The use of international university rankings is an internationally recognized way of evaluating higher education systems and institutions. The QS ranking is one of the best-known among them, and it ranks institutions along six indicators. This study has two objectives. We first examine how the QS ranking and the university rankings derived from the variables obtained from the Scopus/SciVal database by the TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) ranking procedure relate to each other. We find that the QS ranking and the ranking obtained with the Scopus/SciVal data show strong similarity. The second goal was to test the place of the countries on the ranking. A comparison of universities from countries on the QS ranking led to the conclusion that the top-ten ranked countries were mainly smaller Western European countries as well as two city-states from the Far East. Our analysis can be considered somewhat unique as the method for calculating the data determining the QS rankings is not always available on the QS website, so the ranking cannot be repeated. In addition, the ranking results are only available once a year, so only the results of the most recent QS measurement are available between the two dates.

中文翻译：

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基于 Scopus 和 SciVal 数据的 QS 排名的可预测性

使用国际大学排名是国际公认的评估高等教育系统和机构的方式。QS排名是其中最著名的排名之一，它根据六个指标对机构进行排名。本研究有两个目标。我们首先检查 QS 排名和大学排名如何通过 TOPSIS（通过与理想解决方案相似度的优先顺序技术）从 Scopus/SciVal 数据库中获得的变量得出的排名程序相互关联。我们发现 QS 排名和使用 Scopus/SciVal 数据获得的排名表现出很强的相似性。第二个目标是测试这些国家在排名中的位置。对 QS 排名中各国大学的比较得出的结论是，排名前十的国家主要是较小的西欧国家以及两个远东城市国家。我们的分析可以被认为有些独特，因为计算确定 QS 排名的数据的方法并不总是在 QS 网站上可用，因此不能重复排名。此外，排名结果一年只提供一次，因此在两个日期之间只能提供最近一次的 QS 测量结果。