Radial Efficiency Measures in Data

Data envelopment analysis (DEA) is a non-parametric mathematical programming methodology used to not only evaluate the relative efficiencies of comparable decision making units (DMUs) with multiple inputs and outputs, but also provide efficiency targets for the DMUs. For a visualization of this method, see Figure 1. Since the incept of Charnes, Cooper and Rhodes (1978), DEA has gained increasing popularity in theoretical and applied work. Cooper, Seiford and Tone (2006) provided an in-depth coverage of various DEA models. Cook and Seiford (2009) provided a sketch of the major research thrusts in DEA. Examples of the DMUs used in real-world DEA applications include manufacturing firms, financial firms, and departments of organizations such as bank branches, hospitals, universities, schools and business firms, as well as regions and countries. Depending on whether inputs or outputs are discretionary or controllable input-oriented or output-oriented radial models can be employed. Both orientations are described in terms of radial efficiency measures as follows: • Input orientation refers to the emphasis on the evaluated DMU’s inputs that can be proportionately expanded without altering the output quantities. • Output orientation refers to the emphasis on the evaluated DMU’s outputs that can be proportionately reduced without altering the input quantities.