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Agent-Based Modeling of Ambidextrous Organizations: Virtualizing Competitive Strategy
September/October 2007 (vol. 22 no. 5)
pp. 50-57
Nicholas S.P. Tay, University of San Francisco
Robert F. Lusch, University of Arizona
Agent-based modeling is the development of computer simulations in which markets, societies, or other macro structures evolve from the ground up through the actions, interactions, and breeding of digital organisms that mimic real-life economic agents. ABM arrives at an especially appropriate time in the development of economic, marketing, and management thought because competitive markets are increasingly viewed as evolutionary processes and complex adaptive systems. A virtual market where organizations compete for buyers demonstrates ABM's richness for competitive-strategy development. An ambidextrous organization (that is, a firm that both exploits its current competencies and explores new competencies) operating in a turbulent environment is more innovative and responsive to dramatic shifts in consumer preferences, and consequently, more profitable. However, in a stable environment, a nonambidextrous organization (one that exploits its current competencies but doesn't explore new competencies) performs better. This article is part of a special issue on social computing.

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Index Terms:
agent-based model, ambidextrous, competitive strategy, genetic algorithms, fuzzy logic
Citation:
Nicholas S.P. Tay, Robert F. Lusch, "Agent-Based Modeling of Ambidextrous Organizations: Virtualizing Competitive Strategy," IEEE Intelligent Systems, vol. 22, no. 5, pp. 50-57, Sept.-Oct. 2007, doi:10.1109/MIS.2007.81
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