Using an Entropy-GRA, TOPSIS, and PCA Method to Evaluate the Competitiveness of AFVs – The China Case

Feng Xue
Southwest Jiaotong University, Chengdu, China

Qian Huang
Southwest Jiaotong University, Chengdu, China

Chuanlei He
Southwest Jiaotong University, Chengdu, China

Bharat Pathak
Southwest Jiaotong University, Chengdu, China

Abstract

With the increase in severe environmental problems associated with fossil fuel vehicles, the development of Alternative Fuel Vehicles (AFVs) has led to their promotion and use in Chinese provinces and cities. The comprehensive evaluation of competitiveness of the AFV industry in Chinese cities is beneficial to analyse the effects and relationships of different factors to promote the sustainable development of the AFV industry and guide the growth paths of the cities. An industrial competitiveness evaluation index system is established based on the characteristics of AFVs, and the development of the AFV industry in ten typical cities in China is comprehensively evaluated based on the Grey Relative Analysis (GRA) Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) and Principal Component Analysis (PCA) methods. To evaluate the results, the entropy weighting method is used for the weight distribution, and the industrial competitiveness rankings of ten cities are obtained by the entropy-GRA, TOPSIS, PCA (EGTP) method. The results show that Beijing is ranked first, followed by Shanghai, and Qingdao is ranked last. By analysing the correlation between the evaluation methods and indicators, it is found that EGTP has a high correlation with the other three evaluation methods, which proves the rationality of the weighted linear combination of GRA and the other three methods. Indices C₅ (pure electric car proportion) and C₁₃ (average concentration of PM_2.5) were outliers due to the small number of samples.