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Self-organization of R&D search in complex technology spaces

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  • Silverberg, G.

    (MERIT, Maastricht University)

  • Verspagen, B.

    (ECIS, Eindhoven University of Technology)

Abstract

We extend an earlier model of innovation dynamics based on invasive percolation by adding endogenous R&D search by economically motivated firms. The {0,1} seeding of the technol-ogy lattice is now replaced by draws from a lognormal distribution for technology ‘difficulty’. Firms are rewarded for successful innovations by increases in their R&D budget. We compare two regimes. In the first, firms are fixed in a region of technology space. In the second, they can change their location by myopically comparing progress in their local neighborhoods and probabilistically moving to the region with the highest recent progress. We call this the mov-ing or self-organizational regime. We find that as the mean and standard deviation of the log-normal distribution are varied, the relative rates of aggregate innovation switches between the two regimes. The SO regime has higher innovation rates, other things being equal, for lower means or higher standard deviations of the lognormal distribution. This results holds for in-creasing size of the search radius. The clustering of firms in the SO regime grows rapidly and fluctuates in a complex way around a high value which increases with the search radius. We also investigate the size distributions of the innovations generated in each regime. In the fixed one, the distribution is approximately lognormal and certainly not fat tailed. In the SO regime, the distributions are radically different. They are much more highly right skewed and show scaling over at least two decades with a slope of almost exactly one, independently of parame-ter settings. Thus we argue that firm self-organization leads to self-organized criticality. (Keywords: innovation, percolation, search, technological change, R&D, clustering, self-organized criticality.

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Bibliographic Info

Paper provided by Eindhoven Center for Innovation Studies (ECIS) in its series Eindhoven Center for Innovation Studies (ECIS) working paper series with number 05.07.

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Date of creation: 2005
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Handle: RePEc:dgr:tuecis:0507

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Web page: http://ecis.ieis.tue.nl/

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Keywords: R&D; technology; organization;

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References

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  1. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
  2. F. M. Scherer & Dietmar Harhoff & J, rg Kukies, 2000. "Uncertainty and the size distribution of rewards from innovation," Journal of Evolutionary Economics, Springer, vol. 10(1), pages 175-200.
  3. Silverberg, G. & Verspagen, B., 2003. "Brewing the future: stylized facts about innovation and their confrontation with a percolation model," Eindhoven Center for Innovation Studies (ECIS) working paper series 03.06, Eindhoven Center for Innovation Studies (ECIS).
  4. Jerry A. Hausman & Bronwyn H. Hall & Zvi Griliches, 1984. "Econometric Models for Count Data with an Application to the Patents-R&D Relationship," NBER Technical Working Papers 0017, National Bureau of Economic Research, Inc.
  5. Scherer, F. M. & Harhoff, Dietmar, 2000. "Technology policy for a world of skew-distributed outcomes," Research Policy, Elsevier, vol. 29(4-5), pages 559-566, April.
  6. Gerald Silverberg & Bart Verspagen, 2002. "A Percolation Model of Innovation in Complex Technology Spaces," Computing in Economics and Finance 2002 24, Society for Computational Economics.
  7. Silverberg, Gerald, 2002. "The discrete charm of the bourgeoisie: quantum and continuous perspectives on innovation and growth," Research Policy, Elsevier, vol. 31(8-9), pages 1275-1289, December.
  8. Dietmar Harhoff & Frederic M. Scherer & Katrin Vopel, 1997. "Exploring the Tail of Patented Invention Value Distributions," CIG Working Papers FS IV 97-27, Wissenschaftszentrum Berlin (WZB), Research Unit: Competition and Innovation (CIG).
  9. Gerald Silverberg & Bart Verspagen, 2003. "Breaking the waves: a Poisson regression approach to Schumpeterian clustering of basic innovations," Cambridge Journal of Economics, Oxford University Press, vol. 27(5), pages 671-693, September.
  10. Silverberg, G. & Verspagen, B., 2004. "The size distribution of innovations revisited: an application of extreme value statistics to citation and value measures of patent significance," Eindhoven Center for Innovation Studies (ECIS) working paper series 04.17, Eindhoven Center for Innovation Studies (ECIS).
  11. Foray, Dominique & Grubler, Arnulf, 1990. "Morphological analysis, diffusion and lockout of technologies: Ferrous casting in France and the FRG," Research Policy, Elsevier, vol. 19(6), pages 535-550, December.
  12. F. M. Scherer, 1998. "The Size Distribution of Profits from Innovation," Annales d'Economie et de Statistique, ENSAE, issue 49-50, pages 495-516.
  13. Winter, Sidney G., 1984. "Schumpeterian competition in alternative technological regimes," Journal of Economic Behavior & Organization, Elsevier, vol. 5(3-4), pages 287-320.
  14. Nelson, Richard R. & Winter, Sidney G., 1993. "In search of useful theory of innovation," Research Policy, Elsevier, vol. 22(2), pages 108-108, April.
  15. Dietmar Harhoff & Francis Narin & F. M. Scherer & Katrin Vopel, 1999. "Citation Frequency And The Value Of Patented Inventions," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 511-515, August.
  16. Barnett,William A. & Kirman,Alan P. & Salmon,Mark, 1997. "Nonlinear Dynamics and Economics," Cambridge Books, Cambridge University Press, number 9780521471411.
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Cited by:
  1. Sadowski, B.M. & Straathof, B., 2005. "VoIP under the EU Regulatory Framework: Preventing Foreclosure?," Eindhoven Center for Innovation Studies (ECIS) working paper series 05.16, Eindhoven Center for Innovation Studies (ECIS).
  2. Massimo Ricottilli, 2006. "Constraints and Freedom of Action: a fitness trade-off," Working Papers 580, Dipartimento Scienze Economiche, Universita' di Bologna.

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