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    Title: 資料採礦應用於量販店網路購物與宅配之研究
    Other Titles: The study of data mining approach applied to hypermarket's online shopping and home delivery
    Authors: 林益存;Lin, Yi-tsun
    Contributors: 淡江大學管理科學研究所碩士班
    廖述賢;Liao, Shu-hsien
    Keywords: 資料採礦;量販店;宅配;資料庫行銷;組合產品;關聯法則;集群分析;網路購物;data mining;Hypermarket;Home Delivery;database marketing;Bundling;association rule;Cluster Analysis;Online Shopping
    Date: 2009
    Issue Date: 2010-01-11 03:12:45 (UTC+8)
    Abstract: 隨著現代科技的進步,國內的上網人口數逐年增加,在年輕消費族群追求便利、快速的前提下,網路購物成為新的一種消費型態。此外,郵購、電視行銷、網路電子商務等虛擬商店的興起,企業對個人(B2C)的宅配市場也逐漸形成,雖然目前國內宅配業的發展程度不如日本,但國內廠商仍一致看好宅配業的未來發展。
    綜合以上敘述,本研究將量販店的網路購物和宅配加以結合,試圖利用關聯法則探勘出未知的生鮮與非生鮮產品的產品組合,並利用集群分析將顧客加以分群,並根據各分群的消費偏好來設計型錄,增加型錄對顧客的吸引力,提供業者一些網路購物與宅配的服務跟建議,期望藉此吸引更多的顧客,開拓更寬廣的市場,為業者賺取更高的利潤。
    研究結果發現,隨著顧客集群的不同,其消費偏好、宅配意願及網路購物行為皆有所差異:
    1.以蔬菜類的消費偏好為例,集群一的顧客對「根菜類」及「莖菜類」偏好程度最高,集群二的顧客對「葉菜類」及「花果類」偏好程度最高,集群三的顧客對「食用菌類」及「雜類」偏好程度最高。
    2.以飲品的宅配意願為例,集群一的顧客對「鮮乳/調味乳」、「果汁」宅配意願最高,集群二的顧客對「碳酸飲料」、「茶類飲料」宅配意願最高,集群三的顧客對「酒類」、「乳酸產品」宅配意願最高。
    3.以網路購物的產品為例,集群一的顧客對「衣物服飾」、「化妝/保養品」的網路購物意願最高,集群二的顧客對「書籍雜誌」、「3C產品」的網路購物意願最高,集群三的顧客對「音樂」、「食品」的網路購物意願最高。
    With the advancement of the modern science and technology, the domestic population to access the internet increases year by year. Under the young customer to pursue the convenient, fast prerequisite, the online shopping becomes a kind of new comsumption type. In addition, business to customer (B2C) home delivery market gradually take shape, because the virtual stores to rise and develop, e.g. mail-order, TV marketing, e-commerce. Though at present domestic home delivery development inferior to Japan, but the domestic manufacturer still has an optimistic view of the home delivery industry’s future.
    Synthesize the above statements, this research to combine online shopping and home delivery, attempt to use the association rule to prospect unknown bundling of fresh products and non- fresh products. Then divided up customers of some clusters by cluster analysis, and design the catalogue based on each of cluster’s consumption preference. By this method to increasing the catalogue’s attraction to customer, and offering hypermarkets some online shopping’s and home delivery’s services and propose. Expect to attract more customers by this, open up the more broad market, earn the higher profit for the hypermarkets.
    The result of research find, with the difference of customer''s cluster, lead each cluster’s consumption preference, inclination of home delivery and online shopping exist some differences:
    1. Take the consumption preference of the vegetables as an example, the customers of cluster one have a highest perference to “ Root vegetables “ and “ stem vegetables “. The customers of cluster two have a highest perference to “ leaf vegetables “ and “ flower and fruit vegetables “. The customers of cluster three have a highest perference to “ edible fungus vegetables “ and “ miscellany vegetables “.
    2. Take the home delivery’s inclination of the drink as an example, the customers of clusters one have a highest inclination to “ fresh milks / flavored milk “, “ fruit juice “. The customers of cluster two have a highest inclination to “carbonated beverages “, “ tea beverages “. The customer of cluster three have a highest inclination to “ liquor “, “yogurt beverages “.
    3. Take the products of online shopping as an example, the customers of clusters one have a highest inclination to “ clothes dress “, “ makeup /skin care products “. The customers of clusters two have a highest inclination to “ books magazine “, “ 3C products “. The customers of clusters three have a highest inclination for the intensity to “ music “, “ food “.
    Appears in Collections:[Department of Management Sciences] Thesis

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