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The nature of EU funded R&D collaboration networks in the area of Information Society Technologies

The nature of EU funded R&D collaboration networks in the area of Information Society Technologies. Aimilia Protogerou, Yannis Caloghirou and Evangelos Siokas Laboratory of Industrial and Energy Economics National Technical University of Athens

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The nature of EU funded R&D collaboration networks in the area of Information Society Technologies

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  1. The nature of EU funded R&D collaboration networks in the area of Information Society Technologies Aimilia Protogerou, Yannis Caloghirou and Evangelos Siokas Laboratory of Industrial and Energy Economics National Technical University of Athens DIME Workshop “Distributed Networks and the Knowledge-based Economy” GREDEG-DEMOS Juan les Pins, 10-11 May 2007

  2. Aim of the paper • The exploratory study of the structure and evolution of the research collaboration networks formed under the 4th, 5th and 6th EU Framework Programmesduring the period 1994-2006 in the area of Information Society Technologies (IST).

  3. Exploring EU-funded Research Joint Ventures • The STEP to RJVs (TSER Project) was the first attempt to study EU funded research partnerships. • This study is part of a number of studies that employ social network analysis to investigate the formation, structure, and evolution of networks emerging as a response to EU policy initiatives.

  4. 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.

  5. Descriptive statistics of the RJV-IST database

  6. Distribution of entity types in the RJV-IST networks

  7. Returning and new entities by organization type (FP5 vs. FP4 and FP6 vs. FP4 +FP5)

  8. Frequency of participation of all types of entities in FPs.

  9. Structural features of RJV-IST networks

  10. Degree distributions

  11. Preferential attachment

  12. Network resilience

  13. Small-world property

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

  15. Conclusions • 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 • Educational institutions and research centers have a more active and prominent rolecompared to firms and ‘other’ actors.

  16. Suggestions for future research • The analysis of other thematic areas in order to study regularities or structural differences due to different knowledge bases, research organization, industry dynamics and policy choices related to the specific area. • The conduction of survey work and in-depth case studies complementary to network analysis.

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