dc.contributor.author |
Sharma, Satyendra Kumar |
|
dc.date.accessioned |
2023-05-09T09:56:51Z |
|
dc.date.available |
2023-05-09T09:56:51Z |
|
dc.date.issued |
2016-05 |
|
dc.identifier.uri |
https://www.tandfonline.com/doi/abs/10.1080/16258312.2015.11728693?journalCode=tscf20 |
|
dc.identifier.uri |
http://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/10727 |
|
dc.description.abstract |
The Bayesian network based probability model is very new to the field of business management. Its use for risk assessment to predict the supply chain disruption and their consequences on the supply chain goals is very limited. The purpose of this research, is to develop a risk assessment tool to assess and to determine the risk exposure faced by a supply chain. In a global economy with ever-growing competition the firms are facing uncertain disruptions in their supply chains that further dent their brand value. The proposed probabilistic model that updates itself in the light of new evidences and calculates marginal probabilities for all risk variables and supply chain goals through conditional probability tables. The proposed model empowers the supply chain managers to predict the chances of any disruptive risk factors in the supply chain. |
en_US |
dc.language.iso |
en |
en_US |
dc.publisher |
Taylor & Francis |
en_US |
dc.subject |
Management |
en_US |
dc.subject |
Supply Chain |
en_US |
dc.subject |
Supply chain risk assessment |
en_US |
dc.subject |
Bayesian networks |
en_US |
dc.title |
Developing a Bayesian Network Model for Supply Chain Risk Assessment |
en_US |
dc.type |
Article |
en_US |