Exploring the Utilization of a Bayesian Network-Based Risk Management System for Cold Chain Packaging
Issued Date
2023-01-01
Resource Type
Scopus ID
2-s2.0-85174305791
Journal Title
7th IEEE International Conference on Transportation Information and Safety, ICTIS 2023
Start Page
1243
End Page
1246
Rights Holder(s)
SCOPUS
Bibliographic Citation
7th IEEE International Conference on Transportation Information and Safety, ICTIS 2023 (2023) , 1243-1246
Suggested Citation
Ren T., Ren J., Mattellini D.B., Liangrokapart J., Weerawat W., Kritchanchai D. Exploring the Utilization of a Bayesian Network-Based Risk Management System for Cold Chain Packaging. 7th IEEE International Conference on Transportation Information and Safety, ICTIS 2023 (2023) , 1243-1246. 1246. doi:10.1109/ICTIS60134.2023.10243836 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/90734
Title
Exploring the Utilization of a Bayesian Network-Based Risk Management System for Cold Chain Packaging
Author's Affiliation
Other Contributor(s)
Abstract
This paper presents a comprehensive risk management model for cold chain packaging, as there is still a lack of systematic approaches to address this industry-wide issue. The proposed Bayesian network model is based on literature review and expert opinions of existing cold chain packaging systems to identify various risks and factors. The model includes various components related to the cold chain packaging system. This model can be used by stakeholders such as logistic managers and consultants to weigh the impact of each risk factor and identify potential risks that may affect the effectiveness of the cold chain system. In addition, the model can be used to evaluate the overall effectiveness of the cold chain system and suggest ways to further improve the system. The model will provide valuable insights for industry practitioners to better plan and manage cold chain packaging operations.