Evidence map›Paper›PMID 40080469›Full record

ArticlePloS one2025

The impact of carbon information disclosure on corporate green technology innovation in the context of "dual carbon"-- Based on data from heavily polluting industries.

Lumenqiqige Chao, Richa Hu, Boya Shi, Xiaomin Jin

Abstract read
In one paragraph

Article in PloS one, 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

4 authors.

Lumenqiqige ChaoSchool of Accountancy, Inner Mongolia University of Finance and Economics, Hohhot, China.ORCID https://orcid.org/0009-0002-8413-7487
Richa HuSchool of Business Administration, Zhongnan University of Economics and Law, Wuhan, China.ORCID https://orcid.org/0000-0002-1333-7548
Boya ShiSchool of Accountancy, Inner Mongolia University of Finance and Economics, Hohhot, China.
Xiaomin JinSchool of Accountancy, Inner Mongolia University of Finance and Economics, Hohhot, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the current global response to climate change, the "dual carbon" goal has become a common development goal for all countries. In the context of "dual carbon", China's heavily polluting enterprises, as the main governance body, have become the necessary path for green transformation. Green technology innovation is important for heavily polluting industries to achieve green transformation. Starting from the perspective of environmental regulation based on information disclosure, this article mainly explores the mechanism of carbon information disclosure promoting green technology innovation in enterprises. This article takes heavily polluting enterprises in China from 2017 to 2021 as samples and innovatively constructs a carbon information disclosure indicator system based on the "dual carbon" background. Then, empirical tests examine the relationship between carbon information disclosure level, green technology innovation, and financing constraints. Research has shown that the quality of carbon information disclosure improves corporate green technology innovation; The quality of carbon information disclosure can promote green technology innovation by alleviating corporate financing constraints. The research results have theoretical value and significance for incentivizing heavily polluting enterprises to reduce carbon emissions and support China's dual carbon goals.

Indexed as

CarbonDisclosureIndustryInventionsChinaClimate ChangeConservation of Natural ResourcesCarbon

Identifiers

PMID40080469
PMCPMC11906053

What OpenQuestion holds

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LicenceCC BY
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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.