EFFICIENCY IMPROVEMENT IN DATA ENVELOPMENT ANALYSIS

Data envelopment analysis (DEA) is a mathematical programming approach to assessing relative efficiencies within a group of decision making units (DMUs). An important outcome of such an analysis is a set of values for slack variables. Theoretically, the slack variables indicate by how much the associated factors (inputs or outputs) should be adjusted so that all inefficiencies will be eliminated. Nevertheless, in real world applications this is impractical because not all factors can be controlled at wish. In this paper, a modified formulation of the DEA model is presented where bounds are imposed on each factor. Simple relationships between factors are also incorporated. In essence, the results solved from the proposed model provide the top management with a direction which is feasible in reality for achieving Pareto efficiency.