A new robust dynamic Bayesian network approach for disruption risk assessment under the supply chain ripple effect

Ripple effect and supply chain disruption management: new trends and research directions

“…in Industry 4.0 and digital SC systems (Ivanov and The model allows to maximise the SC total profit over multiple periods and to minimise the total travel times for unsatisfied customers, whose demands must be met by retailers to maximise the SC responsiveness (continued). Network design level Impact of the ripple effect on SC resilience and robustness;Sensitivity of different SC designs to the ripple effect;Criticality of some nodes/arcs in the SC for the ripple effect dispersal Lei et al (2020), Dubey et al (2020), Mishra et al (2020), Brintrup, Chauhan, and Perera (2020), Liu et al (2020) Process planning level Proactive policies to mitigate the ripple effect (i.e. inventory and capacity buffers, backup sourcing, product substitution) Ma, He, and Gu (2020), Özçelik, Yılmaz, and Yeni (2020), Azaron, Venkatadri, and Doost (2020), Jahani et al (2020), Gholami-Zanjani et al (2020) Operative control level Reactive policy deployments for ripple effect control and recovery Choi (2020), Lee, Yoon, and Lee (2020) Table 1 provides an overview of the papers included in this special issue, their methodologies and major outcomes.…”

Energy Resilience Impact of Supply Chain Network Disruption to Military Microgrids

“…The process of generating accurate CPTs and DTMCs becomes exhaustive, especially in cases with insufficient sample data. Future iterations of this methodology should consider other processes, such as noisyor modeling or Liu et al's [142] SA algorithm. Finally, the developed metric, E M , only pertains to a specific installation.…”

“…Specifically, the accuracy of CPTs is heavily dependent on expert elicitation or historical data, which may or may not be readily available [140,141]. To cope with the challenges of a scant data environment, Liu et al [142] introduced a robust DBN optimization model for small-size instances and a simulated annealing (SA) algorithm to handle larger-scale problems.…”

Deploying Industry 4.0 Enablers to Strengthen Supply Chain Resilience to Mitigate Ripple Effects: An Empirical Study of Top Relay Manufacturer in China

“…Shaheen et al (2020) asserts that the ripple effect is characterized by downstream supply chain disruptions, which can affect the performance of the entire supply chain [50]. Moreover, Liu et al (2019) argues that under the ripple effect, the risk of disruption is a challenge that all companies must face [51].…”