基于层次分析法-熵权物元模型和神经网络方法的中国武昌稻米产业链欺诈脆弱性定量评估。

Fraud vulnerability quantitative assessment of Wuchang rice industrial chain in China based on AHP-EWM and ANN methods.

机构信息

College of Biosystems Engineering and Food Science, National-Local Joint Engineering Laboratory of Intelligent Food Technology and Equipment, Key Laboratory for Agro-Products Nutritional Evaluation of Ministry of Agriculture and Rural Affairs, Key Laboratory of Agro-Products Postharvest Handling of Ministry of Agriculture and Rural Affairs, Zhejiang Key Laboratory for Agro-Food Processing, Zhejiang International Scientific and Technological Cooperation Base of Health Food Manufacturing and Quality Control, Zhejiang University, Hangzhou 310058, China; Fuli Institute of Food Science, Zhejiang University, Hangzhou 310058, China; Ningbo Research Institute, Zhejiang University, Ningbo 315100, China.

出版信息

Food Res Int. 2021 Feb;140:109805. doi: 10.1016/j.foodres.2020.109805. Epub 2020 Oct 20.

DOI:10.1016/j.foodres.2020.109805

PMID:33648162

Abstract

Vulnerability assessment has been used in the food fraud mitigation based on the subjective judgement of industry participants and simple calculation. To have a more objective result, an improved vulnerability quantitative assessment method was proposed. The overall fraud vulnerability was described by the vulnerability of fraud factors and the health and economic impact of fraud incidents. The fraud factors were related to opportunity, motivation and control measure. Analytic hierarchy process combined with entropy weighting method (AHP-EWM) and artificial neural networking (ANN) to improve judgment accuracy. In the application in Wuchang rice industrial chain, 51 fraud factors were used in the assessment and 10 experts, 36 farmers, 15 suppliers and 15 supervisors were interviewed. Results showed that Wuchang rice industrial chain was highly vulnerable to fraud. The opportunity for fraud was high, the motivation to commit it was moderate, and controls to prevent it needed reinforcing. Fraud vulnerability differed between farmers and suppliers. To reduce the fraud vulnerability, improved regulations and policies and stiffer penalties were strongly recommended.

摘要

脆弱性评估已被用于食品欺诈缓解，其基于行业参与者的主观判断和简单计算。为了获得更客观的结果，提出了一种改进的脆弱性定量评估方法。整体欺诈脆弱性由欺诈因素的脆弱性和欺诈事件的健康与经济影响来描述。欺诈因素与机会、动机和控制措施有关。层次分析法结合熵权法（AHP-EWM）和人工神经网络（ANN）来提高判断准确性。在武昌稻米产业链中的应用中，评估中使用了 51 个欺诈因素，对 10 名专家、36 名农民、15 名供应商和 15 名监管人员进行了访谈。结果表明，武昌稻米产业链极易受到欺诈。欺诈机会高，欺诈动机中等，预防欺诈的控制措施需要加强。农民和供应商之间的欺诈脆弱性存在差异。为降低欺诈脆弱性，强烈建议改进法规政策并加大处罚力度。