Add or Multiply? A Tutorial on Ranking and Choosing with Multiple Criteria

C. Tofallis
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引用次数: 87

Abstract

Simple additive weighting is a well-known method for scoring and ranking alternative options based on multiple attributes. However, the pitfalls associated with this approach are not widely appreciated. For example, the apparently innocuous step of normalizing the various attribute data in order to obtain comparable figures leads to markedly different rankings depending on which normalization is chosen. When the criteria are aggregated using multiplication, such difficulties are avoided because normalization is no longer required. This removes an important source of subjectivity in the analysis because the analyst no longer has to make a choice of normalization type. Moreover, it also permits the modelling of more realistic preference behaviour, such as diminishing marginal utility, which simple additive weighting does not provide. The multiplicative approach also has advantages when aggregating the ratings of panel members. This method is not new but has been ignored for too long by both practitioners and teachers. We aim to present it in a nontechnical way and illustrate its use with data on business schools.
加还是乘?多标准排序和选择教程
简单加性加权是一种众所周知的基于多个属性对备选选项进行评分和排序的方法。然而,与这种方法相关的陷阱并没有得到广泛的重视。例如,为了获得可比较的数字而对各种属性数据进行规范化这一看似无害的步骤,会导致根据选择哪种规范化而产生明显不同的排名。当使用乘法对标准进行聚合时,就避免了这些困难,因为不再需要规范化。这消除了分析中主观性的一个重要来源,因为分析人员不再需要选择规范化类型。此外,它还允许建模更现实的偏好行为,如边际效用递减,这是简单的加法加权无法提供的。乘法方法在汇总小组成员的评级时也有优势。这种方法并不新鲜,但被实践者和教师忽视了太长时间。我们的目标是以一种非技术的方式来呈现它,并用商学院的数据来说明它的使用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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