在线评论中基于动态窗口提取特征观点对的产品推荐模型

在线评论所包含的产品特征观点在帮助用户做出购买决策时发挥着重要作用,然而,目前还没有挖掘客户评论中的产品特征观点作为主要数据来源的推荐系统,并且,监督型方法中提取特征观点对的算法较少关注中文句式结构,提取规则缺乏动态适应性.因此,提出一种基于特征观点对的产品推荐模型,首先,结合中文句式构成分析及特征观点的匹配关系分析,采用动态窗口提取特征观点对;在此基础上,结合特征树汇聚特征观点用于产品间比较,并为用户做出产品推荐;同时,提出情感可信度指标用于展示特征的典型评论.与采用静态窗口的基准方法相比,本模型的召回率和F值都有大幅提升,表明其可以为基于特征观点对的产品推荐提供可靠的数据来源,进而有效帮助用户做出购买决策.     

面对策略顾客和短视顾客的零售商定价

研究了同时面对由策略顾客和短视顾客构成的顾客群体时,零售商如何制定产品的销售价格的问题。构建了由一个零售商和一个顾客群体所组成的报童模型,这个顾客群体中同时包含策略顾客和短视顾客。引入价格保障机制以实现零售商对策略顾客和短视顾客制定统一的销售价格。研究结果表明:在报童模型中,零售商实施价格保障机制可以统一定价,而不用考虑策略顾客和短视顾客的比例;在价格保障机制下,零售商所获得的利润要大于等于单纯按照策略顾客或短视顾客的保留价格定价的利润。     

Products Ranking Through Aspect-Based Sentiment Analysis of Online Heterogeneous Reviews

With the rapid growth of online shopping platforms, more and more customers intend to share their shopping experience and product reviews on the Internet. Both large quantity and various forms of online reviews bring difficulties for potential consumers to summary all the heterogenous reviews for reference. This paper proposes a new ranking method through online reviews based on different aspects of the alternative products, which combines both objective and subjective sentiment values. Firstly, weights of these aspects are determined with LDA topic model to calculate the objective sentiment value of the product. During this process, the realistic meaning of each aspect is also summarized. Then, consumers’ personalized preferences are taken into consideration while calculating total scores of alternative products. Meanwhile, comparative superiority between every two products also contributes to their final scores. Therefore, a directed graph model is constructed and the final score of each product is computed by improved PageRank algorithm. Finally, a case study is given to illustrate the feasibility and effectiveness of the proposed method. The result demonstrates that while considering only objective sentiment values of the product, the ranking result obtained by our proposed method has a strong correlation with the actual sales orders. On the other hand, if consumers express subjective preferences towards a certain aspect, the final ranking is also consistent with the actual performance of alternative products. It provides a new research idea for online customer review mining and personalized recommendation.     

收益管理中考虑顾客策略行为的多航班无约束估计方法

传统的收益管理多航班无约束估计方法假设顾客到达时的购买决策是一次性的,未能充分考虑策略型顾客的跨期替代行为.在仅能获取产品的历史可观察订购量、历史预售开放状态以及市场份额信息的情况下,基于顾客偏好排名列表建立了考虑顾客策略行为的非参数离散选择模型.针对历史预售数据的不完备性,采用EM算法对顾客到达率和非参数离散选择模型的概率质量函数进行联合估计,并提出了考虑历史顾客策略行为的"初始需求"无约束估计计算方法.使用数值算例说明了所提方法的可行性,通过与现有文献中已有方法比较,验证了所提多航班方法能够反映产品价格变化对顾客选择行为的影响,并能更加有效地避免需求预测对未来顾客"初始需求"的高估.     

