یک رویکرد به ارزیابی ریسک اعتباری خودآموز و مسری برای شرکتهای زنجیره تامین براساس روابط ترجیحی فازی

Measuring credit risk for supply chain enterprises is a critical issue for credit agencies and it becomes more complicated thanks to interrelated transactions among enterprises across the supply chain. Firstly, we put forward a basic model for assessing supply chain enterprise credit risk by splitting overall credit risk into spontaneous and contagious credit risk. Secondly, after constructing an evaluation indicator system for supply chain enterprises, we determine spontaneous credit risk by employing fuzzy preference relations. Thirdly, we establish a risk numerical matrix to measure contagious credit risk based on spontaneous credit risk and analyze its cumulative effect using a matrix analysis. Finally, a real-world case study is presented to illustrate how the proposed model can be applied to assess supply chain enterprise credit risk.