Abstract
One of the more useful tools in decision analysis is the risk less, additive multi-attribute utility (MAU) model. The most difficult task in the application of MAU models is that of estimating the importance weight parameters. Two general approaches to the weight estimation problem are reviewed in this paper: direct subjective estimation and indirect holistic estimation. Various methods for directly assessing importance weights are catalogued, including ranking, fractionation, subjective- estimate methods and paired- comparison procedures, and their relationship to one another is discussed.