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A Risk‐Based Approach for Identifying Key Economic and Infrastructure Systems

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  • Kash Barker
  • Joost R. Santos

Abstract

This article introduces approaches for identifying key interdependent infrastructure sectors based on the inventory dynamic inoperability input‐output model, which integrates an inventory model and a risk‐based interdependency model. An identification of such key sectors narrows a policymaker's focus on sectors providing most impact and receiving most impact from inventory‐caused delays in inoperability resulting from disruptive events. A case study illustrates the practical insights of the key sector approaches derived from a value of workforce‐centered production inoperability from Bureau of Economic Analysis data.

Suggested Citation

  • Kash Barker & Joost R. Santos, 2010. "A Risk‐Based Approach for Identifying Key Economic and Infrastructure Systems," Risk Analysis, John Wiley & Sons, vol. 30(6), pages 962-974, June.
    • Handle: RePEc:wly:riskan:v:30:y:2010:i:6:p:962-974
    DOI: 10.1111/j.1539-6924.2010.01373.x
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Olaf Jonkeren & Georgios Giannopoulos, 2014. "Analysing Critical Infrastructure Failure With A Resilience Inoperability Input--Output Model," Economic Systems Research, Taylor & Francis Journals, vol. 26(1), pages 39-59, March.
    2. Cameron MacKenzie & Hiba Baroud & Kash Barker, 2016. "Static and dynamic resource allocation models for recovery of interdependent systems: application to the Deepwater Horizon oil spill," Annals of Operations Research, Springer, vol. 236(1), pages 103-129, January.
    3. Botelho, Vinícius, 2019. "Estimating the economic impacts of power supply interruptions," Energy Economics, Elsevier, vol. 80(C), pages 983-994.
    4. Joost R. Santos & Lucia Castro Herrera & Krista Danielle S. Yu & Sheree Ann T. Pagsuyoin & Raymond R. Tan, 2014. "State of the Art in Risk Analysis of Workforce Criticality Influencing Disaster Preparedness for Interdependent Systems," Risk Analysis, John Wiley & Sons, vol. 34(6), pages 1056-1068, June.
    5. Monsalve, Mauricio & de la Llera, Juan Carlos, 2019. "Data-driven estimation of interdependencies and restoration of infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 167-180.
    6. Krista Danielle S. Yu & Raymond R. Tan & Kathleen B. Aviso & Michael Angelo B. Promentilla & Joost R. Santos, 2014. "A Vulnerability Index For Post-Disaster Key Sector Prioritization," Economic Systems Research, Taylor & Francis Journals, vol. 26(1), pages 81-97, March.
    7. E. E. Koks & M. Bočkarjova & H. de Moel & J. C. J. H. Aerts, 2015. "Integrated Direct and Indirect Flood Risk Modeling: Development and Sensitivity Analysis," Risk Analysis, John Wiley & Sons, vol. 35(5), pages 882-900, May.
    8. Poulin, Craig & Kane, Michael B., 2021. "Infrastructure resilience curves: Performance measures and summary metrics," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    9. Fang, Yi-Ping & Sansavini, Giovanni, 2019. "Optimum post-disruption restoration under uncertainty for enhancing critical infrastructure resilience," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 1-11.

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