作　　者： ;

机构地区： 华南理工大学

出　　处： 《经济地理》 2013年第6期170-175,共6页

摘　　要： 构建了预测提前期需求预测更新模型，研究游客、旅行社、功能性服务提供商组成的三阶段旅游供应链合作预测问题。并基于信息相似度对比分析旅游供应链成员分散信息结构下的单独预测与信息共享下的合作预测，得出：①合作预测能降低预测的误差标准差，预测准确性优于单独预测，且旅游供应链成员信息相似度越大，合作预测效果越不明显；②只有合作预测潜在收益大于成本时，旅游供应链成员才会采取合作预测策略，且在相同潜在收益下，随着信息共享成本的增加以及旅游供应链成员信息相似度的降低，采取合作预测的可能性降低。 This paper analyzes the collaborative forecasting problem in a three-level tourism supply chain, which consists of tourists, travel agencies and service providers. We compare two forecasting approaches through our demand forecast updating model： independent forecasting with decentralized information and collaborative forecasting with information sharing. Specifically, both the lead time and information similarity are considered in this model. The results show that （1） Collaborative forecasting can reduce the standard deviation of forecast error, thus its accuracy will be better than independent forecasting. （2） the decision makers in tourism supply chain will employ collaborative forecasting only when potential benefits outweighs the costs. Moreover, they are less likely to employ the collaborative forecasting approach when dealing with the high information sharing cost and low information similarity.

关 键 词： 旅游供应链 预测更新 合作预测 信息相似度

分 类 号： [F590]

领　　域： []