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Strategic Preparedness for Recovery from Catastrophic Risks to Communities and Infrastructure Systems of Systems

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  • Yacov Y Haimes

Abstract

Natural and human‐induced disasters affect organizations in myriad ways because of the inherent interconnectedness and interdependencies among human, cyber, and physical infrastructures, but more importantly, because organizations depend on the effectiveness of people and on the leadership they provide to the organizations they serve and represent. These human–organizational–cyber–physical infrastructure entities are termed systems of systems. Given the multiple perspectives that characterize them, they cannot be modeled effectively with a single model. The focus of this article is: (i) the centrality of the states of a system in modeling; (ii) the efficacious role of shared states in modeling systems of systems, in identification, and in the meta‐modeling of systems of systems; and (iii) the contributions of the above to strategic preparedness, response to, and recovery from catastrophic risk to such systems. Strategic preparedness connotes a decision‐making process and its associated actions. These must be: implemented in advance of a natural or human‐induced disaster, aimed at reducing consequences (e.g., recovery time, community suffering, and cost), and/or controlling their likelihood to a level considered acceptable (through the decisionmakers’ implicit and explicit acceptance of various risks and tradeoffs). The inoperability input‐output model (IIM), which is grounded on Leontief's input/output model, has enabled the modeling of interdependent subsystems. Two separate modeling structures are introduced. These are: phantom system models (PSM), where shared states constitute the essence of modeling coupled systems; and the IIM, where interdependencies among sectors of the economy are manifested by the Leontief matrix of technological coefficients. This article demonstrates the potential contributions of these two models to each other, and thus to more informative modeling of systems of systems schema. The contributions of shared states to this modeling and to systems identification are presented with case studies.

Suggested Citation

  • Yacov Y Haimes, 2012. "Strategic Preparedness for Recovery from Catastrophic Risks to Communities and Infrastructure Systems of Systems," Risk Analysis, John Wiley & Sons, vol. 32(11), pages 1834-1845, November.
    • Handle: RePEc:wly:riskan:v:32:y:2012:i:11:p:1834-1845
    DOI: 10.1111/j.1539-6924.2012.01930.x
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    1. Yacov Y. Haimes, 2011. "On the Complex Quantification of Risk: Systems‐Based Perspective on Terrorism," Risk Analysis, John Wiley & Sons, vol. 31(8), pages 1175-1186, August.
    2. Stan Kaplan & Yacov Y. Haimes & B. John Garrick, 2001. "Fitting Hierarchical Holographic Modeling into the Theory of Scenario Structuring and a Resulting Refinement to the Quantitative Definition of Risk," Risk Analysis, John Wiley & Sons, vol. 21(5), pages 807-807, October.
    3. Ermoliev, Yuri M. & Ermolieva, Tatiana Y. & MacDonald, Gordon J. & Norkin, Vladimir I. & Amendola, Aniello, 2000. "A system approach to management of catastrophic risks," European Journal of Operational Research, Elsevier, vol. 122(2), pages 452-460, April.
    4. Stanley Kaplan & B. John Garrick, 1981. "On The Quantitative Definition of Risk," Risk Analysis, John Wiley & Sons, vol. 1(1), pages 11-27, March.
    5. Yacov Y. Haimes, 2006. "On the Definition of Vulnerabilities in Measuring Risks to Infrastructures," Risk Analysis, John Wiley & Sons, vol. 26(2), pages 293-296, April.
    6. Yacov Y. Haimes, 2009. "On the Complex Definition of Risk: A Systems‐Based Approach," Risk Analysis, John Wiley & Sons, vol. 29(12), pages 1647-1654, December.
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