Bayesian Network Modelling for Supply Chain Risk Propagation
Ojha, R., Ghadge, A., Tiwari, MK. and Bititci, U. (2018), “Bayesian network modelling for supply chain risk propagation”, International Journal of Production Research, Forthcoming
37 Pages Posted: 29 Apr 2018
Date Written: April 10, 2018
Supply chain risk propagation is a cascading effect of risks on global supply chain networks. The paper attempts to measure the behaviour of risks following the assessment of supply chain risk propagation. Bayesian network theory is used to analyse the multi-echelon network faced with simultaneous disruptions. The ripple effect of node disruption is evaluated using metrics like fragility, service level, inventory cost and lost sales. Developed risk exposure and resilience indices support in assessing the vulnerability and adaptability of each node in the supply chain network. The research provides a holistic measurement approach for predicting the complex behaviour of risk propagation for improved supply chain risk management.
Keywords: Supply chain risk management, Risk propagation, Ripple effect, Risk modelling, Bayesian network, Supply chain disruptions, Uncertainty modelling
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