标题: | 促销档期下之销售预测流程设计与模式构建 Sales Prediction Process Design and Model Building Under Promotion Period |
作者: | 洪明阳 Hung, Ming-Yang 丁承 Ding, Cherng 经营管理研究所 |
关键字: | 长鞭效应;协同预测计画与补货;促销档期;销售预测;自组性演算法;Long-Whip Effect;Collaborative Planning, Forecast and Replenishment;Promotion Period;Sales Prediction;Group Method of Data Handling |
公开日期: | 2011 |
摘要: | 在当今世界激烈的市场竞争和快速多变的市场需求下,企业面临的经营压力已非本身单一方面就可以解决,必须藉由整体供应链成员彼此的沟通、合作,以供应链管理之手法提升竞争优势。但目前发展出来的供应链管理手法中常忽视供应链资讯流的最佳化,为供应链带来“长鞭效应”(Long-Whip Effect) 的问题,需求讯息的不真实性造成供应链所有成员受高库存、高缺货率之影响,进而带来营业额下降。而此问题尤其容易发生在促销档期期间。由于商品销售量在促销档期中会突然的升高,若供应链成员之间没有良好的沟通管道,则更为容易产生长鞭效应。在许多供应链管理方法中,协同计画、预测与补货(Collaborative Planning, Forecasting and Replenishment, CPFR)被认为是最能够解决长鞭效应的手法。 本研究藉由台湾某大型供应商与通路商之合作为实例,企图达成以下三点目标,给予双方建议并为双方带来更大利益:第一,以CPFR之手法作为基础,重新设计原先该供应商与通路商于促销档期间预测与补货模式,使得双方能够更快速应对促销档期间的需求。第二,本研究将该供应商以及通路商所搜集之销售及档期资讯,以复回归模型探讨该供应商提供给该通路商之产品中其中57只产品的关键销售因素;而研究也证实即使为相同品牌,不同的产品的销售量也会被不尽相同的促销方法影响。第三,本研究采用复回归模型以及以人工智慧为基础之自组性演算法模型进行销售量预测,并藉由预测误差了解在何种促销方案下会有较好的准确率,而研究也证明自组性演算法之预测准确率较高。而采用本研究方案之通路商分店,在缺货率、存货减少及订单满足率等指标上皆优于其余未采用此方案之分店,也证实本研究之销售预测流程与预测模型具有其实务上的效果。 In recent year, due to the strong competition and volatility of the market, firms must engage and cooperate with all the members in supply chain to sustain their competitive advantage by using supply chain management method. However, most of the methods have ignored the importance in optimization of information flow, which caused a serious impact to the whole supply chain, the “Long-Whip Effect”. The Long-whip effect indicates that the uncertainty and variation of demand information in supply chain will cause high inventory and high out-of-stock. This situation happens in promotion period often especially. For the demand will drive up in a very short period of time, long-whip effect happened if the supply chain cannot communicate to each other easily. Among all the supply chain management methods, collaborative planning, forecasting and replenishment (CPFR) is considered as the most effective way to deal with long-whip effect problem in supply chain. This study takes the engagement of a large supplier and a retailer in Taiwan as example, and aims to handle below three issues. First, this study re-designed the process in promotion period base on the basis of CPFR. Second, this study used multiple regression to discuss the key promotion factors that will affect sales quantity for 57 SKUs (stock keeping unit) that the supplier provided to the channel. Third, this study uses both multiple regression and Group Method Data Handling (GMDH) to predict sales quantity for each promotion period. With the total solution designed, the result has shown that the retailer has a better performance on out-of-stock rate, inventory reduction rate and order fulfillment rate that both side are eager to reach. |
URI: | http://140.113.39.130/cdrfb3/record/nctu/#GT079937502 http://hdl.handle.net/11536/50222 |
显示于类别: | Thesis |
文件中的档案:
If it is a zip file, please download the file and unzip it, then open index.html in a browser to view the full text content.