Deciding how to decide under uncertainty: A methodology map to address decision- making under uncertainty

This paper presents a methodology map built on a thorough comparison of approaches that can be used to address decision-making under uncertainty based on the level of uncertainty considered. The methodology map is provided to help researchers and practitioners on the selection of the most convenient approach for their specific context. An overview of different approaches for decision-making under uncertainty is provided. Approaches are then compared to each other, where requirements, limits, pros, cons and different circumstances under which each approach is more appropriate are discussed. Four different approaches are studied, the cost-benefit analysis (CBA), Probabilistic decision tree (PDT), Robust decision-making (RDM), and Dynamic adaptation policy pathway (DAPP). Results show that different considerations are expected to rule the selection process. It should depend on the problem in-hand (e.g. type of uncertainty, the number of alternatives) and enclose a rationale that addresses its limitations (e.g. available time, fund). The developed work is expected to support researchers and practitioners in the selection of convenient approaches to inform decision-making based on available knowledge, with awareness of the implications of the selected approach over the final output that will support holistic decisions.