Decision Making under Deep Uncertainty : : From Theory to Practice.

• Author: Marchau, Vincent A. W. J.
• TeilnehmendeR: Walker, Warren E.; Bloemen, Pieter J. T. M.; Popper, Steven W.
• Place / Publishing House: Cham : : Springer International Publishing AG,, 2019.; ©2019.
• Year of Publication: 2019
• Edition: 1st ed.
• Language: English
• Physical Description: 1 online resource (408 pages)

Table of Contents

Intro -- Preface -- Acknowledgements -- Contents -- 1 Introduction -- 1.1 The Need for Considering Uncertainty in Decisionmaking -- 1.2 A Framework for Decision Support -- 1.3 Dealing with Uncertainty in Decisionmaking -- 1.4 Decisionmaking Under Deep Uncertainty -- 1.5 Generic Elements of DMDU Approaches-A Framework -- 1.6 An Introduction to the DMDU Tools and Approaches -- 1.7 Structure of the Book -- References -- DMDU Approaches -- 2 Robust Decision Making (RDM) -- 2.1 Introduction -- 2.2 RDM Foundations -- 2.3 RDM Process -- 2.4 Tools -- 2.5 Example: Carrots and Sticks for New Technology -- 2.5.1 Frame the Analysis -- 2.5.2 Perform Exploratory Uncertainty Analysis -- 2.5.3 Choose Initial Actions and Contingent Actions -- 2.5.4 Iterate and Re-Examine (RDM Steps 2, 3, and 5) -- 2.6 Recent Advances and Future Challenges -- References -- 3 Dynamic Adaptive Planning (DAP) -- 3.1 Introduction -- 3.2 The DAP Approach -- 3.3 A DAP Illustration: Strategic Planning for Schiphol Airport -- 3.4 Implementation and Adaptation -- 3.5 Conclusions -- References -- 4 Dynamic Adaptive Policy Pathways (DAPP) -- 4.1 Introduction -- 4.2 The DAPP Approach -- 4.3 A DAPP Illustration: Navigation along the Waas River -- 4.4 Under What Conditions Is This Approach Useful? -- 4.5 Recent Advances -- 4.6 Links with Other DMDU Approaches -- 4.7 Future Challenges -- References -- 5 Info-Gap Decision Theory (IG) -- 5.1 Info-Gap Theory: A First Look -- 5.2 IG Robustness: Methodological Outline -- 5.2.1 Three Components of IG Robust Satisficing -- 5.2.2 IG Robustness -- 5.2.3 Prioritization of Competing Decisions -- 5.2.4 How to Evaluate Robustness: Qualitative or Quantitative? -- 5.3 IG Robustness: A Qualitative Example -- 5.3.1 Five Conceptual Proxies for Robustness -- 5.3.2 Simple Qualitative Example: Nuclear Weapon Safety.

5.4 IG Robustness and Opportuneness: A Quantitative Example -- 5.4.1 IG Robustness -- 5.4.2 Discussion of the Robustness Results -- 5.4.3 IG Opportuneness -- 5.4.4 Discussion of Opportuneness Results -- 5.4.5 An Innovation Dilemma -- 5.4.6 Functional Uncertainty -- 5.5 Conclusion and Future Challenges -- References -- 6 Engineering Options Analysis (EOA) -- 6.1 Introduction -- 6.2 Methodology of Engineering Options Analysis -- 6.2.1 Setting the Scene -- 6.2.2 Definition of an Option -- 6.2.3 Main Steps of Analysis -- 6.2.4 Details of Each Step -- 6.3 A Simple Example: A Parking Garage -- 6.4 Contrasting Engineering Options Analysis with Real Options Analysis -- 6.4.1 Different Professional Contexts -- 6.4.2 Some Specific Differences -- 6.5 Contrasting Engineering Options Analysis with Other Approaches in This Book -- 6.5.1 Engineering Options Analysis as a Planning Approach -- 6.5.2 Engineering Options Analysis as a Computational Decision-Support Tool -- 6.6 Conclusions -- References -- DMDU Applications -- 7 Robust Decision Making (RDM): Application to Water Planning and Climate Policy -- 7.1 Long-Term Planning for Water Resources and Global Climate Technology Transfer -- 7.2 Review of Robust Decision Making -- 7.2.1 Summary of Robust Decision Making -- 7.3 Case Study 1: Using RDM to Support Long-Term Water Resources Planning for the Colorado River Basin -- 7.3.1 Decision Framing for Colorado River Basin Analyses -- 7.3.2 Vulnerabilities of Current Colorado River Basin Management -- 7.3.3 Design and Simulation of Adaptive Strategies -- 7.3.4 Evaluating Regret of Strategies Across Futures -- 7.3.5 Updating Beliefs About the Future to Guide Adaptation -- 7.3.6 Robust Adaptive Strategies, and Implementation Pathways -- 7.3.7 Need for Transformative Solutions -- 7.4 Case Study 2: Using RDM to Develop Climate Mitigation Technology Diffusion Policies.

