期刊論文
| 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 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/64932 ) |