Visualisation of ripple effect in supply chains under long-term, simultaneous disruptions: a system dynamics approach

Date

2021-10-26

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Taylor and Francis

Department

Type

Article

ISSN

0020-7543

Format

Free to read from

Citation

Ghadge A, Er M, Ivanov D, Chaudhuri A. (2021) Visualisation of ripple effect in supply chains under long-term, simultaneous disruptions: A system dynamics approach. International Journal of Production Research, Volume 60, Issue 20, 2022, pp. 6173–6186

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.

Description

Software Description

Software Language

Github

Keywords

Supply chain risk management, ripple effect, risk propagation, disruption propagation, risk modelling, system dynamics

DOI

Rights

Attribution-NonCommercial-NoDerivatives 4.0 International

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