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Collaborative scenario modeling in emergency management through cross-impact

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  • Bañuls, Victor A.
  • Turoff, Murray
  • Hiltz, Starr Roxanne

Abstract

In this paper we analyze how to apply cross-impact modeling for developing collaborative scenarios in Emergency Preparedness. Scenarios can enhance the understanding of emergency teams about the factors which are involved in the definition of an emergency plan and how different actors participate in it. The version of Cross-Impact Analysis described aims at contributing to this goal through allowing the collaborative development of scenarios out of large event sets. This ultimately reduces the complexity for estimating a working model. In order to illustrate this research effort hypothetical results of a dirty bomb attack scenario exercise are presented, along with the final estimates of relationships based on four rounds of individual estimates followed by discussion of differences in the perceived relationships, in order to achieve a “consensus” model. The purpose of this exercise is to demonstrate the ability of a group to create a working model of the scenario that may be used to examine the consequences of various assumptions about preparedness, plans, and the actions taken during the crisis situation. The method may be used as either a planning tool and/or a training tool. We discuss the process for collecting inputs from a collaborative group and how to improve the consistency of the group inputs in a Delphi-like feedback process. Suggestions for improving details of the wording of items in order to minimize misunderstandings and miscommunication are included, along with suggestions for future extensions to this research.

Suggested Citation

  • Bañuls, Victor A. & Turoff, Murray & Hiltz, Starr Roxanne, 2013. "Collaborative scenario modeling in emergency management through cross-impact," Technological Forecasting and Social Change, Elsevier, vol. 80(9), pages 1756-1774.
    • Handle: RePEc:eee:tefoso:v:80:y:2013:i:9:p:1756-1774
    DOI: 10.1016/j.techfore.2012.11.007
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    Cited by:

    1. Schubert, Johan & Moradi, Farshad & Asadi, Hirad & Luotsinen, Linus & Sjöberg, Eric & Hörling, Pontus & Linderhed, Anna & Oskarsson, Daniel, 2015. "Simulation-based decision support for evaluating operational plans," Operations Research Perspectives, Elsevier, vol. 2(C), pages 36-56.
    2. Cheng, M.N. & Wong, Jane W.K. & Cheung, C.F. & Leung, K.H., 2016. "A scenario-based roadmapping method for strategic planning and forecasting: A case study in a testing, inspection and certification company," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 44-62.
    3. Beiderbeck, Daniel & Frevel, Nicolas & von der Gracht, Heiko A. & Schmidt, Sascha L. & Schweitzer, Vera M., 2021. "The impact of COVID-19 on the European football ecosystem – A Delphi-based scenario analysis," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
    4. Xiaojiao Qiao & Dan Shi, 2019. "Risk Analysis of Emergency Based on Fuzzy Evidential Reasoning," Complexity, Hindawi, vol. 2019, pages 1-10, November.
    5. Zhang, Y. & Weng, W.G. & Huang, Z.L., 2018. "A scenario-based model for earthquake emergency management effectiveness evaluation," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 197-207.
    6. Merfeld, Katrin & Wilhelms, Mark-Philipp & Henkel, Sven & Kreutzer, Karin, 2019. "Carsharing with shared autonomous vehicles: Uncovering drivers, barriers and future developments – A four-stage Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 66-81.
    7. Jiansong Wu & Weipeng Fang & Xing Tong & Shuaiqi Yuan & Weiqi Guo, 2019. "Bayesian analysis of school bus accidents: a case study of China," 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. 95(3), pages 463-483, February.
    8. Turoff, Murray & Hiltz, Starr Roxanne & Bañuls, Víctor A. & Van Den Eede, Gerd, 2013. "Multiple perspectives on planning for emergencies: An introduction to the special issue on planning and foresight for emergency preparedness and management," Technological Forecasting and Social Change, Elsevier, vol. 80(9), pages 1647-1656.
    9. Guertler, Benjamin & Spinler, Stefan, 2015. "Supply risk interrelationships and the derivation of key supply risk indicators," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 224-236.
    10. D. Thorleuchter & D. Van Den Poel, 2013. "Semantic Compared Cross Impact Analysis," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 13/862, Ghent University, Faculty of Economics and Business Administration.
    11. Panula-Ontto, Juha & Luukkanen, Jyrki & Kaivo-oja, Jari & O'Mahony, Tadhg & Vehmas, Jarmo & Valkealahti, Seppo & Björkqvist, Tomas & Korpela, Timo & Järventausta, Pertti & Majanne, Yrjö & Kojo, Matti , 2018. "Cross-impact analysis of Finnish electricity system with increased renewables: Long-run energy policy challenges in balancing supply and consumption," Energy Policy, Elsevier, vol. 118(C), pages 504-513.
    12. Xie, Tian & Wei, Yao-yao & Chen, Wei-fan & Huang, Hai-nan, 2020. "Parallel evolution and response decision method for public sentiment based on system dynamics," European Journal of Operational Research, Elsevier, vol. 287(3), pages 1131-1148.
    13. Roland Broll & Gerald Blumberg & Christoph Weber, "undated". "Thesenpapier: Constructing Consistent Energy Scenarios using Cross Impact Matrices," EWL Working Papers 2005, University of Duisburg-Essen, Chair for Management Science and Energy Economics.
    14. Margherita, Alessandro & Elia, Gianluca & Klein, Mark, 2021. "Managing the COVID-19 emergency: A coordination framework to enhance response practices and actions," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    15. Yang, Zhen & Dong, Xiaobin & Guo, Li, 2023. "Scenario inference model of urban metro system cascading failure under extreme rainfall conditions," Reliability Engineering and System Safety, Elsevier, vol. 229(C).
    16. Barnes, Stuart J. & Mattsson, Jan, 2016. "Understanding current and future issues in collaborative consumption: A four-stage Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 104(C), pages 200-211.
    17. Rongchen Zhu & Xin Li & Xiaofeng Hu & Deshui Hu, 2019. "Risk Analysis of Chemical Plant Explosion Accidents Based on Bayesian Network," Sustainability, MDPI, vol. 12(1), pages 1-20, December.
    18. D. Thorleuchter & D. Van Den Poel, 2013. "Quantitative Cross Impact Analysis with Latent Semantic Indexing," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 13/861, Ghent University, Faculty of Economics and Business Administration.
    19. Panula-Ontto, J. & Piirainen, K.A., 2018. "EXIT: An alternative approach for structural cross-impact modeling and analysis," Technological Forecasting and Social Change, Elsevier, vol. 137(C), pages 89-100.
    20. Sebastian Hinderer & Leif Brändle & Andreas Kuckertz, 2021. "Transition to a Sustainable Bioeconomy," Sustainability, MDPI, vol. 13(15), pages 1-16, July.
    21. Panula-Ontto, Juha, 2019. "The AXIOM approach for probabilistic and causal modeling with expert elicited inputs," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 292-308.

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