Evidence map›Paper›PMID 31058876›Full record

ArticleInternational journal of environmental research and public health2019

The Relationship between Environmental Information Disclosure and Profitability: A Comparison between Different Disclosure Styles.

Hua Yin, Mingyu Li, Yuan Ma, Qiang Zhang

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Valuation Impacts of Environmental Protection Taxes and Regulatory Costs in Heavy-Polluting Industries.International journal of environmental research and public health · 2020
    Article
  7. 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.

Hua YinCollege of Economics and Management, Shandong University of Science and Technology, Qingdao 266590, China. sdqdyh@126.com.
Mingyu LiCollege of Economics and Management, Shandong University of Science and Technology, Qingdao 266590, China. 17854259419@163.com.
Yuan MaCollege of Economics and Management, Shandong University of Science and Technology, Qingdao 266590, China. may@sdust.edu.cn.
Qiang ZhangCollege of Economics and Management, Shandong University of Science and Technology, Qingdao 266590, China. zhangqiang3637@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Combined with the existing research gap, this paper divides firms' environmental information disclosure styles into two types: Substantive style and symbolic style. This paper elaborates on the relationship between environmental information disclosure and firms' profitability of these two disclosure types and tests this relationship using the data from 676 firms employed from the heave-polluting industry. Considering the endogenous and heteroscedasticity problems, 2-stage least squares method and weighted least square method were adopted. The results showed that (1) positive relationships exist between environmental information disclosure and profitability for both types; and (2) the contribution of symbolic-style disclosure to profitability is larger than that of substantive-style disclosure. These findings are important for corporate managers and highlight some policy implications in developing countries.

Indexed as

DisclosureResearch DesignConservation of Natural ResourcesEnvironmental PollutionHumansIndustryenvironmental information disclosureenvironmental performanceprofitabilitysubstantive stylesymbolic style

Identifiers

PMID31058876
PMCPMC6539065

What OpenQuestion holds

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LicenceCC BY
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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.