Abstract
A key component in the development of an additive multiattribute value model for selecting the best alternative is obtaining the attribute weights. In this paper, we assume the decision maker's weight information set consists of ranked swing weights, that is, a ranking of the importance of the attribute ranges, and in this context use ‘surrogate weights’ derived from this ranking. The particular surrogate weights are called ROC, for rank order centroid weights. The paper presents three sets of results: (1) a summary of the efficacy of using ROC weights to select a best alternative; (2) an extension of the method of analysis underlying the efficacy studies to assess the applicability of ROC weights for the analyst's specific value matrix; (3) methods for sensitivity analyses of a specific value matrix. A comprehensive example illustrates all analyses.
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