1 The French research system: which evolution and which borders? Marie-Pierre Bès, Frédéric Rodriguez, University.

Slides:



Advertisements
Similar presentations
Complex Networks Advanced Computer Networks: Part1.
Advertisements

INTRODUCTION TO AP BIOLOGY What is AP Biology  AP Biology is designed to be the equivalent of a University Introductory Biology Course  It.
Emergence of Scaling in Random Networks Albert-Laszlo Barabsi & Reka Albert.
University Knowledge and its Impact on Competitiveness Robert Huggins and Daniel Prokop Centre for International Competitiveness, UWIC, Cardiff Introduction.
Analysing university-firm interaction in the SADC countries: An initial overview Glenda Kruss SARUA workshop October 2008.
Industry Cluster Analysis and IMPLAN Software A Conceptual Overview May 19, 2015.
CS 599: Social Media Analysis University of Southern California1 The Basics of Network Analysis Kristina Lerman University of Southern California.
Alon Arad Alon Arad Hurst Exponent of Complex Networks.
Web as Graph – Empirical Studies The Structure and Dynamics of Networks.
College Strategic Plan by Strategic Planning and Quality Assurance Committee.
Robert Huggins and Daniel Prokop Centre for International Competitiveness, Cardiff School of Management, University of Wales Institute, Cardiff Presentation.
MEASURING KNOWLEDGE AND ITS ECONOMIC EFFECTS THE ROLE OF OFFICIAL STATISTICS Fred Gault Statistics Canada Advancing Knowledge and the Knowledge Economy.
Universities and Firms: A Comparative Analysis of the Interactions Between Market Process, Organizational Strategies and Governance Seminar, September.
(Social) Networks Analysis III Prof. Dr. Daning Hu Department of Informatics University of Zurich Oct 16th, 2012.
Analysis and Modeling of the Open Source Software Community Yongqin Gao, Greg Madey Computer Science & Engineering University of Notre Dame Vincent Freeh.
Addressing National Priorities in TEMPUS Projects TEMPUS Project for Establishing a Center of Excellence for Research & Training at Damascus University.
Innovation Economics Class 2. Shifting Heuristics in the Economics of Innovation Area of specialization in microeconomic theory Area of specialization.
1 The Role of IP Management in Cross-Border Open Innovation Ralph Heinrich UNECE Team of Specialists on Intellectual Property Minsk, 9-10 June 2010.
LANGUAGE NETWORKS THE SMALL WORLD OF HUMAN LANGUAGE Akilan Velmurugan Computer Networks – CS 790G.
Marcus Bellamy Alun Jones Session 6: Knowledge & Collaboration Networks.
The Romanian National Defence College Bucharest, 1-2 November 2007Romania Ministry of Education, Research and Youth National University Research Council.
NETWORK STRUCTURE AND COOPERATION BETWEEN UNIVERSITIES AND INDUSTRY Prof. Ing. Tatiana Čorejová, PhD. Prof. Ing. Ján Čorej, PhD.
Science and the Scientific Method! 5 th grade. What is Science? knowledge about or study of the natural world based on facts learned through experiments.
Baja California’s Business Development Policy: The next steps to reach a regional economy based on Knowledge & Technology.
Self-Similarity of Complex Networks Maksim Kitsak Advisor: H. Eugene Stanley Collaborators: Shlomo Havlin Gerald Paul Zhenhua Wu Yiping Chen Guanliang.
Intelligent Database Systems Lab N.Y.U.S.T. I. M. Batch kernel SOM and related Laplacian methods for social network analysis Presenter : Lin, Shu-Han Authors.
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,
Social Network Analysis Prof. Dr. Daning Hu Department of Informatics University of Zurich Mar 5th, 2013.
The Geography and Evolution of the European Internet Infrastructure Sandra Vinciguerra URU – Utrecht University
Midterm Project Guide Prof. Dr. Daning Hu Department of Informatics University of Zurich Oct 23th, 2012.
7th of March 2007 Regions for Economic Change « REGIONAL GOVERNANCE OF INNOVATION NETWORKS » Brussels, the 7th of March 2007 Thierry Fellmann Director.
1 Agricultural Innovation Networks: Azerbaijan and Uzbekistan Tugrul Temel ISNAR November 17, 2000.
Complex Network Theory – An Introduction Niloy Ganguly.
Economic Research and Policy Analysis Branch May 6, 2010 Access to Business Micro-Data to Support Economic Research and Policy Analysis: Where Do We Go.
Atlantic Innovation Fund Round VIII February 5, 2008.
1. 2 HQP and tacit knowledge codified new knowledge arising from research 96%4% CANADA WORLD investment by MNE’s bringing tacit knowledge commodities.
INSTITUTES OF INNOVATIVE DEVELOPMENT: THEIR ROLE IN REGIONAL CLUSTERS Anna Bykova PhD student, Higher School of Economics Russia 23th September 2011 Milocer,
Academic knowledge externalities: spatial proximity and networks Roderik Ponds, Frank van Oort & Koen Frenken.
Ompetitiveness of the nations is an economic development framework based on the integration of macro and micro economy. It is a way by which firms and.
JOANNEUM RESEARCH Forschungsgesellschaft mbH, Steyrergasse 17, A-8010 Graz, Austria, web: ISO 9001 zert.
Algorithms and Computational Biology Lab, Department of Computer Science and & Information Engineering, National Taiwan University, Taiwan Network Biology.
Paul Wright Chief Executive United Kingdom Science Park Association.
1 Marie-Pierre Bès Professor of economy at ISAE (Engineering School in Aeronautics and Space) University of Toulouse laboratoire LISST (CNRS and U. Toulouse.
1 2 The environment Eastern part of Emilia-Romagna Region - 3 major highways - 3 airports in 80 km. - Port sede di Faenzasede di.
The simultaneous evolution of author and paper networks
Connectivity and the Small World
Structures of Networks
OKAYAMA University TSUSHIMA CAMPUS Access Map. OKAYAMA University TSUSHIMA CAMPUS Access Map.
INNOVATION & TECHNOLOGY MANAGEMENT
The Steps of The Scientific Method
From research to markets : why and how
The Scientific Method and SCIENCE!!!!!!.
Best practices ideas for improvement of industrial return
Empirical analysis of Chinese airport network as a complex weighted network Methodology Section Presented by Di Li.
Warm-Up On a clean sheet of paper, write “Warm-up [today’s date]” and then answer the following question: What kinds of activities does a scientist engage.
IRMA 102: Introduction to Information Science
Section 8.6 of Newman’s book: Clustering Coefficients
The Watts-Strogatz model
Computer Science School of Mathematical and Computer Sciences
What is Physical Science?
Department of Computer Science University of York
Network Science: A Short Introduction i3 Workshop
Clustering Coefficients
Bikalp Chamola (VAF) Shyam Singh (IRMA)
CYBERWATCHING Creating a global living lab including cybersecurity aspects as a guarantee.
WORLD CANADA INNOVATION IN CANADA - the big picture 96% 4%
How does network position affect firms’ innovation?
Principles of Science and Systems
Gérald SANTUCCI Head of Unit INFSO/D-4 “Networked Enterprise & RFID”
Presentation transcript:

