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机构地区:[1]广东工业大学经济管理学院,广东广州510520
出 处:《系统工程》2007年第5期82-86,共5页Systems Engineering
基 金:广东省自然科学基金资助项目(06021495);广州市社科基金资助项目(YZE-58)
摘 要:随着零售商在与制造商的博弈中不断成长以及零售行业竞争的激化,现代零售商逐渐加强了对自有品牌的经营管理力度。零售商甄选自有品牌制造商并与其形成委托代理关系,然而,该委托代理关系的建立和控制过程中存在广泛的信息不对称。本文探讨从契约签订前、后两方面来规避信息不对称带来的风险;综合运用较主观的层次分析法和较客观的人工智能神经网络方法,提出在信息不对称情况下零售商选择委托代理制造商的评价模型和指标以及委托制造商选择后的风险规避方法。Along with retailers unceasingly growing in the contact games with manufacturers and fierce competition in retailing industry, modernized retailers are gradually increasing concern on the management of private brands. However, asymmetric information issue widely exists in the choice of manufacturers that produce private brand commodity. The paper explores how to evade the risks resulting from asymmetric information from the forward and afterward aspects of contracts signed. By comprehensively using the subjective method of Analytic Hierarchy Process and the objective method of Artificial Intelligence Neural Network, the paper brings up the evaluation indexes and methods that retailers choose agency-byagreement manufacturers, and the methods to evade the risks after choosing them.
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