供应链伙伴关系诊断管理研究

Supply chain partnerships diagnosis management

为监控供应链节点企业之间信任的合作状态,提出了供应链伙伴关系诊断管理。应用集成规则推理、案例推理和支持向量机,共同应对供应链伙伴关系诊断管理问题。首先,描述了供应链伙伴关系诊断管理的概念。然后,进行了供应链伙伴关系诊断运作的详细分析。在其基础上,综合规则推理、案例推理和支持向量机的优势,构建了一种新型的混合推理方法,以支撑供应链伙伴关系协同诊断。建立了供应链伙伴关系诊断混合推理的过程与结构。最后,在节点企业意愿信任诊断中应用了该管理过程。

To monitor cooperation status for supply chain partners, Supply Chain Partnerships Diagnosis Management （SC-PDM） was proposed. Rule-Based Reasoning （RBR）, Case-Based Reasoning （CBR） and Support Vector Machines （SVM） were integrated to support the diagnosis mafiagement. The concept of supply chain partnerships diagnosis management was firstly defined. Furthermore, operation of supply chain partnerships diagnosis was analyzed in detail. Then, a new hybrid reasoning method on partnerships diagnosis based on RBR, CBR, and SVM was set up to support collaborative diagnosis for supply chain partnership. Finally, SC-PDM was applied into goodwill trust diagnosis of supply chain partners.