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Intelligence and Green Total Factor Productivity Based on China’s Province-Level Manufacturing Data

Author

Listed:
  • Yining Zhang

    (Business School, University of Shanghai for Science and Technology, Shanghai 200093, China)

  • Zhong Wu

    (Business School, University of Shanghai for Science and Technology, Shanghai 200093, China)

Abstract

The application of intelligent technology has an important impact on the green total factor productivity of China’s manufacturing industry. Based on the provincial panel data of China’s manufacturing industry from 2008 to 2017, this article uses the Malmquist–Luenburger (ML) model to measure the green total factor productivity of China’s manufacturing industry, and further constructs an empirical model to analyze the impact mechanism of intelligence on green total factor productivity. The results show that intelligence can increase the green total factor productivity of the manufacturing industry. At the same time, mechanism analysis shows that intelligence can affect manufacturing green total factor productivity by improving technical efficiency. However, the effect of intelligence on the technological progress of the manufacturing industry is not significant. In addition, the impact of intelligence has regional heterogeneity. It has significantly promoted the green total factor productivity in the eastern and central regions of China, while its role in the western region is not obvious. The research in this article confirms that intelligence has a significant positive impact on the green total factor productivity of the manufacturing industry, and can provide suggestion for the current further promotion of the deep integration of intelligence and the green development of the manufacturing industry to achieve the strategic goal of industrial upgrading.

Suggested Citation

  • Yining Zhang & Zhong Wu, 2021. "Intelligence and Green Total Factor Productivity Based on China’s Province-Level Manufacturing Data," Sustainability, MDPI, vol. 13(9), pages 1-16, April.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:9:p:4989-:d:546024
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    3. Haisheng Chen & Shuiping Zhu & Jianjun Sun & Kaiyang Zhong & Manhong Shen & Xiaoli Wang, 2022. "A Study of the Spatial Structure and Regional Interaction of Agricultural Green Total Factor Productivity in China Based on SNA and VAR Methods," Sustainability, MDPI, vol. 14(12), pages 1-17, June.
    4. Batara Surya & Agus Salim & Seri Suriani & Firman Menne & Emil Salim Rasyidi, 2021. "Economic Growth and Development of a Minapolitan Area Based on the Utilization of Renewable Energy, Takalar Regency, South Sulawesi, Indonesia," International Journal of Energy Economics and Policy, Econjournals, vol. 11(5), pages 255-274.
    5. Yuxin Fang & Hongjun Cao & Jihui Sun, 2022. "Impact of Artificial Intelligence on Regional Green Development under China’s Environmental Decentralization System—Based on Spatial Durbin Model and Threshold Effect," IJERPH, MDPI, vol. 19(22), pages 1-27, November.
    6. Haoran Yang & Yaoben Lin & Yang Hu & Xueqing Liu & Qun Wu, 2022. "Influence Mechanism of Industrial Agglomeration and Technological Innovation on Land Granting on Green Total Factor Productivity," Sustainability, MDPI, vol. 14(6), pages 1-17, March.
    7. Yu Mao & Yonglin Li & Deyi Xu & Yaqi Wu & Jinhua Cheng, 2022. "Spatial-Temporal Evolution of Total Factor Productivity in Logistics Industry of the Yangtze River Economic Belt, China," Sustainability, MDPI, vol. 14(5), pages 1-16, February.
    8. Wang, Jianda & Wang, Kun & Dong, Kangyin & Zhang, Shiqiu, 2023. "Assessing the role of financial development in natural resource utilization efficiency: Does artificial intelligence technology matter?," Resources Policy, Elsevier, vol. 85(PA).
    9. Haisheng Chen & Dingqing Ni & Shuiping Zhu & Ying Ying & Manhong Shen, 2022. "Does the National Credit Demonstration Policy Affect Urban Green Economy Efficiency? Evidence from the Yangtze River Delta Region of China," IJERPH, MDPI, vol. 19(16), pages 1-20, August.
    10. Jiekuan Zhang & Yan Zhang, 2023. "Examining the effects of economic growth pressure on green total factor productivity: evidence from China," Economic Change and Restructuring, Springer, vol. 56(6), pages 4309-4337, December.
    11. Julián Alberto Uribe-Gómez, Sebastián Agudelo-Vallejo Jorge Ariel Franco-López, 2021. "Factores clave en la evaluación de la productividad: estudio de caso," Revista CEA, Instituto Tecnológico Metropolitano, vol. 7(15), pages 1-26.
    12. 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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