A proposed fixed-sum carryovers reallocation DEA approach for social scientific resources of Chinese public universities

• Published in: Scientometrics 2022-07, Vol.127 (7), p.4097-4121
• Main Authors: Xiong, Xi, Yang, Guo-liang, Liu, Kai-di, Zhou, De-qun
• Format: Article
• Language: English
• Subjects: Computer Science; Data envelopment analysis; Decision making; Education; Higher education institutions; Information Storage and Retrieval; Library Science; Optimization; Resource allocation
• ISSN: 0138-9130; 1588-2861
• DOI: 10.1007/s11192-022-04411-9

How to evaluate and optimize the allocative efficiency of multiple research resources is of great importance for decision-makers and has great practical application value. This is especially true in the case of unbalanced allocation and inefficient utilization of research resources in Chinese higher education institutions (HEIs). Data Envelopment Analysis (DEA) brings a new perspective on the resource allocation problem. However, the conventional paradigm of the resource allocation model in DEA assumes that inputs or outputs can be expanded freely when projecting decision-making units (DMUs) onto the efficient frontier. Thus, it is very difficult to deal with a situation where there is a trade-off between the evaluated units with the fixed-sum output. Considering a common resource allocation problem that occurs in multi-period activities where a carry-over indicator has the fixed-sum characteristic, we extend the study of Yang et al. (Eur J Oper Res 246(1):209–217, 2015) into a dynamic framework by taking the time dimension into account. The proposed approach is applied to reallocate the social scientific resources of Chinese HEIs from 2017 to 2019. The results show that all DMUs are in effective condition after reallocation and the optimal adjustments of newly approved projects can be obtained.