An alternate method of deriving priorities and related inferences for group decision making in analytic hierarchy process

Some work has been carried out in the past on statistically deriving priorities in Analytic Hierarchy Process (AHP). In AHP, the aggregated worths of the alternatives, when compared with respect to several criteria, are estimated in a hierarchical comparisons model introduced by Saaty. In this setup, statistical models are used for Saaty’s method of scaling in paired comparisons experiments in any level of the hierarchy. At the end, the final priority weights of the alternatives and related inferences are developed with appropriate statistical methods. Existing statistical methods in the literature assume independence of the entries of the paired comparison matrix. However, these entries are highly dependent among themselves. In this article, we propose a statistical method that allows for the dependence among the entries of the pairwise comparisons matrix. The proposed method is then illustrated with a numerical example.