任务属性在确定多属性加权技术的相对有效性中的作用

Leonard Adelman, Paul J. Sticha, Michael L. Donnell
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引用次数: 25

摘要

大多数比较多属性加权技术相对有效性的研究发现差异不大。然而,这些研究未能系统地改变属性属性,如属性的数量和正确属性权重的分布。假设由于信息处理需求的减少,任何加权技术在得到正确的权重时都越有效。此外,假设不同加权技术的相对有效性取决于正确属性权重分布的峰值,因为不同的加权技术应该比其他技术产生更多的峰值分布。为了验证这些假设,进行了两个实验。第一个实验关注的是个体赋予属性权重的准确性;第二个是关于分组的准确性。两个实验都证实了关于属性数量的第一个假设,但只有第一个实验证实了关于属性权重分布的峰性的第二个假设。
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The role of task properties in determining the relative effectiveness of multiattribute weighting techniques

Most studies comparing the relative effectiveness of multiattribute weighting techniques have found few differences. These studies have, however, failed to systematically vary attribute properties such as number of attributes and distribution of correct attribute weights. It was hypothesized that any weighting technique would be more effective at arriving at the correct weights the smaller the number of attributes because of lessened information processing requirements. In addition, it was hypothesized that the relative effectiveness of different weighting techniques would depend on the peakedness of the distribution of correct attribute weights because different weighting techniques should generate more peaked distributions than others. Two experiments were conducted to test these hypotheses. The first experiment focused on the accuracy of the weights assigned to attributes by individuals; the second on the accuracy of groups. Both experiments confirmed the first hypothesis regarding the number of attributes, but only the first experiment confirmed the second hypothesis regarding the peakedness of the distribution of attribute weights.

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