IDEAS home Printed from https://ideas.repec.org/a/eee/ijocip/v4y2011i3p165-175.html
   My bibliography  Save this article

Fuzzy dynamic input–output inoperability model

Author

Listed:
  • Oliva, Gabriele
  • Panzieri, Stefano
  • Setola, Roberto

Abstract

This paper describes an extension of the input–output inoperability model (IIM) that accommodates uncertain and vague data. In the resulting “fuzzy version” of the dynamic IIM model (FD-IIM), the level of inoperability of each infrastructure and the Leontief coefficients are specified using fuzzy variables that express expert knowledge about infrastructure interdependences. An important result is that, under certain conditions, solution convergence for the fuzzy model can be inferred based on the stability properties of the “crisp” (non-fuzzy) version of the system of interest. A case study involving the Italian critical infrastructure is used to demonstrate the feasibility and utility of the approach.

Suggested Citation

  • Oliva, Gabriele & Panzieri, Stefano & Setola, Roberto, 2011. "Fuzzy dynamic input–output inoperability model," International Journal of Critical Infrastructure Protection, Elsevier, vol. 4(3), pages 165-175.
    • Handle: RePEc:eee:ijocip:v:4:y:2011:i:3:p:165-175
    DOI: 10.1016/j.ijcip.2011.09.003
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1874548211000461
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ijcip.2011.09.003?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Setola, Roberto & De Porcellinis, Stefano & Sforna, Marino, 2009. "Critical infrastructure dependency assessment using the input–output inoperability model," International Journal of Critical Infrastructure Protection, Elsevier, vol. 2(4), pages 170-178.
    2. Kenneth G. Crowther & Yacov Y. Haimes & Gideon Taub, 2007. "Systemic Valuation of Strategic Preparedness Through Application of the Inoperability Input‐Output Model with Lessons Learned from Hurricane Katrina," Risk Analysis, John Wiley & Sons, vol. 27(5), pages 1345-1364, October.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Skorupski, Jacek & Uchroński, Piotr, 2017. "A fuzzy model for evaluating metal detection equipment at airport security screening checkpoints," International Journal of Critical Infrastructure Protection, Elsevier, vol. 16(C), pages 39-48.
    2. Olaf Jonkeren & Bogdan Dorneanu & Georgios Giannopoulos & David Ward, 2012. "Regional economic assessment of Critical Infrastructure failure in the EU: A combined systems engineering and economic model," ERSA conference papers ersa12p92, European Regional Science Association.
    3. Amine El Haimar & Joost R. Santos, 2014. "Modeling Uncertainties in Workforce Disruptions from Influenza Pandemics Using Dynamic Input‐Output Analysis," Risk Analysis, John Wiley & Sons, vol. 34(3), pages 401-415, March.
    4. Niknejad, Ali & Petrovic, Dobrila, 2016. "A fuzzy dynamic Inoperability Input–output Model for strategic risk management in Global Production Networks," International Journal of Production Economics, Elsevier, vol. 179(C), pages 44-58.
    5. 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.
    6. Rahmatallah Poudineh & Tooraj Jamasb, 2017. "Electricity Supply Interruptions: Sectoral Interdependencies and the Cost of Energy Not Served for the Scottish Economy," The Energy Journal, , vol. 38(1), pages 51-76, January.
    7. Heracleous, Constantinos & Kolios, Panayiotis & Panayiotou, Christos G. & Ellinas, Georgios & Polycarpou, Marios M., 2017. "Hybrid systems modeling for critical infrastructures interdependency analysis," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 89-101.
    8. Lam, C.Y. & Tai, K., 2018. "Modeling infrastructure interdependencies by integrating network and fuzzy set theory," International Journal of Critical Infrastructure Protection, Elsevier, vol. 22(C), pages 51-61.
    9. Sina Samimi & Sadoullah Ebrahimnejad & Mohammad Mojtahedi, 2020. "Analysis of the susceptibility of interdependent infrastructures using fuzzy input–output inoperability model: the case of flood hazards in Tehran," 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. 100(1), pages 69-88, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sellevåg, Stig Rune, 2021. "Changes in inoperability for interdependent industry sectors in Norway from 2012 to 2017," International Journal of Critical Infrastructure Protection, Elsevier, vol. 32(C).
