Judgmental consistency and consensus in stochastic multicriteria decision making
Stochastic multicriteria decision making methods are a class of multicriteria decision making methods in which judgments are not taken to be certain. Recently, this class of models has generated increasing interest in the literature. We unify the notions of judgmental consistency and intra-group consensus under a framework of preference homogeneity in the context of this class of models. We propose new methods and measures for examining departures from consistency by using the KullbackLeibler divergence. We also propose a new method, the jackknifed KullbackLeibler divergence, that characterizes the extent to which a group member exhibits preference consensus with the remaining members of the group.
kullbackleibler divergence inconsistency bayesian inference group decision making