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- W4212825009 endingPage "180" @default.
- W4212825009 startingPage "158" @default.
- W4212825009 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." @default.
- W4212825009 created "2022-02-24" @default.
- W4212825009 creator A5059431029 @default.
- W4212825009 creator A5061484983 @default.
- W4212825009 creator A5076107815 @default.
- W4212825009 date "2022-02-16" @default.
- W4212825009 modified "2023-09-25" @default.
- W4212825009 title "Supply-side risk modelling using Bayesian network approach" @default.
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