DEA is a non-parametric linear programming technique for assessing the efficiency of a facility, or a profit centre, usually called a ‘DMU’ (in this case a dry port). From a given set of DMUs, the DEA technique constructs an empirical production frontier representing the most efficient production technology, given factor endowments. The relative performance of an individual DMU is evaluated (benchmarked) by comparing it to the most efficient unit, located on the frontier. The performance measurement is expressed in the form of an efficiency score. This comparison reveals the changes in inputs and outputs, necessary for the individual DMU in order to reach the production frontier (Banker et al, 1984)
In comparison to other techniques of efficiency evaluation, the DEA methodology has significant advantages as it can handle multiple inputs and outputs without the need to postulate a certain production function specification. The model selected for the current article is essentially a multiple output-oriented one, attempting to simultaneously maximize throughput and minimize carbon emissions, while retaining the same tangible inputs, that is number of container handling equipment, manpower deployed and surface area.