IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v200y2024ics0040162523008351.html
   My bibliography  Save this article

Exploratory modelling and analysis to support decision-making under deep uncertainty: A case study from defence resource planning and asset management

Author

Listed:
  • Kahagalage, Sanath Darshana
  • Turan, Hasan Hüseyin
  • Elsawah, Sondoss
  • Gary, Michael Shayne

Abstract

Emerging approaches and tools in the literature for model-based decision support under deep uncertainty are rapidly growing. Exploratory modelling and analysis is one of the unifying ideas behind these approaches. This research leverages exploratory modelling and analysis in the context of a case study within defense resource planning for the Royal Australian Navy. We use a multi-method approach that combines exploratory modelling and analysis and a simulation model. Our research analyses a strategy from a deterministic optimization problem to assess the impact of uncertainties and to identify different model behaviours exhibited under uncertainties and the uncertainty space in which the strategy maintains reasonable performance. To achieve these objectives, we draw upon concepts from Robust Decision-Making, Behaviour-Based Scenario Discovery, and Feasible Scenario Space. The results are then analysed to derive decision-making insights and highlight the potential consequences of neglecting uncertainties. For the first time in defense resource planning, we compare the results from these three approaches and tools. These approaches and tools complement each other, leading to similar conclusions with unique insights. The results also reveal the misleading nature of considering the best approximate conditions in the predictive use of simulation models under deep uncertainty.

Suggested Citation

  • Kahagalage, Sanath Darshana & Turan, Hasan Hüseyin & Elsawah, Sondoss & Gary, Michael Shayne, 2024. "Exploratory modelling and analysis to support decision-making under deep uncertainty: A case study from defence resource planning and asset management," Technological Forecasting and Social Change, Elsevier, vol. 200(C).
    • Handle: RePEc:eee:tefoso:v:200:y:2024:i:c:s0040162523008351
    DOI: 10.1016/j.techfore.2023.123150
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162523008351
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.techfore.2023.123150?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. Steve Bankes, 1993. "Exploratory Modeling for Policy Analysis," Operations Research, INFORMS, vol. 41(3), pages 435-449, June.
    2. Stanton, Muriel C. Bonjean & Roelich, Katy, 2021. "Decision making under deep uncertainties: A review of the applicability of methods in practice," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    3. Steinmann, Patrick & Auping, Willem L. & Kwakkel, Jan H., 2020. "Behavior-based scenario discovery using time series clustering," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
    4. Christopher P. Weaver & Robert J. Lempert & Casey Brown & John A. Hall & David Revell & Daniel Sarewitz, 2013. "Improving the contribution of climate model information to decision making: the value and demands of robust decision frameworks," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 4(1), pages 39-60, January.
    5. Jan H. Kwakkel & Erik Pruyt, 2015. "Using System Dynamics for Grand Challenges: The ESDMA Approach," Systems Research and Behavioral Science, Wiley Blackwell, vol. 32(3), pages 358-375, May.
    6. Edward H. Bowman & Gary T. Moskowitz, 2001. "Real Options Analysis and Strategic Decision Making," Organization Science, INFORMS, vol. 12(6), pages 772-777, December.
    7. Walker, Warren E. & Rahman, S. Adnan & Cave, Jonathan, 2001. "Adaptive policies, policy analysis, and policy-making," European Journal of Operational Research, Elsevier, vol. 128(2), pages 282-289, January.
    8. Lin, Rung-Chuan & Sir, Mustafa Y. & Pasupathy, Kalyan S., 2013. "Multi-objective simulation optimization using data envelopment analysis and genetic algorithm: Specific application to determining optimal resource levels in surgical services," Omega, Elsevier, vol. 41(5), pages 881-892.
    9. Rabbani, M. & Heidari, R. & Yazdanparast, R., 2019. "A stochastic multi-period industrial hazardous waste location-routing problem: Integrating NSGA-II and Monte Carlo simulation," European Journal of Operational Research, Elsevier, vol. 272(3), pages 945-961.
    10. Kwakkel, J.H. & Cunningham, S.C., 2016. "Improving scenario discovery by bagging random boxes," Technological Forecasting and Social Change, Elsevier, vol. 111(C), pages 124-134.
    11. Jan H. Kwakkel, 2019. "A generalized many‐objective optimization approach for scenario discovery," Futures & Foresight Science, John Wiley & Sons, vol. 1(2), June.
    Full references (including those not matched with items on IDEAS)

