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

Manuel Cartier ()
Additional contact information
Manuel Cartier: University of Paris IX Dauphine

Computational and Mathematical Organization Theory, 2004, vol. 10, issue 2, No 2, 147-153

Abstract: 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).

Keywords: innovation process; evolutionism; emergence; simulation; genetic algorithm (search for similar items in EconPapers)
Date: 2004
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://link.springer.com/10.1023/B:CMOT.0000039167.91320.df Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:comaot:v:10:y:2004:i:2:d:10.1023_b:cmot.0000039167.91320.df

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10588

DOI: 10.1023/B:CMOT.0000039167.91320.df

Access Statistics for this article

Computational and Mathematical Organization Theory is currently edited by Terrill Frantz and Kathleen Carley

More articles in Computational and Mathematical Organization Theory from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().