資料探勘於網路互動式科技整合性行銷之研究

淡江大學機構典藏 > 商管學院 > 管理科學學系暨研究所 > 學位論文 > Item 987654321/105315

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题名:	資料探勘於網路互動式科技整合性行銷之研究
其它题名:	The study of data mining on networked interactive technology for integrated marketing
作者:	吳書緯;Wu, Shu-Wei
贡献者:	淡江大學管理科學學系碩士班廖述賢
关键词:	互動科技;整合行銷;虛實整合;推薦機制;資料探勘;Recommendation Mechanism;Click-and-Mortar;Networked interactive technology;integrated marketing;data mining
日期:	2015
上传时间:	2016-01-22 14:53:02 (UTC+8)
摘要:	隨著行動網路設備與技術日漸成熟，單純的快速上網已經滿足不了人們的慾望，面對的不再是冷冰冰的機器，經由互動科技所誕生的是，人與人之間更多的連結與互動，生活跟網路幾乎是密不可分了。網路世界的崛起，帶來了商業模式的轉型，許多網路商店的快速擴張，影響了實體店面的經營模式，對於廠商們來說，利用網路來加強自身的競爭優勢已是不可或缺的一環。網路是二十一世紀的能力放大器，水可載舟，亦可覆舟，因此，業者要如何精準地推薦適當的的產品組合給目標客群、如何運用合適的廣告訊息人來吸引目標客群、或是利用網路社群來提升競爭優勢，便是目前值得研究的議題。本研究採用問卷調查的方式，透過資料探勘的方法以集群分析與關聯法則，歸納出使用者的輪廓，並探討使用互動科技的行為和消費行為之間的關聯性，從互動科技使用者、互動科技業者和廠商三方面的交互關係，再根據推薦機制導出產品推薦以及挖掘出較適合推薦的產品，並運用互動科技的功能，整合實體店面與網路店面的優點，以供業者在整合行銷與社群經營上的策略參考，並針對目標客群加強競爭優勢之建議。 The development of internet technology has changed the ways of purchasing. It has also become the main source of communication and information. The way of internet marketing, as an internet tool, vendors on the internet can use the advertising tools like Facebook, LINE and YouTube to increase the exposure of their production or brand. In recent years, with the purchasing methods changing, many companies in Taiwan must begin to face the problem of business transformation. The study focuses on the analysis of network interactive technology users to conclude the habits of their information sourcing and shopping preference with a further attempt to discuss the relationship between network interactive technology users, network interactive technology companies and the business operators. According to the recommendation mechanism to advice companies how to do integrated marketing in the market strategy. Data mining is a powerful new technology with great potential to help companies focus on the most important information in the data they have collected about the behavior of their customers and potential customers. This study adopts 1,044 users as samples, dividing the research result into two clusters while Association rules are applied to bring out more useful information and knowledge for the finding of similar traits and qualities of consumers'' habits.
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