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This open access book focuses on both the theory and practice associated with the tools and approaches for decisionmaking in the face of deep uncertainty. It explores approaches and tools supporting the design of strategic plans under deep uncertainty, and their testing in the real world, including barriers and enablers for their use in practice. The book broadens traditional approaches and tools to include the analysis of actors and networks related to the problem at hand. It also shows how lessons learned in the application process can be used to improve the approaches and tools used in the design process. The book offers guidance in identifying and applying appropriate approaches and tools to design plans, as well as advice on implementing these plans in the real world. For decisionmakers and practitioners, the book includes realistic examples and practical guidelines that should help them understand what decisionmaking under deep uncertainty is and how it may be of assistance to them. Decision Making under Deep Uncertainty: From Theory to Practice is divided into four parts. Part I presents five approaches for designing strategic plans under deep uncertainty: Robust Decision Making, Dynamic Adaptive Planning, Dynamic Adaptive Policy Pathways, Info-Gap Decision Theory, and Engineering Options Analysis. Each approach is worked out in terms of its theoretical foundations, methodological steps to follow when using the approach, latest methodological insights, and challenges for improvement. In Part II, applications of each of these approaches are presented. Based on recent case studies, the practical implications of applying each approach are discussed in depth. Part III focuses on using the approaches and tools in real-world contexts, based on insights from real-world cases. Part IV contains conclusions and a synthesis of the lessons that can be drawn for designing, applying, and implementing strategic plans under deep uncertainty, as well as recommendations for future work.The publication of this book has been funded by the Radboud University, the RAND Corporation, Delft University of Technology, and Deltares.

Traditional policy analysis approaches are characterized by a focus on system modeling and choosing among policy alternatives. While successful in many cases, this approach has been increasingly criticized for being technocratic and ignoring the behavioral and political dimensions of most policy processes. In recent decades, increased awareness of the multi-actor, multiple perspective, and poly-centric character of many policy processes has led to the development of a variety of different perspectives on the styles and roles of policy analysis, and to new analytical tools and approaches – for example, argumentative approaches, participative policy analysis, and negotiation support. As a result, the field has become multi-faceted and somewhat fragmented. Public Policy Analysis: New Developments acknowledges the variety of approaches and provides a synthesis of the traditional and new approaches to policy analysis. It provides an overview and typology of different types of policy analytic activities, characterizing them according to differences in character and leading values, and linking them to a variety of theoretical notions on policymaking. Thereby, it provides assistance to both end users and analysts in choosing an appropriate approach given a specific policy situation. By broadening the traditional approach and methods to include the analysis of actors and actor networks related to the policy issue at hand, it deepens the state of the art in certain areas. While the main focus of the book is on the cognitive dimensions of policy analysis, it also links the policy analysis process to the policymaking process, showing how to identify and involve all relevant stakeholders in the process, and how to create favorable conditions for use of the results of policy analytic efforts by the policy actors.The book has as its major objective to describe the state-of-the-art and the latest developments in ex-ante policyanalysis. It is divided into two parts. Part I explores and structures policy analysis developments, the development and description of approaches to diagnose policy situations, design policy analytic efforts, and policy process conditions. Part II focuses on recent developments regarding models and modeling for policy analysis, placing modeling approaches in the context of the variety of conditions and approaches elaborated in Part I.