Data Envelopment Analysis (DEA) is a body of concepts and methodologies that have now been incorporated in a collection of models with accompanying interpretive possibilities as follows:
1.
the CCR ratio model (1978)
(i)
yields an objective evaluation of overall efficiency and
(ii)
identifies the sources and estimates the amounts of the thusidentified inefficiencies
2.
the BCC model (1984) distinguishes between technical and scale inefficiencies by
(i)
estimating pure technical efficiency at the given scale of operation and
(ii)
identifying whether increasing decreasing, or constant returns to scale possibilities are present for further exploitation
3.
the Multiplicative models (Charnes et al., 1982, 1983) provide
(i)
a log-linear envelopment or
(ii)
a piecewise Cobb- Douglas interpretation of the production process (by reduction to the antecedent 1981 additive model of Charnes, Cooper, and Seiford); and
4.
the Additive model (as better rendered in Charnes et al., 1985) and the extended Additive model (Charnes et al., 1987)
(i)
relate DEA to the earlier Charnes-Cooper (1959) inefficiency analysis and in the process
(ii)
relate the efficiency results to the economic concept of Pareto optimality as interpreted in the still earlier work of T. Koopmans (1949) in the volume that published the proceedings of the first conference on linear programming.1