The discussion and application of Data Envelopment Analysis (DEA) was initiated after the seminal work by Charnes, Cooper, and Rhodes (1978) and subsequent evidence can be found in (Banker, Charnes, Cooper 1984; Ramanathan 2001; Taluri 2000; Despotis. Dimitris, Smirlis 2002). For an in-depth discussion of DEA, one can refer to Seiford and Thrall (1990). DEA can be used to evaluate the efficiency of a number of producers, generally referred as decision- making unit (DMU). DEA compares each producer with only the “best” DMU in the group, which is better than the comparison with average of the group. In DEA, we can consider number of DMUs, each of them consuming similar inputs to varying level to produce. A fundamental assumption behind this method is that if a given DMU, , is capable of producing units of output with inputs, then other DMUs shall also be able to do the same if they were to operate efficiently. Similarly, if DMU is capable of producing units of output with inputs, then other DMUs should also be capable of the same. DMUs , and others can then be combined to form a composite producer i.e. virtual producer with composite inputs and composite outputs. The emphasis of DEA is on finding the “best” virtual producer for each real producer. If the virtual producer is better than the original producer by either
making more output with the same input or making the same output with less input then the original producer is inefficient.