ORGANIZATIONAL STRATEGIC ADAPTATION IN THE PRESENCE OF INERTIA

Anthony Brabazon (), Arlindo Silva (), Tiago Ferra de Sousa, Michael O'Neill (), Robin Matthews () and Ernesto Costa ()
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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

Advances in Complex Systems (ACS), 2005, vol. 08, issue 04, 497-519

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.

Keywords: Organizational adaptation; particle swarm metaphor; strategic landscape; multi-agent system (search for similar items in EconPapers)
Date: 2005
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DOI: 10.1142/S0219525905000543

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