It is often recognised that in real-life decision situations, classical utility theory puts too strong requirements on the decision-maker. Various interval approaches for decision making have therefore be. developed and these have been reasonably successful. However, a problem that sometimes appears in real-life situations is that the result of an evaluation still has an uncertainty about which alternative is to prefer. This is due to expected utility overlaps rendering discrimination more difficult;. In this article we discuss how adding second-order information may increase a decision-maker's understanding of a decision situation when handling aggregations of imprecise representations, as is the case in decision trees or influence diagrams.
QC 20140923