    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. Moallemi, Enayat A. & Elsawah, Sondoss & Ryan, Michael J., 2020. "Robust decision making and Epoch–Era analysis: A comparison of two robustness frameworks for decision-making under uncertainty," Technological Forecasting and Social Change, Elsevier, vol. 151(C).
    2. Erik Pruyt & Jan H. Kwakkel, 2014. "Radicalization under deep uncertainty: a multi-model exploration of activism, extremism, and terrorism," System Dynamics Review, System Dynamics Society, vol. 30(1-2), pages 1-28, January.
    3. Hidayatno, Akhmad & Jafino, Bramka Arga & Setiawan, Andri D. & Purwanto, Widodo Wahyu, 2020. "When and why does transition fail? A model-based identification of adoption barriers and policy vulnerabilities for transition to natural gas vehicles," Energy Policy, Elsevier, vol. 138(C).
    4. Marchau, Vincent & Walker, Warren & van Duin, Ron, 2008. "An adaptive approach to implementing innovative urban transport solutions," Transport Policy, Elsevier, vol. 15(6), pages 405-412, November.
    5. B. Gersonius & J. Rijke & R. Ashley & P. Bloemen & E. Kelder & C. Zevenbergen, 2016. "Adaptive Delta Management for flood risk and resilience in Dordrecht, The Netherlands," 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. 82(2), pages 201-216, June.
    6. Turan, Hasan Hüseyin & Jalalvand, Fatemeh & Elsawah, Sondoss & Ryan, Michael J., 2022. "A joint problem of strategic workforce planning and fleet renewal: With an application in defense," European Journal of Operational Research, Elsevier, vol. 296(2), pages 615-634.
    7. Marjolijn Haasnoot & Hans Middelkoop & Astrid Offermans & Eelco Beek & Willem Deursen, 2012. "Exploring pathways for sustainable water management in river deltas in a changing environment," Climatic Change, Springer, vol. 115(3), pages 795-819, December.
    8. Moallemi, Enayat A. & Elsawah, Sondoss & Ryan, Michael J., 2020. "Strengthening ‘good’ modelling practices in robust decision support: A reporting guideline for combining multiple model-based methods," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 175(C), pages 3-24.
    9. Lempert Robert J., 2014. "Embedding (some) benefit-cost concepts into decision support processes with deep uncertainty," Journal of Benefit-Cost Analysis, De Gruyter, vol. 5(3), pages 487-514, December.
    10. Jan Kwakkel & Willem Auping, 2021. "Reaction: A commentary on Lustick and Tetlock (2021)," Futures & Foresight Science, John Wiley & Sons, vol. 3(2), June.
    11. Hamarat, Caner & Kwakkel, Jan H. & Pruyt, Erik, 2013. "Adaptive Robust Design under deep uncertainty," Technological Forecasting and Social Change, Elsevier, vol. 80(3), pages 408-418.
    12. Luciano Raso & Jan Kwakkel & Jos Timmermans, 2019. "Assessing the Capacity of Adaptive Policy Pathways to Adapt on Time by Mapping Trigger Values to Their Outcomes," Sustainability, MDPI, vol. 11(6), pages 1-16, March.
    13. Jan H. Kwakkel, 2019. "A generalized many‐objective optimization approach for scenario discovery," Futures & Foresight Science, John Wiley & Sons, vol. 1(2), June.
    14. Jan Kwakkel & Marjolijn Haasnoot & Warren Walker, 2015. "Developing dynamic adaptive policy pathways: a computer-assisted approach for developing adaptive strategies for a deeply uncertain world," Climatic Change, Springer, vol. 132(3), pages 373-386, October.
    15. Luciano Raso & Jan Kwakkel & Jos Timmermans & Geremy Panthou, 2019. "How to evaluate a monitoring system for adaptive policies: criteria for signposts selection and their model-based evaluation," Climatic Change, Springer, vol. 153(1), pages 267-283, March.
    16. Malekpour, Shirin & de Haan, Fjalar J. & Brown, Rebekah R., 2016. "A methodology to enable exploratory thinking in strategic planning," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 192-202.
    17. Steinmann, Patrick & Auping, Willem L. & Kwakkel, Jan H., 2020. "Behavior-based scenario discovery using time series clustering," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
    18. Warren E. Walker & Marjolijn Haasnoot & Jan H. Kwakkel, 2013. "Adapt or Perish: A Review of Planning Approaches for Adaptation under Deep Uncertainty," Sustainability, MDPI, vol. 5(3), pages 1-25, March.
    19. Reichardt, Kristin & Rogge, Karoline S. & Negro, Simona, 2015. "Unpacking the policy processes for addressing systemic problems: The case of the technological innovation system of offshore wind in Germany," Working Papers "Sustainability and Innovation" S2/2015, Fraunhofer Institute for Systems and Innovation Research (ISI).
    20. Guido A Veldhuis & Nico M de Reus & Bas MJ Keijser, 2020. "Concept development for comprehensive operations support with modeling and simulation," The Journal of Defense Modeling and Simulation, , vol. 17(1), pages 99-116, January.

    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:tefoso:v:200:y:2024:i:c:s0040162523008351. 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: http://www.sciencedirect.com/science/journal/00401625 .

    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.