A new modelling approach of evaluating preventive and reactive strategies for mitigating supply chain risks

Abroon Qazi, John Quigley, Alex Dickson, Barbara Gaudenzi

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

3 Citations (Scopus)
99 Downloads (Pure)

Abstract

Supply chains are becoming more complex and vulnerable due to globalization and interdependency between different risks. Existing studies have focused on identifying different preventive and reactive strategies for mitigating supply chain risks and advocating the need for adopting specific strategy under a particular situation. However, current research has not addressed the issue of evaluating an optimal mix of preventive and reactive strategies taking into account their relative costs and benefits within the supply network setting of interconnected firms and organizations. We propose a new modelling approach of evaluating different combinations of such strategies using Bayesian belief networks. This technique helps in determining an optimal solution on the basis of maximum improvement in the network expected loss. We have demonstrated our approach through a simulation study and discussed practical and managerial implications.

Original languageEnglish
Title of host publicationComputational Logistics
Subtitle of host publication6th International Conference, ICCL 2015, Delft, The Netherlands, September 23-25, 2015, Proceedings
EditorsFrancesco Corman, Stefan Voß, Rudy R. Negenborn
PublisherSpringer-Verlag
Pages569-585
Number of pages17
ISBN (Print)9783319242637
DOIs
Publication statusPublished - 20 Oct 2015
Event6th International Conference on Computational Logistics, ICCL 2015 - Delft, Netherlands
Duration: 23 Sep 201525 Sep 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer-Verlag
Volume9335
ISSN (Print)0302-9743

Conference

Conference6th International Conference on Computational Logistics, ICCL 2015
CountryNetherlands
CityDelft
Period23/09/1525/09/15

Keywords

  • Bayesian belief networks
  • network expected loss
  • preventive and reactive strategies
  • simulation study
  • supply chain risks

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