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Applications of Social Systems Modeling to Political Risk Management

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Handbook on Decision Making

Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 33))

Abstract

Risk is inexplicably linked to complex inter-related structural and behavioral factors. Of these, human factors tend to be overarching and predominant. Any model that would assist with exploring the inter-relationships among structural and human factors would be immensely valuable to risk management. A social system model constructed with a valid set of software agent framework and complete with factions, institutions and other organizational descriptors, all based on best-of-breed social science theories, can act as the desired testbed to evaluate effects that may arise from alternative courses of action. Through our past case studies, we describe in this article, how social systems modeling and associated intelligent system tools could be applied to assess and manage political risk (and by extension other social systems based risks). We also enumerate the challenges of such a testbed and describes best-of-breed theories drawn from across the social sciences and synthesized and implemented in an agent-based framework. These predictions are examined in a real world cases (Bangladesh) where the agent models are subjected to a validity check and the political risks are estimated.

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Authors and Affiliations

  1. Ackoff Collaboratory for Advancement of Systems Approaches (ACASA), University of Pennsylvania, 120 Hayden Hall, 220 South 33rd Street, Philadelphia, PA, 19104-6315

    Gnana K. Bharathy & Barry Silverman

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  1. Gnana K. Bharathy
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  2. Barry Silverman
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  1. University of Technology, Sydney (UTS), Australia

    Jie Lu  & Guangquan Zhang  & 

  2. University of South Australia, Australia

    Lakhmi C. Jain

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Bharathy, G.K., Silverman, B. (2012). Applications of Social Systems Modeling to Political Risk Management. In: Lu, J., Jain, L.C., Zhang, G. (eds) Handbook on Decision Making. Intelligent Systems Reference Library, vol 33. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25755-1_17

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  • DOI: https://doi.org/10.1007/978-3-642-25755-1_17

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