Abstract
The fresh cold chain network is complex, and the interruption risk can significantly impact it. Based on the Bayesian theory, we constructed a fresh cold chain network interruption risk topology structure. The probability of each root node was predicted and calculated based on the fuzzy set theory. The evaluation model was then validated and improved through the virus transmission model based on risk transmission. Sensitivity analysis was used to determine significant risk factors. Several strategies for minimizing interruption risks were identified.
Highlights
In China, the second-largest economy in the world, income levels of domestic residents and consumer demands are increasing
We introduced the process of constructing the Bayesian network fresh cold chain network interruption risk assessment model and its importance in evaluating the interruption risk status
We used the Bayesian network for risk assessment of network interruption in the fresh cold chain network
Summary
In China, the second-largest economy in the world, income levels of domestic residents and consumer demands are increasing. Bayesian networks have been used to assess supply chain risks, express causal relationships between supply chain factors through directed tree diagrams and conditional probabilities, and calculate their sensitivity [5,6,7,8,9]. Due to cold chain disruption caused by COVID-19, we postulated that interruption risk depends on various carriers, and spreading, as well as transmission, to other node enterprises and the entire system along the complex network of the fresh cold chain in form of original or new risk is done after the coupling mutation. Erefore, a fresh cold chain network interruption risk assessment model based on Bayesian network theory was constructed to analyze its occurrence probability and major influencing factors in China. Interruption risk factors with a significant impact on sensitivity were analyzed, and effective countermeasures were taken to reduce the impact of interruption risk
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
