Supply-side risk modelling using Bayesian network approach

Abstract

Organisations’ vulnerability to risks exponentially increased in the past decade, thereby highlighting the need to develop additional effective risk management strategies. This research uses a systematic literature review as a foundation for designing a supply risk model that uses a Bayesian belief network. The proposed model aims to identify the most critical objective and subjective risk factors influencing supply chain networks. Moreover, the proposed methodology has been demonstrated through a case study conducted in an Indian manufacturing, in which inputs were taken from supply chain and risk management experts. Hugin Expert software was used to design and run simultaneous simulations on the Bayesian network. The top three factors found to influence business profitability were delays, product technology, and fuel price. The proposed model can be reengineered as conditions change and new information becomes available, thereby ensuring that risk analysis remains current and relevant along the timeline of the any disruption.