The Probabilistic Weighted Average and Its Application in Multiperson Decision Making

摘要

We present the probabilistic weighted average (PWA). It is an aggregation operator that unifies the probability and the weighted average in the same formulation. Its main advantage is that it provides a formulation that it is able to deal with probabilities and weighted averages in the same formulation, considering the degree of importance that each concept has in the analysis. We extend this approach by using moving averages. We study some of its main properties, and we see that the applicability of the PWA is very broad because we can apply it in a wide range of fields including statistics, economics, and engineering. We focus on a multiperson decision-making application regarding the selection of fiscal policies. We see that with this approach we can unify decision-making problems under risk environment with subjective and objective information.