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基于中国数据的食品质量安全监管的ANP-模糊评价模型

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

作者信息

Zhang Xiuhua, Zhang Jun, Chen Tingqiang

机构信息

School of Foreign Language Zhengzhou University of Aeronautics Zhengzhou China.

School of Economics and Management Nanjing Tech University Nanjing China.

出版信息

Food Sci Nutr. 2020 Jun 5;8(7):3157-3163. doi: 10.1002/fsn3.1561. eCollection 2020 Jul.

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.

摘要

政府作为食品质量安全的主要监管主体,如何分别量化并提升政府监管的绩效与效率是一个亟待解决的问题。本研究构建了食品安全监管绩效指标,并运用网络层次分析法-模糊综合评价模型精准量化政府监管绩效。评价结果显示:(a)我国食品质量安全整体形势可控,但政府在食品安全风险监管、食品召回监管及事故总结监管方面表现不佳。(b)内部监管是食品质量安全监管中最薄弱的环节。(c)基层监管薄弱,尤其在地市和县级层面。(d)一个地区的经济水平与监管水平之间不存在正相关关系。本文有助于准确反映我国食品安全监管现状,实现政府监管信息透明化,最终提升政府食品安全监管效率,改善监管状况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2256/7382133/d07eca85ff40/FSN3-8-3157-g001.jpg

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