基于主成分和灰色层次关联的供应链金融信用风险研究  

Credit Risk Analysis of Supply Chain Finance Based on Principal Component Analysis and Gray Multi-hierarchy Relational Analysis

作　　者：李佳桐[1] 刘媛华[1] 

机构地区：[1]上海理工大学管理学院,上海200093

出　　处：《物流科技》2014年第11期16-21,共6页Logistics Sci-Tech

基　　金：教育部人文社会科学基金项目;项目编号:12YJC630127

摘　　要：我国的供应链金融正处在一个全面发展阶段,如何能有效地规避其信用风险具有十分重要的研究意义。文章在根据供应链信用风险来源的基础上,建立综合的信用风险评价指标体系,运用主成分分析法,筛选出关键指标,又通过层次分析法与灰色关联系数结合,得到综合关联度,从而建立信用风险度量模型,确立银行的最佳授信对象,有效地减少银行的信贷风险和维持了整条供应链的稳定性。Our supply chain finance is at a stage of compre-hensive development, how to effectively avoid the risk of credit has important research significance. This article on the basis of the sources of supply chain credit risk, established a comprehensive credit risk evaluation indexes, thenbased on principal component analysis to selected key indicators, estab-lished the indexes weight by analytic hierarchy process, and combined with the gray relational coefficients to obtain syn-thetically relational degree, which could establish credit risk measurement model to choose the best credit target for banks, which effectively reducing the bank＇s credit risk and maintain-ing the stability of the whole supply chain.

关 键 词：供应链金融 主成分分析 层次分析法 灰色关联度 

分 类 号：F275.6[经济管理—企业管理]