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Organization, Learning and Cooperation

Author

Listed:
  • Jason Barr

    (Department of Economics - Tilburg University [Netherlands])

  • Francesco Saraceno

    (OFCE - Observatoire français des conjonctures économiques (Sciences Po) - Sciences Po - Sciences Po)

Abstract

This paper models the organization of the firm as a type of artificial neural network in a duopoly setting. The firm plays a repeated Prisoner's Dilemma type game, but must also learn to map environmental signals to demand parameters and to its rival's willingness to cooperate. We study the prospects for cooperation given the need for the firm to learn the environment and its rival's output. We show how profit and cooperation rates are affected by the sizes of both firms, their willingness to cooperate, and by environmental complexity. In addition, we investigate equilibrium firm size and cooperation rates.

Suggested Citation

  • Jason Barr & Francesco Saraceno, 2004. "Organization, Learning and Cooperation," SciencePo Working papers Main hal-01065495, HAL.
    • Handle: RePEc:hal:spmain:hal-01065495
    Note: View the original document on HAL open archive server: https://hal-sciencespo.archives-ouvertes.fr/hal-01065495
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    References listed on IDEAS

    as
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    Citations

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    Cited by:

    1. Jason Barr & Francesco Saraceno, 2005. "Modeling the Firm as an Artificial Neural Network," Working Papers Rutgers University, Newark 2005-011, Department of Economics, Rutgers University, Newark.
    2. Francesco Saraceno & Jason Barr, 2008. "Cournot competition and endogenous firm size," Journal of Evolutionary Economics, Springer, vol. 18(5), pages 615-638, October.
    3. Francesco Saraceno & Jason Barr, 2008. "Cournot competition and endogenous firm size," Journal of Evolutionary Economics, Springer, vol. 18(5), pages 615-638, October.
    4. Serge Blondel & Ngoc-Thao Noet, 2023. "Quels facteurs expliquent la faible coopération en horticulture ?," TEPP Research Report 2023-01, TEPP.
    5. Fioretti, Guido, 2006. "Recognising investment opportunities at the onset of recoveries," Research in Economics, Elsevier, vol. 60(2), pages 69-84, June.
    6. Eva Bolfikova & Daniela Hrehova & Jana Frenova, 2010. "Manager’s decision-making in organizations empirical analysis of bureaucratic vs. learning approach," Zbornik radova Ekonomskog fakulteta u Rijeci/Proceedings of Rijeka Faculty of Economics, University of Rijeka, Faculty of Economics and Business, vol. 28(1), pages 135-163.
    7. repec:hal:spmain:info:hdl:2441/9922 is not listed on IDEAS
    8. Stefani, Silvana & Ausloos, Marcel & González-Concepción, Concepción & Sonubi, Adeyemi & Gil-Fariña, Ma Candelaria & Pestano-Gabino, Celina & Moretto, Enrico, 2021. "Competing or collaborating, with no symmetrical behaviour: Leadership opportunities and winning strategies under stability," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 187(C), pages 489-504.

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    More about this item

    Keywords

    Artificial Neural Networks; Prisoner's Dilemma; Cooperation; Firm learning;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • D21 - Microeconomics - - Production and Organizations - - - Firm Behavior: Theory
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • L13 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Oligopoly and Other Imperfect Markets

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