A SUPPLY CHAIN RISK EVALUATION MODEL BASED ON INTEGRATION OF DATA CHARACTERISTICS AND SUBJECTIVE PREFERENCE
Keywords:Index weights, Data characteristics, Subjective preference, Relative entropy
In order to assess supply chain risks quantitatively, a multi-attribute group decision-making evaluation model that integrating the data characteristics of decision matrix and subjective preferences of expert groups is proposed. The objective weights of the indicators are obtained based on the data characteristics of the decision matrix, and then the subjective weights of the indicators are obtained on the basis of the preference information of the expert group about the importance of the indicators. The comprehensive weight of the indicator is determined by the convex combination of the objective and subjective weights. Finally, comprehensive evaluation are performed for the evaluation objects. The model has a small amount of calculation and is easy to operate. A case study has verified the validity and practicability of the model.