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Analyzing interdependent impacts of resource sustainability

Author

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  • Zachary Walchuk

    (University of Oklahoma)

  • Kash Barker

    (University of Oklahoma)

Abstract

Quantifying the impact of the shortage of a scarce resource requires a systemic account of the interdependent nature of several industry and infrastructure sectors that rely either directly or indirectly on that resource. An ability to quickly and easily quantify such an impact provides policymakers with a useful measure of the efficacy of discovering, designing, or developing a sustainable alternative. Discussed in this paper is a methodological approach for measuring the broader interdependent impacts of a resource shortage. The dynamic inoperability input–output model (DIIM) is used to illustrate both the economic effects of resource shortages over a period of time and the time-dependent recovery of industry sectors. Extensions to the DIIM are introduced to produce an accessible tool for policymakers and industry decision makers. Case studies using publicly available data illustrate the usefulness of the model for describing local oil production shortages and global rare earth metals supply shortages, highlighting the industries that will need to adapt to changes in resource availability, as well as those industries that will remain relatively unaffected. Above all, the model presented in this paper is an effective means of communicating the impact and importance of resource shortages to assist in the design and development of a sustainable future.

Suggested Citation

  • Zachary Walchuk & Kash Barker, 2013. "Analyzing interdependent impacts of resource sustainability," Environment Systems and Decisions, Springer, vol. 33(3), pages 391-403, September.
    • Handle: RePEc:spr:envsyd:v:33:y:2013:i:3:d:10.1007_s10669-013-9456-3
    DOI: 10.1007/s10669-013-9456-3
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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.
    2. V. Rosato & L. Issacharoff & F. Tiriticco & S. Meloni & S. De Porcellinis & R. Setola, 2008. "Modelling interdependent infrastructures using interacting dynamical models," International Journal of Critical Infrastructures, Inderscience Enterprises Ltd, vol. 4(1/2), pages 63-79.
    3. Joanna Resurreccion & Joost R. Santos, 2012. "Multiobjective Prioritization Methodology and Decision Support System for Evaluating Inventory Enhancement Strategies for Disrupted Interdependent Sectors," Risk Analysis, John Wiley & Sons, vol. 32(10), pages 1673-1692, October.
    4. 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.
    5. Joost R. Santos & Yacov Y. Haimes, 2004. "Modeling the Demand Reduction Input‐Output (I‐O) Inoperability Due to Terrorism of Interconnected Infrastructures," Risk Analysis, John Wiley & Sons, vol. 24(6), pages 1437-1451, December.
    6. George E. Apostolakis & Douglas M. Lemon, 2005. "A Screening Methodology for the Identification and Ranking of Infrastructure Vulnerabilities Due to Terrorism," Risk Analysis, John Wiley & Sons, vol. 25(2), pages 361-376, April.
    7. Eva Andrijcic & Barry Horowitz, 2006. "A Macro‐Economic Framework for Evaluation of Cyber Security Risks Related to Protection of Intellectual Property," Risk Analysis, John Wiley & Sons, vol. 26(4), pages 907-923, August.
    8. Jeroen C.J.M. van den Bergh (ed.), 1999. "Handbook of Environmental and Resource Economics," Books, Edward Elgar Publishing, number 801.
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    Cited by:

    1. Michael Francis D. Benjamin & Aristotle T. Ubando & Luis F. Razon & Raymond R. Tan, 2015. "Analyzing the disruption resilience of bioenergy parks using dynamic inoperability input–output modeling," Environment Systems and Decisions, Springer, vol. 35(3), pages 351-362, September.
    2. Peter A. Beling, 2013. "Multi-scale decision making: challenges in engineering and environmental systems," Environment Systems and Decisions, Springer, vol. 33(3), pages 323-325, September.
    3. Joost R. Santos & Sheree T. Pagsuyoin & Lucia C. Herrera & Raymond R. Tan & Krista D. Yu, 2014. "Analysis of drought risk management strategies using dynamic inoperability input–output modeling and event tree analysis," Environment Systems and Decisions, Springer, vol. 34(4), pages 492-506, December.

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