Can Artificial Intelligence Improve the Energy Efficiency of Manufacturing Companies? Evidence from China

Jun Liu, Yu Qian, Yuanjun Yang and Zhidan Yang
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Jun Liu: School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
Yu Qian: School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
Yuanjun Yang: School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China
Zhidan Yang: School of Management Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China

IJERPH, 2022, vol. 19, issue 4, 1-18

Abstract: Improving energy efficiency is an important way to achieve low-carbon economic development, a common goal of most nations. Based on the comprehensive survey data of enterprises above a designated size in Guangdong Province, this paper studies the impact of artificial intelligence on the energy efficiency of manufacturing enterprises. The results show that: (1) artificial intelligence, as measured by the use of industrial robots, has significantly improved the energy efficiency of manufacturing enterprises. This conclusion is still robust after introducing data on industrial robots in the United States over the same time period as the instrumental variable for the endogeneity test. (2) The mechanism test shows that artificial intelligence mainly promotes the improvement in energy efficiency by promoting technological progress; the impact of artificial intelligence on the technological efficiency of enterprises is not significant. (3) Heterogeneity analysis shows that the age of the manufacturing enterprises inhibits a promoting effect of artificial intelligence on energy efficiency; manufacturing enterprises’ performance can enhance the promoting effect of artificial intelligence on energy efficiency, but this promoting effect can only be shown when the enterprise performance is positive. The paper clarifies both the impact of artificial intelligence on the energy efficiency of manufacturing enterprises and its mechanism of action; this will help provide a reference for future decision-making designed to improve manufacturing enterprises’ energy efficiency.

Keywords: artificial intelligence; manufacturing enterprises; energy efficiency; heterogeneity (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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