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首页> 外文期刊>European Journal of Operational Research >Comparing the predictive validity of alternatively assessed multi-attribute preference models when relevant decision attributes are missing
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Comparing the predictive validity of alternatively assessed multi-attribute preference models when relevant decision attributes are missing

机译:当相关决策属性缺失时,比较备选评估的多属性偏好模型的预测有效性

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Multi-attribute deision problems require that trade-offs between conflicting objectives be made when evaluating choice alternatives. To overcome the shortcomings inherent in unaided intuitive decision maker evaluations, decision theorists have prescribed formal procedure to improve decision making. Such procedures elicit a descriptive model of choice for the alternatives being considered. Although these procedures are founded on thebelieed that the subject's preference are well defined and error free, psychological studies have shown that errors do arise in the elicitation process. Thus, the formal preference elicitation procedure employed should be structurally capable of encoding meaningful preferences in the presence of these response errors. This study employs a simulated decision making environment to compare the predictive validity of alternatively assessed models when relevant attributes are omitted from the elicitation process and preference responses are not error free. The study found that meaningful preference predictions are sensitive to the elicitation procedure employed.
机译:多属性决策问题要求在评估选择方案时在相互矛盾的目标之间进行权衡。为了克服无助的直观决策者评估中固有的缺点,决策理论家已经规定了正式的程序来改进决策。这样的程序为所考虑的替代方案提供了描述性的选择模型。尽管这些程序建立在相信受试者的偏好定义明确且没有错误的基础上,但是心理学研究表明,在启发过程中确实会出现错误。因此,在存在这些响应错误的情况下,采用的形式偏好偏好程序应在结构上能够编码有意义的偏好。这项研究采用模拟决策环境,当启发过程中省略了相关属性并且偏好响应并非没有错误时,比较了替代评估模型的预测有效性。研究发现有意义的偏好预测对采用的启发程序很敏感。

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