© 2009

Innovation Networks

New Approaches in Modelling and Analyzing

  • Andreas Pyka
  • Andrea Scharnhorst

Part of the Understanding Complex Systems book series (UCS)

Table of contents

  1. Front Matter
    Pages i-x
  2. Innovation Networks in Economics

    1. Front Matter
      Pages 17-17
    2. Pier Paolo Saviotti
      Pages 19-41
    3. Koen Frenken, Jarno Hoekman, Suzanne Kok, Roderik Ponds, Frank van Oort, Joep van Vliet
      Pages 43-57
    4. Frank Beckenbach, Ramón Briegel, Maria Daskalakis
      Pages 59-100
    5. Andreas Pyka, Nigel Gilbert, Petra Ahrweiler
      Pages 101-126
    6. Robin Cowan, Nicolas Jonard
      Pages 127-144
  3. Innovation Networks in Complex Theories

    1. Front Matter
      Pages 145-145
    2. Jürg Reichardt, Stefan Bornholdt
      Pages 147-185
    3. Michael D. König, Stefano Battiston, Frank Schweitzer
      Pages 187-267
    4. Albert Diaz-Guilera, Sergio Lozano, Alex Arenas
      Pages 269-284
    5. Ingrid Hartmann-Sonntag, Andrea Scharnhorst, Werner Ebeling
      Pages 285-327
  4. Back Matter
    Pages 329-330

About this book


The science of graphs and networks has become by now a well-established tool for modelling and analyzing a variety of systems with a large number of interacting components. Starting from the physical sciences, applications have spread rapidly to the natural and social sciences, as well as to economics, and are now further extended, in this volume, to the concept of innovations, viewed broadly.

In an abstract, systems-theoretical approach, innovation can be understood as a critical event which destabilizes the current state of the system, and results in a new process of self-organization leading to a new stable state.

The contributions to this anthology address different aspects of the relationship between innovation and networks. The various chapters incorporate approaches in evolutionary economics, agent-based modeling, social network analysis and econophysics and explore the epistemic tension between insights into economics and society-related processes, and the insights into new forms of complex dynamics.


Evolution Innovation agent-based model agent-based modeling agents calculus dynamics economics evolutionary economics knowledge networks modeling social network analysis social networks statistical physics system

Editors and affiliations

  • Andreas Pyka
    • 1
  • Andrea Scharnhorst
    • 2
  1. 1.Universität BremenFB Wirtschaftswissenschaften, LS für WirtschaftstheorieBremenGermany
  2. 2.Royal Netherlands Academy of Arts & ScienceVirtual Knowledge StudioAmsterdamNetherlands

Bibliographic information

Industry Sectors
Finance, Business & Banking


From the reviews:

“This book is a worthwhile contribution aimed at narrowing down the divergence between the socioeconomic research and the physicists’ research on networks. … provides a valuable resource for those interested in how network structures affect innovation and their outcome … . the book presents a rich set of models and empirical evidence of networks that mainly represent the share of knowledge between nodes (firms). Readers looking for methods and modelling techniques across innovation studies and statistical physics will find this book of valuable use.” (Tommaso Ciarli, Journal of Artificial Societies and Social Simulation, Vol. 13 (1), 2010)

“This book is an edited collection of ten articles that address aspects of the relationship between innovation and networks. … will be of much value not only to those interested in complex economic or social behaviour, but also to those interested in graph-theoretic, statistical, probabilistic, and algebraic structure of networks.” (Charles J. Colbourn, Zentralblatt MATH, Vol. 1174, 2009)