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A Computational Theory of the Firm

Author

Listed:
  • Jason Barr
  • Francesco Saraceno

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

Abstract

This paper proposes using computational learning theory (CLT) as a framework for analyzing the information processing behavior of firms; we argue that firms can be viewed as learning algorithms. The costs and benefits of processing information are linked to the structure of the firm and its relationship with the environment. We model the firm as a type of artificial neural network (ANN). By a simulation experiment, we show which types of networks maximize the net return to computation given different environments.

Suggested Citation

  • Jason Barr & Francesco Saraceno, 2002. "A Computational Theory of the Firm," Post-Print hal-03597701, HAL.
    • Handle: RePEc:hal:journl:hal-03597701
    DOI: 10.1016/S0167-2681(02)00002-1
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    Citations

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    Cited by:

    1. Ying Fan & Menghui Li & Zengru Di, 2004. "Increasing Returns to Scale, Dynamics of Industrial Structure and Size Distribution of Firms," Papers cond-mat/0407383, arXiv.org.
    2. Fioretti, Guido, 2006. "Recognising investment opportunities at the onset of recoveries," Research in Economics, Elsevier, vol. 60(2), pages 69-84, June.
    3. Barr, Jason & Saraceno, Francesco, 2009. "Organization, learning and cooperation," Journal of Economic Behavior & Organization, Elsevier, vol. 70(1-2), pages 39-53, May.
    4. repec:spo:wpecon:info:hdl:2441/9832 is not listed on IDEAS
    5. Francesco Saraceno & Jason Barr, 2008. "Cournot competition and endogenous firm size," Journal of Evolutionary Economics, Springer, vol. 18(5), pages 615-638, October.
    6. Ricardo Colomo-Palacios & Israel González-Carrasco & Jose Luis López-Cuadrado & Antonio Trigo & Joao Eduardo Varajao, 2014. "I-Competere: Using applied intelligence in search of competency gaps in software project managers," Information Systems Frontiers, Springer, vol. 16(4), pages 607-625, September.
    7. Jason Barr & Nobuyuki Hanaki, 2008. "Organizations undertaking complex projects in uncertain environments," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 3(2), pages 119-135, December.
    8. Szymon Chudziak, 2025. "Studying economic complexity with agent-based models: advances, challenges and future perspectives," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 20(2), pages 413-449, April.
    9. Nobuyuki Hanaki & Jason Barr, 2005. "Firm Structure, Search and Environmental Complexity," Computing in Economics and Finance 2005 222, Society for Computational Economics.
    10. repec:spo:wpecon:info:hdl:2441/6782 is not listed on IDEAS
    11. repec:spo:wpmain:info:hdl:2441/9832 is not listed on IDEAS
    12. Barr, Jason & Saraceno, Francesco, 2005. "Cournot competition, organization and learning," Journal of Economic Dynamics and Control, Elsevier, vol. 29(1-2), pages 277-295, January.
    13. Marco Corsino & Roberto Gabriele & Enrico Zaninotto, 2009. "How Do Organizational Capabilities Shape Industry Dynamics ?," LEM Papers Series 2009/10, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    14. Francesco Saraceno & Jason Barr, 2008. "Cournot competition and endogenous firm size," Journal of Evolutionary Economics, Springer, vol. 18(5), pages 615-638, October.
    15. repec:spo:wpmain:info:hdl:2441/6782 is not listed on IDEAS
    16. Rand, William & Rust, Roland T., 2011. "Agent-based modeling in marketing: Guidelines for rigor," International Journal of Research in Marketing, Elsevier, vol. 28(3), pages 181-193.
    17. Nobuyuki Hanaki & Jason Barr, 2005. "Firm Structure, Search and Environmental Complexity," Computing in Economics and Finance 2005 222, Society for Computational Economics.
    18. Chang, Myong-Hun & Harrington, Joseph Jr., 2006. "Agent-Based Models of Organizations," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 26, pages 1273-1337, Elsevier.
    19. Michael I.C. Nwogugu, 2019. "Complex Systems, Multi-Sided Incentives and Risk Perception in Companies," Palgrave Macmillan Books, Palgrave Macmillan, number 978-1-137-44704-3, December.

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