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Article . 2025 . Peer-reviewed
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Article . 2025
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Effect of digital transformation on green productivity of China's manufacturing enterprises

Authors: NI Wai; WU Guiquan;

Effect of digital transformation on green productivity of China's manufacturing enterprises

Abstract

[Objective] In the context of “dual carbon” strategic goals and the development of new-quality productivity, this study explores how digital transformation drives the development of green productivity in manufacturing enterprises, providing an micro-level theoretical basis for developing new-quality productivity through digitalization and greening in manufacturing industry. [Methods] Using data from A-share listed manufacturing enterprises in China from 2007 to 2021, the global super-efficiency slacks-based measure (GS-SBM) model was employed to establish and calculate carbon emission efficiency indicators, so as to measure the levels of enterprise green productivity. An empirical examination was conducted to examine the effect of digital transformation on green productivity and its mechanisms. Then an analysis was carried out on the structural heterogeneity of the driving effect of digitization and the backward spillover effects in the industry and supply chains. [Results] (1) Digital transformation significantly enhanced the carbon emission efficiency in manufacturing enterprises, effectively promoting the development of green productivity. (2) The empowerment of green productivity development through digitalization in manufacturing enterprises was primarily achieved through dual mechanisms: green technological innovation and total factor productivity improvement. (3) The empowering effect of digitalization exhibited structural heterogeneity. Compared to the consumer end, digital transformation at the production end had more significant influences on improving carbon emission efficiency. Across the sub-dimensions of digital transformation, a U-shaped relationship existed between digital transformation driven by modern information system and carbon emission efficiency. This improvement effect of carbon efficiency manifested only when enterprises entered the stage of productivity transformation with data as a factor of production. (4) The backward spillover effects of digital empowerment were observed, where the digital transformation of downstream manufacturing enterprises drove improvements in carbon emission efficiency for upstream enterprises. [Conclusion] Digital transformation of manufacturing enterprises can significantly enhance green productivity development. Therefore, manufacturing firms should prioritize the development of digital capacity across production and productive service scenarios. Meanwhile, digital coordination across the industry chain should be strengthened, and staged and incremental approaches to transform data into productivity should be promoted. Governments should actively cultivate digital transformation service providers, improve innovation efficiency support mechanisms, and build data-sharing platforms to facilitate a qualitative leap in the productivity of manufacturing enterprises.

Keywords

Environmental sciences, QH301-705.5, digital transformation|green productivity|carbon emission efficiency|manufacturing enterprises|global super-efficiency sbm model|china, GE1-350, Biology (General)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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