Optimization of Subsidy Policy for New Energy Automobile Industry in China Based on an Integrated Fuzzy-AHP-TOPSIS Methodology

Abstract

With the continuous tension of the international energy supply and the increasing appeal of the global environmental protection, the development of the new energy vehicle industry has attracted international attention. In order to support the development of new energy automobile production, China has frequently issued support policies. However, the problem of subsidy fraud has been exposed. Therefore, in order to help the healthy development of China’s new energy automobile industry and reduce the risk of subsidy fraud, this paper investigates 15 representative new energy auto enterprises in China and independently evaluates their performance from three aspects. We first use triangular fuzzy numbers (TFNs) to simulate an uncertain decision environment and more closely reflect the decision maker’s thinking model; we then propose an analytic hierarchy process (AHP)-technique for order preference by similarity to an ideal solution (TOPSIS) method based on fuzzy data to rank 15 enterprises. Finally, according to the performance of enterprises, we propose differentiated subsidy policy recommendations. The model proposed in this paper takes into account the uncertainty of subjective evaluation so as to increase the credibility of the results. At the same time, the model can also be applied in other industries.