An Application of Analytic Hierarchy Process and Entropy Weight Method in Food Cold Chain Risk Evaluation Model

Abstract

The food cold chain is a special type of cold chain that refers to a system in which refrigerated and frozen food is always kept in the specified low-temperature environment in all links from production, storage, transportation, sales, distribution to consumption, so as to ensure food quality and to prevent food deterioration caused by temperature fluctuation. In recent years, the coronavirus disease 2019 (COVID-19) has brought a great impact on people’s life and the social economy and also threatened the large-scale food cold chain. Through the effective identification and evaluation of high-risk factors in the food cold chain, this article has found the major risks that have a great impact on the entire food cold chain and proposes the specific measures of risk management and control to solve the problems of food cold chain and reduce risks quickly and efficiently to ensure the stability and safety of food cold chain and avoid the serious food safety accidents. The contribution of this article is reflected in three aspects, namely, (1) applies the expert system based on professional knowledge and rich experience and constructs a classification and identification system structure of food cold chain risk indexes, which lay a foundation for further identifying and evaluating the major risks of the food cold chain; (2) designs a comprehensive index weighting method combining the AHP method and entropy weight method to quantitatively evaluate the major risks. This comprehensive method combines a hierarchical structure system, evaluation algorithm, subjective factor correction algorithm, and so on. The evaluation results are more accurate, have a high matching degree with reality, and have good theoretical and practical significance; (3) analyzes and explains the major risks of the food cold chain in the non-epidemic situations and COVID-19 situations. Proposals and measures for risk management and control are put forward, which have wide practical significance.

Factors influencing Chinese public attitudes toward farm animal welfare

“…The statistical analysis involved four steps: (1) Descriptive statistical analyses were performed; (2) the reliability of the scale was examined using Cronbach's alpha coefficients, and the construct validity of the scale was examined using Kaiser–Meyer–Olkin (KMO) values and Bartlett's test of sphericity; (3) mean scores for each item and attitude construct of the scale were calculated to analyze public overall attitudes, affective attitudes, cognitive attitudes, and behavioral attitudes toward farm animal welfare; (4) tobit models were designed to identify factors influencing public overall attitudes, affective attitudes, cognitive attitudes, and behavioral attitudes toward farm animal welfare. An analytic hierarchy process (AHP) and an entropy method were used to determine the weight of each item before regression analysis, and thus, the scores of attitudes were calculated as explained variables (Peng, 2022 ; Shen and Liao, 2022 ). After normalizing the scores, collinearity was tested using variance inflation factors (VIFs).…”

Establishment of an indicator framework for the transmission risk of the mountain-type zoonotic visceral leishmaniasis based on the Delphi-entropy weight method

“…The entropy method is an objective method and mainly uses the characteristics of entropy to judge the dispersion degree of each indicator in the framework through the entropy value [ 22 ]. Thus, the combination of subjective and objective methods has been used in studies to render results more accurate, reasonable, and effective [ 23 – 25 ]. In this study, the Delphi and entropy methods were applied to establish the multilevel risk factors and comprehensive assessment framework to provide a new basis for the MT-ZVL control in endemic areas.…”

Improvement of the Port Development System through the Port Service Index (PSI)

“…At last, the two different weights were combined to be used for the development of Port Service Index (PSI). When weights are combined, the evaluation result is more accurate since it is more reflective of reality (Shen and Liao, 2022) The weights derived from the AHP and entropy methods were combined according to Equation 5 (Shen and Liao, 2022).…”