• DocumentCode
    917806
  • Title

    Agent-Based Modeling of Ambidextrous Organizations: Virtualizing Competitive Strategy

  • Author

    Tay, Nicholas S P ; Lusch, Robert F.

  • Author_Institution
    Univ. of San Francisco, San Francisco
  • Volume
    22
  • Issue
    5
  • fYear
    2007
  • Firstpage
    50
  • Lastpage
    57
  • Abstract
    Turbulence, uncertainty, dynamic processes, and networks increasingly characterize competitive markets and business strategies. Consequently, there´s a need to model such markets and strategies as dynamic, evolutionary processes that is, as complex adaptive systems. Agent-based modeling, a rich platform for studying complex evolving systems, is used to model a market where ambidextrous and nonambidextrous organizations compete for buyers. Viewing competitive market and business processes as interactions among agents who mutually influence each other reduces economics to its most microscopic level. Social networks such as the Internet have attracted much research attention because of the rise in stock fraud on the Internet.
  • Keywords
    Internet; learning by example; multi-agent systems; social sciences computing; virtual enterprises; Internet; adaptive system; agent-based modeling; ambidextrous organization; business strategy; evolutionary process; social network; virtual competitive market; Adaptive systems; Analytical models; Data analysis; Environmental economics; Game theory; Marketing and sales; Microscopy; Technological innovation; Time series analysis; Uncertainty; agent-based model; ambidextrous; competitive strategy; fuzzy logic; genetic algorithms;
  • fLanguage
    English
  • Journal_Title
    Intelligent Systems, IEEE
  • Publisher
    ieee
  • ISSN
    1541-1672
  • Type

    jour

  • DOI
    10.1109/MIS.2007.4338494
  • Filename
    4338494