基于质量屋的顾客需求权重确定方法

通过定义工程特性的计划改进水平、实际改进水平与工程特性修正权重等概念，提出了工程特性改进水平规划模型，并在此基础上建立了顾客需求权重评估模型。该模型能够从不同顾客的需求权重信息中提取统一的顾客需求权重，优化工程特性改进水平，使设计的产品能够满足或者超过目标市场中所有顾客的期望满意度，并利用同一资源实现多种设计目标。仿真研究表明，该模型有效的、可行的。     

面向重要供应商和客户的供应链设计方法

与重要供应商和高价值客户建立良好的关系，已经成为企业获得竞争优势的必然选择。本文从供应链核心企业的角度出发，提出了一种面向重要供应商和客户的供应链设计方法。该方法将供应链设计分成两个阶段。首先，利用模糊综合评判法对核心企业的供应商和客户进行评价，获得它们的重要度。然后，建立一个多目标混合整数规划模型来描述供应链设计问题。与基于成本最小化或利润最大化的传统供应链设计模型相比，该模型体现了关系管理的思想，考虑（1）优先向具有较高重要度的供应商采购原料，以建立长期稳定的合作关系。（2）分销中心的选址要尽量接近重要的客户或客户区，以缩短订货的提前期，提高客户服务水平。     

消费者交互作用对网络效应产品扩散的影响——基于产品生命周期的视角

从消费者采用产品过程的生命周期(PLC)视角出发,运用微观扩散模型仿真分析消费者交互作用对网络效应产品扩散的影响.研究表明:消费者交互作用所产生的局部网络效应能够加快产品扩散早期和中期速度,而聚集效应则会降低产品扩散中期速度; 消费者之间交互强度越强,产品扩散中期速度越快; 全局交互型消费者则会降低产品扩散早期速度,但能提高产品扩散中期速度;且上述因素对网络效应产品PLC不同阶段扩散速度的影响还会由于消费者交互作用所形成的复杂社会网络结构差异而呈现不同模式.这些研究结论能够为网络外部性市场中企业的营销策略提供一定新启示.     

基于序列对齐的客户购买行为相似比较方法

序列对齐方法(SAM)是一种比较字符串序列间差异程度的方法。在SAM的基础上,提出了客户购买行为的相似比较标准,并给出了快速计算客户购买行为相似度的算法,从新的角度解决了客户的相似性比较问题。该方法可以发现客户购买产品和购买金额的差异,对基于客户购买行为的市场细分具有实际应用价值。     

存在顾客购买转移的双分销渠道订货与库存转运策略

库存在渠道间的转运可以降低企业的缺货成本并提高对顾客的服务水平；当存在顾客购买转移时，双分销渠道的库存转运与渠道间的顾客竞争紧密相关，决策的复杂度增加. 该文针对实行转运的情形，研究了存在顾客购买转移的网上商城与传统零售商的最优库存策略，以及均衡解存在的条件，并与不实行转运的情形进行对比分析. 最后通过算例，指出存在顾客购买转移时，实行转运策略的优势.     

Integrating OWA and Data Mining for Analyzing Customers Churn in E-Commerce

Customers are of great importance to E-commerce in intense competition.It is known that twenty percent customers produce eighty percent profiles.Thus,how to find these customers is very critical.Customer lifetime value(CLV) is presented to evaluate customers in terms of recency,frequency and monetary(RFM) variables.A novel model is proposed to analyze customers purchase data and RFM variables based on ordered weighting averaging(OWA) and K-Means cluster algorithm.OWA is employed to determine the weights of RFM variables in evaluating customer lifetime value or loyalty.K-Means algorithm is used to cluster customers according to RFM values.Churn customers could be found out by comparing RFM values of every cluster group with average RFM.Questionnaire is conducted to investigate which reasons cause customers dissatisfaction.Rank these reasons to help E-commerce improve services.The experimental results have demonstrated that the model is effective and reasonable.     

