论文标题
上游供应链预测中销售点的价值：一项实证调查
The value of point of sales information in upstream supply chain forecasting: an empirical investigation
论文作者
论文摘要
传统上，制造商使用过去的订单（从某些下游供应链级别接收）来预测未来的订单，然后将这些预测转变为适当的库存和生产优化决策。随着信息共享技术的最新进展，上游供应链（SC）公司可能可以访问下游销售点（POS）数据。此类数据可以用作预测的替代信息来源。有一些研究调查了在上游SC预测中使用订单与POS数据的好处。结果是混合的，缺乏经验证据，尤其是在多echelon SC的背景下以及促销的情况下。我们使用684系列研究了一个实际的三乙烯SC，制造商的目标是使用DC级别的汇总POS数据或从DCS收到的历史订单来预测从分销中心（DC）收到的订单。我们的结果表明，基于订单的方法的表现优于基于POS的方法6 \％-15 \％。我们发现，POS数据的均值，方差，非线性和熵的低值以及促销的存在对基于POS的预测的性能产生负面影响。此类发现对于确定适当的数据来源和SC中订单预测的串联特征的影响很有用。
Traditionally, manufacturers use past orders (received from some downstream supply chain level) to forecast future ones, before turning such forecasts into appropriate inventory and production optimization decisions. With recent advances in information sharing technologies, upstream supply chain (SC) companies may have access to downstream point of sales (POS) data. Such data can be used as an alternative source of information for forecasting. There are a few studies that investigate the benefits of using orders versus POS data in upstream SC forecasting; the results are mixed and empirical evidence is lacking, particularly in the context of multi-echelon SCs and in the presence of promotions. We investigate an actual three-echelon SC with 684 series where the manufacturer aims to forecast orders received from distribution centers (DCs) using either aggregated POS data at DC level or historical orders received from the DCs. Our results show that the order-based methods outperform the POS-based ones by 6\%-15\%. We find that low values of mean, variance, non-linearity and entropy of POS data, and promotion presence negatively impact the performance of the POS-based forecasts. Such findings are useful for determining the appropriate source of data and the impact of series characteristics for order forecasting in SCs.
