On the use of super-efficiency procedures for ranking efficient units and identifying outliers
- 399 Downloads
Prior research (Banker and Chang in Eur J Oper Res 175: 1311–1320, 2006) has found that super-efficiency based procedures are effective in identifying outliers, but not in ranking efficient units. In this paper, we investigate why the procedures failed to rank efficient units satisfactorily and examine the performance of super-efficiency procedures in different “regions” of production set. We find that the unsatisfactory results mainly originate from the “left corners” of DMUs, those units with relatively smaller values. We further examine the effect of different noise levels on outlier detection using the BG procedure (Banker and Gifford in A relative efficiency model for the evaluation of public health nurse productivity. Mimeo, Carnegie Mellon University, Pittsburgh, 1988). Our results show that the BG procedure is more effective when the noise level is high. We conduct extensive simulation experiments by considering different production functions (Cobb–Douglas and Polynomial), different DEA formulations (BCC and CCR) and different returns-to-scale (CRS and NIRS) assumptions. Our simulation results confirm that the findings in Banker and Chang (2006) are robust under different DEA formulations, production functions and returns to scale assumptions.
KeywordsDEA Super-efficiency Outlier identification Efficiency ranking Simulation study
- Banker, R. D., Das, S., & Datar, S. M. (1989). Analysis of cost variances for management control in hospitals. Research in Governmental and Nonprofit Accounting, 5, 269–291.Google Scholar
- Banker, R. D., & Gifford, J. L. (1988). A relative efficiency model for the evaluation of public health nurse productivity. Pittsburgh: Mimeo, Carnegie Mellon University.Google Scholar
- Charnes, A., & Neralic, L. (1992). Sensitivity analysis of the proportionate change of inputs (or outputs) in data envelopment analysis. Glasnik Matematicki, 27, 393–405.Google Scholar