Decision maps: A framework for multi-criteria decision support under severe uncertainty

a r t i c l e i n f o In complex strategic decision-making situations the need for well-structured support arises. To evaluate decision alternatives, information about the situation and its development must be determined, managed and processed by the best available experts. For various types of information different reasoning principles have been developed: deterministic, probabilistic, fuzzy and techniques for reasoning under ignorance (i.e., the likelihood of an event cannot be quantified). We propose a new approach based on Decision Maps supporting decision makers under fundamental uncertainty by generating descriptions of different possible situation developments (scenarios) in a distributed manner. The scenarios are evaluated using Multi-Criteria Decision Analysis techniques. In complex strategic decision-making situations often decisions among a finite set of feasible alternatives respecting multiple conflicting objectives must be made [3]. Multi-Criteria Decision Analysis (MCDA) supports decision makers in these situations [77], as it allows for a transparent evaluation of alternatives. Yet, the use of MCDA can be problematic when uncertainties are significant [22]. Uncertainties, however, play an important role in most strategic decision-making situations, as information is often imprecise, uncertain or lacking [50]. Decision-making is particularly challenging when severe uncertainties forestalling to judge and quantify the likelihood of relevant events persist [4]. To describe and operationalise a lack of knowledge, this paper adopts the terminology introduced by Knight [41], which is still commonly used in today's decision theory (e.g., [14,50,57]). The terms risk, uncertainty and ignorance have the following precise meanings: • In decisions under risk the decision makers know the probability of the possible outcomes. • In decisions under ignorance these probabilities are either unknown or non-existent. • Uncertainty is used as a broad term referring to both risk and ignorance. In this thesis, the latter definition is used. Scenarios offer a possibility to deal with severe uncertainties as they explore fundamentally different descriptions of a situation and its possible developments [65]. Being plausible, consistent and coherent [64], scenarios appeal to decision makers and help in overcoming cognitive biases such as overconfidence or misjudgement of likelihoods [79]. To construct scenarios describing a large and complex decision problem, knowledge and expertise from various domains have to be brought together [50,68]. In this paper a new approach for decision support under heterogeneous types of uncertainty in distributed settings is presented. Decision Maps, a new framework facilitating scenario construction and assessment with MCDA techniques combine Directed Acyclic Graphs (DAGs) used …