Dynamic Green Growth Assessment of China's Industrial System with an Improved SBM Model and Global Malmquist Index

This study proposes a method for resource management and optimisation in the industrial sector of China. Differing from previous research on the green assessment of industrial systems focusing on black box evaluation, our approach contributes to the two-stage structure of an industrial system that consists of an industrial production process and a pollution treatment process. The corresponding network slack-based model (SBM) is proposed to analyse the performance of China's provincial industry sector. Based on our network SBM, the global Malmquist index is built to analyse the total factor productivity changes of system and individual processes to evaluate the consistency of sustainable development where dynamic green growth assessment is realized. The results show that the whole system and its pollution treatment process performance are poor and disorganised, while the industrial production process maintains a stable ranking for the 30 regions in China. We find that the main cause of this phenomenon is the variable technical efficiency change in the 30 regions, which reflects the immaturity of the management of the pollution treatment process. System performance is also highly related to regionalism.

Automated summary

This study proposes a method for resource management and optimization in the industrial sector of China, analyzing the total factor productivity changes and consistency of sustainable development. The results show poor performance of the system and pollution treatment process, while the industrial production process remains stable in ranking. System performance is closely related to regionalism.