摘要：本文利用英国《泰晤士报高等教育增刊》2007年世界大学排名的原始数据，分别采用主成分分析、因子分析、TOPSIS法、秩和比法、灰色关联法、熵权法六种客观赋权法进行排序，然后比较了各种评价结果，并将这六种客观赋权评价结果与泰晤士报主观赋权评价结果进行了两两比较。研究发现：客观赋权法的评价结果无法得到公认，比较适用宏观分级评价；评价对象自身的差异程度会影响不同评价方法评价结果之间的一致性；在评价数据呈正态分布情况下，客观赋权法评价结果与权威主观评价结果相比，处于数据中间段的评价结果相差较大，而处于数据系列两端的评价对象会得到较为一致的评价；主客观赋权方法相结合是综合评价的发展方向。

Abstract: To see the difference among various objective weighting methods, the world 200 universities are re-ranked using the six methods, such as principal component analysis, factor analysis, TOPSIS, rank sum ratio, grey system, and entropy weight based on 2007 Times world university ranking data originally given by Times Higher Eduation Supplement, then the new rankings are compared with Times rankings. The results show that objective weighting can’t be ensured entirely. Evaluation objects sitting in middle range of data series would get bigger ranking difference than those sitting on the two ends of data series when using different evaluation methods if the data present the normal distribution. Objective evaluation methods seem more appropriate to attribute evaluated institutes into macro-scale rough categories. The gap between evaluated institutes affects the agreement among different objective evaluation results. The future trend seems to conduct more assessment exercises which combine subjective weighting methods with objective weighting methods.