Agent-based modeling of ambidextrous organizations

Virtualizing competitive strategy

Nicholas S P Tay, Robert F Lusch

Research output: Contribution to journalArticle

23 Citations (Scopus)

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 languageEnglish (US)
Pages (from-to)50-57
Number of pages8
JournalIEEE Intelligent Systems
Volume22
Issue number5
DOIs
StatePublished - Sep 2007

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Fuzzy inference
Testing
Macros
Decision making
Industry

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Artificial Intelligence

Cite this

Agent-based modeling of ambidextrous organizations : Virtualizing competitive strategy. / Tay, Nicholas S P; Lusch, Robert F.

In: IEEE Intelligent Systems, Vol. 22, No. 5, 09.2007, p. 50-57.

Research output: Contribution to journalArticle

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