Evidence map›Paper›PMID 32486520›Full record

ArticleVaccines2020

Game Analysis on the Evolution of Decision-Making of Vaccine Manufacturing Enterprises under the Government Regulation Model.

Na Zhang, Yingjie Yang, Xiaodong Wang, Xinfeng Wang

Abstract read
In one paragraph

Article in Vaccines, 2020. 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

4 authors.

Na ZhangSchool of Economics and Management, Shihezi University, Shihezi 832000, China.ORCID 0000-0002-3433-9921
Yingjie YangInstitute of Artificial Intelligence, De Montfort University, Leicester LE1 9BH, UK.
Xiaodong WangBusiness School, Zhengzhou University of Aeronautics, Zhengzhou 450046, China.
Xinfeng WangCollege of Animal Science and Technology, Shihezi University, Shihezi 832000, China.

Funding

Natural Science Foundation of China 41801119
6 · The paper itself

Abstract

The harm caused by defective vaccines to human health and social stability is immeasurable. Aiming at the government's supervision of the vaccine market, an evolutionary game model is constructed to analyze the quality of supervision and the key factors in the dynamic interaction between government departments and vaccine manufacturers under different supervision modes in the vaccine manufacturing process. The results show that: (1) Severe punishment by government regulatory authorities, and increased costs of rectification after investigation and handling of involuntary behaviors of vaccine enterprises can effectively prevent involuntary behaviors of vaccine enterprises. (2) In the early stage of the game, the success rate of the government's efficient supervision will make the vaccine enterprises continuously self-disciplined; when the vaccine market is relatively stable, the government's supervision departments tend to be more conducive to passive supervision. (3) The success rate of government regulatory departments and the probability of a third-party reporting to play a great role in promoting the self-discipline of enterprises. (4) The power of government and regulation are conducive to promoting the active supervision of the government regulatory authorities but corruption of government and awareness of people are different. Once the phenomenon of vaccine enterprises' non-discipline increases, the government regulation must change from passive regulation to active regulation. Therefore, the government should implement different measures according to the characteristics of each period in the manufacturing process to effectively prevent problematic vaccines. The conclusions and policy recommendations are significant for addressing the issue of insufficient self-discipline of vaccine manufacturers.

Indexed as

defective vaccinesevolutionary gamegovernment regulationsevere punishment

Identifiers

PMID32486520
PMCPMC7378765

What OpenQuestion holds

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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.