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Scenario analysis: a review of methods and applications for engineering and environmental systems

Author

Listed:
  • Yousra Tourki

    (US Army Engineer Research and Development Center)

  • Jeffrey Keisler

    (University of Massachusetts)

  • Igor Linkov

    (US Army Engineer Research and Development Center
    US Army Corps of Engineers)

Abstract

Changing environment, uncertain economic conditions, and socio-political unrest have renewed interest in scenario analysis, both from theoretical and applied points of view. Nevertheless, neither the processes for scenario analysis (SA) nor evaluation criteria and metrics have been regularized. In this paper, SA-reported applications and implementation methodology are discussed in the context of an extensive literature review covering papers published between 2000 and 2010. Over 340 papers were identified through a series of queries in the web of science database. The papers were classified based on the North American Industrial Classification System and SA application goals (environmental, business, and social). SA methodology used in each paper was assessed based on four main criteria: coverage, consistency, uncertainty assessment, and efficiency. We find a significant increase in SA applications, especially in the environmental field. Theoretical developments in the field represent a small fraction of published studies and do not increase in time. The methods used to develop different scenarios vary widely across the academic literature and applications reviewed. Similarly, the methods and data used to characterize the scenarios and develop response strategies are extremely diverse and are limited by factors such as computational tractability and available time and resources. Based on this review, we recommend a regular process for scenario analysis that includes the steps of analysis, scenario definition, and evaluation.

Suggested Citation

  • Yousra Tourki & Jeffrey Keisler & Igor Linkov, 2013. "Scenario analysis: a review of methods and applications for engineering and environmental systems," Environment Systems and Decisions, Springer, vol. 33(1), pages 3-20, March.
  • Handle: RePEc:spr:envsyd:v:33:y:2013:i:1:d:10.1007_s10669-013-9437-6
    DOI: 10.1007/s10669-013-9437-6
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    References listed on IDEAS

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    Cited by:

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    3. Parker, Andrew M. & Srinivasan, Sinduja V. & Lempert, Robert J. & Berry, Sandra H., 2015. "Evaluating simulation-derived scenarios for effective decision support," Technological Forecasting and Social Change, Elsevier, vol. 91(C), pages 64-77.
    4. Thomas P. Bostick & Thomas H. Holzer & Shahryar Sarkani, 2017. "Enabling Stakeholder Involvement in Coastal Disaster Resilience Planning," Risk Analysis, John Wiley & Sons, vol. 37(6), pages 1181-1200, June.
    5. Qing’e Wang & Mengmeng Su & Lei Zeng & Huihua Chen, 2022. "A New Method to Assist Decision-Making of Water Environmental Emergency in Expressway Region," IJERPH, MDPI, vol. 19(16), pages 1-19, August.
    6. Vallet, Améline & Locatelli, Bruno & Levrel, Harold & Wunder, Sven & Seppelt, Ralf & Scholes, Robert J. & Oszwald, Johan, 2018. "Relationships Between Ecosystem Services: Comparing Methods for Assessing Tradeoffs and Synergies," Ecological Economics, Elsevier, vol. 150(C), pages 96-106.
    7. Hanna, Richard & Gross, Robert, 2021. "How do energy systems model and scenario studies explicitly represent socio-economic, political and technological disruption and discontinuity? Implications for policy and practitioners," Energy Policy, Elsevier, vol. 149(C).
    8. Papargyropoulou, Effie & Fearnyough, Kate & Spring, Charlotte & Antal, Lucy, 2022. "The future of surplus food redistribution in the UK: Reimagining a ‘win-win’ scenario," Food Policy, Elsevier, vol. 108(C).
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    10. Roland W. Scholz, 2017. "Managing complexity: from visual perception to sustainable transitions—contributions of Brunswik’s Theory of Probabilistic Functionalism," Environment Systems and Decisions, Springer, vol. 37(4), pages 381-409, December.

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