The Impact of Industrial Intelligence on Carbon Emissions: Evidence from the Three Largest Economies

Xiekui Zhang and Hongfei Zhu ()
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Xiekui Zhang: China-ASEAN Collaborative Innovation Center for Regional Development Co-Constructed by the Province and Ministry, Guangxi University, Nanning 530004, China
Hongfei Zhu: School of Business, Guangxi University, Nanning 530004, China

Sustainability, 2023, vol. 15, issue 7, 1-15

Abstract: Many studies are exploring the generated factors of carbon emissions to make a contribution to environmentally sustainable development as carbon emissions have increased by more than 5% in the past ten years. However, few investigations have considered the effects of industrial intelligence on carbon emissions. In order to discover whether the development of industrial robots will influence the environment, this paper employs the IFR data of industrial robots from 2006 to 2021 to investigate their impacts on carbon emissions in the three largest economies by using the classical linear regression model, OLS (Ordinary Least Squares), from the factors of robot installations and robot density, which are measured by ownership per thousand manufacturing people, respectively. The positive correlation coefficients of robot installation and density in the USA are 0.010 and 0.011; they are 0.185 and 0.204 in China; and 0.156 and 0.142 in Japan. To ensure the reliability of the results, we also do a robustness test and an endogeneity test by using the two-way fixed effect model, and they show the same results. The main findings of our study show that industrial intelligence can have significant positive impacts on carbon emissions in the three economies and this means that the application of industrial intelligence not only accelerates economic growth, but also causes the pressure on the environment. Moreover, the verification results also indicate that the impacts of industrial intelligence on carbon emissions are dominated by driving effects, and the higher the robot density, the stronger the driving effects on carbon emissions. Based on the findings, corresponding policy suggestions are proposed to guide governments in trimming their environment protection policies more efficiently.

Keywords: industrial intelligence; robots; robot density; carbon emissions (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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