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基于企业客户互动价值的客户关系研究
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摘要
在以客户为中心的经济时代,企业越发认识到客户关系于自身战略发展的重要性,客户关系管理成为热门的研究与实践对象。但是,目前人们依然为过低的实施成功率而困扰。本文认为主要是对于客户关系的价值驱动因素的混淆和对于客户关系缺乏一个客观有效的评估方法所致。本文的研究就是针对上述问题。
     本文从企业与客户价值互动的角度系统地研究了客户关系,对于客户关系的价值互动本质、企业到客户的价值(B2C价值)以及客户到企业的价值(C2B价值)的定量评价指标体系和权重确定方法、基于企业与客户价值互动的客户关系评价、智能的客户价值及客户关系评价以及基于企业与客户互动价值的动态客户关系等五个方面进行了系统深入的研究。主要的研究内容如下:
     1.在从价值的视角研究客户关系的文献综述基础之上,系统地分析了企业与客户间的价值互动,提出从企业与客户双方来研究客户关系。以客户忠诚为平台,构建了企业到客户的价值以及客户到企业的价值的定量战略评价指标体系。进一步针对评价体系,提出利用德尔菲法和模糊层次分析法来确定评价指标体系的权重,并设计了模糊层次分析法的计算机程序。在此基础上,沿用通用电气矩阵的方法,构建了基于企业客户价值互动的客户关系评价模型,实现对客户关系的分类与评价,进而提出了不同类型的客户关系发展策略建议。在模型的应用基础上,提出了一种新的定量评价客户关系资产的方法。并将本文所提出的理论和方法,在某商业银行进行了案例研究。
     2.提出了基于支持向量机的智能客户关系评价方法。在支持向量机技术的理论以及基于支持向量机的回归模型基础之上,分别构建了基于支持向量机的B2C价值智能评价模型与C2B价值智能评价模型,并设计了基于支持向量机智能评价模型的计算机程序。案例仿真表明,基于支持向量机的B2C价值与C2B价值的评价是高效可行的。在此基础上进一步研究了智能的客户关系评价方法。
     3.研究了基于企业客户价值互动的动态客户关系模型。以客户生命周期理论框架为基础,利用吸收马尔可夫链为工具,建立了客户关系的动态发展模型。进一步,利用吸收马尔可夫链基本矩阵的特征,提出了客户关系生命周期价值的定量评价公式,分别用来定量评价在整个客户关系生命周期内,企业获得的生命周期价值和客户获得的生命周期价值以及客户关系的长期价值;进一步分析了客户生命周期价值计算公式中的变量对它的影响,并对于企业客户关系的发展提出了建议。
In the customer-centered economic era, it was found that relationship between customers and business is increasingly important. So customer relationship management has been the hot topic both in academic and practice fields. We, however, are still confused about the low rate of successful implementation of customer relationship management. The misunderstanding of the value-driven customer relationships and the lack of effective way to evaluate the customer relationships lead to the failure of customer relationships. This dissertation attempts to solve the problem.
     Customer relationships were studied systematically from a view of business-customer value interaction in this dissertation. Five topics are mainly included, such as (1) The interaction nature of value in customer relationships; (2) The assessment indexes of B2C value, which flows from the business to customer and the assessment indexes of C2B value, which flows from customer to business. Followed by the way of deciding the weights of assessment indexes; (3) Evaluation of customer relationships based on value interaction between Business and Customer; (4) Intelligent assessment of customer value and customer relationships; (5) Dynamic customer relationships based on business-customer value interaction. Generally, the major contents of this dissertation can be described as follows:
     1. Based on a systematic review of the existing literatures about value-view customer relationship, business-customer values interaction were systematically studied. Then, a dyadic value way to study customer relationships was put forward. With customer loyalty as medium, the assessment indexes of B2C value and C2B value were constructed. The Delphi method and the fuzzy hierarchical procedure, which was programmed, were used to decide the weights of the assessment systems. Using General Electronic Matrix, a model to evaluate the customer relationships was constructed. A new way to quantitatively assess the customer relationships asset was put forward. And then different advices for developing the different categories of customer relationships were given accordingly. The theory and method were used in a commercial bank as a case study.
     2. An intelligent assessment system of customer relationships was investigated based on support vector machine. After analysis of the theory of support vector machine, the assessment models for B2C value and C2B value were given. Then the models were implemented in computing language. The results of real data empirical experiments show its feasibility and efficiency.
     3. A new model of dynamic customer relationships based on business-customer interaction value was discussed. With Customer relationship lifetime cycle theory as framework, using absorbing Markov Chain, the model of dynamic customer relationships was constructed. A new quantitative way to assess the customer relationship lifetime value was put forward based on the features of the submatrice of the Markov chain, which not only for calculating the value of customer relationship lifetime for the Business, but also for the customer. And the factors that affect the customer relationship lifetime value were further analyzed. Management implications were then presented.
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