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Static and dynamic metrics of economic resilience for interdependent infrastructure and industry sectors

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  • Pant, Raghav
  • Barker, Kash
  • Zobel, Christopher W.

Abstract

Infrastructures are needed for maintaining functionality and stability of society, while being put under substantial stresses from natural or man-made shocks. Since avoiding shock is impossible, increased focus is given to infrastructure resilience, which denotes the ability to recover and operate under new stable regimes. This paper addresses the problem of estimating, quantifying and planning for economic resilience of interdependent infrastructures, where interconnectedness adds to problem complexity. The risk-based economic input–output model enterprise, a useful tool for measuring the cascading effects of interdependent failures, is employed to introduce a framework for economic resilience estimation. We propose static and dynamic measures for resilience that confirm to well-known resilience concepts of robustness, rapidity, redundancy, and resourcefulness. The quantitative metrics proposed here (static resilience metric, time averaged level of operability, maximum loss of functionality, time to recovery) guide a preparedness decision making framework to promote interdependent economic resilience estimation. Using the metrics we introduce new multi-dimensional resilience functions that allow multiple resource allocation scenarios. Through an example problem we demonstrate the usefulness of these functions in guiding resource planning for building resilience.

Suggested Citation

  • Pant, Raghav & Barker, Kash & Zobel, Christopher W., 2014. "Static and dynamic metrics of economic resilience for interdependent infrastructure and industry sectors," Reliability Engineering and System Safety, Elsevier, vol. 125(C), pages 92-102.
    • Handle: RePEc:eee:reensy:v:125:y:2014:i:c:p:92-102
    DOI: 10.1016/j.ress.2013.09.007
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    References listed on IDEAS

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    1. Joost Santos & Kash Barker & Paul Zelinke, 2008. "Sequential Decision-making in Interdependent Sectors with Multiobjective Inoperability Decision Trees: Application to Biofuel Subsidy Analysis," Economic Systems Research, Taylor & Francis Journals, vol. 20(1), pages 29-56.
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    4. Miller,Ronald E. & Blair,Peter D., 2009. "Input-Output Analysis," Cambridge Books, Cambridge University Press, number 9780521517133.
    5. Miller,Ronald E. & Blair,Peter D., 2009. "Input-Output Analysis," Cambridge Books, Cambridge University Press, number 9780521739023.
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    9. Barker, Kash & Ramirez-Marquez, Jose Emmanuel & Rocco, Claudio M., 2013. "Resilience-based network component importance measures," Reliability Engineering and System Safety, Elsevier, vol. 117(C), pages 89-97.
    10. Yasuhide Okuyama & Geoffrey J. D. Hewings & Michael Sonis, 2004. "Measuring Economic Impacts of Disasters: Interregional Input-Output Analysis Using Sequential Interindustry Model," Advances in Spatial Science, in: Yasuhide Okuyama & Stephanie E. Chang (ed.), Modeling Spatial and Economic Impacts of Disasters, chapter 5, pages 77-101, Springer.
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    12. Pant, Raghav & Barker, Kash & Grant, F. Hank & Landers, Thomas L., 2011. "Interdependent impacts of inoperability at multi-modal transportation container terminals," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(5), pages 722-737, September.
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