Evidence map›Paper›PMID 39524765›Full record

ArticleHeliyon2024

Exploring the impact of FDI on environmental innovation in China: An empirical investigation.

Yan Jiang

RetractedAbstract readRetracted Publication
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. 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

5 · Who and what money

Authors and funding

1 author.

Yan JiangHunan University of Information Technology, Changsha, Hunan, 410151, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Today, firms face several environmental concerns, including but not limited to: decreasing natural resources, pollution management, and climate change. Little is known about the factors that motivate the many forms of environmental innovation or the effects of these endeavors on the financial success of businesses, despite the growing demand for eco-friendly goods and services. For the first time, this study introduces the core environmental determinants for China's 30 provinces covering the period of 2005-2022. In these determinants, this study considers foreign direct investment (FDI), financial development (FDI), natural resources (NRs), human capital (HC), and green energy (GE). However, to investigate the study objectives, the present study utilizes an advanced series of estimators that can overcome all panel data problems. In these estimators, the Augmented Mean Group (AMG), the Common Correlated Effect Mean Group (CCE-MG), and the Panel Quantile Regression (P-QR) are being considered. However, the results of the long-term investigation obtained interesting outcomes for selected provinces. For example, financial proxies such as economic development and foreign direct investment significantly increase the environmental innovations across the selected regions. Conversely, natural resources negatively affect environmental innovations and become a leading hurdle in the clean & green innovation process. Finally, empirical analysis finds a positive response of ecological regulations and green energy to an explained variable. This article outlined policy proposals for a low-carbon economy that would guarantee environmental innovation in certain provinces by reducing emissions; these proposals included increasing the use of renewable energy sources, sustainable technology, and environmentally friendly technology.

Indexed as

ChinaEnvironmental innovationFinancial developmentForeign direct investmentNatural resources

Identifiers

PMID39524765
PMCPMC11550050

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.