Bayesian Belief Network Approach for Supply Risk Modelling

Bayesian Belief Network Approach for Supply Risk Modelling

Anil Jindal, Satyendra Kumar Sharma, Srikanta Routroy
Copyright: © 2022 |Pages: 17
DOI: 10.4018/IJISSCM.2022010102
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Abstract

Today’s global and complex world increased the vulnerability to risks exponentially and organizations are compelled to develop effective risk management strategies for its mitigation. The prime focus of research is to design a supply risk model using Bayesian Belief Network bear in mind the tie-in of risk factors (i.e. objective and subjective) those are critical to a supply chain network. The proposed model can be re-engineered as per new information available at disclosure, so risk analysis will be current and relevant along the timeline as so situation is strained. The top three factors which influenced profitability were transportation risk and price risks. Netica is the platform used for designing and running simultaneous simulations on the Bayesian Network. The proposed methodology is demonstrated through a case study conducted in an Indian manufacturing supply chain taking inputs from supply chain/risk management experts. .
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2. Literature Review

The first step in supply chain risk management is to identify the risks associated with supply chain network from supplier end and to find their possible drivers. Therefore to identify the possible sources of risks in supply chain network a through literature review of the published papers is done and summarised in Table 1.

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