Evidence map›Paper›PMID 39671458›Full record

ArticlePloS one2024

Does environmental information disclosure promote enterprise green technology innovation?

Kun Zhang, Ji Li, Weigang Ma, Xingqi Wang

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

4 authors.

Kun ZhangSchool of Economics, Zhongnan University of Economics and Law, Wuhan, China.ORCID 0009-0006-4942-1801
Ji LiSchool of Economics and Management, Shihezi University, Shihezi, China.
Weigang MaSchool of Economics and Management, Shihezi University, Shihezi, China.
Xingqi WangSchool of Economics and Management, Shihezi University, Shihezi, China.ORCID 0009-0007-3469-2403

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accelerating green technology innovation is essential for promoting economic transformation and achieving sustainable development. Environmental information disclosure (EID) at the city level, as a crucial component of the environmental governance system, provides new opportunities to drive enterprise green technology innovation. This study utilizes the Pollution Source Supervision Information Disclosure Index (PITI), implemented in China since 2008, as a quasi-natural experiment for EID. By integrating data from Chinese A-share listed companies spanning the period from 2003 to 2020, a multi-period difference-in-differences (DID) model is employed to identify the influence of EID. The findings indicate a positive association between EID and enterprise green technology innovation, resulting in concurrent enhancements in both quantity and quality. The robustness of the conclusions remains intact even after addressing endogeneity concerns. Mechanism analysis reveals that EID stimulates environmental governance by facilitating public participation-based, command-control, and market-incentive environmental regulation, thereby fostering enterprise green technology innovation. In addition, the impact of EID on enterprise green technology innovation is heterogeneous, with the policy effect being more pronounced in highly marketized and resource-rich samples. Finally, combining theoretical analyses and empirical results, relevant suggestions are made for formulating more flexible environmental regulatory policies and building a diversified environmental governance system.

Indexed as

InventionsChinaConservation of Natural ResourcesDisclosureEnvironmentEnvironmental PolicyHumansSustainable DevelopmentTechnology

Identifiers

PMID39671458
PMCPMC11642913

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.