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Can tools help unify organization theory? Perspectives on the state of computational modeling

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  • Michael J. Ashworth

    (Carnegie Mellon University)

  • Kathleen M. Carley

    (Carnegie Mellon University)

Abstract

Scholars engaged in the study of work group and organizational behavior are increasingly calling for the use of integrated methods in conducting research, including the wider adoption of computational models for generating and testing new theory. Our review of the state of modern computational modeling incorporating social structures reveals steady increases in the incorporation of dynamic, adaptive, and realistic behaviors of agents in network settings, yet exposes gaps that must be addressed in the next generation of organizational simulation systems. We compare 28 models according to more than two hundred evaluation criteria, ranging from simple representations of agent demographic and performance characteristics, to more richly defined instantiations of behavioral attributes, interaction with non-agent entities, model flexibility, communication channels, simulation types, knowledge, transactive memory, task complexity, and resource networks. Our survey assesses trends across the wide set of criteria, discusses practical applications, and proposes an agenda for future research and development.

Suggested Citation

  • Michael J. Ashworth & Kathleen M. Carley, 2007. "Can tools help unify organization theory? Perspectives on the state of computational modeling," Computational and Mathematical Organization Theory, Springer, vol. 13(1), pages 89-111, March.
    • Handle: RePEc:spr:comaot:v:13:y:2007:i:1:d:10.1007_s10588-006-9000-9
    DOI: 10.1007/s10588-006-9000-9
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    References listed on IDEAS

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    1. Kreps, David M., 1990. "Game Theory and Economic Modelling," OUP Catalogue, Oxford University Press, number 9780198283812.
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    Cited by:

    1. Lucio Biggiero & Enrico Sevi, 2009. "Opportunism by cheating and its effects on industry profitability. The CIOPS model," Computational and Mathematical Organization Theory, Springer, vol. 15(3), pages 191-236, September.
    2. Matthias Meyer & Michael A. Zaggl & Kathleen M. Carley, 2011. "Measuring CMOT’s intellectual structure and its development," Computational and Mathematical Organization Theory, Springer, vol. 17(1), pages 1-34, March.
    3. Mark Hoogendoorn & Catholijn M. Jonker & Jan Treur, 2011. "A generic architecture for redesign of organizations triggered by changing environmental circumstances," Computational and Mathematical Organization Theory, Springer, vol. 17(2), pages 119-151, May.
    4. Christos Ellinas & Christos Nicolaides & Naoki Masuda, 2022. "Mitigation strategies against cascading failures within a project activity network," Journal of Computational Social Science, Springer, vol. 5(1), pages 383-400, May.
    5. Kalloniatis, Alexander C. & McLennan-Smith, Timothy A. & Roberts, Dale O., 2020. "Modelling distributed decision-making in Command and Control using stochastic network synchronisation," European Journal of Operational Research, Elsevier, vol. 284(2), pages 588-603.
    6. Brian W. Kulik & Timothy Baker, 2008. "Putting the organization back into computational organization theory: a complex Perrowian model of organizational action," Computational and Mathematical Organization Theory, Springer, vol. 14(2), pages 84-119, June.
    7. Jahangirian, Mohsen & Eldabi, Tillal & Naseer, Aisha & Stergioulas, Lampros K. & Young, Terry, 2010. "Simulation in manufacturing and business: A review," European Journal of Operational Research, Elsevier, vol. 203(1), pages 1-13, May.

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