Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6896829 | European Journal of Operational Research | 2015 | 31 Pages |
Abstract
There are numerous examples of supply chain disruptions that have occurred which have had devastating impacts not only on a single firm but also on various other firms in the supply network. We utilize a Bayesian Network (BN) approach and develop a model of risk propagation in a supply network. The model takes into account the inter-dependencies among different risks, as well as the idiosyncrasies of a supply chain network structure. Specific risk measures are derived from this model and a simulation study is utilized to illustrate how these measures can be used in a supply chain setting.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Myles D. Garvey, Steven Carnovale, Sengun Yeniyurt,