信息经济时代的客户知识模型

客户知识由客户界定，沟通渠道，客户需求，客户行为以及客户赢利价值五个层次组成。其中每个知识层次都是包含该层次具体内容的客户知识子集。客户知识的掌握是一个过程，它从了解客户的基本信息以实现对客户进行界定开始，到识别客户对企业的赢利价值这一客户知识的核心。客户知识是制定“以客户为中心”的整合营销行动计划的基础。     

面向顾客资产的三维顾客细分模型及其应用

简单依照顾客利润贡献对顾客细分未能充分考虑顾客的无形贡献,会低估顾客对企业的价值.从面向顾客资产的视角进行顾客细分,可以兼顾到顾客当前的利润贡献和顾客的潜在有形和无形贡献,从而提出基于顾客当前显性贡献、潜在显性贡献和潜在隐性贡献三维顾客细分模型及度量方法,并结合实证阐述顾客细分方法的实现过程.     

基于报表数据的上市公司顾客资产测量与提升——中国联通公司的应用研究

顾客资产体现企业在市场竞争中获取顾客资源的能力,本研究旨在利用报表数据对上市公司的顾客资产进行测量,并依据测量结果提出提升策略。首先,运用Matlab编程模拟上市公司的每期期末顾客存量适用的技术替代模型,进而求得顾客资产。其次,依据β转换模型原理估算企业现有顾客的终身价值总和,在同时考虑顾客的获取与流失的前提下求得顾客资产可持续比率。再次,依据顾客资产可持续比率和顾客资产的计算结果构建二维坐标图,以分析企业顾客资产的时间序列特征,作为提升顾客资产的依据。最后,将该方法在中国联通公司进行了应用。研究结果表明,该方法对上市公司的顾客资产测量和提升具有较好的适用性和可操作性。研究结果对于上市公司的顾客资产管理具有一定的参考价值。     

Multi-server queueing system with a generalized phase-type service time distribution as a model of call center with a call-back option

A multi-server queueing system with a Markovian arrival process and finite and infinite buffers to model a call center with a call-back option is investigated. If all servers are busy during the customer arrival epoch, the customer may leave the system forever or move to the buffer (such a customer is referred to as a real customer), or, alternatively, request for call-back (such a customer is referred to as a virtual customer). During a waiting period, a real customer can be impatient and may leave the system without service or request for call-back (becomes a virtual customer). The service time of a customer and the dial time to a virtual customer for a server have a phase-type distribution. To simplify the investigation of the system we introduce the notion of a generalized phase-type service time distribution. We determine the stationary distribution of the system states and derive the Laplace–Stieltjes transforms of the sojourn and waiting time distributions for real and virtual customers. Some key performance measures are calculated and numerical results are presented.     

基于指数标度的G1-概率系数法和熵的需求重要度修正

顾客需求重要度的获取是进行顾客需求综合分析过程的一个重要环节,它的确定对质量屋的优化以及之后的优化决策有着重要的作用.科学准确地计算顾客需求重要度有助于企业有针对性的生产满足顾客需求的产品,从而提高顾客满意度,增强市场竞争力.基于QFD理论,文章从顾客和专家双视角出发收集数据,采用指数标度的G1-概率系数法代替传统的权重概率综合系数法来确定顾客初始需求权重,并结合市场竞争性因素对初始需求权重进行修正,简单准确地确定了顾客需求重要度,并通过IT外包案例验证了该方法的实效性.     

客户关系动态优化模型与实证研究

提出了客户关系与营销活动的动态交互模型,以长期收益最大化为目标,优化企业的营销活动。模型假设客户关系可离散为几个层级状态,并设客户关系所处状态受营销活动的影响而动态的变化,服从马尔可夫决策过程。客户关系状态所处层级不可直接观测,但其与客户购买水平有概率相关关系。提出模型参数估计的最大似然估计方法。以国内某企业的客户关系管理数据为例,说明了模型变量的定义方法,通过客户交互历史数据估计模型参数,并对客户管理策略进行优化。结果表明,最优策略管理下期望提升客户价值61％～82％。     

Simple Heuristics for the Vehicle Routeing Problem with Soft Time Windows

We describe three simple heuristics for the vehicle routeing problem with customer time windows that can be violated by paying appropriate penalties. The customer demands are known, and a homogeneous fleet of vehicles stationed at a single depot is considered. The penalty payable to a customer is assumed to be a linear function of the amount of time window violation. Upper limits are imposed on both the penalty payable and the waiting time allowed at any customer. At each customer in a route, the PC-based heuristics simultaneously determine the actual time to begin service, and the next customer to serve. To achieve this, each heuristic uses different measures to compare the cost of waiting and penalty payable, with the benefit obtained by leaving immediately for the next customer. Computational results on a set of benchmark problems show that the procedure is efficient and enables significant reduction in the number of vehicles required and/or the total route distances while controlling both customer penalties and waiting times.     

