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Computational Modeling of Organizations Comes of Age

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  • Raymond E. Levitt

Abstract

As they are maturing—i.e., as they are becoming validated, calibrated and refined—computational emulation models of organizations are evolving into: powerful new kinds of organizational design tools for predicting and mitigating organizational risks; and flexible new kinds of organizational theorem-provers for validating extant organization theory and developing new theory. Over the past 50 years, computational modeling and simulation have had enormous impacts on the rate of advancement of knowledge in fields like physics, chemistry and, more recently, biology; and their subsequent application has enabled whole new areas of engineering practice. In the same way, as our young discipline comes of age, computational organizational models are beginning to impact behavioral, organizational and economic science, and management consulting practice. This paper attempts to draw parallels between computational modeling in natural sciences and computational modeling of organizations as a contributor to both social science and management practice. To illustrate the lifecycle of a computational organizational model that is now relatively mature, this paper traces the evolution of the Virtual Design Team (VDT) computational modeling and simulation research project at Stanford University from its origins in 1988 to the present. It lays out the steps in the process of validating VDT as a “computational emulation” model of organizations to the point that VDT began to influence management practice and, subsequently, to advance organizational science. We discuss alternate research trajectories that can be taken by computational and mathematical modelers who prefer the typical natural science validation trajectory—i.e., who attempt to impact organizational science first and, perhaps subsequently, to impact management practice. The paper concludes with a discussion of the current state-of-the-art of computational modeling of organizations and some thoughts about where, and how rapidly, the field is headed.

Suggested Citation

  • Raymond E. Levitt, 2004. "Computational Modeling of Organizations Comes of Age," Computational and Mathematical Organization Theory, Springer, vol. 10(2), pages 127-145, July.
    • Handle: RePEc:spr:comaot:v:10:y:2004:i:2:d:10.1023_b:cmot.0000039166.53683.d0
    DOI: 10.1023/B:CMOT.0000039166.53683.d0
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    1. Douglas B. Fridsma & Jan Thomsen, 1998. "Representing Medical Protocols for Organizational Simulation: An Information-Processing Approach," Computational and Mathematical Organization Theory, Springer, vol. 4(1), pages 71-95, March.
    2. Tim Carroll & Richard M. Burton, 2000. "Organizations and Complexity: Searching for the Edge of Chaos," Computational and Mathematical Organization Theory, Springer, vol. 6(4), pages 319-337, December.
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    Cited by:

    1. Regine Pei Tze Oh & Susan M. Sanchez & Thomas W. Lucas & Hong Wan & Mark E. Nissen, 2009. "Efficient experimental design tools for exploring large simulation models," Computational and Mathematical Organization Theory, Springer, vol. 15(3), pages 237-257, September.
    2. Richard M. Burton & Børge Obel, 2011. "Computational Modeling for What-Is, What-Might-Be, and What-Should-Be Studies---And Triangulation," Organization Science, INFORMS, vol. 22(5), pages 1195-1202, October.
    3. Kent Wickstrøm Jensen & Dorthe Døjbak Håkonsson & Richard M. Burton & Børge Obel, 2010. "The effect of virtuality on the functioning of centralized versus decentralized structures—an information processing perspective," Computational and Mathematical Organization Theory, Springer, vol. 16(2), pages 144-170, June.

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