An improved ISM method based on GRA for hierarchical analyzing the influencing factors of food safety. (May 2019)

• Record Type: Journal Article
• Authors: Lin, Xiaoyong; Cui, Shiying; Han, Yongming; Geng, Zhiqiang; Zhong, Yanhua
• Is Part Of: Food control. Volume 99(2019)
• Page Start: 48
• Page End: 56
• Publication Date: 2019-05
• Subjects: Grey relational analysis (GRA) -- Interpretative structural modeling (ISM) -- Food safety -- Risk early warning -- Infant formula -- Sterilized milk; Food -- Quality -- Periodicals; Food -- Analysis -- Periodicals; Food handling -- Periodicals; Food industry and trade -- Quality control -- Periodicals; Aliments -- Industrie et commerce -- Qualité -- Contrôle -- Périodiques; Aliments -- Qualité -- Périodiques; Aliments -- Analyse -- Périodiques; Hygiène alimentaire -- Périodiques; Food -- Analysis; Food handling; Food -- Quality; Periodicals; Electronic journals; 664.07
• DOI: 10.1016/j.foodcont.2018.12.020
• Languages: English
• ISSNs: 0956-7135

Abstract

Abstract: Food safety is closely related to economic development and daily life of people. The valid food safety and risk warning contribute to the social health and sustainable development. However, the inspection data of food safety is characterized by high complexity, high dimension and non-linearity. Therefore, an improved interpretative structural modeling (ISM) method based on the grey relational analysis (GRA) (GRA-ISM) is proposed to hierarchical analyze influencing factors of food safety. The correlation coefficient between the influencing factors is calculated by the GRA. Then the ISM is used for stratifying and establishing the multi-hierarchical structure of influencing factors of food safety. Finally, the infant formula data and the sterilized milk data of food safety in China are hierarchical analyzed by the GRA-ISM. The multi-hierarchical structure model of different factors affecting food safety can be obtained. The Student's t-test ( t -test) is used to verify the validity of the threshold selection and the result of the GRA-ISM. Meanwhile, through the early warning analysis of the major factors, the proposed method can guide relevant departments to strengthen supervision and urge enterprises to work safely. Highlights: An improved GRA-ISM method is proposed. The multi-hierarchical structure model of different factors affecting food safety is established. The validity and the practicability of the proposed method are verified by food safety inspection data. The proposed method can guide relevant departments to strengthen supervision and urge enterprises to work safely.