Evidence map›Paper›PMID 36231837›Full record

ArticleInternational journal of environmental research and public health2022

Environmental Regulation, Greenwashing Behaviour, and Green Governance of High-Pollution Enterprises in China.

Tingfa Zhang, Huaying Qin, Weishuang Xu

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. 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

3 authors.

Tingfa ZhangSchool of Economics and Management, Qilu Normal University, Jinan 250200, China.ORCID 0000-0003-1544-1370
Huaying QinSchool of Economics and Management, Qilu Normal University, Jinan 250200, China.
Weishuang XuSchool of Accountancy, Shandong Youth University of Political Science, Jinan 250103, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study analyses the relationship between greenwashing behaviour, a lack of government supervision, and imperfect green certification mechanisms in China. To improve green governance and greenwashing governance in light of rent-seeking behaviour between high-pollution enterprises and third-party green certification institutions (GCIs), we construct a tripartite game model for the green governance system using an evolutionary game and analyse the interaction and evolutionary trajectory between the three parties. Our results indicate that increasing local government incentives and penalties not only facilitate strengthened green governance by high-pollution enterprises that do not greenwash but also help third-party GCIs to decline to engage in rent-seeking. However, increased incentives lead to relaxed governmental supervision. In addition, the government's incentives and penalties only meet conditions that each agent's total incentives and penalties exceed its speculative gain, and green governance systems can be effectively prevented from resulting in unsatisfactory and unstable strategies. Moreover, the accountability that higher levels of government have to local governments effectively enables high-pollution enterprises' refusal to greenwash and third-party GCIs' refusal to engage in rent-seeking. Our results counsel further research on environmental regulation, green governance, and enterprises' greenwashing, with theoretical and practical applications for both policymakers and enterprises.

Indexed as

Environmental PollutionGovernmentBiological EvolutionChinaenvironmental regulationevolutionary gamegreen governancegreenwashing behaviourhigh-pollution enterprisesrent-seeking

Identifiers

PMID36231837
PMCPMC9566786

What OpenQuestion holds

Textmetadata
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.