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Simulating Organizations: Computational Models of Institutions and Groups

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Editor Info

  • Michael Prietula
    () (Emory University)
  • Kathleen Carley
    () (Carnegie Mellon University)
  • Les Gasser
    () (University of Illinois at Urbana-Champaign)

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Abstract

The globalization of the economy, increasing number of transnational organizations, and rapid changes in robotics, information, and telecommunication technologies are just a few of the factors significantly altering organizational time scales, forms, complexity, and environments. Time scales have shrunk, new organizational forms are emerging, and organizational environments are expanding and mutating at unprecedented rates. Computational modeling affords opportunities to both understand and respond to these complex changes. Paralleling developments in the physical sciences, computational modeling is emerging in the social and organizational sciences. Organizational researchers are using computational models to gain insights into organizational phenomena and to explore dynamic processes and configurations that are difficult or impossible to investigate with other methods. Many interesting insights have already resulted from this research, such as how group cooperation arises or dissipates in social dilemma settings, and how honesty and benevolence affect behavior in a group task. On the practical side, computational modeling is increasingly effective for organizational design, analysis, and reengineering. Although a great deal of work remains to be done, the era is approaching when both theorists and practitioners will routinely state theories, design organizations, and derive their implications using widely shared computational tools. This volume brings together a range of work from many of the leading researchers in the field.

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Bibliographic Info

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This book is provided by The MIT Press in its series MIT Press Books with number 026266108x and published in 1998.

Volume: 1
Edition: 1
ISBN: 0-262-66108-X
Handle: RePEc:mtp:titles:026266108x

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Web page: http://mitpress.mit.edu

Related research

Keywords: organizations; computational models;

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Cited by:
  1. Stefano Balbi & Carlo Giupponi, 2009. "Reviewing agent-based modelling of socio-ecosystems: a methodology for the analysis of climate change adaptation and sustainability," Working Papers 2009_15, Department of Economics, University of Venice "Ca' Foscari".
  2. Max Boisot & Yan Li, 2006. "Organizational versus Market Knowledge: From Concrete Embodiment to Abstract Representation," Journal of Bioeconomics, Springer, vol. 8(3), pages 219-251, December.
  3. Frank Beckenbach & Ramón Briegel, 2010. "Multi-agent modeling of economic innovation dynamics and its implications for analyzing emission impacts," International Economics and Economic Policy, Springer, vol. 7(2), pages 317-341, August.
  4. Sheen S. Levine & Robert Kurzban, 2006. "Explaining clustering in social networks: towards an evolutionary theory of cascading benefits," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 27(2-3), pages 173-187.
  5. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, EconWPA, revised 15 Aug 2002.
  6. Richard Freeman & Douglas Kruse & Joseph Blasi, 2008. "Worker Responses To Shirking Under Shared Capitalism," NBER Working Papers 14227, National Bureau of Economic Research, Inc.
  7. Douglas Kruse & Joseph Blasi & Richard B. Freeman, 2004. "Monitoring colleagues at work: profit-sharing, employee ownership, broad-based stock options and workplace performance in the United States," LSE Research Online Documents on Economics 19943, London School of Economics and Political Science, LSE Library.
  8. Yuya Ushida & Kiyohiko Hattori & Keiki Takdama, 2010. "Modeling collective adaptive agent design and its analysis in Barnga game," Journal of Economic Interaction and Coordination, Springer, vol. 5(2), pages 137-154, December.

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