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Exploring the Utilization of a Bayesian Network-Based Risk Management System for Cold Chain Packaging

  • Liverpool John Moores University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publication7th IEEE International Conference on Transportation Information and Safety, ICTIS 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1243-1246
Number of pages4
ISBN (Electronic)9798350308532
DOIs
Publication statusPublished - 2023
Event7th IEEE International Conference on Transportation Information and Safety, ICTIS 2023 - Xi'an, China
Duration: 4 Aug 20236 Aug 2023

Publication series

Name7th IEEE International Conference on Transportation Information and Safety, ICTIS 2023

Conference

Conference7th IEEE International Conference on Transportation Information and Safety, ICTIS 2023
Country/TerritoryChina
CityXi'an
Period4/08/236/08/23

Keywords

  • Bayesian Network
  • cold chain packaging
  • cold storage
  • risk management

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