客户价值研究及其对客户关系管理绩效的影响

客户价值研究是客户关系管理研究中的重要内容，本基于客户视角对客户价值进行分析，提出客户价值应包含五个关键维度：功能价值、社会价值、情感价值、知识价值和感知牺牲。同时建立了客户价值对基于客户行为的客户关系管理(CRM)绩效的影响理论模型并提出相关假设，然后通过实证分析验证该假设，最后讨论了实证结果及其对客户关系管理实践的指导意义。     

A queueing model for crowdsourcing

Crowdsourcing is getting popular after a number of industries such as food, consumer products, hotels, electronics, and other large retailers bought into this idea of serving customers. In this paper, we introduce a multi-server queueing model in the context of crowdsourcing. We assume that two types, say, Type 1 and Type 2, of customers arrive to a c-server queueing system. A Type 1 customer has to receive service by one of c servers while a Type 2 customer may be served by a Type 1 customer who is available to act as a server soon after getting a service or by one of c servers. We assume that a Type 1 customer will be available for serving a Type 2 customer (provided there is at least one Type 2 customer waiting in the queue at the time of the service completion of that Type 1 customer) with probability \(p, 0 \le p \le 1\). With probability \(q = 1 - p\), a Type 1 customer will opt out of serving a Type 2 customer provided there is at least one Type 2 customer waiting in the system. Upon completion of a service a free server will offer service to a Type 1 customer on an FCFS basis; however, if there are no Type 1 customers waiting in the system, the server will serve a Type 2 customer if there is one present in the queue. If a Type 1 customer decides to serve a Type 2 customer, for our analysis purposes that Type 2 customer will be removed from the system as Type 1 customer will leave the system with that Type 2 customer. Under the assumption of exponential services for both types of customers we study the model in steady state using matrix analytic methods and establish some results including explicit ones for the waiting time distributions. Some illustrative numerical examples are presented.     

基于人工神经网络的客户价值评价体系

企业对客户价值的评价是进行客户分类及实施客户策略的依据,也是实现客户关系管理的核心所在.客户为企业带来的价值本身是具有层次性和动态性,然基于客户全生命周期的客户终生价值计算方法显然无法将其动态发展过程准确的考虑在内,也就无法规避其计算结果所带来的误差风险.因此,在现有客户价值评价理论的基础上,结合客户生命周期理论,以企业与客户的双赢为最终目标,提出分阶段细化的评价思想,构建完善的评价体系,并根据该指标体系的指标特性选择人工神经网络作为评价方法,给出模型求解,最后依据此评价结果对客户分类及营销策略进行相关的分析.     

基于期望视角的感知服务质量与顾客满意度区别研究

从期望出发,比较顾客视角的感知服务质量与满意度的区别。首先对期望概念进行明确界定,借鉴卡诺模型分类方法划分期望类别,基于重要性维度得到期望的三个类别:核心属性期望、重要属性期望和附加属性期望。以餐饮行业为实证研究背景,比较期望视角下的顾客满意度和感知服务质量的区别。发现核心属性期望、重要属性期望对顾客的服务质量评价影响更大,而附加属性期望对顾客的满意度评价影响更大。最后,给出企业对顾客期望、服务质量与顾客满意度的管理意义。     

On the customer lifetime value: a mathematical perspective

The customer lifetime value (CLV) is an important concept increasingly considered in the field of general marketing and in the management of firms, of organizations to increase the captured profitability. It represents the total value that a customer produces during his or her lifetime, or better represents the measure of the potential profit generating by a customer. The companies use the customer lifetime value to segment customers, analyze probability of churn, allocate resources or formulate strategies and, therefore, they increasingly derive revenue from the creation and from sustenance of long-term relationships with their customers. For this reason, the customer lifetime value is increasingly considered a touchstone for the management of customer relationships. In this article, the authors deepen the concept and use of customer lifetime value and present some mathematical models for its determination. There is many models for this purpose but most of them are theoretic, complex and not applicable. Though not exhaustive, the major contribution of this paper is that it provides a general mathematical formulation to estimate the CLV and that it has a context less specific compared to papers, present in literature, on the customer lifetime.     

Modeling customer impatience in a newsboy problem with time-sensitive shortages

Customers across all stages of the supply chain often respond negatively to inventory shortages. One approach to modeling customer responses to shortages in the inventory control literature is time-dependent partial backlogging. Partial backlogging refers to the case in which a customer will backorder shortages with some probability, or will otherwise solicit the supplier’s competitors to fulfill outstanding shortages. If the backorder rate (i.e., the probability that a customer elects to backorder shortages) is assumed to be dependent on the supplier’s backorder replenishment lead-time, then shortages are said to be represented as time-dependent partial backlogging. This paper explores various backorder rate functions in a single period stochastic inventory problem in an effort to characterize a diversity of customer responses to shortages. We use concepts from utility theory to formally classify customers in terms of their willingness to wait for the supplier to replenish shortages. Under mild assumptions, we verify the existence of a unique optimal solution that corresponds to each customer type. Sensitivity analysis experiments are conducted in order to compare the optimal actions associated with each customer type under a variety of conditions. Additionally, we introduce the notion of expected value of customer patience information (EVCPI), and then conduct additional sensitivity analyses to determine the most and least opportune conditions for distinguishing between customer behaviors.     

