Evidence map›Paper›PMID 37831729›Full record

ArticlePloS one2023

Evaluation of coupling coordination development between digital economy and green finance: Evidence from 30 provinces in China.

Zebin Liu, Xiaoheng Zhang, Jingjing Wang, Lei Shen, Enlin Tang

Abstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Zebin LiuSchool of Finance and Mathematics, Huainan Normal University, Huainan, Anhui Province, China.ORCID 0000-0002-6037-2469
Xiaoheng ZhangSchool of Economics and Management, Anhui University of Science & Technology, Huainan, Anhui Province, China.
Jingjing WangSchool of Finance and Mathematics, Huainan Normal University, Huainan, Anhui Province, China.
Lei ShenSchool of Finance and Mathematics, Huainan Normal University, Huainan, Anhui Province, China.
Enlin TangSchool of Finance and Mathematics, Huainan Normal University, Huainan, Anhui Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The convergence of China's digital economy and green finance holds great significance for fostering a sustainable and high-quality developmental path. However, existing studies have not explored the coupling coordination development between these two crucial subsystems. To bridge this gap, this paper employs a modified coupling coordination degree (CCD) model to assess and affirm the coupling coordination degree between the digital economy and green finance across 30 provinces in China from 2015-2021. Based on degree results, provinces are classified into three clusters by using K-means and hierarchical clustering algorithm. Our findings unveil that the current level of coupling coordination development in China is at a primary coordination stage. Although regional disparities significantly exist, the overall level of coordination remains steadily increasing, with the eastern region outperforming the western region. Additionally, we determine that the COVID-19 pandemic's disruption on the coupling coordination development of these systems has been limited. This research sheds light on the evolution of coupling systems and offers practical recommendations for strengthening the coordinated development of the digital economy and green finance.

Indexed as

COVID-19AlgorithmsChinaCluster AnalysisEconomic DevelopmentHumansPandemics

Identifiers

PMID37831729
PMCPMC10575532

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LicenceCC BY
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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.