1. EU funded R&D collaboration networks in the area of Information Society Technologies and the role of Greek actors Aimilia Protogerou Team for the Technological, Economic and Strategic Analysis of the Information Society, LIEE/NTUA Ermoupolis Seminars 2007 12-15 July

2. Aim of the presentation To show some interesting findings on the structure and evolution of the research collaboration networks formed under the 4 th, 5 th and 6 th EU Framework Programmes during the period 1994-2006 in the area of Information Society Technologies (IST). To contribute to a better understanding of the role of Greek actors in these networks.

3. The RJV-IST type of networks These networks are comprised of firms, universities, research institutes and other organizations that get connected by cooperative contractual agreements. Exploration networks Policy-driven networks vs. other network types studied through patent citations or technology alliances.

4. Descriptive statistics of the RJV-IST database  Fewer projects, larger in size and with higher average funding in FP6 FP4FP5FP6 No of organizations4,8797,4063,879 No of participations9,30216,38110,582 No of projects1,4162,206799 Average duration (months)*25.65 (8.5)26.3 (8.82)32.85 (8.07) Average budget per project (million €)2.25 (3.72)2.68 (2.05)3.6 (6.45) Average funding per project (million €)1.08 (2.17)1.5 (1.04)2.2 (3.57) Average no of participants per project6.57 (4.26)7.43 (5.05)13.24 (9.11) Average project number per participant1.9 (3.15)2.2 (5.09)2.7 (5.6)

5. Returning and new entities by organization type (FP5 vs. FP4 and FP6 vs. FP4 +FP5)  There is a core of returning organizations exhibiting more stable relationships than others

6. Frequency of participation for all entity types in FPs  The grand majority of entities participate in only one project

7. Structural features of RJV-IST networks  FP networks are highly interconnected FP4FP5FP6 Nodes4,8797,4063,879 Edges35,69473,30980,437 No. of components601317 Giant component (size)4,6187,0383,854 % of total network94.795.199.2 Density0.0030.00270.0107 Stand. Deviation (density)0.05470,05170.1029 Characteristic path length3.393.152.373 Diameter776 Clustering coefficient0.8540.8420.846 Mean degree14.6919.841.47 Stand. Deviation (degree)21.9938.10470.903 Normalised degree (avg)0.30.30.2681.069

8. Degree distributions  Network connectivity is controlled by a few important actors

9. Preferential attachment  Highly connected nodes become even more connected through time

10. Network resilience  The network is vulnerable to the removal of the most connected nodes

11. Small-world property  The network under study seems to be an effective mechanism for the diffusion and exchange of technological knowledge FPNetwork Characteristic path length Clustering coefficient 4th Actual3.390.854 Random3.1640.003 5th Actual3.150.842 Random2.9840.003 6th Actual2.3730.846 Random2.2180.011

12. Top 1% and top 5% central actors (based on a composite index of four centrality measures)

13. Very active Greek participation in the RJV- IST networks

14. So far the networks examined: display characteristics typical for complex networks, such as scale-free distributions and small-world property are highly-connected and robust, gaining in connectivity through the years are dependent on a core of central actors finally, educational institutions and research centers assume a more active and prominent role compared to firms and ‘other’ actors.

15. Participation by organization type in the RJV- IST network: the participation of universities and research centers is increasing in time

16. Greece has a central role in the RJV-IST network, based on a composite 4-dimension centrality index

17. The ten most central Greek actors: 9 out of 10 are Universities and Research Centres --> Greek central role is mainly “Education & Research” based Organization nameRegionTypeParticipationsNo of PC National Technical University of AthensAtticaEducation17721 Intracom S.A.AtticaIndustry10729 National and Kapodistrian University of AthensAtticaEducation746 Foundation for Research and Technology - HellasCreteResearch6813 Aristotle University of ThessalonikiThessalonikiEducation581 University of PatrasPatraEducation527 National Centre for Scientific Research "Demokritos" AtticaResearch5011 Centre for Research and Technology HellasThessalonikiResearch4913 Athens University of Economics and BusinessAtticaEducation243 Technical University of CreteCreteEducation221

18. The increased presence (>70%) of the Attica region in the FP-driven IST network with Greek participation  The geography of Greek presence is highly concentrated

19. Universities and Research Centers located in the Attica region have a prominent position in the IST network

20. The impact of FP-driven research networks on innovation in Greece: Evidence from case studies  Mainly intangible benefits. The direct network impact, i.e. commercial deployment, was assessed as generally less intensive or significant compared to the indirect impact (i.e. improvement of skills and new knowledge diffusion, relations and trust built between partners, access to complementary knowledge and expertise). Nevertheless indirect impact is important and could be further exploited.

21. Deviation of the Greek ICT sector from EU average, based on aggregate innovation measures Greek ICT sector is deviating from EU average in all three variables measured (R&D intensity, share of market novelties in turnover, contribution to the labour productivity growth).

22. Why this mismatch? The size and nature of Greek ICT firms. The creators of technological knowledge in Greece do not generally think in terms of market opportunities exploitation. There is a lack of a critical mass of demanding users There is no early involvement of users The Greek environment operates in a rather disorganized and ‘anarchic’ manner

23. Why this mismatch? The purchasing practices of i.e. the Public sector- a major buyer- do not fit with the concept of intelligent customer. The nature and the quality of entrepreneurship as measured by the educational level of new entrepreneurs and the type and knowledge intensity of ventures undertaken (Global Entrepreneurship Monitoring, 2003-2006).

24. How this mismatch can be overcome? System of policies “activating knowledge” throughout the knowledge generation and diffusion value chain, and promoting knowledge-based entrepreneurship as a mechanism to convert research outputs into viable products. Not just policies providing incentives for SMEs. Promote intelligent customer practices in ICT procurement within the Public Sector. Enhancing human capital for the promotion of technology-based entrepreneurship: Target specific groups (engineers and scientists) by enriching and broadening the engineering education curriculum (coupling “technical thinking and engineering feeling” with “market and business understanding” and managerial skills).