An approach to evaluating the spontaneous ana contagious credit risk for supply chain enterprises based on fuzzy preference relations

被引：18

作者：

Gu, Jing ^{[1
]}

Xia, Xiongxing ^{[4
]}

He, Yue ^{[2
]}

Xu, Zeshui ^{[2
,3
]}

机构：

[1] Sichuan Univ, Sch Econ, Chengdu 610064, Peoples R China

[2] Sichuan Univ, Sch Business, Chengdu 610064, Peoples R China

[3] Nanjing Univ Informat Sci & Technol, Sch Comp & Software, Nanjing 210044, Jiangsu, Peoples R China

[4] Univ Int Business & Econ, Sch Banking & Finance, Beijing 100029, Peoples R China

来源：

COMPUTERS & INDUSTRIAL ENGINEERING | 2017年 / 106卷

基金：

中国国家自然科学基金;

关键词：

Credit risk; Contagious effect; Fuzzy preference relation; Matrix analysis; Supply chain enterprise; GROUP DECISION-MAKING; HESITANT INFORMATION; SQUARE METHOD; PRIORITY; DEFAULT; VECTOR; MODEL;

D O I：

10.1016/j.cie.2017.02.012

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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. (C) 2017 Elsevier Ltd. All rights reserved.

引用

页码：361 / 372

页数：12

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