评估信用申请:多属性效用权重引出技术的验证

William G. Stillwell, F.Hutton Barron, Ward Edwards
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引用次数: 49

摘要

多属性效用度量(MAUM)提供了一套工具和程序,旨在帮助决策者在面对复杂和模糊的决策问题时,不借助辅助,直观的判断很可能导致选择次优方案。验证MAUM程序的尝试主要有三种类型:(1)对公理系统进行行为测试,这些公理系统来自于关于什么构成合理行为的假设;(2)收敛验证,对不同程序甚至不同主体的结果进行比较;(3)标准验证,将判断及其结果与某些外部标准进行比较。从行为的角度来看,最后一点,标准有效性,是迄今为止最强的。过去在MAUM标准验证方面的努力受到三个限制:受试者不是专家,没有比较不同的体重引出程序,每种情况下使用的标准的强度都有问题。本实验的目的是在提供有意义的外部标准以及使用该标准的专家的情况下,对许多可选的maumm权重引出程序进行经验比较。高质量的决策来自于对所有权重提取程序作出的权重判断,只要单个维度首先被单独缩放,然后加权进行汇总。一个程序,其中的备选方案被评为整体和权重和单维效用函数派生统计显示较差的质量决策。因此,“分而治之”的主题得到了维护。
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Evaluating credit applications: A validation of multiattribute utility weight elicitation techniques

Multiattribute Utility Measurement (MAUM) provides a set of tools and procedures that are designed to aid the decision maker who is faced with decision problems of such complexity and ambiguity that unaided, intuitive judgment is likely to lead to the selection of suboptimal alternatives. Attempts to validate MAUM procedures have been primarily of three types: (1) behavioral tests of axiom systems derived from assumptions about what constitutes reasonable behavior; (2) convergent validation, in which the results of different procedures or even different subjects are compared; and (3) criterion validation, in which judgments and their resultant decisions are compared with some external criterion. From a behavioral point of view, the last of these, criterion validity, is by far the strongest. Past efforts at criterion validation of MAUM have suffered from three limitations: the subjects were not experts, alternative weight elicitation procedures were not compared, and the strength of the criterion used in each case is open to question. The purpose of this experiment was to provide an empirical comparison of a number of alternative MAUM weight elicitation procedures in a situation that offered a meaningful external crtierion along with subjects expert in its use. High quality decisions resulted from weight judgments provided in response to all weight elicitation procedures as long as single dimensions were first individually scaled and then weighted for aggregation. A procedure in which alternatives were rated holistically and weights and single dimension utility functions derived statistically showed poorer quality decisions. Thus, the “divide and conquer” theme of MAUM was upheld.

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