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Analysing Critical Infrastructure Failure With A Resilience Inoperability Input--Output Model

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  • Olaf Jonkeren
  • Georgios Giannopoulos

Abstract

Over the past few years much effort has been made in modelling economic losses resulting from critical infrastructure failure. It has appeared that including resilience measures in the modelling approach, which may mute the losses considerably, is a challenging task. At the same time it is necessary because it prevents the modeller from generating overestimates. This study presents two directions to improve the modelling of (economic) resilience for which the state-of-the art with respect to dynamic inoperability input--output modelling is taken as a starting point. Firstly, the new model allows for a different recovery path than the traditionally assumed 'concave up decreasing curve' describes for a disrupted infrastructure or economic sector in the aftermath of a disaster. In this paper, we explain how the recovery path may depend on the type of disaster. Secondly, the model refines the aspect of 'inventory' as a resilience measure. Inventory is interpreted in a broad sense here: it can be any resilience measures which enable an infrastructure or economic sector to continue its supply despite being disrupted. The model is applied to both a simple two-sector illustrative example and a severe winter storm scenario in Europe using economic data from the World Input--Output Database to show its practical usefulness.

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  • 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.
    • Handle: RePEc:taf:ecsysr:v:26:y:2014:i:1:p:39-59
    DOI: 10.1080/09535314.2013.872604
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    Cited by:

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    2. Edward J. Oughton & Daniel Ralph & Raghav Pant & Eireann Leverett & Jennifer Copic & Scott Thacker & Rabia Dada & Simon Ruffle & Michelle Tuveson & Jim W Hall, 2019. "Stochastic Counterfactual Risk Analysis for the Vulnerability Assessment of Cyber‐Physical Attacks on Electricity Distribution Infrastructure Networks," Risk Analysis, John Wiley & Sons, vol. 39(9), pages 2012-2031, September.
    3. Luiijf, Eric & Klaver, Marieke, 2021. "Analysis and lessons identified on critical infrastructures and dependencies from an empirical data set," International Journal of Critical Infrastructure Protection, Elsevier, vol. 35(C).
    4. Edward J. Oughton, 2021. "The Economic Impact of Critical National Infrastructure Failure Due to Space Weather," Papers 2106.08945, arXiv.org.
    5. Pradeep V. Mandapaka & Edmond Y. M. Lo, 2023. "Assessing Shock Propagation and Cascading Uncertainties Using the Input–Output Framework: Analysis of an Oil Refinery Accident in Singapore," Sustainability, MDPI, vol. 15(2), pages 1-24, January.
    6. Selerio, Egberto & Maglasang, Renan, 2021. "Minimizing production loss consequent to disasters using a subsidy optimization model: a pandemic case," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 112-124.
    7. Matteo Coronese & Davide Luzzati, 2022. "Economic impacts of natural hazards and complexity science: a critical review," LEM Papers Series 2022/13, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    8. Annarelli, Alessandro & Nonino, Fabio, 2016. "Strategic and operational management of organizational resilience: Current state of research and future directions," Omega, Elsevier, vol. 62(C), pages 1-18.
    9. Chopra, Shauhrat S. & Khanna, Vikas, 2015. "Interconnectedness and interdependencies of critical infrastructures in the US economy: Implications for resilience," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 865-877.
    10. Aaron Opdyke & Amy Javernick-Will & Matt Koschmann, 2017. "Infrastructure hazard resilience trends: an analysis of 25 years of research," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(2), pages 773-789, June.
    11. Botelho, Vinícius, 2019. "Estimating the economic impacts of power supply interruptions," Energy Economics, Elsevier, vol. 80(C), pages 983-994.
    12. 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.
    13. Poulin, Craig & Kane, Michael B., 2021. "Infrastructure resilience curves: Performance measures and summary metrics," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    14. Leonie Wenz & Sven Norman Willner & Robert Bierkandt & Anders Levermann, 2014. "Acclimate—a model for economic damage propagation. Part II: a dynamic formulation of the backward effects of disaster-induced production failures in the global supply network," Environment Systems and Decisions, Springer, vol. 34(4), pages 525-539, December.
    15. Huang, Michael C. & Hosoe, Nobuhiro, 2017. "Fiscal and social costs of recovery programs for an earthquake disaster in northern Taiwan," Journal of Asian Economics, Elsevier, vol. 53(C), pages 1-17.
    16. Tao Sun, 2024. "Systemic importance of financial services and insurance sectors: a world input–output network analysis," The Geneva Papers on Risk and Insurance - Issues and Practice, Palgrave Macmillan;The Geneva Association, vol. 49(1), pages 63-96, January.

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