信息不对称条件下产品供应链质量协同研究

The quality effort provided by the suppliers or manufactures are generally unobservable along a supply chain. Hence, supply chain quality management concerns the design of incentive mechanisms to reduce the ex post moral hazard. However, when the outsourcing contract is built, the supply chain participants may have hidden type information (e.g., quality improvement cost and product manufacturability), and the quality incentive mechanisms heavily depend on that information. In this study, we address the supply chain quality management problems with both hidden action and hidden types. Both Stackelberg and bilateral bargaining game approaches are used to analyze the screening, signaling and incentive policies along a supply chain. In addition, a principal-agent model with multiple agents is developed for the incentive mechanism in a supply chain with multiple suppliers, who may help or compete with each other. A signaling model is developed for the warranty length and pricing decision of two competitive manufacturers, whose quality is unobservable for the customers. Some case studies are conducted and empirical data are collected to test and verify the findings from these models. It is expected to obtain innovative theories and methods for supply chain quality management with asymmetric information and shed lights for practices.

由于质量努力水平不可观察或不可合同化，供应链质量管理考虑如何设计有效的激励机制以抑制合同签订后的道德风险。在合同签订时，供应链成员间还往往拥有不对称的质量改进成本、产品可制造性等类型信息，而激励机制的设计严密依赖于这些信息。本课题拟考虑隐藏的类型（事前的道德风险）、隐藏的行为（事后的道德风险）两类不对称信息，应用斯坦伯格和讨价还价博弈方法，研究供应链成员间的信息甄别、信号传递以及质量奖惩机制设计策略。在此基础上，针对供应商间存在团队合作或质量竞争关系的多供应商-单制造商供应链，构建多代理人委托代理模型；并针对质量信息不对称条件下竞争性制造商的保修与产品定价联合决策问题，建立多制造商信号传递博弈模型，为复杂结构供应链上的质量协同提出管理对策。最后，通过案例和实证研究，对理论结果进行检验和修正。本项目有望为信息不对称条件下供应链质量管理提出新理论与方法，为企业实践提供理论指导和方法支持

由于质量努力水平不可观察或不可合同化，供应链质量管理考虑如何设计有效的激励机制以抑制合同签订后的道德风险。在合同签订时，供应链成员之间还往往拥有不对称的产品可制造性等类型信息，而激励机制的设计严密依赖于这些信息。本课题应用斯坦伯格和讨价还价博弈方法，研究供应链之成员间的信息甄别、信号传递以及质量奖惩机制设计策略。在此基础上，针对供应商之间存在团队合作或质量竞争关系的多供应商-单制造商供应链，构建了多代理人委托代理模型；并针对质量信息不对称条件下竞争性制造商的保修与产品定价联合决策问题，建立多制造商信号传递博弈模型，为复杂供应链结构上的质量协同提出了管理对策。

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