<i>Retracted:</i> An ANP‐fuzzy evaluation model of food quality safety supervision based on China's data

Zhang, Xun; Jun, Zhang; Chen, Tingqiang

doi:10.1002/fsn3.1561

Cited by 7 publications

(4 citation statements)

References 21 publications

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“…Wang et al [ 31 ] found that when the willingness of food enterprises or grassroots food regulatory agencies to change their strategies is low, the legal production by food enterprises and the strategies of grassroots food regulatory agencies to strictly regulate are in a pure strategic stable state. Zhang et al [ 32 ] constructed a food safety regulation performance index and utilized an analytic network process-fuzzy comprehensive evaluation model to precisely quantify the performance of government regulation.…”

Section: Literature Reviewmentioning

confidence: 99%

Government and dealer regulatory decisions on producer illegal production in China’s food supply chain

Cai,

Lai,

Guo

2023

Heliyon

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Section: Literature Reviewmentioning

confidence: 99%

Government and dealer regulatory decisions on producer illegal production in China’s food supply chain

Cai,

Lai,

Guo

2023

Heliyon

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“…Zhang et al ( 29 ) and Zhang and Song ( 30 ) highlighted two shortcomings in the existing methods. First, the effect of food safety supervision funding and other auxiliary supervision equipment on the efficiency of supervision is not duly being considered.…”

Section: Variable Selection and Data Collectionmentioning

confidence: 99%

Digital Technology, Knowledge Level, and Food Safety Governance: Implications for National Healthcare System

Wei

Lin

et al. 2021

Front. Public Health

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Exploring the intrinsic relationship between digital technology and the efficiency of food safety supervision contributes to a better understanding of the role of digital technology in food safety supervision and how to maximize its influence. This study employed sample data from 31 regions in China between 2015 and 2017 for an empirical analysis of the correlation between the two and to examine the moderating effects of the knowledge levels of food producers and consumers. The results show that the development of digital technology contributes to enhancing the efficiency of food safety supervision. In this process, the higher the knowledge level of consumers, the greater the positive promotional effect of digital technology. On the contrary, when the knowledge level of producers is higher, it is not conducive to enhancing the effect of digital technology on the efficiency of food safety supervision. The author holds the view that this is related to the fact that employees in the food production and manufacturing industry have insufficient moral and legal knowledge. This not only limits the effect of digital technology on enhancing the efficiency of food safety supervision, but also opens the door to illegal production for some unprincipled producers. The policy implications are that digital technology should be used to improve food safety supervision, the moral and legal knowledge of food producers should be improved, and consumers should be encouraged to use digital technology more in the pursuit of food safety. Implications for national healthcare system would be also discussed in our paper.

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“…In 1995, academician D. Y. Li proposed the Cloud model concept based on the limitations of probability theory and fuzzy mathematics on the analysis of uncertainty problems [30], using three feature numbers to represent the ambiguity and randomness of the Cloud model. It can intuitively reflect the mathematical mapping of qualitative language [31,32].…”

Section: Cloud Modelmentioning

confidence: 99%

Risk Early Warning Evaluation of Coal Mine Water Inrush Based on Complex Network and Its Application

Bai

Yan

et al. 2021

Advances in Civil Engineering

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As one of the five major coal mine disasters, the water inrush disaster poses a serious threat to the safety of the country and people, so the prevention work for that becomes very important. However, there is no perfect assessment system that can better solve the complex dependence relationships among disaster-causing factors of water inrush disasters. This study applied the knowledge of Complex Networks to research water inrush disaster, and based on that, the early warning evaluation system that combined ANP and Cloud model was established in order to solve the complex dependence problem and prevent the occurrence of water inrush. Moreover, this evaluation model was applied to the example Y coal mine to verify its superiority and feasibility. The results showed that the main cloud of goal was located at the yellow-strong warning level, and the first-level indicators were, respectively, at that the yellow-strong level of mining conditions, the yellow-strong warning level of hydrological factors, between the yellow-strong warning level and purple-general level of the geological structure, and among the blue-slightly weak warning level, purple-general level, and yellow-strong level of the human factor. The prediction results were consistent with the actual situation of the coal water inrush disaster in Y mine, which further proved that this early warning evaluation model is reliable. In response to the forecast results, the authors put forward relative improvements necessary to strengthen the prevention ability to disaster-causing factors among hydrological factors, mining conditions, and geological structure, which should comprehensively increase knowledge, technology, and management of workers to avoid leaving out disaster-causing factors. Meanwhile, the warning evaluation model also provides the relevant experience basis for other types of early warning assessment networks.

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Retracted: An ANP‐fuzzy evaluation model of food quality safety supervision based on China's data

Cited by 7 publications

References 21 publications

Government and dealer regulatory decisions on producer illegal production in China’s food supply chain

Government and dealer regulatory decisions on producer illegal production in China’s food supply chain

Digital Technology, Knowledge Level, and Food Safety Governance: Implications for National Healthcare System

Risk Early Warning Evaluation of Coal Mine Water Inrush Based on Complex Network and Its Application

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