Performance evaluation of AI driven low carbon manufacturing industry in China: An interactive network DEA approach

Abstract

By optimizing production and industrial structure, artificial intelligence (AI) is considered to play a key role in low carbon manufacturing. Understanding the performance of AI driven low carbon manufacturing is of great significance to achieve carbon emission reduction targets and sustainable development of resources. In this paper, for the first time, the production process of manufacturing industry is modeled as a network system integrated by AI technology development stage, AI application stage and AI upgrade stage. Then, an interactive three stage network DEA model with ratio data is developed to evaluate the manufacturing industry in China from 2016 to 2019. The results show that many regions perform well in the AI application stage while most of them have low AI technology development and AI upgrade performance. Moreover, although the change trends of the sub efficiency values in each region are different during the sample period, the overall efficiency values of most regions show a rising trend. Finally, policy implications are provided to improve the performance of low carbon manufacturing China’s manufacturing industry from both national and regional levels.