【作者】 杜娟；

【导师】 张李义；

【作者基本信息】 武汉大学 ， 管理科学与工程， 2004， 硕士

【摘要】 需求链管理是供应链管理发展的新趋势。它以终端客户的需求为驱动，通过前馈的消费信息和反馈的供应信息，将供应商、制造商、分销商、零售商和最终客户连成一个整体，为达到将正确的产品，在正确的时间，按正确的数量、正确的质量、正确的状态，送到正确的地点，并使总成本最小这一最终目的，而协同运作。 数据挖掘技术是商业智能的一部分。它是一项面向应用的，能够从大量的、不完全的、有噪声的、模糊的、随机的数据中，提取隐含在其中的、人们事先不知道的、但又是潜在有价值的信息、知识、模型或规则的技术。 将数据挖掘引入到需求链管理中，是当前数据分析技术发展的必然结果。它能帮助企业管理者从企业业务系统及其他来源的海量数据中，发现企业生产运营过程中的潜在规则和问题，协助管理者做出决策。 本文首先介绍了需求链管理的研究背景、含义与内容，并将需求链管理与我们目前所熟谙的供应链管理间的关系和异同做了分析和比较。然后分析了需求链上的牛鞭效应。接着文章介绍了数据挖掘技术的基本理论，对数据挖掘的过程与模式进行了分析。然后文章主要探讨了需求链管理与数据挖掘技术相结合的应用方法，阐述了在客户管理、供应商管理及物流配送管理中运用数据挖掘技术所能解决的问题。其中重点提出了基于分类与聚类分析模式的产品需求分析模型，并通过使用实际数据对模型进行的验证，证明了它的正确性与实用性。最后文章还提出了需求链管理系统的构建思路。阐述了系统的主要组成模块及功能，其中详细介绍了需求管理模块的功能及其所采用的新技术，为将需求链管理的理论研究向实践的转化推进了一步。更多还原

【Abstract】 DCM ( Demand Chain Management) is new tendency of the developing SCM (Supply Chain Management). It is drived by the demand of the terminal customer. And it makes the separated units, such as suppliers, manufacturers, distributors and shopkeepers, into an integer by the feed-forward information of consuming and the feedback ones of supplying. Those suppliers, manufactures, distributors and shopkeepers work collaboratively for the object of sending the correct goods with correct status to the correct place in correct time.DM (Data Mining) is one of the Business Intelligence (BI) technologies. It is oriented to applications. And it can pick up those potential, valued information, knowledge, model or rule etc, from those data that are abundance, imperfection, noisy, blurry and random.Introducing data mining to demand chain management is the result of the development of data analysis technology. It can help the managers of enterprise find the potential problems and rules from the data warehouse, and work out the corresponding decision.Firstly, this article introduces the background, definition and content of demand chain management. Then it discusses the relation and the difference between DCM and SCM, and analyses the bull-whip effect on demand chain. Secondly, it talks about the theory and method about using data mining. Thirdly, it illustrates how to apply the technology of data mining to demand chain management from three aspects, which are customer management, suppliers management and logistics management. In this part, it puts emphatically forward a forecasting model of product, which has proved its correctness and practicability by evaluating with actual data. In the end, the article looks forward the proposition about how to design the demand chain management, and the function and of the module of demand management, which transforms the theory to practice.更多还原