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Employing artificial intelligence and enhancing resource efficiency to achieve carbon neutrality

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  • Shang, Yunfeng
  • Yang, Qin
  • Pu, Yuanjie
  • Taghizadeh-Hesary, Farhad

Abstract

This study collected annual data from 2000 to 2020 for ten polluting industries in China, investigating the impact of energy efficiency and artificial intelligence on carbon neutralization. The findings indicate that increased industrial robot installation facilitates short-term and long-term carbon neutralization. In addition, an increase in energy efficiency facilitates short-term and long-term carbon neutralization. Investing in artificial intelligence (AI) and robotic technologies to boost carbon neutralization is recommended. Key practical recommendations from this research include promoting sustainable AI, investing in green technologies, and hiring a green-minded, skilled workforce.

Suggested Citation

  • Shang, Yunfeng & Yang, Qin & Pu, Yuanjie & Taghizadeh-Hesary, Farhad, 2024. "Employing artificial intelligence and enhancing resource efficiency to achieve carbon neutrality," Resources Policy, Elsevier, vol. 88(C).
  • Handle: RePEc:eee:jrpoli:v:88:y:2024:i:c:s0301420723012217
    DOI: 10.1016/j.resourpol.2023.104510
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    References listed on IDEAS

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    Cited by:

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    4. Zhang, Ming & Wei, Xuejiao, 2024. "Resource efficiency, cultural industry, and green economic growth: A synergistic approach," Resources Policy, Elsevier, vol. 90(C).

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    More about this item

    Keywords

    Resource utilization; Resource efficiency; Carbon neutralization; Artificial intelligence; Sustainable robot;
    All these keywords.

    JEL classification:

    • Q30 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - General
    • D61 - Microeconomics - - Welfare Economics - - - Allocative Efficiency; Cost-Benefit Analysis
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models

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