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The influence of digital intelligence transformation on carbon emission reduction in manufacturing firms.

Authors :
Cao, Bin
Li, Lianqing
Zhang, Kai
Ma, Wanli
Source :
Journal of Environmental Management. Sep2024, Vol. 367, pN.PAG-N.PAG. 1p.
Publication Year :
2024

Abstract

Severe global climate change has resulted in the focus of social attention shifting to the manufacturing industry's low-carbon transformation. Digital intelligent transformation (DIT) in enterprises is identified as a crucial driver in mitigating carbon emissions. An estimation of DIT's impact on manufacturing industries' carbon emission intensity (CEI) and its underlying mechanisms was conducted using data from Chinese A-share listed companies. Research findings indicate that DIT significantly reduces corporate CEI. Robustness tests, such as the instrumental variable method and variable substitution method, confirm this conclusion. By enhancing labor productivity and accelerating capital renewal, DIT indirectly lowers CEI. Furthermore, non-state-owned enterprises with superior market competitiveness have been observed to be markedly adept at harnessing DIT for CEI. The heterogeneity test found that DIT has a considerably significant effect on reducing CEI in enterprises that are not low-carbon pilots, non-broadband pilots, smart pilots, non-provincial capitals, and eastern cities. This study provides new evidence supporting the promotion of enterprise DIT for achieving green development, offering insights for corporate policy making. Fig. The graphical abstract of the paper. [Display omitted] • Establish comprehensive indicators for the digital intelligence transformation. • Digital intelligent transformation significantly reduced carbon emission intensity. • Labor productivity and capital renewal acted as mediating mechanisms. • Market competitiveness can positively moderate the carbon reduction effect. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03014797
Volume :
367
Database :
Academic Search Index
Journal :
Journal of Environmental Management
Publication Type :
Academic Journal
Accession number :
178942732
Full Text :
https://doi.org/10.1016/j.jenvman.2024.121987