Mining customer knowledge to implement online shopping and home delivery for hypermarkets
學年 99
學期 2
出版（發表）日期 2011-04-01
作品名稱 Mining customer knowledge to implement online shopping and home delivery for hypermarkets
作品名稱（其他語言）
著者 Liao, Shu-Hsien; Chen, Yin-Ju; Lin, Yi-Tsun
單位 淡江大學經營決策學系
出版者 Kidlington: Pergamon
著錄名稱、卷期、頁數 Expert Systems with Applications 38(4), pp.3982–3991
摘要 With advances in modern technology, the Internet population has increased year by year globally. For young customers who consider convenience and speed as prerequisites, online shopping has become a new type of consumption. In addition, business-to-customer (B2C) home delivery markets have taken shape gradually, because virtual stores have risen and developed, e.g. mail-order, TV marketing, e-commerce. To integrate the above statements, this study combines online shopping and home delivery, and attempts to use association rules to determine unknown bundling of fresh products and non-fresh products in a hypermarket. Customers are then divided up in clusters by clustering analysis, and the catalog is design based on each of the cluster’s consumption preferences. By this method, to increase the catalogue’s attraction to customers, hypermarkets are offered an online shopping and home delivery business model for sales services and propositions. With such a model, we can expect to attract more customers open up more broad markets, and earn the higher profits for hypermarkets.
關鍵字 Data mining; Association rule; Cluster analysis; On-line shopping; Home delivery; Electronic commerce; Database marketing
語言 en
ISSN 0957-4174
期刊性質 國外
收錄於 SCI EI
產學合作
通訊作者 Liao, Shu-Hsien
審稿制度
國別 GBR
公開徵稿
出版型式 紙本
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