Project

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R&D Network Life Cycles

English title R&D Network Life Cycles
Applicant Schweitzer Frank
Number 126865
Funding scheme Project funding (Div. I-III)
Research institution Departement Management, Technologie und Ökonomie D-MTEC ETH Zürich
Institution of higher education ETH Zurich - ETHZ
Main discipline Economics
Start/End 01.05.2010 - 31.10.2012
Approved amount 192'891.00
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All Disciplines (5)

Discipline
Economics
Theoretical Physics
Science of management
Sociology
Mathematics

Keywords (10)

alliances; networks; innovation; research & development; network evolution; centrality; research and development; networks of firms; knowledge transfer

Lay Summary (English)

Lead
Lay summary
It is widely agreed that research and development (R&D) is the driving force of economic growth. R&D activities are distributed across different economic actors, notably firms, which interact in many ways, e.g. through collaboration or knowledge transfer. Using the conceptual network approach, these firms can be seen as nodes and their interactions as links of a network that may evolve over time, both with respect to the actors and their interactions. Many studies have been devoted to the investigation of the consequences of a given R&D network structure on a firm's performance. However, only little is known about the time evolution of this structure, or the antecedents of this evolution. Emphasizing temporal aspects, this proposal focuses both on the relationship between the structure of an R&D network and its performance, on an individual firm and aggregate industry level, and on the dynamics of network creation and evolution.This project contributes to increasing our understanding of the efficiency and evolution of R&D networks. Our aim is to explain the formation of R&D networks as a purely endogenous phenomenon, emerging from the behavior of individual firms. A distinctive feature of this proposal, the analysis of the evolution of R&D networks is carried out both on an empirical and on a theoretical level.Governments have increasingly become aware of the growing importance of R&D networks. However, due to the limited knowledge we currently have of R&D networks and their efficient functioning, network-facilitating policies often lack a thorough economic rationale. More networking may not always be efficient and some policies may support clusters that are locked into inefficient network structures. The empirically grounded theoretical understanding of R&D networks developed in this project shall point at practical implications for policies to foster the innovativeness of an R&D intensive industry in which firms exchange knowledge through R&D collaborations.
Direct link to Lay Summary Last update: 21.02.2013

Responsible applicant and co-applicants

Employees

Publications

Publication
A model of dynamic rewiring and knowledge exchange in R&D networks
Tomasello Mario Vincenzo, Tessone Claudio Juan, Schweitzer Frank (2016), A model of dynamic rewiring and knowledge exchange in R&D networks, in Advances in Complex Systems, 19(1-2), 1650004.
Innovator Networks
Tomasello Mario Vincenzo, Mueller Moritz, Schweitzer Frank (2014), Innovator Networks, in Professor Reda Alhajj Professor Jon Rokne (ed.), Springer, New York, 737-742.
Nestedness in Networks: A Theoretical Model and Some Applications
Koenig Michael D., Tessone Claudio J., Zenou Yves (2014), Nestedness in Networks: A Theoretical Model and Some Applications, in Theoretical Economics, 9(3), 695-752.
The role of endogenous and exogenous mechanisms in the formation of R&D networks
Tomasello Mario Vincenzo, Perra Nicola, Tessone Claudio Juan, Karsai Marton, Schweitzer Frank (2014), The role of endogenous and exogenous mechanisms in the formation of R&D networks, in SCIENTIFIC REPORTS, 4, 5679.
Betweenness preference: Quantifying correlations in the topological dynamics of temporal networks
Pfitzner Rene, Scholtes Ingo, Garas Antonios, Tessone Claudio Juan, Schweitzer Frank (2013), Betweenness preference: Quantifying correlations in the topological dynamics of temporal networks, in Physical Review Letters, 110(19), 198701.
The social climbing game
Bardoscia Marco, Luca Giancarlo, Livan Giacomo, Marsili Matteo, Tessone Claudio Juan (2013), The social climbing game, in Journal of Statistical Physics, 151(3), 440-457.
A k-shell decomposition method for weighted networks
Garas A, Schweitzer F, Havlin S (2012), A k-shell decomposition method for weighted networks, in NEW JOURNAL OF PHYSICS, 14, 083030.
Network evolution based on centrality
Konig MD, Tessone CJ (2011), Network evolution based on centrality, in PHYSICAL REVIEW E, 84(5), 056108.
Recombinant knowledge and the evolution of innovation networks
Konig MD, Battiston S, Napoletano M, Schweitzer F (2011), Recombinant knowledge and the evolution of innovation networks, in JOURNAL OF ECONOMIC BEHAVIOR & ORGANIZATION, 79(3), 145-164.

