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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. 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.
    2. 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.
    3. Oliva, Gabriele & Panzieri, Stefano & Setola, Roberto, 2010. "Agent-based input–output interdependency model," International Journal of Critical Infrastructure Protection, Elsevier, vol. 3(2), pages 76-82.
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    6. 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.
    7. Miller,Ronald E. & Blair,Peter D., 2009. "Input-Output Analysis," Cambridge Books, Cambridge University Press, number 9780521517133.
    8. Miller,Ronald E. & Blair,Peter D., 2009. "Input-Output Analysis," Cambridge Books, Cambridge University Press, number 9780521739023.
    9. Barker, Kash & Haimes, Yacov Y., 2009. "Assessing uncertainty in extreme events: Applications to risk-based decision making in interdependent infrastructure sectors," Reliability Engineering and System Safety, Elsevier, vol. 94(4), pages 819-829.
    10. Karen J. Horowitz & Mark A. Planting, 2006. "Concepts and Methods of the U.S. Input-Output Accounts," BEA Papers 0066, Bureau of Economic Analysis.
    11. Henry, Devanandham & Emmanuel Ramirez-Marquez, Jose, 2012. "Generic metrics and quantitative approaches for system resilience as a function of time," Reliability Engineering and System Safety, Elsevier, vol. 99(C), pages 114-122.
    12. Barker, Kash & Santos, Joost R., 2010. "Measuring the efficacy of inventory with a dynamic input-output model," International Journal of Production Economics, Elsevier, vol. 126(1), pages 130-143, July.
    13. Whitson, John C. & Ramirez-Marquez, Jose Emmanuel, 2009. "Resiliency as a component importance measure in network reliability," Reliability Engineering and System Safety, Elsevier, vol. 94(10), pages 1685-1693.
    14. 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.
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