供应链环境下客户满意度评价的未确知均值聚类模型

Client Satisfaction Degree of Supply Chain Based on Unascertained Means Cluster

未确知均值聚类结合未确知理论和聚类理论构造未确知测度作为集合隶属度来表示样本与各类间的隶属关系.从产品合格、柔性、可靠性等几方面对影响供应链客户满意度的因素进行分析,构建供应链环境下的客户满意度评价指标体系.在此基础上,应用未确知均值聚类理论对供应链环境下的客户满意度进行综合评价,得出聚类结果,找出各类类中心,并给出样本属于各类的隶属度,较好的解决了对供应链环境下客户满意度的分类问题,最后以实例来论证该方法的可行性和有效性.

The unascertained means clusters methods conjoins with unascertained theory and clusters theory to establish unascertained measure as a muster to denote the subjection relations between the samples and the classifications. The paper analysis the affecting factors of supply chain client satisfaction degree from production eligibility, flexibility, reliability etc to establish the appraisal index system based on supply. And then, apply the unascertained means cluster theory to cluster the client satisfaction degree to find the center of the clusters. And then, the subjection degrees of all the samples are also given. It resolves the client satisfaction degree based on supply chain cluster problem well. At last, the examples are used to verify that the method is useful and validity.