Collaboration

Group / person Country
Types of collaboration
Robin Cowan, University of Maastricht Netherlands (Europe)
- Publication
Mauro Napoletano, Observatoire Français des Conjonctures Economiques, Nice France (Europe)
- in-depth/constructive exchanges on approaches, methods or results
Y. Zenou, Stockholm University and Research Institute of Industrial Economics Sweden (Europe)
- Publication
Shlomo Havlin, Bar-Ilan University, Ramat-Gan Israel (Asia)
- Publication
Matteo Marsili, Abdus Salam International Centre for Theoretical Physics, Trieste Italy (Europe)
- in-depth/constructive exchanges on approaches, methods or results
H. Gersbach, Chair of Macroeconomics: Innovation and Policy, ETH Zürich Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results
Swiss Institute for Business Cycle Research (KOF), ETH Zürich Switzerland (Europe)
- in-depth/constructive exchanges on approaches, methods or results

Scientific events

Active participation

Title Type of contribution Title of article or contribution Date Place Persons involved
Latsis Symposium Talk given at a conference The rise and fall of R&D networks across industries 11.09.2012 Zurich, Switzerland Tomasello Mario;
Latsis Symposium Poster Network dynamics and the creation of knowledge in R&D networks 11.09.2012 Zurich, Switzerland Tomasello Mario;
ECCS 2012 Talk given at a conference The evolution of R&D networks across industries 06.09.2012 Brussels, Belgium Tomasello Mario;
ECCS 2012 Talk given at a conference Network dynamics and the creation of knowledge in R&D networks 03.09.2012 Brussels, Belgium Tomasello Mario;
SKEMA Business School Talk given at a conference Evolution of R&D Networks across industries 25.06.2012 Sophia Antipolis, France Tomasello Mario;
Application of Social Network Analysis (ASNA) Conference Talk given at a conference Cuttlefish for visualization of network dynamics in research alliances 13.09.2011 Zurich, Switzerland Tomasello Mario;


Abstract

It is widely agreed that research and development (R&D), with itssubsequent technological innovations, is the driving force in economicgrowth. R&D activities are distributed across different economic actors,notably firms, which interact in many ways, e.g. through collaboration orknowledge transfer. Using a conceptual network approach, these firmscan be seen as nodes and their interactions as links of a network thatmay evolve over time, both with respect to the actors and theirinteractions. Our aim is to explain the formation of R&D networks as apurely endogenous phenomenon, emerging from the behavior of individualfirms. Many studies have been devoted to the investigation of theconsequences of a certain R&D network structure on a firm'sperformance. However, only little is known about the time evolution ofthis structure, or the antecedents of this evolution. Emphasizingtemporal aspects, this proposal focuses both on the relationship betweenthe structure of an R&D network and its performance, on an individualfirm and aggregate industry level, and on the dynamics of networkcreation and evolution. In the project we study, first, how the behavior of firms affects thetypes of networks that emerge at the aggregate level and, second, how afirm's position in the network affects its knowledge productivity andperformance. A distinctive feature of this proposal, the analysis of theevolution of R&D networks is carried out both on an empirical and on atheoretical level. The empirical analysis will allow us to identifyspecific firm and network characteristics that can serve as thefoundation and benchmark for realistic models of R&D networks. Thetheoretical approach aims at developing such a realistic model to explainthe architecture and formation of the network as well as the productivityof the firms embedded in the network. The joint analysis shall point atpractical implications for policies to foster the innovativeness of anR&D intensive industry in which firms exchange knowledge through R&Dcollaborations.
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