Evidence map›Paper›PMID 36766045›Full record

ArticleFoods (Basel, Switzerland)2023

Food Fraud Vulnerability Assessment in the Chinese Baijiu Supply Chain.

Yiqin Wang, Jiali Liu, Yanling Xiong, Xuefan Liu, Xiaowei Wen

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. 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

5 authors.

Yiqin WangCollege of Economics and Management, South China Agricultural University, Wushan Road 483, Tianhe District, Guangzhou 510642, China.
Jiali LiuCollege of Economics and Management, South China Agricultural University, Wushan Road 483, Tianhe District, Guangzhou 510642, China.
Yanling XiongCollege of Economics and Management, South China Agricultural University, Wushan Road 483, Tianhe District, Guangzhou 510642, China.
Xuefan LiuCollege of Economics and Management, South China Agricultural University, Wushan Road 483, Tianhe District, Guangzhou 510642, China.
Xiaowei WenResearch Center for Green Development of Agriculture, South China Agricultural University, Wushan Road 483, Tianhe District, Guangzhou 510642, China.

Funding

National Natural Science Foundation of China 71633002
6 · The paper itself

Abstract

As a representative of Chinese alcoholic drinks, baijiu has developed into a mass-consumption commodity. Its simple industrial chain makes it a suitable target for fraudsters. In order to understand the differences and potential factors of fraud vulnerability among groups at various levels, this study constructed a food fraud vulnerability assessment system for the Chinese baijiu supply chain based on routine activities theory. We examined the fraud vulnerability in the baijiu supply chain with data from 243 producers and 45 retailers by using the safe supply of affordable food everywhere (SSAFE) food fraud vulnerability assessment (FFVA) tool. The results indicate that fraud factors related to opportunities have an overall medium vulnerability, while those related to motivations and control measures have an overall medium-low vulnerability. In addition, there are significant differences in the perceived vulnerability of fraud factors across the supply chain. Moreover, retailers have overall higher fraud vulnerability in terms of opportunities and control measures than producers. The main reasons for the frequent occurrence of fraud in the baijiu industry are numerous technical opportunities, strong economic drivers, and insufficient control measures.

Indexed as

baijiu supply chaincontrol measuresfood fraud vulnerability assessmentmotivationsopportunities

Identifiers

PMID36766045
PMCPMC9914212

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.