Evaluation of Green Manufacturing Level in China’s Provincial Administrative Regions Based on Combination Weighting Method and TOPSIS

Mingtao Wang (), Chunming Ye and Dingkun Zhang
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Mingtao Wang: School of Computer and Information Engineering, Anyang Normal University, Anyang 455000, China
Chunming Ye: Business School, University of Shanghai for Science and Technology, Shanghai 200093, China
Dingkun Zhang: School of Electromechanical Engineering, Heilongjiang University, Harbin 150006, China

Sustainability, 2022, vol. 14, issue 20, 1-26

Abstract: Green manufacturing is becoming an important emerging field in the new round of global industrial revolution and scientific and technological competition. Scientific evaluation of China’s regional green manufacturing level has far-reaching significance for promoting the transformation and upgrading of the manufacturing industry and enhancing international competitiveness. This paper defines the connotation of green manufacturing in China in the new era, proposes four dimensions of green production, green emission, green technology, and green benefit as the framework of the evaluation system, and constructs the evaluation index system. By taking 30 provincial administrative regions as research samples, based on the data from 2017 to 2020, the combination weighting method and TOPSIS are used for evaluation from the perspective of “static” and “dynamic” to identify the current situation and development of green manufacturing level in each region. It was found that the important factors affecting the green manufacturing level in each region are green products, green invention patents, sulfur dioxide, green factories, and coal consumption. The “static” evaluation results show that the green manufacturing level varies significantly among regions. The eastern area is generally better than the central and western areas, and only six regions are at high-level and medium to high-level. In addition, the four dimensions in most regions are imbalanced, with an obvious Matthew effect. The “dynamic” evaluation results show that the green manufacturing level in 30 regions appears to have six different types of dynamic trends. There is a small change in the ranking of most regions, indicating that the dynamic development of green manufacturing level has clear regional dependence, which is difficult to change in the short term. The research results show that the index system and model can effectively evaluate the regional green manufacturing level. Finally, combined with the important influencing factors, some suggestions are proposed to enhance the regional green manufacturing level.

Keywords: green manufacturing; static evaluation; dynamic evaluation; combination weight; TOPSIS (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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