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  • 學位論文

資料採礦於壽險市場需求鏈探勘與新產品組合開發之研究

The Research of Data Mining on Demand Chain of Insurance Market and New Product Development

指導教授 : 廖述賢
共同指導教授 : 高棟梁(Tong-liang Kao)

摘要


人壽保險為一種社會性的事業,兼具「保障」與「儲蓄」的雙重功能,也是一種分散風險、消化損失之經濟制度,對個人、家庭、企業與國家社會而言,是不可或缺的商品與產業。但隨著全球化的來臨與時代之潮流的演進,保險市場在業務多元化、金融法令的開放、金融控股公司成立、金融商品的多樣化、多重通路的擠壓與保險大眾對保險的需要深入與多樣化,保險公司如何因應這股競爭且具挑戰性的社會環境,脫離不斷的在以價格、產品差異、產品通路與仿冒等方法廝殺競爭對手的紅海,追求還沒有被開發的市場,以及尚未被創造的需求,開創屬於保險公司的一片藍海契機。 為了創造出尚未發展之市場空間,形成無人競爭之藍海,壽險業應創造產品之附加價值,提升企業競爭優勢,而途徑就是把握市場需求的趨勢,重視顧客的需求以及未被滿足的需求,改善原有商品組合,提供更高價值的新產品組合,並於原商品附增其他服務,結合服務方面的需求滿足,便能避開或減弱市場競爭並進入藍海。由於壽險業者皆具有龐大的消費者資料庫,可針對資料庫進行探勘工作,挖掘出不同市場區隔之未滿足之需求、特質與趨向,將有助於行銷策略之規劃與執行。因此,本研究以市場區隔與需求鏈的概念,針對一般消費大眾進行集群分析以做市場區隔,挖掘不同市場區隔之消費者之需要與慾望之差異,並配合關聯法則技術做分析,了解顧客未被滿足之需求為何,針對其需求設計新產品組合與附加服務的提供。

並列摘要


Human Insurance, indispensable product and industry to individual、family、interprise and country, is a kind of social business, including both function, “Insurance” and “Deposite.” However, following the trend of globalization, the market has faced strong competition, including multi-business, openness of finance laws, various insurance products, multi-channel to products and customers’ changing and diversed needs to the product. To get away from the competitive and blooded red sea, the enterprise should stop use the strategy of adjusting price, differentiation of products, imitation of other company, but try to build an undeveloped, potential and profitable blue sea market In order to create undeveloped blue sea market, human insurance enterprise should create product’s additional value to promote enterprise competitive advantage by focusing on customer’s needs and unsatisfied needs to improve original products design and provide more highly valued new product mix design. Besides, combining additional insurance service can also be a strategy to avoid market competition. Owing to the reason that human insurance has enormous customer database which can be used for data mining to discover useful marketing information. Therefore, the research takes the concept of market segmentation and demand chain, used the method of Cluster Analysis to divide into five groups, Association Rules to discover each group’s customer’s needs and unsatisfied needs to design new product mix and provide additional service.

參考文獻


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被引用紀錄


張瑋玲(2011)。資料採礦於精品業需求鏈推薦機制探勘之研究〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2011.00142
楊逢杰(2008)。以本體論為基礎的資料採礦方法應用於台灣飲料商品產品及品牌光譜之研究〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846/TKU.2008.01137
陳威頤(2014)。應用Dagging集成式學習演算法改善分類準確度之研究〔碩士論文,國立虎尾科技大學〕。華藝線上圖書館。https://doi.org/10.6827/NFU.2014.00169

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