A new approach on the homogeneous weighting in data envelopment analysis

The concept of efficiency in Data Envelopment Analysis (DEA) is defined as "weighted sum of outputs / weighted sum of inputs". In order to calculate the maximum efficiency score, each decision making unit (DMU) 's inputs and outputs are assigned to different weights. Hence, the classical DEA allows the weight flexibility. Therefore, the important inputs or outputs of some DMUs can be assigned zero weights. In this case, the inputs and outputs are neglected in this evaluation. So, the results are found unrealistic. In order to eliminate the problem of weight flexibility, weight restrictions are made in DEA. Inputs and outputs are related in the degree of correlation between each other in the production. Previous studies did not take into account the correlations between input and output variables. In our study, we proposed new DEA models restricted with correlation coefficients (CCRCOR, BCCCOR) that the weights were determined according to the correlations between input and output variables.Suggested models are compared with the other DEA models on two different applications and a simulation study. In simulation study, we think different combinations of inputs and outputs. Each combinations of variables are conducted for 1000 different experiments. The results are compared with Spearman Test. The results obtained with applications and simulation show that CCRCOR and BCCCOR models are better than the other weight restricted methods.