How robot application empowers industrial low-carbon development: A study based on the perspective of carbon reduction and efficiency enhancement

Shan Wang, Haiqian Chen and Donghua Yu

Technological Forecasting and Social Change, 2025, vol. 220, issue C

Abstract: In the digital economy era, robot application has become an effective pathway to enhance the industrial carbon emission efficiency. This paper theoretically analyzes the effect and mechanism of robot application in empowering industrial low-carbon development from the dual perspectives of carbon reduction and efficiency enhancement. Empirical tests are conducted based on 212 cities data in China from 2010 to 2019. The results show that the robot application improves the industrial carbon emission efficiency. Specifically it has a significant inhibitory effect on industrial carbon emissions and a promotive effect on industrial added-value, demonstrating a dual effect of carbon reduction and efficiency enhancement. Mechanism research shows that the robot application can significantly promote green technology innovation, manifested by an increase in green invention patents and green utility model patents, as well as the decrease in energy intensity. Heterogeneity analysis indicates that the empowering effect of robot application on industrial low-carbon development is more pronounced in cities with higher carbon emissions, larger scale, and richer technical talents. This paper not only provides a valuable supplement to the research of the carbon reduction effect of digital economy, but also offers policy insights for accelerating industrial low-carbon development from the perspectives of carbon reduction and efficiency enhancement.

Keywords: Robot application; Industrial carbon emission efficiency; Carbon reduction and efficiency enhancement (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:220:y:2025:i:c:s0040162525003324

DOI: 10.1016/j.techfore.2025.124301

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