DSpace logo

Please use this identifier to cite or link to this item: http://dspace.bits-pilani.ac.in:8080/jspui/handle/123456789/10727
Full metadata record
DC FieldValueLanguage
dc.contributor.authorSharma, Satyendra Kumar-
dc.date.accessioned2023-05-09T09:56:51Z-
dc.date.available2023-05-09T09:56:51Z-
dc.date.issued2016-05-
dc.identifier.urihttps://www.tandfonline.com/doi/abs/10.1080/16258312.2015.11728693?journalCode=tscf20-
dc.identifier.urihttp://dspace.bits-pilani.ac.in:8080/xmlui/handle/123456789/10727-
dc.description.abstractThe 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.isoenen_US
dc.publisherTaylor & Francisen_US
dc.subjectManagementen_US
dc.subjectSupply Chainen_US
dc.subjectSupply chain risk assessmenten_US
dc.subjectBayesian networksen_US
dc.titleDeveloping a Bayesian Network Model for Supply Chain Risk Assessmenten_US
dc.typeArticleen_US
Appears in Collections:Department of Management

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.