Steven W. Popper(editor)
Steven W. Popper (RAND Corporation) is a RAND Senior Economist and professor of science and technology policy in the Pardee RAND Graduate School. His work on macro transitions led to an invitation by President Vaclav Havel to advise the government of Czechoslovakia, participation in an OECD delegation on the first foreign visit to one of the secret cities of the former Soviet Union, and consultation to the World Bank on issues of industrial restructuring in Hungary and in Mexico. His work on micro-level transition focuses on innovation. From 1996 to 2001 he was the Associate Director of the Science and Technology Policy Institute, providing analytic support to the White House Office of Science and Technology Policy and other executive branch agencies. He has taught planning under deep uncertainty at the Pardee RAND Graduate School, the India School of Business, and the Shanghai Climate Institute. He is co-developer of the Robust Decision Making (RDM) approach. He is an elected a Fellow of the American Association for the Advancement of Science, served as chair of the AAAS Industrial Science and Technology section and is the founding chair for education and training of the Society for Decision Making under Deep Uncertainty.Steven W. Popper (RAND Corporation) is a RAND Senior Economist and professor of science and technology policy in the Pardee RAND Graduate School. His work on macro transitions led to an invitation by President Vaclav Havel to advise the government of Czechoslovakia, participation in an OECD delegation on the first foreign visit to one of the secret cities of the former Soviet Union, and consultation to the World Bank on issues of industrial restructuring in Hungary and in Mexico. His work on micro-level transition focuses on innovation. From 1996 to 2001 he was the Associate Director of the Science and Technology Policy Institute, providing analytic support to the White House Office of Science and Technology Policy and other executive branch agencies. He has taught planning under deep uncertainty at the Pardee RAND Graduate School, the India School of Business, and the Shanghai Climate Institute. He is co-developer of the Robust Decision Making (RDM) approach. He is an elected a Fellow of the American Association for the Advancement of Science, served as chair of the AAAS Industrial Science and Technology section and is the founding chair for education and training of the Society for Decision Making under Deep Uncertainty.
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Steven W. Popper (RAND Corporation) is a RAND Senior Economist and professor of science and technology policy in the Pardee RAND Graduate School. His work on macro transitions led to an invitation by President Vaclav Havel to advise the government of Czechoslovakia, participation in an OECD delegation on the first foreign visit to one of the secret cities of the former Soviet Union, and consultation to the World Bank on issues of industrial restructuring in Hungary and in Mexico. His work on micro-level transition focuses on innovation. From 1996 to 2001 he was the Associate Director of the Science and Technology Policy Institute, providing analytic support to the White House Office of Science and Technology Policy and other executive branch agencies. He has taught planning under deep uncertainty at the Pardee RAND Graduate School, the India School of Business, and the Shanghai Climate Institute. He is co-developer of the Robust Decision Making (RDM) approach. He is an elected a Fellow of the American Association for the Advancement of Science, served as chair of the AAAS Industrial Science and Technology section and is the founding chair for education and training of the Society for Decision Making under Deep Uncertainty.
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Decision Making under Deep Uncertainty: From Theory to Practice
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.
