Evidence map›Paper›PMID 39123578›Full record

ArticleFoods (Basel, Switzerland)2024

Study on the Influences of Inter-Governmental Information Flow and Interdepartmental Collaborative Supervision on Pork Quality: A Case Study in China.

Linhai Wu, Zhiyu Chen

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2024. 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
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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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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.

Linhai WuSchool of Business, Institute for Food Safety Risk Management, Jiangnan University, Wuxi 214122, China.ORCID 0000-0003-0397-9579
Zhiyu ChenSchool of Business, Institute for Food Safety Risk Management, Jiangnan University, Wuxi 214122, China.

Funding

National Social Science Fund of China: Research on social co-governance of food safety risks and cross-border cooperative governance mechanism 20&ZD117
6 · The paper itself

Abstract

To study the influences of the degree of interdepartmental collaborative supervision on the behavioral strategy selection of pig farmers, pig slaughterers, and pork processing manufacturers in the pork supply chain system, this study established a three-party evolutionary game model involving pig farmers, pig slaughterers, and pork processing manufacturers based on the social co-governance framework by focusing on the interdepartmental information sharing mechanism and cooperative governance. Here, we examined how the degree of collaborative supervision among government departments influences the behavioral strategy selection of these parties by focusing on key mechanisms such as information sharing and interdepartmental collaborative governance. Our findings revealed that within a social co-governance system, the strategic choices of the three entities in the pork supply chain closely correlate with the coordination level of collaborative supervision among government departments, particularly through information-sharing mechanisms. Additionally, the strategies are influenced by market-based contract supervision among entities, consumer reporting intensity, and the collaborative governance capabilities of the government, market actors, and consumers. Higher levels of social co-governance are associated with fewer risky links in the pork supply chain and reduced overall risk. Key factors affecting the behavioral strategy selection of the subjects in the pork supply chain include interdepartmental collaborative governance among government departments (e.g., optimizing random inspection frequencies, adjusting economic penalties, and disclosing enterprise market credit information via information sharing mechanisms), consumer complaint probabilities, and the intensity of mutual supervision among enterprises. Therefore, to enhance pork supply chain quality and mitigate risks, it is crucial to enhance the coordination of collaborative supervision among government departments, encourage consumer reporting, and improve market-based mutual supervision mechanisms among upstream and downstream subjects in the supply chain.

Indexed as

coordination degreeevolutionary gameinterdepartmental collaborative governancepork supply chainsocial co-governance

Identifiers

PMID39123578
PMCPMC11311583

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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.