Most often, important decisions involve several unknown attributes. This pro- duces a double challenge in the sense that both assessing the individual multiattribute pre- ferences and assessing the joint distribution of the attributes can be extremely hard. To handle the first challenge, we suggest multivariate almost stochastic dominance, a relation based on bounding marginal utilities. We provide necessary and sufficient characteriza- tions in terms of simple transfers, which are easily communicated to decision makers and, thus, can be used for preference elicitation. To handle the second challenge, we develop sufficient conditions that do not consider the dependence structure and are based on either marginal distributions of the attributes or just their means and variances. We apply the the- oretical results to a case study of comparing the efficiency of photovoltaic plants.
Multivariate almost stochastic dominance: transfer characterizations and sufficient conditions under dependence uncertainty / Müller, Alfred; Scarsini, Marco; Tsetlin, Ilia; Winkler, Robert L.. - In: OPERATIONS RESEARCH. - ISSN 0030-364X. - (In corso di stampa), pp. 1-15. [10.1287/opre.2022.0596]
Multivariate almost stochastic dominance: transfer characterizations and sufficient conditions under dependence uncertainty
Scarsini, Marco;
In corso di stampa
Abstract
Most often, important decisions involve several unknown attributes. This pro- duces a double challenge in the sense that both assessing the individual multiattribute pre- ferences and assessing the joint distribution of the attributes can be extremely hard. To handle the first challenge, we suggest multivariate almost stochastic dominance, a relation based on bounding marginal utilities. We provide necessary and sufficient characteriza- tions in terms of simple transfers, which are easily communicated to decision makers and, thus, can be used for preference elicitation. To handle the second challenge, we develop sufficient conditions that do not consider the dependence structure and are based on either marginal distributions of the attributes or just their means and variances. We apply the the- oretical results to a case study of comparing the efficiency of photovoltaic plants.File | Dimensione | Formato | |
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