7.4.1 Decision Framing for Climate Technology Policy Analysis -- 7.4.2 Modeling International Technological Change -- 7.4.3 Evaluating Policies Across a Wide Range of Plausible Futures -- 7.4.4 Key Vulnerabilities of Climate Technology Policies -- 7.4.5 Developing a Robust Adaptive Climate Technology Policy -- 7.5 Reflections -- References -- 8 Dynamic Adaptive Planning (DAP): The Case of Intelligent Speed Adaptation -- 8.1 Introduction to the Approach -- 8.2 Introduction to the Case -- 8.3 Reason for Choosing the DAP Approach -- 8.4 Methods for Applying DAP -- 8.5 Setting up a DAP Workshop on ISA Implementation -- 8.6 Results of the DAP-ISA Workshop -- 8.7 Evaluation of the DAP Approach -- 8.8 Lessons Learned About the Process of Developing Dynamic Adaptive Plans -- 8.9 Conclusions -- References -- 9 Dynamic Adaptive Policy Pathways (DAPP): From Theory to Practice -- 9.1 Introduction to the Case -- 9.2 Reason for Choosing DAPP -- 9.3 Setup of Approach for Case Study in Practice -- 9.4 Applying DAPP in Practice -- 9.5 Results of Applying the Approach -- 9.6 Reflections (Lessons Learned) for Practice and Theory -- References -- 10 Info-Gap (IG): Robust Design of a Mechanical Latch -- 10.1 Introduction -- 10.2 Application of Info-Gap Robustness for Policymaking -- 10.3 Formulation for the Design of a Mechanical Latch -- 10.4 The Info-Gap Robust Design Methodology -- 10.5 Assessment of Two Competing Designs -- 10.6 Concluding Remarks -- References -- 11 Engineering Options Analysis (EOA): Applications -- 11.1 Case Study 1: Liquid Natural Gas in Victoria State, Australia -- 11.2 Setup of the EOA Approach for the LNG Case Study -- 11.2.1 Design Alternatives -- 11.2.2 Parameter Values -- 11.2.3 Characterization of Sources of Uncertainty -- 11.3 Results from Applying the EOA Approach to the LNG Case Study -- 11.3.1 Fixed Design.