Towards exploring when and what people reviewed for their online shopping experiences

Web 2.0 technologies have attracted an increasing number of people with various backgrounds to become active online writers and viewers. As a result, exploring reviewers’ opinions from a huge number of online reviews has become more important and simultaneously more difficult than ever before. In this paper, we first present a methodological framework to study the “purchasing-reviewing” behavior dynamics of online customers. Then, we propose a review-to-aspect mapping method to explore reviewers’ opinions from the massive and sparse online reviews. The analytical and experimental results with real data demonstrate that online customers can be sectioned into groups in accordance with their reviewing behaviors and that people within the same group may have similar reviewing motivations and concerns for an online shopping experience.     

Service Mechanism and Pricing Based on Fairness Preference of Customers in Queuing System

Service providers often adopt the mechanism of customer classification due to the heterogeneity of customer waiting cost. However, the classification service may cause unfairness feeling of regular customers, then affect the revenue and social welfare. This paper provides the first exact analysis about the situation that service providers offer two classes of non-preemptive priority service when customer fairness perception is explicitly modeled. We model customer fairness perception as a negative utility on regular customers that's proportional to the waiting time difference between the two queues. By analyzing a stylized M/M/1 queue in monopoly service system, we can derive important results some of which reaffirm existed research results. First, from the perspective of revenue maximization, service providers should adopt the mechanism of customer classification and set up the two kinds of customers where they can see each other. Next, considering customer utility maximization,service providers should cancel the mechanism of customer classification, and keep one queue(regular customers) only. Then, from the perspective of social welfare maximization, service providers shouldalso adopt the mechanism of customer classification but set up the two kinds of customers where they cannot feel each other. Finally, this paper concludes the optimal pricing based on customer classification in the above three different perspectives. This research shows important reference value and practical significance for service providers who adopt the mechanism of classification service.     

顾客有限理性对最后一公里配送服务系统的影响

最后一公里配送服务系统中存在不完备信息，顾客互相竞争，彼此造成拥堵，表现出有限理性行为。从顾客期望效用角度，考虑顾客取货距离和运费等因素，运用排队模型描述了顾客自提和送货上门两种配送服务。基于随机最优反应均衡，刻画了顾客无法准确计算他们的期待损失或者等待效用的有限理性，证明了最后一公里配送服务系统存在Logit均衡且均衡唯一，并分析了顾客理性程度、取货距离和运费对均衡的影响。从企业的视角，构建了顾客有限理性条件下企业利润最大化模型。仿真实验揭示了忽视顾客有限理性将对企业造成重大的利润损失。     

客户低估服务价值情境下混合产品定价策略

针对服务价值初始被客户低估的现象,若制造企业将产品服务集成并捆绑销售,将产生客户不愿为混合产品支付的问题,考虑客户对衍生服务价值感知的波动性,将客户购买混合产品的过程视为一个包含实物期权的多阶段动态投资规划,并通过贝叶斯统计估算客户服务价值感知的波动率,实现对混合产品的多阶段分割式定价,以好孩子旗下口袋车POKIT 2为例,验证了定价策略的可行性与有效性。研究表明:基于客户理解价值的定价策略使得供需交易更有灵活性;客户低估服务价值的持续时间决定了客户购买的价值理解;客户低估服务价值时,混合产品的总价大于客户未低估服务价值时混合产品的价格。     

智能ICAQFD 系统中HOQ 多目标优化模型关键技术研究

产品质量表示产品的质量特征(PQC)在其整个生命周期内满足用户需求(VOC)的程度,提高产品质量、迅速开发出满足用户需求的产品是企业生存的关键.虚拟原型逼真设计主要研究虚拟环境下的产品建模问题以及基于仿真的集成产品和过程设计问题,能有效地提高企业的市场竞争力.智能计算机辅助质量功能配置(ICAQFD)模型是虚拟原型逼真设计实现的关键技术之一.在论述ICAQFD系统实现的几个关键技术的基础上,针对质量屋(HOQ)中的决策问题是一复杂的多变量、多目标决策过程的特点,研究了模糊环境下HOQ多目标优化模型实现的关键技术,建立了基于HOQ信息的PQC(产品质量特征)技术先进度的模糊线性规划(FLP)模型和基于模糊回归分析的PQC目标值的FLP模型,结合应用实例,验证了模型的有效性.     

