基于影响因子的供应链协同预测方法

Supply chain collaborative forecasting approach based on affecting factors

探讨了影响因子在时间序列预测中的作用,提出了基于影响因子的供应链协同预测方法并进行了实证研究,依据企业历史实际销售数据分层级分区域分别提取了春运因子及停车检修、小修因子并进行了量化,同时在企业的销售预测值中进行了还原.实证研究表明:影响因子对供应链销售预测具有重要作用,对其加以利用可以大大提高分预测及总预测的精度并体现协同预测的思想;有利于对供应链的隐含或显著信息加以利用,有利于将供应链企业可能存在的负面约束条件加以正面利用,有利于将供应链视为一个信息整体来加以管理,是分层次分模块进行经济信息滤波的一个拓展.在这种协同预测的方法下,供应链的分销商或最终用户的销售状况可以向上传递,生产企业的生产、储运或其它状况可以向下传递,即以影响因子作为纽带将供应链企业视为一个整体来进行销售预测研究.

It aims to explore the role of affecting factors in the chronological forecasting;it proposes the supply chain collaborative forecasting approach on the basis of affecting factors and provides empirical evidence;it extracts and then quantifies the factors of spring festival transportation and those of minor repairs respectively with reference to the enterprises＇ historical actual sales data on different levels and in distinct districts,which have been reverted in their sales forecasting value.The data have shown that the affecting factors play a key role in supply chain collaborative sales forecasting.Their application can greatly improve the accuracy of specific and general forecasting and represent the perspective of collaborative forecasting;it can benefit the implicit or explicit information in the supply chain;it can transfer the potential negative constraints in the supply chain into positive employment;it facilitates the management of supply chain as an information whole,which can be seen as an expansion of the economic information filtering in separate hierarchies and modules.By adopting this collaborative forecasting approach,the sales status regarding distributors or terminal users in the supply chain can be transmitted upwards. Also,information relating to production,storage,transportation and other circumstances can be spread downwards.In other words,affecting factors as ties can take enterprises in the supply chain as a whole in relation to research on sales forecasting.