Robot adoption and energy performance: Evidence from Chinese industrial firms
Geng Huang,
Ling-Yun He and
Xi Lin
Energy Economics, 2022, vol. 107, issue C
Abstract:
With the continuous development of technology, intelligent production, which brings huge changes to social welfare, has gradually become the main trend in the economic development of many countries. Does intelligent production featuring robot adoption help improve the environment and solve energy problems? In this study, we first construct a theoretical model at the micro-level to analyze how robot adoption affects a firm’s energy efficiency. Then, based on Propensity Score Matching-Difference in Differences (PSM-DID) method, we use the data of China’s firms from 2001 to 2012 to identify the causal relationship between robot adoption and firm’s energy efficiency. We find that the adoption of robots in production can significantly increase firms’ energy efficiency. Further mechanism tests show that the increase of productivity is an important factor through which adopting robots can improve a firm’s energy efficiency. In addition, the increase in the firm’s energy efficiency is mainly due to the increase in the firm’s output rather than the decrease in total energy consumption. Altogether, this study provides the first micro evidence on the relationship between robot adoption and energy efficiency, providing significant implications for the world’s sustainable development.
Keywords: Intelligent production; Robot adoption; Energy efficiency; Energy performance (search for similar items in EconPapers)
JEL-codes: O33 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (46)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0140988322000214
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:eneeco:v:107:y:2022:i:c:s0140988322000214
DOI: 10.1016/j.eneco.2022.105837
Access Statistics for this article
Energy Economics is currently edited by R. S. J. Tol, Beng Ang, Lance Bachmeier, Perry Sadorsky, Ugur Soytas and J. P. Weyant
More articles in Energy Economics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().