一种基于CPFR的订单预测方法研究

协同规划、预测与补货(Collaborative Planning Forecasting and Replenishment,CPFR)强调零售商与供货商共同合作建立一个供应链的预测方式,其中协同预测阶段又分为订单预测与销售预测.以订单预测阶段为研究对象,归纳出协同合作下订单需求的影响因素作为模型的解释变量,然后结合传统时间序列与多元回归分析,建立了基于CPFR的订单预测模型.最后将该预测模型应用于国内某公司的订单资料.验证结果表明所提出的订单预测方法比传统使用单一时间序列方法的预测结果精度更高.     

基于CPFR的供方可选择的协同补货模型与仿真

针对传统的供应链补货模型中没有考虑在供方可选择情况下的协同, 从而影响库存补充策略及供应链成本的问题, 研究了由供应商、分销商和零售商组成的多级供应链中的基于CPFR的协同补货问题. 考虑订货概率参数, 建立了基于分销商订货量和零售商订货量之间函数关系的协同补货模型, 以求通过分销商和零售商之间的协同来降低整个供应链的总成本, 并采用MATLAB对协同补货模型进行了数值仿真分析. 其结果验证了所构建的模型是有效的.     

基于供应链的联合计划、预测与补货系统

随着企业的扩张和信息技术的迅猛发展，企业集团间的商战大大加剧，物流管理已不能满足客户的需求，因此具有整合性和全局色彩的各种供应链管理模式应运而生。介绍了CPFR联合计划、预测与补货系统——这一新型的供应链管理模式的起源、基本理念、实施原则、一般流程以及面临的挑战，以期为我国商业企业开展基于供应链管理的CPFR模式做好准备。     

供应链整合新技术——联合计划预测、补货

为了让更多的国内厂商了解并参与到联合计划预测、补货（CPFR）实施,分析CPFR的指导模型及其3个重要组成部分,总结影响CPFR成功实施的4个关键因素,回顾国内外CPFR的应用现状和成功实施项目取得的效益,提出在中国实施CPFR需解决的问题.     

Information sharing and strategic signaling in supply chains

Information sharing in procurement occurs in rich and varied industry contexts in which managerial decisions are made and organizational strategy is formulated. We explore how information sharing ought to work in procurement contexts that involve investments in inter-organizational information systems (IOS) and collaborative planning, forecasting and replenishment (CPFR) practices. How and under what circumstances does a firm that plays the role of a supply chain buyer decide to share information on key variables, such as point-of-sale consumer demand data with its supplier, up the supply chain? This is a key issue that crosses the boundary between supply chain management and information systems (IS) management. The answers that we provide are based on our use of a game-theoretic signaling model of buyer and supplier strategy in the presence of uncertainties about final consumer demand. We also explore the connection between operational costs that are associated with the firm’s information sharing and information withholding strategies. Our results provide normative guidance to supply chain buyers about how to interpret different demand uncertainty scenarios to improve their decisions and generate high value. From the IS management perspective, we show the impacts on the firm of different information sharing approaches that are made possible by present day technologies.     

A study on factors for retailers implementing CPFR — A fuzzy AHP analysis

Since collaborative,planning,forecasting,and replenishment(CPFR)was first proposed in 1998,numerous studies have focused on exploring its implementation in retailing contexts.While a considerable body of research has emphasized reduced costs,increased sales and improved forecasting ability,there has been a lack of research on the importance of each of the various factors which affect such implementations.In order to find out the critical success factors affecting CPFR implementation,this paper first collected related influence factors regarding adopting CPFR or business to business(B2B)information systems,and further constructed a factor table with a three-layer hierarchical structure.A pair wise analytic hierarchy process(AHP)questionnaire was designed and distributed to experts who were familiar with implementing CPFR in the retailing industry.After questionnaires were returned,we found out the weights of each impact factor by using a fuzzy analytic hierarchy process(fuzzy AHP)approach.The importance of each critical impact factor was investigated,and the paths of the critical success factors were also analyzed.The results of this study can provide more precise information with regard to allocating optimal resources for retailers implementing CPFR.     

协同商务下基于CPFR的供应链管理研究

合作计划、预测与补给(CPFR)是近年来出现的供应链管理的一个新模式。分析了CPFR与其他合作方式的联系,提出了CPFR的过程模型和CPFR的库存控制策略,最后探讨了CPFR的实施方案。     

基于CPFR的协同补货方法

针对传统的供应链需求预测模型中信息结构呈分散状态、对各成员预测结构差别大、影响库存补充策略的问题,创新地将CPFR技术应用到了协同补货的方法研究中,建立了基于最佳库存和最佳运送周期之间的函数关系的数学模型,并在此基础上采用进化策略法对建立的模型求解.结果表明,随着各项参数值的提高,总成本也随之增加,即最佳运输周期与最佳库存量受各项参数值的影响,其结论也验证了此方法的有效性.     

基于指数加权分位数回归预测的CPFR成本模型

针对某些商品的高易变性、不对称性的需求模式,基于预测方法高精确度的要求,采用计量经济学前沿预测研究方法指数加权分位数回归预测法,建立了由零售商、制造商的成本模型和供应链系统总成本模型构成的CPFR供应链系统成本模型,为基于多层次CPFR的三级库存协调与优化研究中提高需求预测精度探索新的视角.该模型通过直接预测销售序列的分位数,避免既存研究中基于假设的预测失误,使预测结果更加贴近需求模式的真实值.数值分析表明指数加权分位数回归预测模型的预测精度较高.