Evidence map›Paper›PMID 36078759›Full record

ArticleInternational journal of environmental research and public health2022

Dynamic Game Analysis of Enterprise Green Technology Innovation Ecosystem under Double Environmental Regulation.

Yan Li, Yi Shi

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 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
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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

2 authors.

Yan LiSchool of Economics and Management, Taiyuan University of Technology, Taiyuan 030024, China.ORCID 0000-0003-4064-4532
Yi ShiSchool of Economics and Management, Taiyuan University of Technology, Taiyuan 030024, China.ORCID 0000-0003-4020-473X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the context of China's "double carbon" target, an urgent problem that remains to be solved is how to drive the construction of an enterprise green innovation ecosystem through effective environmental regulations to alleviate the pressure of energy saving and emission reduction. Based on this, we constructed a tripartite evolutionary game model of enterprises, governments and financial institutions, and used the evolutionary game theory and MATLAB simulation to analyze the evolutionary process of the interaction of the subjects of the green technology innovation of enterprises under the dual environmental regulation. The research finds that: (1) Both formal and informal environmental regulations can promote green technology innovation in enterprises, provided that the enforcement is controlled within an appropriate range; (2) Informal environmental regulations are a weaker driver of green technology innovation in firms than formal environmental regulations; (3) Six types of environmental regulation strategies, namely, the "penalty enterprises mechanism", "financial support mechanism", "public supervision mechanism", "punishes financial institutions mechanism", "financial subsidy mechanism" and "carbon tax mechanism", have a decreasing effect on promoting the development of the green technology innovation ecosystem of enterprises; (4) Combining the implementation of a middle-intensity subsidy mechanism, a high-intensity penalty mechanism, a low-intensity public supervision mechanism and a middle-intensity carbon tax mechanism is the optimal strategy combination to encourage collaborative green technology innovation between companies and financial institutions.

Indexed as

EcosystemInventionsCarbonChinaGame TheoryGovernmentHumansCarbonevolutionary gameformal environmental regulationgreen financegreen technological innovationinformal environmental regulation

Identifiers

PMID36078759
PMCPMC9518494

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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.