an effective European research policy: The design and impacts of the 7th framework (pp. 93–141). The Netherlands: Springer.

  • Peterson, J., & Sharp, M. (1998). Technology policy in the European Union. New York: St. Martin’s Press.

    Google Scholar 

  • Polt, W., Vonortas, N., & Fisher, R. (2008). Innovation Impact of FP5 and FP6. Final Report to DG Enterprise of the European Commission.

  • Powell, W. W., Koput, K. W., & Smith-Doerr, L. (1996). Interorganizational collaboration and the locus of innovation: Networks of learning in biotechnology. Administrative Science Quarterly, 41, 116–145.

    Article  Google Scholar 

  • Roediger-Schluga, T., & Barber, M. J. (2008). R&D collaboration networks in the European Framework Programmes: Data processing, network construction and selected results. International Journal of Foresight and Innovation Policy, 4, 321–347.

    Article  Google Scholar 

  • Soete, L. (2009). The European Research Area as industrial policy tool. In H. Delanghe, U. Muldur, & L. Soete (Eds.), European Science and Technology Policy: Towards integration or fragmentation. Cheltenham: Edward Elgar.

    Google Scholar 

  • Vonortas, N. S. (2009). Scale and scope in research. In H. Delanghe, U. Muldur, & L. Soete (Eds.), European Science and Technology Policy: Towards Integration or Fragmentation. Cheltenham: Edward Elgar.

    Google Scholar 

  • Wasserman, S., & Faust, K. (1994). Social network analysis: Methods and applications. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Watts, D. J. (1999). Networks, dynamics and the small-world phenomenon. American Journal of Sociology, 105, 493–528.

    Article  Google Scholar 

Download references

Acknowledgments

We thank all participants and paper discussants for their insightful comments and suggestions. We also wish to thank two anonymous referees for their valuable comments that contributed significantly to the improvement of our work.

Author information

Authors and Affiliations

  1. Laboratory of Industrial and Energy Economics, National Technical University of Athens, Heroon Polytechniou 9 str., Zografou Campus, 157 80, Athens, Greece

    Aimilia Protogerou, Yannis Caloghirou & Evangelos Siokas

Authors
  1. Aimilia Protogerou
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yannis Caloghirou
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Evangelos Siokas
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Aimilia Protogerou.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Protogerou, A., Caloghirou, Y. & Siokas, E. Twenty-five years of science-industry collaboration: the emergence and evolution of policy-driven research networks across Europe. J Technol Transf 38, 873–895 (2013). https://doi.org/10.1007/s10961-012-9278-3

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10961-012-9278-3

Keywords

JEL Classification

Search

Navigation