Blessing or Curse? The Impact of the Penetration of Industrial Robots on Green Sustainable Transformation in Chinese High-Energy-Consuming Industries

The rapid development and widespread application of artificial intelligence (AI) and robots have profoundly impacted the economy, society, and the environment. This article focuses on the relationship between industrial robots and green sustainable transformation in high-energy-consuming industries. Through the Poisson distribution fixed effect, the negative binomial fixed-effect model, and the two-way fixed-effect model, we found that the penetration of industrial robots in high-energy-consuming enterprises (HEEs) has a significant and positive effect on green innovation. In particular, we verified that total factor productivity and ESG, included in the zero-inflation model, have a breakthrough-accelerating role in the application of industrial robots to promote green sustainable transformation. Further analysis indicated that the adoption of industrial robots is also positively correlated with the improvement of corporate green sustainable transformation in non-state-owned enterprises, but state-owned enterprises are not sensitive. In the classification of segmented industries, only the metallurgical industry demonstrates the empowering role of green sustainable transformation. This article provides a new avenue for reshaping the low-carbon green sustainable transformation strategy of HEEs, as well as useful insights, supporting the achievement of carbon peak and carbon neutrality by promoting the application of industrial robots and further improving total factor productivity and ESG performance.

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Publication Details

Journal
Energies
Published
2025-02-01
DOI
https://doi.org/10.3390/en18030684
Citations
1
Primary Topic
Energy, Environment, Economic Growth
Type
article
Field-Weighted Citation Impact
3.13
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article

Blessing or Curse? The Impact of the Penetration of Industrial Robots on Green Sustainable Transformation in Chinese High-Energy-Consuming Industries

Hsing Hung Chen, Fang Yang, Yueqi Sun, Junlong Ti
1 citations
Energies
Energy, Environment, Economic Growth
3.13
article

Blessing or Curse? The Impact of the Penetration of Industrial Robots on Green Sustainable Transformation in Chinese High-Energy-Consuming Industries

Hsing Hung Chen, Fang Yang, Yueqi Sun, Junlong Ti
article en
1 citations

Abstract

The rapid development and widespread application of artificial intelligence (AI) and robots have profoundly impacted the economy, society, and the environment. This article focuses on the relationship between industrial robots and green sustainable transformation in high-energy-consuming industries. Through the Poisson distribution fixed effect, the negative binomial fixed-effect model, and the two-way fixed-effect model, we found that the penetration of industrial robots in high-energy-consuming enterprises (HEEs) has a significant and positive effect on green innovation. In particular, we verified that total factor productivity and ESG, included in the zero-inflation model, have a breakthrough-accelerating role in the application of industrial robots to promote green sustainable transformation. Further analysis indicated that the adoption of industrial robots is also positively correlated with the improvement of corporate green sustainable transformation in non-state-owned enterprises, but state-owned enterprises are not sensitive. In the classification of segmented industries, only the metallurgical industry demonstrates the empowering role of green sustainable transformation. This article provides a new avenue for reshaping the low-carbon green sustainable transformation strategy of HEEs, as well as useful insights, supporting the achievement of carbon peak and carbon neutrality by promoting the application of industrial robots and further improving total factor productivity and ESG performance.

EnergiesVol. 18(3)
Macau University of Science and Technology (MO), Xiamen University (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 10%
Energy, Environment, Economic Growth
3.13
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