Climbing university rankings under resources constraints: a combined approach integrating DEA and directed Louvain community detection
提出一种结合数据包络分析和有向Louvain社区检测的方法，基于财务资源为大学设定现实排名目标，识别财务优化标杆，帮助政策制定者和大学管理者在资源有限时提升排名。
Abstract 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.