Data envelopment analysis and cross efficiency

Data Envelopment Analysis (DEA) has a widespread usage method for measuring and benchmarking relative efficiency of peer decision making units (DMUs) with multiple inputs and outputs. Beside of its widespread usage, DEA has some drawbacks, the most known of which is the unrealistic weight dispersion. Although this case is unreasonable and undesirable, unrealistic weight dispersion occurs, when some DMUs are rated as efficient because of input and output weights have the extreme or zero values. DMUs which have extreme values have potential to be a false positive.