11.3.2 Performance of Fixed Design Under Uncertainty -- 11.3.3 Flexible Strategies -- 11.3.4 Flexible Strategy-Timing (But No Learning) -- 11.3.5 Flexible Strategy-Timing and Location (But No Learning) -- 11.3.6 Flexible Strategy-Learning -- 11.3.7 Learning Combined with Economies of Scale -- 11.3.8 Multi-criteria Comparison of Strategies -- 11.3.9 Guidance from Applying EOA to This Case -- 11.4 Case Study 2: Water Management Infrastructure in the Netherlands: IJmuiden Pumping Station -- 11.5 Setup of the EOA Approach for the IJmuiden Pumping Station -- 11.5.1 Characterization of Sources of Uncertainty -- 11.5.2 Design Alternatives -- 11.5.3 Details of the Analysis -- 11.6 Results from Applying the EOA Approach to the IJmuiden Pumping Station -- 11.6.1 Inland Water Level Regulation Function -- 11.6.2 Flood Defense Function -- 11.6.3 Guidance from Applying EOA to This Case -- 11.7 Conclusions and Reflections for Practice and Theory -- References -- DMDU-Implementation Processes -- 12 Decision Scaling (DS): Decision Support for Climate Change -- 12.1 Introduction -- 12.2 Technical Approach -- 12.2.1 Overview -- 12.2.2 Step 1. Decision Framing -- 12.2.3 Step 2. Climate Stress Test -- 12.2.4 Step 3. Estimation of Climate-Informed Risks -- 12.3 Case Study: Assessing Climate Risks to the Water Supply for Colorado Springs, Colorado, USA -- 12.3.1 Step 1: Decision Framing -- 12.3.2 Step 2: Climate Stress Test -- 12.3.3 Step 3. Estimation of Climate-Informed Risks -- 12.4 Conclusions -- References -- 13 A Conceptual Model of Planned Adaptation (PA) -- 13.1 Introduction -- 13.2 Planned Adaptation Cases -- 13.2.1 Particulate Matter Standards -- 13.2.2 Delta Management in the Netherlands -- 13.2.3 Air Transportation Safety -- 13.2.4 Internet Number Delegation -- 13.3 Generalizing Elements of Planned Adaptation -- 13.3.1 Disentangling Primary and Secondary Rules.

13.3.2 Triggers and Events -- 13.3.3 Evaluation -- 13.4 Conclusions and Ongoing Work -- 13.4.1 Combinations of Adaptive Capabilities -- 13.4.2 Planning and Designing for Adaptation -- 13.4.3 Implications for Future Study -- References -- 14 DMDU into Practice: Adaptive Delta Management in The Netherlands -- 14.1 Organizational Aspects of Putting a DMDU Approach into Practice -- 14.2 The Case Study: Adaptive Delta Management -- 14.3 Phase I: Prior to the Start of ADM (Politicization and De-politicization) -- 14.3.1 Build a Constituency for Change that Will Allow Political Commitments to Be Made -- 14.3.2 Develop Attractive and Plausible Perspectives: The Second Delta Committee -- 14.3.3 Enhance Public Awareness and Political Commitment -- 14.3.4 Stabilize Processes -- Build Trust and Continuity into the Structure of the programme -- 14.4 Phase II: Developing Strategies and Decisionmaking -- 14.4.1 Create a Narrative that Mobilizes Administrative and Political Decisionmakers -- 14.4.2 Involve All Parties in Developing an Approach for Dealing with Deep Uncertainty -- 14.4.3 Evaluate and Upgrade the Approach Regularly -- 14.4.4 Operationalize the DMDU Approach -- 14.5 Phase III: Elaborating, Implementing, and Adjusting Strategies -- 14.5.1 Plan the Adaptation -- 14.5.2 Organize the Adaptation -- 14.5.3 Rethink Monitoring and Evaluation -- 14.6 Conclusions, Reflections, and Outlook -- References -- DMDU-Synthesis -- 15 Supporting DMDU: A Taxonomy of Approaches and Tools -- 15.1 Introduction -- 15.2 Key Ideas -- 15.2.1 Exploratory Modeling -- 15.2.2 Adaptive Planning -- 15.2.3 Decision Support -- 15.3 A Taxonomy of Approaches and Tools for Supporting Decision Making Under Deep Uncertainty -- 15.3.1 Policy Architecture -- 15.3.2 Generation of Policy Alternatives and Generation of Scenarios -- 15.3.3 Robustness Metrics -- 15.3.4 Vulnerability Analysis.

15.4 Application of the Taxonomy.