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Measuring Agreement Among Ranks: Sustainability Application

机译:等级之间的衡量标准:可持续性应用

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摘要

Is it possible to compare rankings from different sources when the individual rankings of the top x elements differ? To investigate this question, 2015 sustainable rankings from 4 sources that have ranked the top globally most sustainable corporations are considered (Corporate Knights, Fortune's World's Most Admired Companies, Newsweek's Green Rankings, and Harris). These rankings are analyzed using common rank comparison methods (Spearman's ρ, Kendall's τ). Then, they are analyzed to see if the sources ranking the data are doing so at random or if there is a specific pattern of agreement (Kendall's W and a method by Alvo, Cabilio & Feigin (1982)). The insights from these methods as well as possible limitations are considered. A truly sustainable corporation would transcend all definitions and be good for the environment and the people relying on the company. This paper will attempt to identify data points that tend to cluster close together in one or more groups, thereby justifying the feasibility of identifying sets of companies that are truly the "most" sustainable.
机译:当顶部x个元素的各个排名不同时,是否可以比较不同来源的排名?为了调查该问题,我们考虑了来自4个来源的2015年可持续发展排名,这些来源在全球最具可持续性的公司中排名最高(企业骑士团,《财富》杂志全球最受尊敬的公司,《新闻周刊》绿色排名和哈里斯)。使用常见的排名比较方法(Spearman的ρ,Kendall的τ)来分析这些排名。然后,对它们进行分析,以查看对数据进行排名的来源是否是随机进行的,或者是否存在特定的协议模式(Kendall's W和Alvo,Cabilio和Feigin的方法(1982年))。这些方法的见解以及可能的局限性都在考虑之列。一个真正的可持续发展的公司将超越所有定义,对环境和依赖公司的人民有利。本文将尝试确定倾向于聚集在一起的一个或多个组的数据点,从而证明确定真正“可持续”程度最高的公司的可行性。

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