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Innovation Waves, Self-organised Criticality and Technological Convergence

Author

Listed:
  • Rainer Andergassen

    () (Faculty of Economics (Rimini), University of Bologna)

  • Franco Nardini

    () (Department of Mathematics for the Social Sciences, University of Bologna)

  • Massimo Ricottilli

    () (Department of Economics, University of Bologna)

Abstract

The purpose of this paper is to investigate the evolutionary process of imitation and innovation as a process of searching in a given neighbourhood of firms. Networks are the main source of information for firms willing to actively search and upgrade and which define the reachable neighbourhood whose width is strictly related to cognitive distance. We have identified two major forms of information setting off innovative behaviour: the first comes in the shape of random events which are exogenous, at least in terms of the firms' own search activity, while the second is determined by searching for technological opportunities in other economic sectors. It is this activity that generates the spreading of a new technological paradigm and that makes for technological convergence. All firms are a heterogeneous set of agents bounded by their competence, technological specificity and, more generally, rationality. The spreading of information through cognitive neighbourhoods allows firms to gradually acquire full knowledge leading to innovation waves. Imitation follows innovation as firms attempt to glean information on best practise techniques to join their sector technological leaders. Whilst innovators are temporarily allowed to reap quasi rents the imitative band wagon effect drives the profit rate down to its normal level. Productivity growth lowers the prices of sectors involved in the process of technological advance causing obsolescence and, thus, creative destruction in a Schumpeterian sense.

Suggested Citation

  • Rainer Andergassen & Franco Nardini & Massimo Ricottilli, "undated". "Innovation Waves, Self-organised Criticality and Technological Convergence," Modeling, Computing, and Mastering Complexity 2003 19, Society for Computational Economics.
  • Handle: RePEc:sce:cplx03:19
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    References listed on IDEAS

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    1. Arenas, Alex & Diaz-Guilera, Albert & Perez, Conrad J. & Vega-Redondo, Fernando, 2002. "Self-organized criticality in evolutionary systems with local interaction," Journal of Economic Dynamics and Control, Elsevier, vol. 26(12), pages 2115-2142, October.
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    5. Auerswald, Philip & Kauffman, Stuart & Lobo, Jose & Shell, Karl, 2000. "The production recipes approach to modeling technological innovation: An application to learning by doing," Journal of Economic Dynamics and Control, Elsevier, vol. 24(3), pages 389-450, March.
    6. Pasinetti,Luigi, 1993. "Structural Economic Dynamics," Cambridge Books, Cambridge University Press, number 9780521432825, May.
    7. Franke, R., 2001. "Wave trains, innovation noise, and long waves," Journal of Economic Behavior & Organization, Elsevier, vol. 45(1), pages 49-68, May.
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    12. Iwai, Katsuhito, 2000. "A contribution to the evolutionary theory of innovation, imitation and growth," Journal of Economic Behavior & Organization, Elsevier, vol. 43(2), pages 167-198, October.
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    Citations

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    Cited by:

    1. Andergassen, Rainer & Nardini, Franco & Ricottilli, Massimo, 2017. "Innovation diffusion, general purpose technologies and economic growth," Structural Change and Economic Dynamics, Elsevier, vol. 40(C), pages 72-80.
    2. Ricottilli, Massimo, 2015. "Innovation through local interaction, imitation and investment waves," Structural Change and Economic Dynamics, Elsevier, vol. 33(C), pages 58-70.
    3. Blume, Andreas & Duffy, John & Temzelides, Ted, 2010. "Self-organized criticality in a dynamic game," Journal of Economic Dynamics and Control, Elsevier, vol. 34(8), pages 1380-1391, August.
    4. Andergassen, Rainer & Nardini, Franco & Ricottilli, Massimo, 2009. "Innovation and growth through local and global interaction," Journal of Economic Dynamics and Control, Elsevier, vol. 33(10), pages 1779-1795, October.
    5. Kim, Namil & Lee, Hyeokseong & Kim, Wonjoon & Lee, Hyunjong & Suh, Jong Hwan, 2015. "Dynamic patterns of industry convergence: Evidence from a large amount of unstructured data," Research Policy, Elsevier, vol. 44(9), pages 1734-1748.
    6. Hyeokseong Lee & Namil Kim & Kiho Kwak & Wonjoon Kim & Hyungjoon Soh & Kyungbae Park, 2016. "Diffusion Patterns in Convergence among High-Technology Industries: A Co-Occurrence-Based Analysis of Newspaper Article Data," Sustainability, MDPI, Open Access Journal, vol. 8(10), pages 1-18, October.
    7. Rainer Andergassen & Franco Nardini & Massimo Ricottilli, 2015. "Emergence and Resilience in a Model of Innovation and Network Formation," Networks and Spatial Economics, Springer, vol. 15(2), pages 293-311, June.
    8. repec:pit:wpaper:276 is not listed on IDEAS
    9. R. Andergassen & F. Nardini & M. Ricottilli, 2013. "Innovation diffusion, technological convergence and economic growth," Working Papers wp912, Dipartimento Scienze Economiche, Universita' di Bologna.

    More about this item

    Keywords

    Technological change; Self-organized criticality; Innovation and diffusion; Innovation waves; Creative distruction.;

    JEL classification:

    • D50 - Microeconomics - - General Equilibrium and Disequilibrium - - - General
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General
    • O30 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - General

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