A modified DDF-based super-efficiency model handling negative data

Super-efficiency model in the presence of negative data is a relatively neglected issue in the DEA field. The existing super-efficiency models have some shortcoming in practice. In this paper, the radial super-efficiency model based on Directional Distance Function (DDF) is modified to provide a complete ranking order of the DMUs (including efficient and inefficient DMUs). This model shows more reliability on differentiating efficient DMUs from inefficient ones via a new super-efficiency measure. The properties of proposed model include feasibility, monotonicity and unit invariance. Moreover, the model can produce positive outputs when data are non-negative. An empirical study in bank sector demonstrates the superiority of the proposed model