Climbing university rankings under resources constraints: a combined approach integrating DEA and directed Louvain community detection

Over recent years, scholarly interest in universities' allocation and effective utilisation of financial resources has been growing. When used efficiently, financial resources may improve universities' quality of research and teaching, and therefore their positions in world university rankings. However, despite the relevance of financial efficiency to university placement in academic rankings, universities' total available financial resources appear much more significant. In the present study, we propose an innovative methodology to determine realistic ranking targets for individual universities, based on their available financial resources. In particular, we combine data envelopment analysis, as developed by Banker et al. (Manag Sci 30(9):1078-1092, 1984), and a directed Louvain community detection algorithm to examine 318 universities across five countries, considering their ARWU scores alongside key financial indicators (i.e., long-term physical capital, total operating revenues). We identify clusters of universities with similar financial profiles and corresponding ARWU scores, as well as universities that have optimised their use of financial resources, representing benchmarks for similar universities to emulate. The approach is subsequently applied to Italian universities, as a specific national case. The findings may be useful for policy makers and university managers seeking reliable strategies for climbing academic rankings, particularly in countries with limited public investment in higher education.