Evidence map›Paper›PMID 41258244›Full record

ArticleScientific reports2025

Digital supply chain transformation improves corporate carbon emission efficiency in Chinese listed companies.

Jiangying Wei, Xiuwu Zhang, Yingtian Cheng

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Jiangying WeiInstitute of Quantitative Economics and Statistics, Huaqiao University, Xiamen, 361021, People's Republic of China. 1315075352@qq.com.
Xiuwu ZhangInstitute of Quantitative Economics and Statistics, Huaqiao University, Xiamen, 361021, People's Republic of China.
Yingtian ChengInstitute of Quantitative Economics and Statistics, Huaqiao University, Xiamen, 361021, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Supply chain digitalization presents significant potential for aligning economic growth with environmental sustainability; however, the mechanisms through which it enhances carbon emission efficiency remain insufficiently explored in emerging economies. This study investigates the impact of digital transformation on corporate carbon performance in China, utilizing the Supply Chain Innovation and Application Pilot Initiative as a quasi-natural experiment. By analyzing data from Chinese A-share listed companies between 2013 and 2021 using a difference-in-differences approach, the study finds that pilot companies exhibited a substantial improvement in carbon emission efficiency. Two key mechanisms drive this effect: first, external collaboration, wherein digital platforms facilitate co-innovation with supply chain partners to develop low-carbon solutions, and second, internal capability restructuring, which optimizes management processes and promotes data-driven decision-making. The heterogeneity analysis identifies stronger effects in firms characterized by mature governance, non-state ownership, and involvement in competitive, low-pollution industries. These findings contribute to the advancement of green development theory by illustrating how digitalization functions as a dual catalyst, reshaping internal organizational capabilities and nurturing external innovation ecosystems. The study offers empirical insights from China's institutional context, providing guidance for achieving climate-industrial compatibility in emerging economies while emphasizing the need for context-specific validation across different institutional environments.

Indexed as

Carbon emission efficiencyOrganizational capabilitiesQuasi-natural experimentSupply chain digitalization

Identifiers

PMID41258244
PMCPMC12630620

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.