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基于资源观点的供应链核心企业识别分析
引用本文:肖玉明.基于资源观点的供应链核心企业识别分析[J].科技管理研究,2015(6):202-205.
作者姓名:肖玉明
作者单位:四川大学商学院,四川成都,610064
基金项目:国家自然科学基金资助项目“引入虚拟第三方的供应链激励协调与效率研究”(71071103);教育部人文社科西部和边疆地区项目青年项目“双方逆向选择下供应链协调与效率研究”(13XJC630014)
摘    要:基于资源的观点,从企业投入到供应链的资源这个角度分析供应链核心企业的识别问题。从资源对供应链的重要性和资源数量在供应链中的分布两个方面对供应链各节点企业进行评价。用重要性权重度量各种资源对供应链的重要性,用熵权度量资源在供应链中的分布情况,将重要性权重和熵权进行综合得到各资源的综合权重,在此基础上对各节点企业进行综合评价,从而确认谁是核心企业。最后用论文提出的方法进行算例分析。

关 键 词:供应链  核心企业  基于资源观点  (RBV)  熵权
收稿时间:2014/5/11 0:00:00
修稿时间:2014/5/11 0:00:00

Identification Analysis on Core Enterprise of Supply Chain Based on Resource-based View
XIAO Yuming.Identification Analysis on Core Enterprise of Supply Chain Based on Resource-based View[J].Science and Technology Management Research,2015(6):202-205.
Authors:XIAO Yuming
Institution:XIAO Yuming;School of Business,Sichuan University;
Abstract:Based on the resource-based view,this paper analyses the identification problem of core enterprise of supply chain from the perspective of the resourses invested in the supply chain by the node enterprises(In fact,this is also an evaluating problem). Every node enterprise is evaluated from two aspects of importance and quantity of the resources. The importance of the resources is measured by an importance weight.The distributions of the resources are measured by entropy weights.The synthetic weights of resources are obtained by synthesizing the two weights. On the basis of calculating the synthetic weights of the resources,Every node enterprise is evaluated with the synthetic weights. Thus,which node enterprise is the core enterprise is affirmed, the enterprise obtaining the highest score is the core enterprise.The importance weight is obtained by means of Analytic Hierarchy Process(AHP).So,it possesses some subjectivity. Only objective datum are used when calculating entropy weight.So it is not influenced by subjective factors.Finally,an example is analysed in order to explain how to use the method put forward in this paper.
Keywords:supply chain  core enterprise  resource -based view (RBV)  entropy weight
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