Agent-based modeling of ambidextrous organizations: Virtualizing competitive strategy

Nicholas S.P. Tay; Robert F. Lusch

doi:10.1109/MIS.2007.4338494

Agent-based modeling of ambidextrous organizations: Virtualizing competitive strategy

Nicholas S.P. Tay, Robert F. Lusch

Marketing

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27 Scopus citations

Abstract

Agent-based modeling (ABM) creates a virtual competitive market that provides business strategies to Petri dish for investigating competitive strategy in an ambidextrous organization. A virtual world of testing various competitive strategies is based on organizations with stable environment and turbulent environment. The simplest set of assumptions are explored to allow the virtual worlds to generate the pattern of explanatory interest. The decision making and learning of an organization are modeled by possibility elaboration and possibility reduction tests. Fuzzy inferences of ABM are made and the relevant pseudocode to illustrate the model of inductive learning is defined. The proper use of ABM for virtual competitive market of an ambidextrous organization includes use of no precise quantitative predictions, testing of strategies, and use of micro and macro models.

Original language	English (US)
Pages (from-to)	50-57
Number of pages	8
Journal	IEEE Intelligent Systems
Volume	22
Issue number	5
DOIs	https://doi.org/10.1109/MIS.2007.4338494
State	Published - Sep 2007

ASJC Scopus subject areas

Computer Networks and Communications
Artificial Intelligence

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Agent-based modeling of ambidextrous organizations: Virtualizing competitive strategy

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