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Analysis of Critical Infrastructure Network Failure in the European Union: A Combined Systems Engineering and Economic Model

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  • Olaf Jonkeren
  • Ivano Azzini
  • Luca Galbusera
  • Stavros Ntalampiras
  • Georgios Giannopoulos

Abstract

Over the past few years, the European Commission has placed Critical Infrastructure Protection under the spotlight. Therefore, the Joint Research Centre is developing a tool to estimate the economic impact of Critical Infrastructure (CI) network failure, resulting from a hazard, on the regional or national level. This tool, which is presented in this study, is a combined Systems Engineering and Dynamic Inoperability Input–output model (SE-DIIM). The resilience of infrastructures and economic sectors, in terms of their ability to withstand and recover from disruptions, is included in the model. We discuss the model by analyzing the economic losses incurred in the 2003 Italian electricity network outage. The losses are estimated at both national and regional levels i.e. northern, central and southern parts of Italy and Sicily with a focus on 9 CI’s. We estimate that the economic loss for the case study under consideration is between €46 million and €173 million. We conclude that the combination of the SE and the DIIM components provides a complete framework for assessing the economic impact of critical infrastructure network failure on the national or regional level taking account of resilience. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Olaf Jonkeren & Ivano Azzini & Luca Galbusera & Stavros Ntalampiras & Georgios Giannopoulos, 2015. "Analysis of Critical Infrastructure Network Failure in the European Union: A Combined Systems Engineering and Economic Model," Networks and Spatial Economics, Springer, vol. 15(2), pages 253-270, June.
    • Handle: RePEc:kap:netspa:v:15:y:2015:i:2:p:253-270
    DOI: 10.1007/s11067-014-9259-1
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    Cited by:

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    2. Galbusera, Luca & Trucco, Paolo & Giannopoulos, Georgios, 2020. "Modeling interdependencies in multi-sectoral critical infrastructure systems: Evolving the DMCI approach," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    3. Rokhaya Dieye & Ahmed Bounfour & Altay Ozaygen & Niaz Kammoun, 2020. "Estimates of the macroeconomic costs of cyber‐attacks," Risk Management and Insurance Review, American Risk and Insurance Association, vol. 23(2), pages 183-208, June.
    4. Jan Abrell & Friedrich Kunz, 2015. "Integrating Intermittent Renewable Wind Generation - A Stochastic Multi-Market Electricity Model for the European Electricity Market," Networks and Spatial Economics, Springer, vol. 15(1), pages 117-147, March.
    5. HOSSAIN, Niamat Ullah Ibne & Amrani, Safae El & Jaradat, Raed & Marufuzzaman, Mohammad & Buchanan, Randy & Rinaudo, Christina & Hamilton, Michael, 2020. "Modeling and assessing interdependencies between critical infrastructures using Bayesian network: A case study of inland waterway port and surrounding supply chain network," Reliability Engineering and System Safety, Elsevier, vol. 198(C).
    6. Mohamad Darayi & Kash Barker & Joost R. Santos, 2017. "Component Importance Measures for Multi-Industry Vulnerability of a Freight Transportation Network," Networks and Spatial Economics, Springer, vol. 17(4), pages 1111-1136, December.
    7. Anne Neumann & Juan Rosellón & Hannes Weigt, 2015. "Removing Cross-Border Capacity Bottlenecks in the European Natural Gas Market—A Proposed Merchant-Regulatory Mechanism," Networks and Spatial Economics, Springer, vol. 15(1), pages 149-181, March.
    8. Gianluca Pescaroli & David Alexander, 2018. "Understanding Compound, Interconnected, Interacting, and Cascading Risks: A Holistic Framework," Risk Analysis, John Wiley & Sons, vol. 38(11), pages 2245-2257, November.
    9. Guibing, Gao & Wenhui, Yue & Wenchu, Ou & Hao, Tang, 2018. "Vulnerability evaluation method applied to manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 255-265.
    10. Poulin, Craig & Kane, Michael B., 2021. "Infrastructure resilience curves: Performance measures and summary metrics," Reliability Engineering and System Safety, Elsevier, vol. 216(C).

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