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论文编号：	8512
作者编号：	2120142410
上传时间：	2016/6/14 19:37:32
中文题目：	基于流失预测及供应链管理的汽车行业客户挽留管理研究
英文题目：	Research on Customer Retention Management in Automobile Industry Based on Loss Prediction and Supply Chain Management
指导老师：	李勇建
中文关键字：	客户流失；客户挽留；客户细分；数据挖掘；供应链管理
英文关键字：	Customer Churn； Customer Retention； Customer Segmentation； Data Mining；Supply Chain Management
中文摘要：	经历飞速发展后，我国汽车保有量逐渐趋于饱和，目前，新车销售正面临着来自竞争、成本、全球化等多方面的压力，挑战远大于机遇。售后服务市场却处于初级阶段，发展空间大，逐渐发展为整个行业最重要的利润来源，但是，售后服务渠道众多，竞争激烈，因而，保证客户群体的稳定变得尤为重要，汽车行业的客户流失管理研究有着重要的实践意义。汽车行业的客户流失管理问题是一个基于供应链系统的涉及到客户流失预测，客户细分，客户挽留等多方面跨领域的综合问题。该问题的研究既需要对客户群体认识的深入，也需要供应链层面的分析。本文主要分为两个部分，客户流失预测与客户挽留管理。基于决策树及Logistic回归的客户流失预测模型提取了影响客户流失的重要属性，预测了客户的流失状态，也总结了流失客户的特征，为客户挽留措施的设计提供了依据。客户挽留问题的研究是从供应链的角度在客户挽留努力基础上进行的，由Stackelberg博弈模型分析了在分散决策下，厂商及经销商为取得最大收益，如何决策单位潜在流失客户返场补贴，单位潜在流失客户的挽留投入，客户挽留努力水平。在此基础上，接着分析各方决策及收益与客户挽留努力水平效应的关系。通过对比发现，集中决策可以显著提高供应链的挽留市场容量及挽留收益，为避免由分散决策造成供应链系统客户挽留效率降低，本文以SHAPLEY法分配了供应链系统的客户挽留收益，研究结果表明该方法可以实现帕累托改进。本文将客户流失规律分析、客户挽留资源投入、客户挽留策略分析相结合，建立了一套比较科学完整的客户流失管理方法。
英文摘要：	After rapid development, Chinese car market has gradually become saturated. As a result, the new car sales is facing pressures from competition, cost, globalization and so on, which make it face more challenge than opportunity. After-sales service market is in the initial stage, with greater development space, and has gradually develops as the most important source of profit of the industry. However, there are many channels in after-sales service market, which make it face fierce competition. Therefore, it becomes particularly important to ensure stable customer groups. The customer churn management of automotive industry is significantly important. Customer Churn Management in the automotive industry is a comprehensive problem based on the supply chain system related to customer churn prediction, customer segmentation and customer retention. The study of this problem requires in-depth understanding of customer groups, but also the supply chain level of cooperation. The research of this thesis contains two parts, customer churn prediction and customer retention management. Customer churn prediction model extracts important attributes of customer churn, predicts the state of customer churn and summarizes the characteristics of customer churn based on Decision Tree Analysis and Logistic regression, which provide basis for the design of customer churn measures. The research of customer retention is built based on customer retention efforts from the perspective of the supply chain. This thesis analysis the parties’ optimal choice under decentralized decision-making by the Stackelberg game model and the impact of the customer retention effect level on the decision and revenue. By comparison, we found that centralized decision-making can significantly improve the supply chain performance in the aspect of retention market capacity and retention earnings. In order to avoid retention efficiency reducing caused by decentralized decision making caused by reduced customer of the supply chain, this thesis assigned customer retention revenue by the method of SHAPLEY to coordinated supply chain. The results show that the method can realize the Pareto improvement. This thesis establishes a set of more scientific customer churn management method, which contains customer churn reason analysis, customer retention resource assignment and customer retention strategy analysis.
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