A supply chain risk assessment model based on multistage influence diagram

2009 ◽  
Author(s):  
Zhengchi Liu ◽  
Mingyong Lai ◽  
Tang Zhou ◽  
Yang Zhou
Keyword(s):  
Risk Assessment ◽  
Supply Chain ◽  
Assessment Model ◽  
Influence Diagram ◽  
Risk Assessment Model ◽  
Supply Chain Risk ◽  
Model Based

Evaluation of Electronic Products OEM Industry Supply Chain Risk Based on Fuzzy Influence Diagram

2013 ◽  
Vol 380-384 ◽  
pp. 4740-4744
Author(s):  
Xiao Feng Zhou ◽  
Hong Lv ◽  
Shi Wei Xu
Keyword(s):  
Risk Assessment ◽  
Supply Chain ◽  
Model Evaluation ◽  
Assessment Model ◽  
Influence Diagram ◽  
Risk Assessment Model ◽  
Supply Chain Risk ◽  
Diagram Method ◽  
Electronic Products

The method of fuzzy influence diagram is a very effective way when assessing the supply chain risk of electronic products foundries. Firstly, this paper puts forward a idea that using the fuzzy influence diagram method to assess the supply chain risk of electronic products OEM industry. Then construct a supply chain risk assessment model of electronic products OEM industry which is based on fuzzy influence diagram. Through the two points, we can determine how much the probability of risk events and the damage is. Except that, this paper also introduces the steps of model evaluation briefly.

Supply Chain Risk Evaluation Based on Bayesian Network

2013 ◽  
Vol 680 ◽  
pp. 550-553
Author(s):  
Bo Chao Liu
Keyword(s):  
Risk Assessment ◽  
Supply Chain ◽  
Bayesian Network ◽  
Risk Evaluation ◽  
Evaluation Model ◽  
Assessment Model ◽  
Risk Assessment Model ◽  
Supply Chain Risk ◽  
Logistics Company ◽  
Proposed Model

The evaluation for supply chain risk is very important to show the latent risk and eliminate the risk. In the study, Bayesian network is proposed to evaluate the supply chain risk. The assessment indexes of supply chain risk are analyzed before supply chain risk assessment. Then, the assessment indexes of supply chain risk can be used to construct the supply chain risk assessment model. We apply a certain logistics company to study the evaluation ability of Bayesian network evaluation model proposed here. The experimental results prove the effectiveness of the proposed model.

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