Evidence map›Paper›PMID 39472659›Full record

ArticleScientific reports2024

Impact of the digital trade on lowering carbon emissions in 46 countries.

Xiuxiang Li, Yan Hu, Liang Ding, Qiyu Huang, Yi Jiang

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

5 authors.

Xiuxiang LiSchool of International Economics and Politics, Jiangxi University of Finance and Economics, Nanchang, 330013, China.
Yan HuSchool of International Economics and Politics, Jiangxi University of Finance and Economics, Nanchang, 330013, China.
Liang DingApplied Economic Research Center, Jiangxi Institute of Fashion Technology, Nanchang, 330201, China. dingeric2000@hotmail.com.
Qiyu HuangSchool of Economics, Nankai University, Tianjin, 300071, China.
Yi JiangSchool of International Economics and Politics, Jiangxi University of Finance and Economics, Nanchang, 330013, China.

Funding

2022 Pure Zixi(City) Carbon Neutrality Practice Innovation Center 2022JDA072023 Jiangxi Province Social Science Fund Project 23YJ392024 Jiangxi Province Social Science Fund Project NO.24YJ22
6 · The paper itself

Abstract

Digital trade, as one of the vanguards of the global technological revolution and industrial transformation, empowers low-carbon economic cooperation on a global scale. This study based on panel data from 2007 to 2021 of 46 countries with varied development levels, constructed a multi-dimensional indicator system from six aspects: trade potential, digital infrastructure, digital innovation, digital skills and security, scale of digital trade, and digital trade environment, aim to measure the development level of digital trade and explore its impact on carbon emissions, followed by a heterogeneity analysis. The research results indicate that there are significant differences in the development levels of digital trade among countries with different economic strengths. Countries with stronger economic power and larger trade scales have a higher level of digital trade development, while less developed regions lag in digital trade. As the level of digital trade development increases, the impact of digital trade on carbon emissions will also change. Overall, digital trade exhibits a pronounced low-carbon effect, while its impact varies among countries with different development levels.

Indexed as

AHP-EntropyCarbon emissionsDigital TradeThreshold effect

Identifiers

PMID39472659
PMCPMC11522511

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

None linked

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.