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Research on supply network resilience considering the ripple effect with collaboration

Research on supply network resilience considering the ripple effect with collaboration Local disruptions can be propagated from one firm to another in a supply network (SN) and eventually influence the whole SN. Therefore, numerous studies on SN resilience considering the ripple effect have been reported recently. However, previous studies paid less attention to this phenomenon from a network structure perspective: if a firm is facing the risk of failure, then its partners may help it to mitigate the risk of failure by collaboration during the process of disruption propagation. Specifically, how SN structures (e.g. characterised by different scaling exponents) and other parameters (e.g. redundancy) influence the effectiveness of collaboration on improving SN resilience considering the ripple effect is not clear. Accordingly, we propose a ripple effect with collaboration (REC) model to consider the aforementioned phenomenon. We also present three new SN resilience metrics to evaluate SN resilience. Then, using both generated (by a novel SN generating model) and real-life SNs, we simulate the SN resilience considering REC under random and targeted disruptions. Our results demonstrate that the effectiveness of collaboration can be affected by SN structures and other parameters, and collaboration can even negatively affect SN resilience in some cases. We also summarise managerial implications and give future research directions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Production Research Taylor & Francis

Research on supply network resilience considering the ripple effect with collaboration

Research on supply network resilience considering the ripple effect with collaboration

International Journal of Production Research , Volume 60 (18): 18 – Sep 17, 2022

Abstract

Local disruptions can be propagated from one firm to another in a supply network (SN) and eventually influence the whole SN. Therefore, numerous studies on SN resilience considering the ripple effect have been reported recently. However, previous studies paid less attention to this phenomenon from a network structure perspective: if a firm is facing the risk of failure, then its partners may help it to mitigate the risk of failure by collaboration during the process of disruption propagation. Specifically, how SN structures (e.g. characterised by different scaling exponents) and other parameters (e.g. redundancy) influence the effectiveness of collaboration on improving SN resilience considering the ripple effect is not clear. Accordingly, we propose a ripple effect with collaboration (REC) model to consider the aforementioned phenomenon. We also present three new SN resilience metrics to evaluate SN resilience. Then, using both generated (by a novel SN generating model) and real-life SNs, we simulate the SN resilience considering REC under random and targeted disruptions. Our results demonstrate that the effectiveness of collaboration can be affected by SN structures and other parameters, and collaboration can even negatively affect SN resilience in some cases. We also summarise managerial implications and give future research directions.

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References (110)

Publisher
Taylor & Francis
Copyright
© 2021 Informa UK Limited, trading as Taylor & Francis Group
ISSN
1366-588X
eISSN
0020-7543
DOI
10.1080/00207543.2021.1966117
Publisher site
See Article on Publisher Site

Abstract

Local disruptions can be propagated from one firm to another in a supply network (SN) and eventually influence the whole SN. Therefore, numerous studies on SN resilience considering the ripple effect have been reported recently. However, previous studies paid less attention to this phenomenon from a network structure perspective: if a firm is facing the risk of failure, then its partners may help it to mitigate the risk of failure by collaboration during the process of disruption propagation. Specifically, how SN structures (e.g. characterised by different scaling exponents) and other parameters (e.g. redundancy) influence the effectiveness of collaboration on improving SN resilience considering the ripple effect is not clear. Accordingly, we propose a ripple effect with collaboration (REC) model to consider the aforementioned phenomenon. We also present three new SN resilience metrics to evaluate SN resilience. Then, using both generated (by a novel SN generating model) and real-life SNs, we simulate the SN resilience considering REC under random and targeted disruptions. Our results demonstrate that the effectiveness of collaboration can be affected by SN structures and other parameters, and collaboration can even negatively affect SN resilience in some cases. We also summarise managerial implications and give future research directions.

Journal

International Journal of Production ResearchTaylor & Francis

Published: Sep 17, 2022

Keywords: Supply network; supply network resilience; ripple effect; collaboration; supply network disruption

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