THE EFFECTIVENESS OF PARTIAL INFORMATION ABOUT ATTRIBUTE WEIGHTS FOR RANKING ALTERNATIVES IN MULTIATTRIBUTE DECISION-MAKING

Weighted additive evaluation functions are widely used to rank alternatives in decision making under certainty with multiple evaluation attributes. Some researchers have suggested that approximate attribute weights may be adequate to accurately rank alternatives. Use of approximate weights would simplify decision analysis since detailed elicitation of weights can be time consuming and controversial. This article investigates the degree to which partial information about the relative magnitudes of attribute weights is sufficient to rank alternatives as a function of the number of decision alternatives, the number of attributes, and the number of allowed levels for each attribute. A simulation analysis, as well as a reanalysis of an actual application, shows that partial information about weights is often not sufficient to determine the most preferred alternative for realistic decision problems. Hence, approximation procedures for specifying weights may lead to errors. However, our work also shows that a simple analysis procedure can be used to accurately determine whether partial information about weights is adequate to correctly specify the most preferred alternative. This procedure can be useful for identifying situations in which detailed elicitation of weights is not needed. © 1993 Academic Press, Inc.