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Carbon emission reduction effects of industrial robot applications: Heterogeneity characteristics and influencing mechanisms

Author

Listed:
  • Yaya Li
  • Yuru Zhang
  • An Pan
  • Minchun Han
  • Eleonora Veglianti

    (Lille Catholic University)

Abstract

No abstract is available for this item.

Suggested Citation

  • Yaya Li & Yuru Zhang & An Pan & Minchun Han & Eleonora Veglianti, 2022. "Carbon emission reduction effects of industrial robot applications: Heterogeneity characteristics and influencing mechanisms," Post-Print hal-04522085, HAL.
    • Handle: RePEc:hal:journl:hal-04522085
    DOI: 10.1016/j.techsoc.2022.102034
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    Citations

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    Cited by:

    1. Mao, Fengfu & Hou, Yuqiao & Wang, Rong & Wang, Zongshun, 2023. "Can industrial intelligence break the carbon curse of natural resources in the context of Post-Covid-19 period? Fresh evidence from China," Resources Policy, Elsevier, vol. 86(PA).
    2. Lin, Boqiang & Xu, Chongchong, 2024. "The effects of industrial robots on firm energy intensity: From the perspective of technological innovation and electrification," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    3. Zhou, Wei & Zhuang, Yan & Chen, Yan, 2024. "How does artificial intelligence affect pollutant emissions by improving energy efficiency and developing green technology," Energy Economics, Elsevier, vol. 131(C).
    4. Liu, Lei & Rasool, Zeeshan & Ali, Sajid & Wang, Canghong & Nazar, Raima, 2024. "Robots for sustainability: Evaluating ecological footprints in leading AI-driven industrial nations," Technology in Society, Elsevier, vol. 76(C).
    5. Lin, Boqiang & Xu, Chongchong, 2024. "Enhancing energy-environmental performance through industrial intelligence: Insights from Chinese prefectural-level cities," Applied Energy, Elsevier, vol. 365(C).
    6. Chen, Pengyu & Chu, Zhongzhu & Zhao, Miao, 2024. "The Road to corporate sustainability: The importance of artificial intelligence," Technology in Society, Elsevier, vol. 76(C).
    7. Ke Zhao & Chao Wu & Jinquan Liu, 2024. "Can Artificial Intelligence Effectively Improve China’s Environmental Quality? A Study Based on the Perspective of Energy Conservation, Carbon Reduction, and Emission Reduction," Sustainability, MDPI, vol. 16(17), pages 1-18, September.
    8. Özköse, Hakan & Güney, Gül, 2023. "The effects of industry 4.0 on productivity: A scientific mapping study," Technology in Society, Elsevier, vol. 75(C).
    9. Lee, Chien-Chiang & Yan, Jingyang, 2024. "Will artificial intelligence make energy cleaner? Evidence of nonlinearity," Applied Energy, Elsevier, vol. 363(C).
    10. Zhao, Congyu & Dong, Kangyin & Wang, Kun & Nepal, Rabindra, 2024. "How does artificial intelligence promote renewable energy development? The role of climate finance," Energy Economics, Elsevier, vol. 133(C).

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