"Low carbon energy R&D portfolios: Finding common ground when experts and models disagree"
Inspired by challenges in designing energy technology policy in the face of climate change, we introduce an approach we call Robust Portfolio Decision Analysis, building on Belief Dominance as a prescriptive operationalization of a concept that has appeared in the literature under a number of names. The Belief Dominance concept synthesizes multiple conflicting sources of information to uncover alternatives that are intelligent responses in the presence of many beliefs or models. We use this concept to determine the set of non-dominated portfolios and to identify corresponding robust individual alternatives, thereby uncovering viable alternatives that may not be revealed otherwise. Using multiple large scale expert elicitation studies and multiple Integrated Assessment Models, we illustrate how Robust Portfolio Decision Analysis helps identify robust R&D investments into individual technologies.
Erin Baker is the Chair of Faculty Diversity at the College of Engineering; and Professor of Industrial Engineering and Operations Research at University of Massachusetts, Amherst. She is the Director of the Wind Energy Fellows, and the Faculty Director of the Energy Transition Institute, which is focused on stakeholder-engaged research at the intersection of energy and technology. She has a Ph.D. in Engineering-Economic Systems & Operations Research from the department of Management Science and Engineering at Stanford University, and a B.A. in Mathematics from U.C. Berkeley. She is an Associate Editor at IISE Transactions and Decision Analysis. Her research is in decision making under uncertainty applied to the field of energy and the environment; with focus on energy justice and publicly-funded energy technology Research and Development portfolios in the face of climate change. Her work appears in leading academic journals including Science, Nature Energy, Operations Research, Management Science, and Climatic Change. Her current work uses modeling to address questions about energy policy and planning in the face of climate change. She links models to bridge geographic and temporal scales, and uses multiple parallel models to derive robust insights.
