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Supply Chain Vulnerability Analysis Using Scenario‐Based Input‐Output Modeling: Application to Port Operations

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  • Shital A. Thekdi
  • Joost R. Santos

Abstract

Disruptive events such as natural disasters, loss or reduction of resources, work stoppages, and emergent conditions have potential to propagate economic losses across trade networks. In particular, disruptions to the operation of container port activity can be detrimental for international trade and commerce. Risk assessment should anticipate the impact of port operation disruptions with consideration of how priorities change due to uncertain scenarios and guide investments that are effective and feasible for implementation. Priorities for protective measures and continuity of operations planning must consider the economic impact of such disruptions across a variety of scenarios. This article introduces new performance metrics to characterize resiliency in interdependency modeling and also integrates scenario‐based methods to measure economic sensitivity to sudden‐onset disruptions. The methods will be demonstrated on a U.S. port responsible for handling $36.1 billion of cargo annually. The methods will be useful to port management, private industry supply chain planning, and transportation infrastructure management.

Suggested Citation

  • Shital A. Thekdi & Joost R. Santos, 2016. "Supply Chain Vulnerability Analysis Using Scenario‐Based Input‐Output Modeling: Application to Port Operations," Risk Analysis, John Wiley & Sons, vol. 36(5), pages 1025-1039, May.
  • Handle: RePEc:wly:riskan:v:36:y:2016:i:5:p:1025-1039
    DOI: 10.1111/risa.12473
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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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    5. 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.
    6. Ellen C. Rogerson & James H. Lambert & Alexander F. Johns, 2013. "Runway safety program evaluation with uncertainties of benefits and costs," Journal of Risk Research, Taylor & Francis Journals, vol. 16(5), pages 523-539, May.
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    Cited by:

    1. Jasper Verschuur & Raghav Pant & Elco Koks & Jim Hall, 2022. "A systemic risk framework to improve the resilience of port and supply-chain networks to natural hazards," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 24(3), pages 489-506, September.
    2. Heather Holden & Maha Hussein Abdallah & Dane Rowlands, 2023. "A study to assess the applicability of using remote sensing to minimize service interruption of Canadian port physical infrastructure," Journal of Transportation Security, Springer, vol. 16(1), pages 1-18, December.
    3. Linn Svegrup & Jonas Johansson & Henrik Hassel, 2019. "Integration of Critical Infrastructure and Societal Consequence Models: Impact on Swedish Power System Mitigation Decisions," Risk Analysis, John Wiley & Sons, vol. 39(9), pages 1970-1996, September.
    4. Jessica Olivares-Aguila & Alejandro Vital-Soto, 2021. "Supply Chain Resilience Roadmaps for Major Disruptions," Logistics, MDPI, vol. 5(4), pages 1-18, November.
    5. Stanislav Shmelev & Harrison Roger Brook, 2021. "Macro Sustainability across Countries: Key Sector Environmentally Extended Input-Output Analysis," Sustainability, MDPI, vol. 13(21), pages 1-46, October.
    6. Shital A. Thekdi & Joost Santos, 2019. "Decision‐Making Analytics Using Plural Resilience Parameters for Adaptive Management of Complex Systems," Risk Analysis, John Wiley & Sons, vol. 39(4), pages 871-889, April.

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