This paper aims to develop an efficiency evaluation framework for higher education institutions (HEIs) that addresses the equitable allocation of shared central resources (e.g. energy, funding and infrastructure) across heterogeneous academic subunits to ensure sustainable governance and strategic planning.
The study proposes a disaggregated data envelopment analysis framework that decomposes HEIs into natural sciences and humanities/social sciences subunits. It uses a meta-frontier approach incorporating both convex and nonconvex technologies to endogenously determine shared resource allocation while accounting for regional operational variations among Chinese HEIs.
Empirical analysis reveals significant regional disparities, with institutions in eastern China exhibiting systematic efficiency advantages. The results demonstrate that accounting for internal heterogeneity and shared resource competition allows for more precise identification of managerial inefficiencies versus structural constraints, leading to differentiated improvement strategies for varying regional contexts.
This research advances the existing literature by explicitly modeling internal subunit heterogeneity and the mechanism of shared resource distribution. Unlike conventional models, it distinguishes managerial inefficiency from structural rigidity by relaxing convexity assumptions, providing a more realistic and data-driven tool for integrated resource management under binding constraints.
