IDEAS home Printed from https://ideas.repec.org/p/aug/augsbe/0287.html
   My bibliography  Save this paper

Simulating Knowledge-Generation and -Distribution Processes in Innovation Collaborations and Networks

Author

Listed:
  • Andreas Pyka

    (University of Augsburg, Department of Economics)

  • Nigel Gilbert

    (School of Human Sciences, University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom)

  • Petra Ahrweiler

    (Research Center Media and Politics, Institute for Political Science, University of Hamburg, Germany)

Abstract

An agent-based simulation model representing a theory of the dynamic processes involved in innovation in modern knowledge-based industries is described. The agent-based approach al-lows the representation of heterogeneous agents that have individual and varying stocks of knowledge. The simulation is able to model uncertainty, historical change, effect of failure on the agent population, and agent learning from experience, from individual research and from partners and collaborators. The aim of the simulation exercises is to show that the artificial innovation networks show certain characteristics they share with innovation networks in knowledge intensive industries and which are difficult to be integrated in traditional models of industrial economics.

Suggested Citation

  • Andreas Pyka & Nigel Gilbert & Petra Ahrweiler, 2006. "Simulating Knowledge-Generation and -Distribution Processes in Innovation Collaborations and Networks," Discussion Paper Series 287, Universitaet Augsburg, Institute for Economics.
    • Handle: RePEc:aug:augsbe:0287
    as

