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Eigen weight vectors and least-distance approximation for revealed preference in pairwise weight ratios. (English) Zbl 0552.90050

A new eigenweight vector is derived for the data of pairwise weight ratios. The well-known eigenweight vector derived by T. L. Saaty [”The analytic hierarchy process”, New York (1980)] is then compared and contrasted in the light of least-distance approximation models. It is shown that the new eigenweight vector commands advantages over saaty’s, including less rigid assumptions on the error terms, robustness of solution, in addition to the fact that the new eigenweight vector can be computed very easily. The reader can construct other types of eigenweight vectors and least-distance approximation models using the framework of this article.

MSC:

90B50 Management decision making, including multiple objectives
91B06 Decision theory
91B08 Individual preferences
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References:

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