Production efficiency evaluation of energy companies based on the improved super-efficiency data envelopment analysis considering undesirable outputs

Abstract

The introduction of a precise and effective production efficiency evaluative model has vital theoretical importance. It can promote the improvement of production efficiency in energy companies and the enhancement of China’s energy supply. Data envelopment analysis (DEA) is a nonparametric method to evaluate the relative effectiveness of decision-making units (DMU). While DEA has many theoretical advantages, it is also very sensitive to the number of decision-making units being evaluated as well as the accuracy of the data. Super-efficiency DEA can make up this limitation. However, this model has several shortcomings, like the possible exaggeration of the efficiency value and the variety of the evaluating benchmarks. Integrating the measurement of undesirable outputs, this paper combined the traditional CCR model, super-efficiency DEA model and ideal-DMU-based benchmark sorting model to get an improved super-efficiency DEA model. Then, we applied this method to 10 subsidiaries of a well-known domestic energy corporation to testify to the feasibility of it.