Construction of a green development performance index of industrial enterprises: Based on the empirical study of 458 listed industrial enterprises in China. (December 2021) - He, Lingyun; Sun, Yameng; Xia, Yufei; Zhong, Zhangqi
Highlights: Construct the green development performance system of industrial enterprises from the micro perspective. Simulated the green development performance index of industrial enterprises with the functional data analysis method. Analysis the regional difference of the index. Verify the stability and reference value of the index. Abstract: This paper constructs an enterprise green development performance system by integrating green development concept and enterprise performance measurement. Based on the panel data of 458 industrial listed enterprises in China from 2011 to 2018, this paper simulates the green development performance index of industrial enterprises by using the functional data analysis method and functional entropy weight method. There are four main conclusions. First, the change in the green development performance index of industrial enterprises is U-shaped, which shows an upward trend overall. Within a range of [0.006–0.05], the minimum value is 0.006, and considering the strength and trend of future policies there is no maximum value. The higher the value is, the higher the level of green development of industrial enterprises. Second, according to the weight and fitting curves, we can find that the importance and development level of social performance are at the highest, and the importance level basically floats around 0.5, far higher than the average level. The importance of economic performance and the development level of innovation performance are at the lowest respectively, and there is a big gap with the average level. Third, the shape and trend of the index generated by the average weight and the subjective weight of social performance are basically consistent with the index generated by the objective weight. This shows that the index is not sensitive to the weight and has certain robustness and representativeness. Finally, according to the location of enterprises, they were divided into three categories: middle, east and west. The boost Trap method was used to conduct FANOVA (Functional ANOVA) with the P value of 0.314. The results showed that the index did not differ significantly between regions at the significance level of 0.05.