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Visualisation of ripple effect in supply chains under long-term, simultaneous disruptions: A System Dynamics approach

Ghadge, A. and Er, M. and Ivanov, D. and Chaudhuri, A. (2021) 'Visualisation of ripple effect in supply chains under long-term, simultaneous disruptions: A System Dynamics approach.', International Journal of Production Research .

Abstract

Supply chains (SCs) are exposed to multiple risks and vulnerable to disruption propagation (i.e., the ripple effect). Despite established literature, quantitative analysis of the ripple effect in SCs considering simultaneous, long-term disruptions (i.e., induced by the COVID-19 pandemic) remains limited. This study defines, applies and demonstrates the capability of system dynamics modelling to recognise and visualise the ripple effect subject to supply, demand, and logistics disruptions as well as a combined, simultaneous disruption of supply, demand and logistics. Simulation results for these four risk scenarios indicate that disruption propagation and its impacts vary based on risk type, combination of risks and the impacting node. The bi-directional, increasing effect is significant for disruptions of longer duration. Retailers and manufacturers are most fragile to multiple disruptions due to broader risk exposure points. In generalised terms, systems theory-based study provides insights into the complex behaviour of simultaneous risks and associated disruptions occurring at a node and across the SC. The outcomes derived can help practitioners visualise and recognise the dynamic nature of the ripple effect cascading across the SC network. In addition, some novel insights on the systemic nature and delayed impact of disruption propagations are uncovered and discussed.

Item Type:Article
Full text:Publisher-imposed embargo
(AM) Accepted Manuscript
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Available under License - Creative Commons Attribution Non-commercial No Derivatives 4.0.
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Status:Peer-reviewed
Publisher Web site:https://doi.org/10.1080/00207543.2021.1987547
Publisher statement:© 2021 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
Date accepted:26 August 2021
Date deposited:14 September 2021
Date of first online publication:26 October 2021
Date first made open access:11 January 2022

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