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dc.contributor.authorPerera, Supun
dc.contributor.authorBell, Michael G. H.
dc.contributor.authorKurauchi, Fumitaka
dc.contributor.authorKasthurirathna, Dharshana
dc.date.accessioned2019-05-30
dc.date.available2019-05-30
dc.date.issued2019-05-01
dc.identifier.issn1832-570X
dc.identifier.urihttp://hdl.handle.net/2123/20477
dc.description.abstractRecent developments in the area of network science has encouraged researchers to adopt a topological perspective in modelling Supply Chain Networks (SCNs). While topological models can provide macro level insights into the properties of SCN systems, the lack of specificity due to high level of abstraction in these models limit their real-world applicability, especially in relation to assessing the impact on SCNs arising due to individual firm or supply channel level disruptions. In particular, beyond the topological structure, a more comprehensive method should also incorporate the heterogeneity of various components (i.e. firms and inter-firm links) which together form the SCN. To fill the above gap, this work proposes using the idea of absorbing Markov chains to model disruption impacts on SCNs. Since this method does not require path enumeration to identify the number of supply chains which form the SCN, it is deemed more efficient compared to the other traditional methods.en_AU
dc.relation.ispartofseriesITLS-WP-19-10en_AU
dc.subjectsupply chain network; absorbing markov chain; supply network disruptionsen_AU
dc.titleAbsorbing Markov Chain Approach to Modelling Disruptions in Supply Chain Networksen_AU
dc.typeWorking Paperen_AU
dc.contributor.departmentInstitute of Transport and Logistics Studies (ITLS)en_AU


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