Stochastic Dominance Decision Rules when the Attributes are Utility Independent
研究多属性风险决策中，在属性效用独立假设下，如何用随机占优规则比较不同选项，适用于风险厌恶等偏好，是单变量规则的直接扩展。
In multivariate decisions under risk, assessing the complete utility function can be a major obstacle. Decision rules are investigated which characterize uniformly better alternatives with respect to a whole class of utility functions. In this paper independence assumptions are imposed on the preference structure while the levels of attributes may be stochastically dependent in an arbitrary way. The utilities considered are additive, multiplicative, or multilinear. Necessary and sufficient conditions are developed for uniform decisions over utilities with common substitutional structure and where the univariate conditional utilities show qualitative properties such as risk aversion. The rules are direct extensions of known univariate rules and easy to evaluate.