基于Geom/G/1休假排队的顾客止步策略研究

将决策行为引入排队模型中, 以顾客追求利益最大化为出发点, 研究空竭服务、多重休假Geom/G/1排队模型中顾客的优化止步策略. 在不可见排队的前提下, 基于"收益-成本"结构, 采取均值分析的方法, 构建顾客个人和顾客总体的收益函数, 进而, 在不同参数范围内, 分析并确定出顾客均衡策略和社会最优策略. 最后, 通过数值模拟完善结论.     

移动电商顾客购买行为——基于拓展BG/NBD模型的实证研究

基于移动渠道的特征，拓展了客户关系管理领域具有代表性的BG/NBD模型，通过在模型中引入协变量，并考虑不同交叉购买行为下，分析移动客户和传统线上客户在购买率和流失率上的差异。进一步，以2012~2014年京东商城上19189名客户购买数据为分析单位，对拓展模型进行估计和分析。研究结果表明：移动客户的购买率要显著高于传统线上客户购买率，而且移动客户的流失率显著低于传统线上客户的流失率。同时发现，交叉购买行为对上述关系具有显著的调节作用：在有交叉购买行为的情况下，移动客户与传统线上客户无论是在购买率还是流失率上的差异要比没有交叉购买行为下的差异更显著。     

一对多交互式在线客户服务排队模型

以聊天工具为基础的在线客服大量取代了电话形式的传统客服。与电话客服不同,一个在线客服人员能同时为多个顾客提供交互式的服务,而传统的排队公式都是以一对一服务为基础推导的,无法直接用来计算在线客服的排队指标。分析了一对多交互模式下的排队特点,提出了该模式下的服务水平指标,构建了包含顾客层和消息层的双层排队模型,推导了系统平均客户数量、平均服务时间、平均等待回复时间等指标公式,最后进行了公式解析值的仿真验证。仿真结果表明,顾客平均服务时间和消息平均等待时间等指标能有效描述服务系统的排队状况,而本文提出的双层排队模型能准确计算一对多服务模式下的排队指标。     

基于顾客价值的竞争战略开发方法

顾客价值是竞争优势的重要源泉。构建基于顾客价值的竞争战略是企业获取竞争优势的新途径。针对以往研究的不足，提出新的基于顾客价值构建竞争战略的方法，突出顾客期望价值的作用，拓展鉴别不同类型顾客价值要素的维度．并通过一个实例说明实施方法。     

A comparative study of the inventory system with service facility and postponed demands

In this article, we present a continuous review （s,S） inventory system with a service facility consisting of finite buffer （capacity N ） and a single server. The customers arrive according to a Poisson process. The individual customer＇s unit demand is satisfied after a random time of service, which is assumed to be exponential. When the inventory level drops to s＇an order for Q（= S-s） items is placed. The lead time of reorder is assumed to be exponential distribution. An arriving customer, who finds the buffer is full, enters into the pool of infinite size or leaves the system according to a Bernolli trial. At the time of service completion, if the buffer size drops to a preassigned level L （1 〈 L 〈 N） or below and the inventory level is above s, we select the customers from the pool according to two different policy ： in first policy, with probability p （0 〈 p 〈 1） we select the customer from the head of the pool and we place the customer at the end of the buffer; in the second policy, with p （0 〈 p 〈 1） the customer from the pool is transferred to the buffer for immediate service and after completion of his service we provide service to the customer who is in the buffer with probability one. If at a service completion epoch the buffer turns out to be empty, there is at least one customer in the pool and the inventory level is positive, then the one ahead of all waiting in the pool gets transferred to the buffer, and his service starts immediately. The joint probability distribution of the number of customers in the pool, number of customers in the buffer and the inventory level is obtained in the steady-state case. Various stationary system performance measures are computed and total expected cost rate is calculated. A comparative result of two models is illustrate numerically.