Computational Economics

, Volume 19, Issue 1, pp 51–65

Competing R&D Strategies in an Evolutionary Industry Model

  • Murat Yildizoglu
Article

DOI: 10.1023/A:1014945023982

Cite this article as:
Yildizoglu, M. Computational Economics (2002) 19: 51. doi:10.1023/A:1014945023982

Abstract

This article aims to test the relevance of learning throughgenetic algorithms, in contrast to fixed R&D rules, in a simplifiedversion of the evolutionary industry model of Nelson and Winter.These two R&D strategies arecompared from the points of view of industry performance(welfare) and firms' relative performance (competitive edge):simulations results clearly show that learning is a source oftechnological and social efficiency as well as a means formarket domination.

bounded rationality genetic algorithms industry dynamics innovation learning 

Copyright information

© Kluwer Academic Publishers 2002

Authors and Affiliations

  • Murat Yildizoglu
    • 1
  1. 1.IFREDE-E3iUniversité Montesquieu Bordeaux IVPESSAC

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