Evidence map›Paper›PMID 37107391›Full record

ArticleFoods (Basel, Switzerland)2023

Analysis of Cross-Regional Transfer of Food Safety Risks and Its Influencing Factors-An Empirical Study of Five Provinces in East China.

Kai Li, Shijiu Yin, Yuanyan Chen

Abstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Kai LiSchool of Economics, Qufu Normal University, Rizhao 276826, China.ORCID 0000-0001-6063-3625
Shijiu YinSchool of Economics, Qufu Normal University, Rizhao 276826, China.
Yuanyan ChenSchool of Economics, Qufu Normal University, Rizhao 276826, China.

Funding

Social Science Foundation of China 20CGL027Social Science Foundation of Shandong 20DGLJ06
6 · The paper itself

Abstract

The cross-regional transfer of food safety risks has become more prominent, bringing new challenges to food safety regulation. This study used a social network analysis to delve into the nuanced features and determinants of the cross-regional transfer of food safety risks based on the food safety inspection data of five provinces in East China from 2016 to 2020, thus contributing to the establishment of effective cross-regional cooperation in food safety regulation. The main findings are as follows: First, the cross-regional transfer of unqualified products accounts for 36.09% of all unqualified products. Second, the food safety risk transfer network presents a typical complex network-a relatively low but increasing network density, heterogeneous nodes, numerous subgroups, and a dynamic structure-bringing more difficulties to food safety cross-regional cooperation. Third, territorial regulation and intelligent supervision both contribute to restricting cross-regional transfers. However, the advantages of intelligent supervision have not yet been brought into play due to low data utilization. Fourth, the development of the food industry helps to mitigate the cross-regional transfer of food safety risks. To achieve effective cross-regional cooperation in food safety risks, it is essential to use food safety big data as a guide and to maintain synchronization between the development of the food industry and the improvement of regulations.

Indexed as

cross-regional cooperationcross-regional transfer of food safety risksFE model with Driscoll–Kraay standard errorsintelligent supervisionsocial network analysis

Identifiers

PMID37107391
PMCPMC10138065

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.