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Organizational Strategic Adaptation In The Presence Of Inertia

Author

Listed:
  • ANTHONY BRABAZON

    (School of Business, University College Dublin, Belfield, Dublin 4, Ireland)

  • ARLINDO SILVA

    (Escola Superior de Tecnologia, Instituto Politecnico de Castelo Branco, Av. do Empresario, 6000 Castelo Branco, Portugal)

  • TIAGO FERRA DE SOUSA

    (Escola Superior de Tecnologia, Instituto Politecnico de Castelo Branco, Av. do Empresario, 6000 Castelo Branco, Portugal)

  • MICHAEL O'NEILL

    (School of Computer Science and Informatics, University College Dublin, Belfield, Dublin 4, Ireland)

  • ROBIN MATTHEWS

    (Center for International Business Policy, Kingston University, London, United Kingdom)

  • ERNESTO COSTA

    (Centro de Informatica e Sistemas da Universidade de Coimbra, Polo II-Pinhal de Marrocos, 3030 Coimbra, Portugal)

Abstract

This paper extends the particle swarm metaphor into the domain of organization science. A simulator (OrgSwarm) which can be used to model the adaptation of a population of organizations on a strategic landscape is introduced. The simulator embeds a number of features of the process of organizational adaptation, including the resistance of organizations to change (strategic inertia), errorful assessments of the payoffs to proposed strategies, and market competition. These features allow the examination of a wide range of real-life scenarios in organizational adaptation. The paper reports the results of a number of simulation experiments and these suggest that agent (management) uncertainty as to the payoffs to potential strategies has the effect of lowering the average payoffs obtained by a population of organizations. The results also suggest that a degree of strategic inertia can assist rather than hamper adaptive efforts at a populational level.

Suggested Citation

  • Anthony Brabazon & Arlindo Silva & Tiago Ferra De Sousa & Michael O'Neill & Robin Matthews & Ernesto Costa, 2005. "Organizational Strategic Adaptation In The Presence Of Inertia," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 8(04), pages 497-519.
    • Handle: RePEc:wsi:acsxxx:v:08:y:2005:i:04:n:s0219525905000543
    DOI: 10.1142/S0219525905000543
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    References listed on IDEAS

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    1. Stuart Kauffman & Jose Lobo & William G. Macready, 1998. "Optimal Search on a Technology Landscape," Research in Economics 98-10-091e, Santa Fe Institute.
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