Industrial robots application and collaborative governance of pollution reduction and carbon reduction

The green and intelligent transformation of the manufacturing industry has become the focus of attention in various countries. Through the analysis of China's empirical data, this paper found that the application of industrial robots can effectively reduce the emission intensity and total emission of industrial carbon dioxide and sulfur dioxide to promote green development, so as to realize the collaborative governance of reducing environmental pollution and carbon emission. In terms of mechanism, industrial robot applications play a role by improving capacity utilization, realizing economies of scale, attracting foreign investment and promoting biased technological progress, so as to realize the collaborative governance of reducing environmental pollution and carbon emission. Further analyses find that the application of industrial robots made technological progress tend to use capital factor, save energy and labor factors input, and the industrial structure optimization plays a positive moderating role in it. Through LMDI decomposition, it is found that the current production mode of "simple machine replacing human" can't reduce pollutant emissions, and it is necessary to give full play to the productivity improvement, technological progress, factor substitution, and foreign capital introduction brought by robot applications to promote the collaborative governance of reducing environmental pollution and carbon emission.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2025-05-25
DOI
https://doi.org/10.1038/s41598-025-97559-2
Citations
2
Primary Topic
Sustainable Supply Chain Management
Type
article
Field-Weighted Citation Impact
4.45

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Industrial robots application and collaborative governance of pollution reduction and carbon reduction

Zhengxing Zuo, Zilong Qin
2 citations
Scientific Reports
Sustainable Supply Chain Management
4.45
article

Industrial robots application and collaborative governance of pollution reduction and carbon reduction

Zhengxing Zuo, Zilong Qin
article en
2 citations

Abstract

The green and intelligent transformation of the manufacturing industry has become the focus of attention in various countries. Through the analysis of China's empirical data, this paper found that the application of industrial robots can effectively reduce the emission intensity and total emission of industrial carbon dioxide and sulfur dioxide to promote green development, so as to realize the collaborative governance of reducing environmental pollution and carbon emission. In terms of mechanism, industrial robot applications play a role by improving capacity utilization, realizing economies of scale, attracting foreign investment and promoting biased technological progress, so as to realize the collaborative governance of reducing environmental pollution and carbon emission. Further analyses find that the application of industrial robots made technological progress tend to use capital factor, save energy and labor factors input, and the industrial structure optimization plays a positive moderating role in it. Through LMDI decomposition, it is found that the current production mode of "simple machine replacing human" can't reduce pollutant emissions, and it is necessary to give full play to the productivity improvement, technological progress, factor substitution, and foreign capital introduction brought by robot applications to promote the collaborative governance of reducing environmental pollution and carbon emission.

Scientific ReportsVol. 15(1)
Shanghai University of Finance and Economics (CN), Xi'an Jiaotong University (CN)
Shanghai University of Finance and Economics
Openalex Percentile: Top 6%
Sustainable Supply Chain Management
4.45
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Industrial robots application and collaborative governance of pollution reduction and carbon reduction — Zhengxing Zuo, Zilong Qin · Scientific Reports (2025) | TGRS Research Map | TGRS