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

Silverberg, Gerald and Verspagen, Bart (2005). Self-organization of R&D search in complex technology spaces. UNU-MERIT Research Memoranda. UNU-MERIT.

Document type:
Report

Metadata
Documents
Versions
Statistics
  • Attached Files (Some files may be inaccessible until you login with your UNU Collections credentials)
    Name Description MIMEType Size Downloads
    rm2005-017.pdf PDF application/pdf 873.40KB
  • Sub-type Working paper
    Author Silverberg, Gerald
    Verspagen, Bart
    Title Self-organization of R&D search in complex technology spaces
    Series Title UNU-MERIT Research Memoranda
    Volume/Issue No. 17
    Publication Date 2005
    Publisher UNU-MERIT
    Language eng
    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.
    Keyword Innovation
    Percolation
    Search
    Technological change
    R&D
    Clustering
    Self-organized criticality
    JEL C15
    C63
    D83
    O31
    Copyright Year 2005
    Copyright type All rights reserved
  • Versions
    Version Filter Type
  • Citation counts
    Google Scholar Search Google Scholar
    Access Statistics: 499 Abstract Views, 135 File Downloads  -  Detailed Statistics
    Created: Fri, 13 Dec 2013, 12:39:11 JST