顾客忠诚计划作用机制研究

顾客忠诚计划作为一种重要的关系营销手段,已经越来越多的受到企业界和学术界的重视.基于以往关于忠诚计划的研究,从企业利益到顾客利益视角,提出基于顾客利益的忠诚计划作用机制,并进一步探讨关系价值对顾客忠诚的影响.结果显示关系价值对顾客忠诚的影响则主要是通过计划满意和计划忠诚两个中介变量间接实现的.     

Product form solution for exponential G-networks with dependent service and completion of service of killed customers

Queueing networks with negative customers (G-networks), Poisson flow of positive customers, multi-server exponential nodes, and dependent service at the different nodes are studied. Every customer arriving at the network is defined by a set of random parameters: customer route, the length of customer route, customer volume and his service time at each route stage as well. A killed positive customer is removed at the last place in the queue and quits the network just after his remaining service time will be elaborated. For such G-networks, the multidimensional stationary distribution of the network state probabilities is shown to be representable in product form.     

关系感知在银行业顾客忠诚形成中的中介机制研究

以银行业为背景,以顾客关系感知中的满意和信任为中介变量,建立企业形象、转换成本和服务质量三个典型营销要素影响顾客忠诚意向和忠诚行为的概念模型,并进行了实证检验.研究发现:企业形象、服务质量和转换成本会显著影响顾客忠诚行为,其中服务质量影响最大;顾客满意在企业形象和服务质量对顾客忠诚行为的影响中有不完全中介作用;信任在服务质量对顾客忠诚行为的影响中也有不完全中介作用.此外,顾客忠诚意向是营销要素影响顾客忠诚行为的重要中介变量.     

A hybrid fuzzy-optimization approach to customer grouping-based logistics distribution operations

This paper presents an integrated fuzzy-optimization customer grouping based logistics distribution methodology for quickly responding to a variety of customer demands. The proposed methodology involves three main mechanisms: (1) pre-route customer classification using fuzzy clustering techniques, (2) determination of customer group-based delivery service priority and (3) en-route goods delivery using multi-objective optimization programming methods. In the process of pre-route customer classification, the proposed method groups customers’ orders primarily based on the multiple attributes of customer demands, rather than by static geographic attributes, which are mainly considered in classical vehicle routing algorithms. Numerical studies including a real-world application are conducted to illustrate the applicability of the proposed method and its potential advantages over existing operational strategies. Using the proposed method, it is shown that the overall performance of a logistics distribution system can be improved by more than 20%, according to the numerical results from the case studied.     

住宅房地产顾客感知价值评估

不同的顾客对同一住宅房地产的感知价值是不同的,购房决策主要取决于对住宅房地产的顾客感知价值.提出了住宅房地产顾客感知价值评估的质量功能配置逆过程法,在已知住宅房地产工程特性的条件下,确定顾客需求值.利用该方法,给出了评估住宅房地产的顾客感知价值的过程和数学模型,案例研究表明,方法能有效评估住宅房地产的顾客感知价值,帮助购房者选择住宅房地产项目.     

适合中小型制造企业的客户信用评估的研究

本在对中小型制造企业的客户管理调研基础上，建立了适合中小型制造企业的信用评估指标体系，提出了基于AHP、TOPSIS和聚类分析的客户信用评估方法，并在上海某企业进行了实践，取得了较好的效果。     

Modeling customer satisfaction with new product design using a flexible fuzzy regression-data envelopment analysis algorithm

The success of new products depends greatly on customer satisfaction and meeting the customer needs is vital for new product development. By incorporating customer needs in the design and development process, organizations can improve productivity for their new products and reduce the risks associated with new product markets. Hence, design teams require methods to model customer satisfaction when setting the associated product design attributes. Thus, different approaches have been developed for modeling the relationship between customer satisfaction and product design parameters. In this study, 16 well-known fuzzy regression (FR) models are considered to understand the relationship between customer satisfaction and new product design. The design of FR models is based on the 4Ps marketing mix (product, price, place, and promotion) concept in fuzzy environments. A flexible algorithm is then presented based on the index of confidence, error measures, and data envelopment analysis for selecting the best FR model. The applicability and usefulness of the proposed algorithm is demonstrated experimentally based on an actual case study, where the flexible algorithm is employed to predict customer satisfaction with a new product design in the freezer/refrigerator industry.