finding an improved region of efficiency via dea-efficient hyperplanes

The analysis of efficiency is conducted for two vital purposes: firstly, in order to evaluate the current level of efficiency; secondly, to provide information on how to improve the level of efficiency, which is to provide benchmarking information. the inefficient decision making units (dmus) are usually able to improve their performance, and data envelopment analysis (dea) projections provide a prescription for improvement. however, sometimes, an inefficient dmu cannot move its performance toward the best practice by either decreasing its inputs or increasing its outputs. on the other hand, it can scarcely reach its efficient benchmark. this research suggests a method to find an improved region of efficiency through dea-efficient hyperplanes by providing an algorithm for detecting an improved efficiency path. in addition to the production of reasonable benchmarking information, the proposed algorithm provides the general requirements that satisfy the demands which every professional decision-maker should meet. finally, we provide a more detailed description of some new issues, extending the insights from this analysis of the benchmark region from the under-evaluated inefficient dmu. finally, numerical examples are provided to demonstrate the results of the analysis.