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Efficiency Evaluation of Chinese Provincial Industrial System Based on Network DEA Method

Author

Listed:
  • Kai He

    (School of Statistics, Southwestern University of Finance and Economics, Chengdu 611130, China)

  • Nan Zhu

    (Western Business School, Southwestern University of Finance and Economics, Chengdu 611130, China)

  • Wu Jiang

    (School of Statistics, Southwestern University of Finance and Economics, Chengdu 611130, China)

  • Chuanjin Zhu

    (School of Statistics, Southwestern University of Finance and Economics, Chengdu 611130, China)

Abstract

The operation process of the Chinese provincial industrial system consists of four stages, namely the production (P) stage, wastewater treatment (WWT) stage, solid waste treatment (SWT) stage, and sulfur dioxide treatment (SDT) stage. Based on this structure, a four-stage data envelopment analysis (DEA) model is developed to evaluate the eco-efficiency, production efficiency, wastewater treatment efficiency, solid waste treatment efficiency, and sulfur dioxide treatment efficiency of provincial industrial systems in China, considering the undesirable output and variable returns to scale (VRS). Based on the objective data from 2011 to 2015, the following conclusions are drawn: Firstly, the eco-efficiency of the Chinese provincial industrial system has not been significantly improved during the study period, and the average eco-efficiency score is low, only 0.3805. Secondly, the reasons for the low eco-efficiency of the industrial system are different in the Eastern, Central, Western, and Northeastern regions. Thirdly, compared with the P stage, industrial WWT stage, and SWT stage, the efficiency of SDT stage is still relatively weak.

Suggested Citation

  • Kai He & Nan Zhu & Wu Jiang & Chuanjin Zhu, 2022. "Efficiency Evaluation of Chinese Provincial Industrial System Based on Network DEA Method," Sustainability, MDPI, vol. 14(9), pages 1-24, April.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5264-:d:803232
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    References listed on IDEAS

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    2. Lipeng Sun & Nur Ashikin Mohd Saat, 2023. "How Does Intelligent Manufacturing Affect the ESG Performance of Manufacturing Firms? Evidence from China," Sustainability, MDPI, vol. 15(4), pages 1-20, February.

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