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

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  • Fenfen Li

    (School of Public Administration, Hunan University of Finance and Economics, Changsha 410205, China
    School of Public Administration, Xiangtan University, Xiangtan 411105, China)

  • Bo Dai

    (School of Management, Hunan University of Technology and Business, Changsha 410205, China)

  • Qifan Wu

    (School of Business, Central South University, Changsha 410083, China)

Abstract

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.

Suggested Citation

  • Fenfen Li & Bo Dai & Qifan Wu, 2021. "Dynamic Green Growth Assessment of China’s Industrial System with an Improved SBM Model and Global Malmquist Index," Mathematics, MDPI, vol. 9(20), pages 1-26, October.
    • Handle: RePEc:gam:jmathe:v:9:y:2021:i:20:p:2594-:d:657184
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