Efficiency Improvement with Target Setting Models in Data Envelopment Analysis: Theory and Applications

Data Envelopment Analysis (DEA) evaluates efficiency of homogeneous units using a frontier as an approximation for production function, to identify the efficient and inefficient units. Target setting offers strategic efficiency improvement for inefficient units, thus providing ex-ante efficiency improvement strategy. To that effect, two approaches for target setting are proposed. First approach uses the most productive scale size (MPSS) hyperplane vector to guide an inefficient unit to the efficiency frontier, consequently incorporating feasible productivity improvement and enhancing efficiency. The second approach has two folds which are based on decision makers‘ desire. One is based on predefined inputs, which uses decision makers‘ input capabilities to propose efficient output targets. The other is based on predefined outputs targets by the decision maker, where desired output are presented, and the required efficient inputs are proposed. Empirical analysis with real life applications are used to validate the proposed models. Keywords: Data Envelopment Analysis, Efficiency improvement, Target setting, Most Productive Scale Size, Predefined inputs, Predefined outputs.