Evidence map›Paper›PMID 40388539›Full record

ArticlePloS one2025

Pharmaceutical enterprises integrity supervision strategy when considering rent-seeking behavior and government reward and punishment mechanism.

Yanhua Chen, Lilong Zhu

Abstract read
In one paragraph

Article in PloS one, 2025. 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
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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

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.

Yanhua ChenSchool of Business, Shandong Normal University, Ji'nan, China.
Lilong ZhuSchool of Business, Shandong Normal University, Ji'nan, China.ORCID https://orcid.org/0000-0002-9697-3012

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The integrity of pharmaceutical enterprises is crucial to public health, social stability, and national security, consistently garnering attention from both the government and society. The efficiency of pharmaceutical integrity supervision is closely linked to government oversight mechanisms and the behaviors of third-party testing agencies. This study constructs an evolutionary game model that incorporates rent-seeking dynamics and introduces a reward-punishment mechanism, integrating drug production enterprises, third-party testing agencies, government regulators, and drug wholesale enterprises. By solving for the stable equilibrium points of each participant's strategic choices and analyzing the stability of strategy combinations using Lyapunov's first method, the study employs Matlab 2022b for simulation analysis to verify the impact of various decision variables on the strategic choices of different entities. The findings reveal that: 1) The rejection of rent-seeking by third-party testing agencies enhances the incentives for drug production enterprises to operate with integrity, indicating that the government should increase penalties for accepting rent-seeking behavior. 2) Drug wholesale enterprises' reporting likelihood increases production enterprises' integrity and third-party testing agencies' rejection of rent-seeking, inversely tied to reporting costs. 3) Reducing the costs of stringent government supervision and increasing the speculative costs of rent-seeking for third-party testing agencies help prevent dishonest practices among drug production enterprises. 4) A well-designed reward and punishment mechanism facilitates a synergistic environment of government supervision, self-discipline among pharmaceutical enterprises, and social harmony. This paper enriches the theoretical foundation of pharmaceutical integrity supervision and offers pertinent countermeasures and recommendations.

Indexed as

Drug IndustryPunishmentGame TheoryGovernmentHumansReward

Identifiers

PMID40388539
PMCPMC12088600

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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.