Optimizing university restructuring for targeted knowledge output: A preliminary evaluation of Chinese university mergers incorporating preferences

Abstract

Chinese universities have experienced a significant wave of mergers since the late 1990s, raising questions about the impact of such consolidation on the knowledge output efficiency and economies of scale and scope in higher education. In this study, we propose a nonparametric model that takes into account specific output preferences during a preliminary evaluation of merger proposals. Additionally, our model addresses the challenges related to the existence of infeasible solutions that have been highlighted in related literature. Empirical analysis using a sample of Chinese research universities suggests that the current number of universities is below optimal in most provinces regardless of the type of knowledge outcome used to assess university performance. This suggests that further university mergers are unnecessary in these regions. However, multiple beneficial merger scenarios still exist in the provinces of Guizhou and Gansu. In Guizhou, some merger plans could lead to efficiency gains when scholarly publications are used as the knowledge outcome, while in Gansu, several consolidation scenarios show potential gains when research projects serve as outputs. Moreover, we found evidence of widespread diseconomies of scale across most merger scenarios along with relatively modest economies of scope within these two provinces.