    2. Cottafava, Dario & Gastaldo, Michele & Quatraro, Francesco & Santhiá, Cristina, 2022. "Modeling economic losses and greenhouse gas emissions reduction during the COVID-19 pandemic: Past, present, and future scenarios for Italy," Economic Modelling, Elsevier, vol. 110(C).
    3. Wenping Xu & Zongjun Wang & Liu Hong & Ligang He & Xueguang Chen, 2015. "The uncertainty recovery analysis for interdependent infrastructure systems using the dynamic inoperability input–output model," International Journal of Systems Science, Taylor & Francis Journals, vol. 46(7), pages 1299-1306, May.
    4. Maria Iglesias-Mendoza & Akilu Yunusa-Kaltungo & Sara Hadleigh-Dunn & Ashraf Labib, 2021. "Learning How to Learn from Disasters through a Comparative Dichotomy Analysis: Grenfell Tower and Hurricane Katrina Case Studies," Sustainability, MDPI, vol. 13(4), pages 1-18, February.
    5. Rahmatallah Poudineh and Tooraj Jamasb, 2017. "Electricity Supply Interruptions: Sectoral Interdependencies and the Cost of Energy Not Served for the Scottish Economy," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    6. Baghersad, Milad & Zobel, Christopher W., 2015. "Economic impact of production bottlenecks caused by disasters impacting interdependent industry sectors," International Journal of Production Economics, Elsevier, vol. 168(C), pages 71-80.
    7. Singh, Abhishek Narain & Gupta, M.P. & Ojha, Amitabh, 2014. "Identifying critical infrastructure sectors and their dependencies: An Indian scenario," International Journal of Critical Infrastructure Protection, Elsevier, vol. 7(2), pages 71-85.
    8. 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.
    9. Wang, Yanhui & Bi, Lifeng & Lin, Shuai & Li, Man & Shi, Hao, 2017. "A complex network-based importance measure for mechatronics systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 180-198.
    10. Å arÅ«nienÄ—, Inga & MartiÅ¡auskas, Linas & KrikÅ¡tolaitis, RiÄ ardas & Augutis, Juozas & Setola, Roberto, 2024. "Risk assessment of critical infrastructures: A methodology based on criticality of infrastructure elements," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    11. Rehak, David & Senovsky, Pavel & Hromada, Martin & Lovecek, Tomas & Novotny, Petr, 2018. "Cascading Impact Assessment in a Critical Infrastructure System," International Journal of Critical Infrastructure Protection, Elsevier, vol. 22(C), pages 125-138.
    12. Hassan Al-Zarooni & Hamdi Bashir, 2020. "An integrated ISM fuzzy MICMAC approach for modeling and analyzing electrical power system network interdependencies," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(6), pages 1204-1226, December.
    13. Petar Radanliev & David Roure & Max Kleek & Uchenna Ani & Pete Burnap & Eirini Anthi & Jason R. C. Nurse & Omar Santos & Rafael Mantilla Montalvo & La’Treall Maddox, 2021. "Dynamic real-time risk analytics of uncontrollable states in complex internet of things systems: cyber risk at the edge," Environment Systems and Decisions, Springer, vol. 41(2), pages 236-247, June.
    14. Argenti, Francesca & Landucci, Gabriele & Reniers, Genserik & Cozzani, Valerio, 2018. "Vulnerability assessment of chemical facilities to intentional attacks based on Bayesian Network," Reliability Engineering and System Safety, Elsevier, vol. 169(C), pages 515-530.
    15. Fang, Zhixiang & Shaw, Shih-Lung & Tu, Wei & Li, Qingquan & Li, Yuguang, 2012. "Spatiotemporal analysis of critical transportation links based on time geographic concepts: a case study of critical bridges in Wuhan, China," Journal of Transport Geography, Elsevier, vol. 23(C), pages 44-59.
    16. 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.
    17. Banerjee, Joydeep & Basu, Kaustav & Sen, Arunabha, 2018. "On hardening problems in critical infrastructure systems," International Journal of Critical Infrastructure Protection, Elsevier, vol. 23(C), pages 49-67.
    18. Oliva, Gabriele & Panzieri, Stefano & Setola, Roberto, 2010. "Agent-based input–output interdependency model," International Journal of Critical Infrastructure Protection, Elsevier, vol. 3(2), pages 76-82.
    19. Chiradip Chatterjee & Pallab Mozumder, 2014. "Understanding Household Preferences for Hurricane Risk Mitigation Information: Evidence from Survey Responses," Risk Analysis, John Wiley & Sons, vol. 34(6), pages 984-996, June.
    20. 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).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ijocip:v:4:y:2011:i:3:p:165-175. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/international-journal-of-critical-infrastructure-protection .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.