    Download full text from publisher

    File URL: https://vwl.wiwi.uni-augsburg.de/vwl/institut/paper/287.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. d'Aspremont, Claude & Jacquemin, Alexis, 1988. "Cooperative and Noncooperative R&D in Duopoly with Spillovers," American Economic Review, American Economic Association, vol. 78(5), pages 1133-1137, December.
    2. Cantner, Uwe & Pyka, Andreas, 1998. "Absorbing Technological Spillovers: Simulations in an Evolutionary Framework," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 7(2), pages 369-397, June.
    3. Alice Lam, 2003. "Organizational Learning in Multinationals: R&D Networks of Japanese and US MNEs in the UK," Journal of Management Studies, Wiley Blackwell, vol. 40(3), pages 673-703, May.
    4. Petra Ahrweiler & Andreas Pyka & Nigel Gilbert, 2004. "Simulating Knowledge Dynamics In Innovation Networks (Skin)," World Scientific Book Chapters, in: Roberto Leombruni & Matteo Richiardi (ed.), Industry And Labor Dynamics The Agent-Based Computational Economics Approach, chapter 14, pages 284-296, World Scientific Publishing Co. Pte. Ltd..
    5. Cohen, Wesley M & Levinthal, Daniel A, 1989. "Innovation and Learning: The Two Faces of R&D," Economic Journal, Royal Economic Society, vol. 99(397), pages 569-596, September.
    6. N. Gilbert, 1997. "A Simulation of the Structure of Academic Science," Sociological Research Online, , vol. 2(2), pages 91-105, June.
    7. Horst Hanusch & Andreas Pyka, 2007. "Principles of Neo-Schumpeterian Economics," Cambridge Journal of Economics, Cambridge Political Economy Society, vol. 31(2), pages 275-289, March.
    8. Amable, Bruno, 2003. "The Diversity of Modern Capitalism," OUP Catalogue, Oxford University Press, number 9780199261147.
    9. Richard C. Levin & Peter C. Reiss, 1988. "Cost-Reducing and Demand-Creating R&D with Spillovers," RAND Journal of Economics, The RAND Corporation, vol. 19(4), pages 538-556, Winter.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Martin Blom & Fulvio Castellacci & Arne Fevolden, 2014. "Defence firms facing liberalization: innovation and export in an agent-based model of the defence industry," Computational and Mathematical Organization Theory, Springer, vol. 20(4), pages 430-461, December.
    2. Flavio Lenz-Cesar & Almas Heshmati, 2010. "Agent-based Simulation of Cooperative Innovation," TEMEP Discussion Papers 201052, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Jan 2010.
    3. Olivier Barreteau & Christophe Le Page, 2011. "Using Social Simulation to Explore the Dynamics at Stake in Participatory Research," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 14(4), pages 1-12.
    4. Kurt Dopfer, 2011. "Economics in a Cultural Key: Complexity and Evolution Revisited," Chapters, in: John B. Davis & D. Wade Hands (ed.), The Elgar Companion to Recent Economic Methodology, chapter 14, Edward Elgar Publishing.
    5. Dan Farhat, 2013. "An Agent-based Model of Interdisciplinary Science and the Evolution of Scientific Research Networks," Working Papers 1302, University of Otago, Department of Economics, revised Jan 2013.
    6. Bruce Edmonds & Nigel Gilbert & Petra Ahrweiler & Andrea Scharnhorst, 2011. "Simulating the Social Processes of Science," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 14(4), pages 1-14.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gilbert, Nigel & Ahrweiler, Petra & Pyka, Andreas, 2007. "Learning in innovation networks: Some simulation experiments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 378(1), pages 100-109.
    2. Mário Alexandre Patrício Martins da Silva, 2016. "R&D investments and spillovers under endogenous technological opportunity," FEP Working Papers 571, Universidade do Porto, Faculdade de Economia do Porto.
    3. Wolfgang Becker & Juergen Peters, 2000. "Technological Opportunities, Absorptive Capacities, and Innovation," Discussion Paper Series 195, Universitaet Augsburg, Institute for Economics.
    4. Thomas Doring & Jan Schnellenbach, 2006. "What do we know about geographical knowledge spillovers and regional growth?: A survey of the literature," Regional Studies, Taylor & Francis Journals, vol. 40(3), pages 375-395.
    5. Flavio Lenz-Cesar & Almas Heshmati, 2010. "Agent-based Simulation of Cooperative Innovation," TEMEP Discussion Papers 201052, Seoul National University; Technology Management, Economics, and Policy Program (TEMEP), revised Jan 2010.
    6. Becker Wolfgang & Peters Jürgen, 2005. "Innovation Effects of Science-Related Technological Opportunities / Innovationseffekte von technologischen Möglichkeiten aus dem Wissenschaftsbereich: Theoretical Considerations and Empirical Findings," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 225(2), pages 130-150, April.
    7. Christopher A. Laincz & Ana Rodrigues, 2006. "The Impact of Cost Reducing R\&D Spillovers on the Ergodic Distribution of Market Structures," Computing in Economics and Finance 2006 307, Society for Computational Economics.
    8. Hall, Joshua & Laincz, Christopher, 2012. "Optimal R&D Subsidies with Heterogeneous Firms in a Dynamic Setting," School of Economics Working Paper Series 2012-13, LeBow College of Business, Drexel University.
    9. Kaiser, Ulrich & Licht, Georg, 1998. "R&D cooperation and R&D intensity: theory and micro-econometric evidence for german manufacturing industries," ZEW Discussion Papers 98-32, ZEW - Leibniz Centre for European Economic Research.
    10. Christian Henning & Volker Saggau, 2010. "Information Networks and Knowledge Spillovers: Simulations in an Agent-based Model Framework," Chapters, in: Neri Salvadori (ed.), Institutional and Social Dynamics of Growth and Distribution, chapter 11, Edward Elgar Publishing.
    11. Cassiman, Bruno, 2000. "Research joint ventures and optimal R&D policy with asymmetric information," International Journal of Industrial Organization, Elsevier, vol. 18(2), pages 283-314, February.
    12. Bettina Becker, 2013. "The Determinants of R&D Investment: A Survey of the Empirical Research," Discussion Paper Series 2013_09, Department of Economics, Loughborough University, revised Sep 2013.
    13. Becker, Wolfgang & Dietz, Jurgen, 2004. "R&D cooperation and innovation activities of firms--evidence for the German manufacturing industry," Research Policy, Elsevier, vol. 33(2), pages 209-223, March.
    14. Kaiser, Ulrich, 2002. "Measuring knowledge spillovers in manufacturing and services: an empirical assessment of alternative approaches," Research Policy, Elsevier, vol. 31(1), pages 125-144, January.
    15. Wolfgang Becker, 2003. "Evaluation of the Role of Universities in the Innovation Process," Discussion Paper Series 241, Universitaet Augsburg, Institute for Economics.
    16. Claudio A. Piga & Marco Vivarelli, 2004. "Internal and External R&D: A Sample Selection Approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 66(4), pages 457-482, September.
    17. Petra Ahrweiler & Nigel Gilbert & Andreas Pyka, 2011. "Agency and structure: a social simulation of knowledge-intensive industries," Computational and Mathematical Organization Theory, Springer, vol. 17(1), pages 59-76, March.
    18. Belderbos, Rene & Carree, Martin & Diederen, Bert & Lokshin, Boris & Veugelers, Reinhilde, 2004. "Heterogeneity in R&D cooperation strategies," International Journal of Industrial Organization, Elsevier, vol. 22(8-9), pages 1237-1263, November.
    19. De Bondt, Raymond, 1997. "Spillovers and innovative activities," International Journal of Industrial Organization, Elsevier, vol. 15(1), pages 1-28, February.
    20. Grunfeld, Leo A., 2003. "Meet me halfway but don't rush: absorptive capacity and strategic R&D investment revisited," International Journal of Industrial Organization, Elsevier, vol. 21(8), pages 1091-1109, October.

    More about this item

    Keywords

    innovation networks; agent-based modelling; scale free networks;
    All these keywords.

    JEL classification:

    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • L22 - Industrial Organization - - Firm Objectives, Organization, and Behavior - - - Firm Organization and Market Structure

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aug:augsbe:0287. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Dr. Simone Raab-Kratzmeier (email available below). General contact details of provider: https://edirc.repec.org/data/ivaugde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.