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An Agent-Based Model of Innovation Emergence in Organizations: Renault and Ford Through the Lens of Evolutionism

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  • Manuel Cartier

    (University of Paris IX Dauphine)

Abstract

Based on evolutionist theories and project management knowledge, a connectionist model based on genetic algorithm is built to simulate innovation process in organizations. Transformation and selection produce micro dynamics to create macro behavior in the agents' population. Results clarify Darwinian Lamarckian adaptation mechanisms as their relation to environment and their interactions. Simulations show the existence of an optimal level of experimentation and selection of projects upstream the innovation process, demonstrate that the efficiency of evolutionist processes is contingent to environment complexity and allow exploring interdependencies and coexistence between two paths of evolution. The model validity is approached through similarity to admitted theory and through a comparative study of the innovation processes of two car makers (Renault and Ford).

Suggested Citation

  • Manuel Cartier, 2004. "An Agent-Based Model of Innovation Emergence in Organizations: Renault and Ford Through the Lens of Evolutionism," Computational and Mathematical Organization Theory, Springer, vol. 10(2), pages 147-153, July.
    • Handle: RePEc:spr:comaot:v:10:y:2004:i:2:d:10.1023_b:cmot.0000039167.91320.df
    DOI: 10.1023/B:CMOT.0000039167.91320.df
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    References listed on IDEAS

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    1. Robert Axelrod, 1997. "Advancing the Art of Simulation in the Social Sciences," Working Papers 97-05-048, Santa Fe Institute.
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    Cited by:

    1. Kotaro Ohori & Shingo Takahashi, 2012. "Market design for standardization problems with agent-based social simulation," Journal of Evolutionary Economics, Springer, vol. 22(1), pages 49-77, January.

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