Evidence map›Paper›PMID 36925535›Full record

ArticleHeliyon2023

Debt default, financial risk transmission and governance from the perspective of supply chain network.

Yongli Zhang, Xi Nan

Abstract read
In one paragraph

Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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

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.

Yongli ZhangCollege of Economics and Management, Tianjin University of Science and Technology, Tianjin 300222, China.
Xi NanSchool of Management, Hebei GEO University, Shijiazhuang 050031, Hebei Province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The stock risk spillovers of 31 associated enterprises of Evergrande supply chain in China were measured with DCC-GARCH and CoVaR model, and high, moderate and low risk overflow networks in four periods were constructed, finally the overall metrics and dynamic evolution of risk spillover network were explored. The results showed that: With COVID-19 under control in China, the risk spillover of Evergrande supply chain associated enterprises continues to diverge, with the quantity and scope of high risk declining and moderate and low risk rising; The infection scope of high risk spillover has narrowed, from indirect to direct infection; Evergrande subsidiaries play obvious bridge roles in moderate and low risk networks, have strong control over the risk spread; Commercial banks suffer and trigger more risk spillovers, a number of risk spillover groups with commercial banks as cores formed in high and moderate risk networks.

Indexed as

Complex networkCoVar-DCC-GARCHRisk spilloverSupply chain network

Identifiers

PMID36925535
PMCPMC10010984

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.