Evidence map›Paper›PMID 37167323›Full record

ArticlePloS one2023

Green supply chain decision of discarded drugs recycling: Evolutionary game and strategy simulation.

Chao Wang, Zhe Huang, Guiyu Lian

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.

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

3 authors.

Chao WangSchool of Business Administration, Shenyang Pharmaceutical University, Shenyang, Liaoning, China.
Zhe HuangSchool of Business Administration, Shenyang Pharmaceutical University, Shenyang, Liaoning, China.ORCID 0000-0002-3170-9341
Guiyu LianSchool of Business Administration, Shenyang Pharmaceutical University, Shenyang, Liaoning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The research on the recycling of discarded drugs has become an important direction of the green supply chain in China. Faced with the great challenge of recycling discarded drugs in China, it is necessary to make clear the behavior choice of each recycling subject. This paper constructs an evolutionary game model among government, drugs recycling companies and consumers, describes the evolutionary game process, and analyzes the influence of the gain of government, drug recycling enterprises and consumers on the evolutionary stable strategy trend. By using Matlab simulation software to simulate the evolution of tripartite behavior, the final result is obtained: The government's choice of a strong regulatory strategy has an important positive role in guiding the entire discarded drug recovery market. Consumer's choice of active participation strategy and enterprise's choice of active participation strategy are most beneficial to the healthy development of the discarded drug recovery market. This study provides some valuable theoretical support and reference for the national decision-making of discarded drug recovery, helps to solve the problem of discarded drug recovery, and provides theoretical support and policy-making recommendations for the ultimate achievement of sustainable development goals.

Indexed as

GovernmentSustainable DevelopmentChinaGame TheoryPolicy MakingRecycling

Identifiers

PMID37167323
PMCPMC10174494

What OpenQuestion holds

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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.