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Critical Incident Management: an Empirically Derived Computational Model

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Abstract

The main purpose of this paper is to demonstrate an empirical approach to social simulation. The systems and the behaviour of middle-level managers of a real company are modelled. The managers' cognition is represented by problem space architectures drawn from cognitive science and an endorsements mechanism adapted from the literature on conflict resolution in rulebased systems. Both aspects of the representation of cognition are based on information provided by domain experts. Qualitative and numerical results accord with the views of domain experts.

Suggested Citation

  • Scott Moss, 1998. "Critical Incident Management: an Empirically Derived Computational Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 1(4), pages 1-1.
    • Handle: RePEc:jas:jasssj:1998-9-1
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    1. Moss, Scott, 1995. "Control Metaphors in the Modelling of Economic Learning and Decision-Making Behaviour," Computational Economics, Springer;Society for Computational Economics, vol. 8(4), pages 283-301, November.
    2. George P. Huber, 1991. "Organizational Learning: The Contributing Processes and the Literatures," Organization Science, INFORMS, vol. 2(1), pages 88-115, February.
    3. C. K. Prahalad & Richard A. Bettis, 1986. "The dominant logic: A new linkage between diversity and performance," Strategic Management Journal, Wiley Blackwell, vol. 7(6), pages 485-501, November.
    4. Moss, S. & Edmonds, B., 1997. "A knowledge-based model of context-dependent attribute preferences for fast moving consumer goods," Omega, Elsevier, vol. 25(2), pages 155-169, April.
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    1. Rosaria Conte & Bruce Edmonds & Scott Moss & R. Keith Sawyer, 2001. "Sociology and Social Theory in Agent Based Social Simulation: A Symposium," Computational and Mathematical Organization Theory, Springer, vol. 7(3), pages 183-205, October.
    2. Shah Jamal Alam & Ruth Meyer & Gina Ziervogel & Scott Moss, 2007. "The Impact of HIV/AIDS in the Context of Socioeconomic Stressors: an Evidence-Driven Approach," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(4), pages 1-7.
    3. Scott Moss, 2000. "Canonical Tasks, Environments and Models for Social Simulation," Computational and Mathematical Organization Theory, Springer, vol. 6(3), pages 249-275, September.
    4. Riccardo Boero & Flaminio Squazzoni, 2005. "Does Empirical Embeddedness Matter? Methodological Issues on Agent-Based Models for Analytical Social Science," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(4), pages 1-6.

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