A Prediction Study on the Daily Number of E-commerce Orders Based on Site Search Data

摘要：

　　The search data of E-commerce site reflects millions of online consumers concerns and interests,as well as trends of their behavior,so it can also provide essential data basis for the study of daily number of E-commerce orders.This paper firstly establishes a conceptual framework,revealing that there is a certain correlation and lead-lag relationship between E-commerce site search data and orders.Then,by empirical analysis of orders and search data of an E-commerce site,the paper processes a search data index and builds a prediction model based on it,which confirming that this relationship is statistically significant.Prediction results of the following seven days show that it works well,which can be helpful for E-commerce enterprises to improve their inventory management and its steady development.

关键词： Electronic Commerce Orders Site Search Data Search Index Prediction

作者: Na Li Geng Peng Hang Chen Jaxing Bao

作者单位: Management Department.Graduate School of Chinese Academy of Sciences,GUCAS Beijing,China

会议类型: 国际会议

会议名称: 2012 IEEE 5th International Conference on Management Engineering & Technology of Statistics (第五届(2012)管理工程与统计技术国际学术研讨会(ICMETS2012))

会议地点: 青岛

会议语种:英文

页码: 180-185

在线出版日期: 2012-07-20（万方平台首次上网日期，不代表论文的发表时间）