How to allocate multi-period research resources? Centralized resource allocation for public universities in China using a parallel DEA-based approach

Abstract

In many real scenarios, all decision-making units (DMUs) fall under the umbrella of a central unit, such as banks, supermarkets and public universities, that has the power to supervise and control them. In such centralized decision-making circumstances, how to allocate fixed resources across DMUs when there is competition for resources has always been an important problem for managers. Data envelopment analysis (DEA) offers a new performance-based solution to resource allocation issues. In this paper, we propose a parallel DEA-based approach to reallocate multi-period resources among all DMUs by treating individual periods (e.g., years) as divisions operating at the parallel level. To balance the goals of the organization and the individual preferences of each DMU in resource allocation, we introduce the concept of cross-efficiency. Hence, we combined the operations of individual periods and the concept of cross-efficiency in one method simultaneously. Such allocations for multi-period resources are more acceptable by both the central manager and the evaluated DMUs. Finally, we assessed the R&D performance of each one of the 61 public universities in China and reallocated government funding resources among them.