The effect of congestion on the estimation of the rate of progress and regression of decision- making units in data envelopment analysis

Abstract

Abstract DEA is a technique for measuring the efficiency and performance of decision-making units (DMUs) with multiple inputs and outputs. The term overload in the literature DEA refers to the overuse of the source, which reduces the output and thus the efficiency. This problem changes over time, and the progress and rate of decline of the units can be measured by these changes. In this paper, the Malmquist productivity index and congestion are used to measure the progress and regression of units over time. The proposed model can change the congestion changes in addition to calculating the efficiency and technology changes by changing the relative distances in the Mamquist productivity index. The criterion for congestion is the fraction \(({e}_{o}^{i}\)(j))/\({c}_{o\left(j\right)}^{i}\), and the lower it is, the lower the congestion to be evaluated, and if it is 1, there is no congestion. Thus, by applying this criterion to the structure of the Malmquist productivity index, two categories of distances, performances, and congestion are used in the calculation of progress and regression of unity.