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学术论坛:Leveraging Consumer Technology to Learn Demand Information in Lieu of Supply Chain Collaboration
发布日期 :2018-06-13浏览次数 :

 

【讲座主题】:Leveraging Consumer Technology to Learn Demand Information in Lieu of Supply Chain Collaboration            

                                       

【讲座时间】:20180614日(周四)下午14:30-16:30        

                                                           

【讲座地点】:学院南路校区主教615        

                                       

【讲座主讲人】:岳晓航教授,威斯康星大学密尔沃基校园澳门永利线上娱乐教授

                                     

【主讲人先容】

岳晓航博士是美国威斯康星大学密尔沃基校园(The University of Wisconsin- Milwaukee)澳门永利线上娱乐教授,美国供应链管理协会、管理科学及运筹学协会和运营管理协会会员;主要从事供应链与物流管理、生产与市场管理和工业制造系统管理的研究工作,担任国际知名期刊POM的编委。岳晓航教授在包括Operations ResearchProduction and Operations ManagementNaval Research LogisticsIIE TransactionsIEEE TransactionsDecisions ScienceEJOR等国际主流期刊上发表论文40多篇。相关工作被包括Management ScienceProduction and Operations ManagementIIE TransactionsEJORJBROmega等主流期刊广泛引用。

                   

Abstract:Supply chain collaborations have traditionally been enabled by inter-organizational systems such as electronic data interchanges (EDI) and business-to-business (B2B) platforms. Demand information sharing has been one of the cornerstones of these efforts. However, such collaborations are not always realized due to implementation impediments (e.g., cost, training, etc.) or lack of trust between involved firms. In this paper, we examine a recent innovative program that exploits a ubiquitous mobile phone technology to acquire demand information directly from consumers. However, the information acquired from consumers is a censored version of the information that could be acquired through supply chain collaboration. We present a simple procedure to “recover” the true demand information over time from that acquired from consumers. We show that the proposed procedure is indeed an effective substitute for supply chain collaboration in a highly variable but low demand situation where the fill rate is high. Using real-life data from a manufacturer in China that has implemented a mobile app (WeChat) program for learning consumer demand information, we demonstrate the value of such a mobile app program can be substantial.

           

 

 

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