An application of DEA with tradeoff factors on evaluating higher education institutions performances

Data Envelopment Analysis (DEA) is a widely used method in academic literature to evaluate relative efficiency of units under an establishment that is responsible for turning resources into service and goods. Based on linear programming principles, DEA has the advantage of overcoming problems usually faced while measuring a non-profit organization's performance such as uncertainty of input and outputs or unit discrepancies. This method requires a homogenous data set to reach the most accurate results. To obtain homogeneity, classifying the data set accurately is a crucial process in DEA but also other extensions such as tradeoff relations can play a vital role in improving the homogeneity. Tradeoff relations can be defined as the relationship between input and output factors and added to the standard DEA as additional constraints which expands the effective frontier. This study includes evaluating the efficiency of academic units under Hacettepe University which contains 290 divisions, 80 departments and 32 faculties by using DEA models with tradeoff relations. Models with tradeoff relations have been compared to the classical DEA model to test the changes in efficiency scores. With few modifications such as decomposition of data according to its characteristics and the addition of tradeoff factors, 54 different scenarios were tested. Besides from measuring the performance of academic units of Hacettepe University, results and change in model behaviors depending on different cases have also been observed to find out the improvement areas for the classical DEA approach.