Multivariate approach to imposing additional constraints on the Benefit-of-the-Doubt model: The case of QS World University Rankings by Subject

Abstract

Composite indexes have become a valuable asset for stakeholders as they provide ranks of entities and information upon which decisions are made. However, certain questions about their development procedure have been raised recently, especially regarding the weighting process. To tackle the observed issue, in this paper we propose a new multivariate approach for defining weights. Namely, the model based on the Data Envelopment Analysis (DEA), the Benefit-of-the-Doubt (BoD) model, has been used with significant success in the process of composite index development. On the other hand, the Composite I-distance Indicator (CIDI) methodology stands out as an impartial method for assigning weights to indicators. By combining these two approaches, some of the limitations of the original BoD model could be overcome. As a result, new entity-specific weights which maximize the value of the composite index can be proposed. As a case study, we analysed the Quacquarelli Symonds (QS) World University Rankings by Subject in the field of statistics and operational research. The obtained results, which are based on the data-driven weights, can provide new insights into the nature of the observed ranking. The approach presented here might provoke further research on the topic of composite index weights and on the university rankings by subject.

Keywords

• benefit-of-doubt model
• composite i-distance indicator (cidi)
• operational research
• university rankings by subject