Simulation-based ripple effect modelling in the supply chain: a network perspective

This research investigates the ripple effects of supply chain disruptions across supply chain echelons and identifies vulnerable network characteristics. Utilising simulation methods, the study analyses the impact of disruption scale, propagation extent, and delay on supply chain performance. Employing AnyLogistix software, the study evaluates ripple effects across four different network structures under disruption scenarios resembling the COVID-19 pandemic, characterised by prolonged impacts on supply, demand, logistics, and uncertain recovery times. Comparative analysis across network structures reveals insights into recovery strategies, highlighting the influence of network characteristics on performance outcomes. The findings demonstrate that both disruption severity and propagation delay significantly affect supply chain performance, with high connectivity and betweenness centrality enhancing resilience during prolonged disruptions. This study contributes to the literature by integrating ripple effect assessment with network topology considerations, providing both theoretical insights and practical guidance for optimising supply chain design and management in the post-COVID era. [Submitted: 8 February 2024; Accepted: 3 September 2024]

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Publication Details

Journal
European J of Industrial Engineering
Published
2025-01-01
DOI
https://doi.org/10.1504/ejie.2025.148090
Primary Topic
Business Process Modeling and Analysis
Type
article
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article

Simulation-based ripple effect modelling in the supply chain: a network perspective

Kaixuan Hou, Zhanwen Niu, Yuzhao Zhang
European J of Industrial Engineering
Business Process Modeling and Analysis
article

Simulation-based ripple effect modelling in the supply chain: a network perspective

Kaixuan Hou, Zhanwen Niu, Yuzhao Zhang
article en

Abstract

This research investigates the ripple effects of supply chain disruptions across supply chain echelons and identifies vulnerable network characteristics. Utilising simulation methods, the study analyses the impact of disruption scale, propagation extent, and delay on supply chain performance. Employing AnyLogistix software, the study evaluates ripple effects across four different network structures under disruption scenarios resembling the COVID-19 pandemic, characterised by prolonged impacts on supply, demand, logistics, and uncertain recovery times. Comparative analysis across network structures reveals insights into recovery strategies, highlighting the influence of network characteristics on performance outcomes. The findings demonstrate that both disruption severity and propagation delay significantly affect supply chain performance, with high connectivity and betweenness centrality enhancing resilience during prolonged disruptions. This study contributes to the literature by integrating ripple effect assessment with network topology considerations, providing both theoretical insights and practical guidance for optimising supply chain design and management in the post-COVID era. [Submitted: 8 February 2024; Accepted: 3 September 2024]

European J of Industrial EngineeringVol. 20(3)
Tianjin University (CN)
Openalex Percentile: Top 63%
Business Process Modeling and Analysis
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Simulation-based ripple effect modelling in the supply chain: a network perspective — Kaixuan Hou, Zhanwen Niu, et al. · European J of Industrial Engineering (2025) | TGRS Research Map | TGRS