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Disruption propagation and resilience optimization in complex supply networks: considering enterprises’ heterogeneity

Disruption propagation and resilience optimization in complex supply networks: considering... The impacts of enterprise disruptions may propagate across the entire supply network (SN), inducing ripple effects. Resilience enables enterprises’ survival during disruption propagation and ensures the viability and competitiveness of SNs. This study develops a novel model that considers enterprises’ heterogeneity to capture the dynamic process of disruption propagation in SNs. Drawing on business ecosystem theory, the study characterizes enterprises’ heterogeneity by classifying their ecological niches as high, medium, and low. After analyzing the dynamic process of disruption propagation, the study then conducts a novel investigation into the impact of enhancing enterprises’ resilience, including robustness and recoverability, on optimizing SN resilience (SNR) under random disruption and targeted disruption. This impact is investigated through multivariate simulation experiments and univariate regression analysis based on an electric vehicle SN. The results show that, firstly, enhancing enterprises’ resilience in three ecological simultaneously is effective in optimizing SNR, and improving recoverability is more effective than improving robustness. Secondly, for enterprises in high and medium ecological niches, improving their recoverability is more effective than improving robustness, while in the low ecological niche, improving recoverability is ineffective. Moreover, improving the enterprises' resilience in the medium ecological niche has the greatest impact on optimizing SNR than in other ecological niches. Thirdly, the effects of enhancing enterprises’ resilience on SNR optimization in random disruption and targeted disruption are different. This research provides a theoretical foundation for better understanding the dynamics of disruption propagation in SNs and optimizing SNR from the view of complex networks by considering the enterprises’ heterogeneity. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of Operations Research Springer Journals

Disruption propagation and resilience optimization in complex supply networks: considering enterprises’ heterogeneity

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References (109)

Publisher
Springer Journals
Copyright
Copyright © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025
ISSN
0254-5330
eISSN
1572-9338
DOI
10.1007/s10479-025-06664-y
Publisher site
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Abstract

The impacts of enterprise disruptions may propagate across the entire supply network (SN), inducing ripple effects. Resilience enables enterprises’ survival during disruption propagation and ensures the viability and competitiveness of SNs. This study develops a novel model that considers enterprises’ heterogeneity to capture the dynamic process of disruption propagation in SNs. Drawing on business ecosystem theory, the study characterizes enterprises’ heterogeneity by classifying their ecological niches as high, medium, and low. After analyzing the dynamic process of disruption propagation, the study then conducts a novel investigation into the impact of enhancing enterprises’ resilience, including robustness and recoverability, on optimizing SN resilience (SNR) under random disruption and targeted disruption. This impact is investigated through multivariate simulation experiments and univariate regression analysis based on an electric vehicle SN. The results show that, firstly, enhancing enterprises’ resilience in three ecological simultaneously is effective in optimizing SNR, and improving recoverability is more effective than improving robustness. Secondly, for enterprises in high and medium ecological niches, improving their recoverability is more effective than improving robustness, while in the low ecological niche, improving recoverability is ineffective. Moreover, improving the enterprises' resilience in the medium ecological niche has the greatest impact on optimizing SNR than in other ecological niches. Thirdly, the effects of enhancing enterprises’ resilience on SNR optimization in random disruption and targeted disruption are different. This research provides a theoretical foundation for better understanding the dynamics of disruption propagation in SNs and optimizing SNR from the view of complex networks by considering the enterprises’ heterogeneity.

Journal

Annals of Operations Research – Springer Journals

Published: Jun 10, 2025

Keywords: Disruption propagation; Supply network resilience; Enterprises’ heterogeneity; Complex network; Business ecosystem

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