1 The French research system: which evolution and which borders? Marie-Pierre Bès, Frédéric Rodriguez, University of Toulouse EAEPE 2007 Conference, Porto

2 Objectives Explanation of the French research organization system Analysis of series of contracts between CNRS units and firms Highlight the questions of concentration and scientific communities Test the methods used in Social Networks Analysis

3 Outline 1.Some descriptive statistics highlighted by other studies focused on research partnerships : the concentration phenomena 2.Application of Social Network method : scale- free network or small world ? 3.Discussion about the old notion of scientific community (Crane, 1972) revisited with the social networks approach

4 Data the name of research unit, its location (12 areas), the leader’s name, the scientific domain (classified into 8 departments), the firm’s identity, its location, the start date of the contract, the duration done by number of months + economic activity (coded by us). Number of contracts26024 Number of firms3642 Number of scientific labs1680 Average number of contracts per firm7 Average number of contracts per lab15 Average duration of a contract20 months Period Confidential data base of contracts of CNRS including information about :

5 First Part : descriptive data

6 Number of contracts per CNRS scientific department

7 Evolution in number of contracts during the period

8 Distribution of CNRS units per number of contracts during ( )

9 Distribution of labs per number of contracts Number of contractsNumber of labs Share of contracts > % > % > % > %

10 Distribution of economic partners per number of contracts during ( )

11 Distribution of contracts per activity sector Activity sectorNumber of contracts share Industry % Public836732% Service641025% Other2161% Agriculture270% Total260241

12 Results from descriptive statistics Intense concentration in this data base, characterized by the presence of some labs specialized in Engineering Sciences, located in Province, engaged in some contracts with a public industrial firm. This concentration does not provide information on neither the centrality of the actors nor their positioning in the partnership chain.

13 Second Part : research networks (with Ucinet Software)

14 1. The Networks of CAC 40 firms Observation of the evolution of research activity of the major firms. Selection of the “CAC 40” firms = major French firms. 20% of the data base. Building of labs-firms Networks (2 “dimensions”) Hypothesis : a)the relation is an exchange of knowledge b)the network describes diffusion of knowledge

15 1 st Network labs-CAC40 firms,

16 2 nd Network public labs-CAC40 firms,

17 3 rd Network public labs-CAC40 firms,

18 2. Scientific “networks” Selection of chemistry domain Building of labs-labs Matrix through the existence of k contracts signed by the 2 labs with the same k firms. 2 kinds of ties : contracts and social indirect ties. Drawing of a meta-network i.e. the whole ties between the labs.

19 Chemistry/1 st Network,

20 Chemistry/2 nd Network,

21 Which kind of general structure ? Some social networks are “scale-free” (Barabasi & alii, 2002) as in -Biotechnology (Gay & Doucet, 2005) Many of these networks are “small worlds” (Watts, 1998) as in -Scientific collaboration (Newman, 2001) -Innovation (Cowan, 2004) Test with our data

22 Major criteria for a “small world” 1.High clustering coefficient 2.Short average path lengths 3.Weak densities 4.A Degree distribution (after smoothing plot of log-log) that follows a decline line => There are several short cuts between two isolated members.

23 “Worldation” in the Chemistry networks Indicators1st network “ ” 2nd network “ ” Number of actors Number of ties Clustering coefficient Average path length Connection degree>2 density

24 log-log Plot of degree distribution Smoothing Smoothing

25 conclusion The major firms’s scientific network is dominated by competition and strategy The chemistry’s network is a “small world” => existence of a scientific communities Several “small worlds” in this database as in the scientific collaboration networks the industrial research doesn’t disturb the property of scientific network.