机构地区: 华南理工大学经济与贸易学院
出 处: 《物流技术(装备版)》 2013年第2期238-243,共6页
摘 要: 基于不同需求预测技术,研究了游客、旅行社、功能性服务提供商组成的三阶段旅游供应链中的牛鞭效应问题。对比分析了在一定的预测提前期下,旅行社分别运用移动平均、指数平滑和权重预测三种不同预测技术来预测游客需求时的牛鞭效应现象,数据实验结果表明:(1)缩短预测提前期有助于减少牛鞭效应;(2)增大移动平均中的历史数据个数或减小指数平滑中的平滑系数都能减弱牛鞭效应。通过三种预测技术的对比,证实在降低牛鞭效应上移动平均预测技术要优于指数平滑以及权重预测技术。 On the basis of demand forecasting,this paper aims to study the bullwhip effect in a three-level tourism supply chain which consists of tourists,travel agencies,functional service providers.Hypothetically,the travel agency will forecast with a certain lead time the demand of tourists with three forecasting techniques respectively,which are moving average,exponential smoothing and weighted prediction.The results show that shortening the forecast lead time will mitigate bullwhip effect and both increasing the number of historical data in the moving average and reducing the smoothing coefficient in the exponential smoothing will mitigate the bullwhip effect.Finally,through comparison,it is shown that the moving average forecasting technique is better than the other two methods in mitigating the bullwhip effect.