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

Xiuhua Zhang, Jun Zhang, Tingqiang Chen

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

A government acts as the main supervisor of food quality and safety. How to quantify and improve the performance and efficiency of government supervision, respectively, is an urgent problem. This study constructs a food safety supervision performance index and utilizes an analytic network process-fuzzy comprehensive evaluation model to precisely quantify the performance of government supervision. The evaluation results show that, (a) although the overall situation of food quality and safety in China is controllable, the government does not do well in food safety risk supervision, food recall supervision, and accident summary supervision. (b) Internal supervision is the weakest link in food quality and safety supervision. (c) Grassroots supervision is weak especially in prefecture and county levels. (d) There is no positive correlation between the economy level and supervision level in one region. This paper contributes to accurately reflecting the status quo of China's food safety supervision and realizing the transparency of government regulatory information, which ultimately boosts the government's efficiency in food safety supervision and improves the regulatory situation.

Original languageEnglish
Pages (from-to)3157-3163
Number of pages7
JournalFood Science and Nutrition
Volume8
Issue number7
DOIs
StatePublished - 1 Jul 2020

Keywords

  • analytic network process
  • empirical research
  • food safety
  • fuzzy comprehensive evaluation method
  • supervision performance

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