Journal
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
Volume 61, Issue 8, Pages 2493-2512Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207543.2022.2126021
Keywords
Spatial dynamics; ripple effect; propagation; disruption; global supply chain
Ask authors/readers for more resources
This paper discusses the ripple effects of disruptions in supply networks caused by the pandemic and proposes a model that combines logistics with an epidemiological model to predict and simulate the impact on workforce in the supply chain. The findings can provide useful insights for managers and scholars to mitigate the impact of a pandemic.
An increasing number of disruptions in ports, plants and warehouses have generated ripple effects over supply networks impacting economic activity. We demonstrate how the spread of the pandemic geographically expands the ripple effect by reducing the workers' participation in production, so undermining the ability of firms and, as a result, the entire cross-border sup- ply chain network to satisfy customers' demands. Our model of the spatio-temporal dynamics of the propagation of Covid-19 infection for supply networks contributes toward ripple effect visualisation and quantification by combining the flow of goods and materials through a typical global supply chain with an epidemiological model. The model enables prospective analyses to be performed in what-if scenarios to simulate the impact on the workforce in each node. The outcome should be helpful tools for managers and scholars. Results from this research will help mitigate the impact and spread of a pandemic in a particular region and the ability of a supply network to overcome the ripple effect. A stylised case study of a cross-border supply chain illustrates the ripple effect by showing how waves with crests at varying dates impact the ability to serve demand showing how a supply chain manager can obtain a forward-looking picture.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available