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Identification of Key Production Factors in China's Environmental Protection Industry Based on Deep Learning

Author

Listed:
  • Jiakai Li
  • Yan Wang
  • Weihua Tian
  • Xuehua Zhang

Abstract

Analyzing from the micro level of the basic unit of environmental protection industry -- enterprise, this paper takes relevant information of more than 8000 key enterprises in China's environmental protection industry from 2018 to 2020 as the big data training samples, and uses BP neural network method to identify the key production factors that have great impact on the output of the whole China's environmental protection industry and its main subdivisions. The results show that China's environmental protection industry is still in the growing stage in the current stage, with significant capital pulling, technological innovation driving, and management innovation also plays an important role. There are differences in the performance of water, air and solid waste in the environmental protection industry. In detail, R&D expenses from the government plays the most important role in water pollution prevention and control industry. Technology innovation plays the most important role in air pollution prevention and control industry. And staff play the most important role in solid waste treatment and resource recycling industry.

Suggested Citation

  • Jiakai Li & Yan Wang & Weihua Tian & Xuehua Zhang, 2023. "Identification of Key Production Factors in China's Environmental Protection Industry Based on Deep Learning," Energy and Environment Research, Canadian Center of Science and Education, vol. 13(1), pages 1-27, June.
  • Handle: RePEc:ibn:eerjnl:v:13:y:2023:i:1:p:27
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    More about this item

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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