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  • 學位論文

資料採礦技術應用於國內航空市場之顧客價值分析研究

Data Mining Techniques Applied to Customer Value Analysis for Domestic Airline Industry

指導教授 : 張德儀

摘要


國內航空市場之逐年萎縮,面對台灣高鐵即將營運通車,業者若能透過顧客價值的辨識將市場有效區隔,保留具有價值之顧客並提高其忠誠度,強化企業與顧客間之互動,將能創造更多競爭優勢。 隨著資訊科技的發展,透過資料採礦技術的分析,可以輔助業者從資料庫中挖掘出更多有意義的資訊,將資料轉化為知識。本研究即以國內某航空公司為研究對象,將該公司之飛行常客計畫所建立之顧客資料庫,透過顧客價值理論之RFM模式作為分群工具,將不同貢獻價值之顧客有效區隔,同時透過資料採礦技術之C4.5決策樹分析,以顧客的貢獻價值之高低及航線型態區隔作為目標變數,以瞭解不同區隔之顧客其消費屬性與特徵為何,並依據資料採礦分析之結果研擬不同的行銷策略與產品組合。 研究結果顯示,RFM模式可以將價值不同之顧客有效區隔,決策樹分析能夠依據顧客屬性之不同進行規則分類,在最有價值的顧客中,以顧客之性別、年齡、居住地、職業、哩程數等變數具有辨識旅客搭乘本島航線或離島航線之決策作用;在潛在價值顧客中,則以顧客之居住地、哩程數、季節性、年齡等變數具有辨識旅客搭乘本島航線或離島航線之決策作用。本研究之結果為建立一套資料採礦流程,同時依據資料採礦結果具體建立相關之行銷策略,使業者可以透過學術研究的支持建立顧客關係管理,有效運用資料庫行銷提升營運效能。

並列摘要


As business in domestic flights will decline following the launch of the high-speed railway, airline managers have been seeking the solution to maintain the customers now they have. It is said, corporate success depends on an organization’s ability to build and maintain loyal and valued customers. As the result of it, airline managers should make their marketing segment more efficient base on customer value. With the growth of the information technology, enterprises nowadays could extract valid, previously unknown, comprehensible information from their large databases, to transform their data into profitable knowledge by using data mining technique. This research focuses on the study of domestic airline in Taiwan. We extracted customers’ flight record from their frequent flyer program by using RFM model to make the cluster efficiently. C4.5 Decision Tree is used as a data mining tool to find out the classified rule to indicate the customer behavior. Strategies building according to customer segment and characteristics will also be illustrated. The result indicated that the age of customers, sex, location of their residence, occupation, and their mileage accounts came out as characteristics of customers in current value. In the potential value analysis, the age of customers, location of their residence, mileage accounts, and seasonal reason are revealed as the most important criteria. The proposed approach for mining the characteristics of valued customers can assist airline managers in developing better marketing strategies and using them to make crucial business decisions.

並列關鍵字

Airline Industry Data Mining RFM Model Decision Tree

參考文獻


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被引用紀錄


黃俊良(2016)。臺北市公共自行車系統旅次特性分析〔碩士論文,淡江大學〕。華藝線上圖書館。https://doi.org/10.6846%2fTKU.2016.00154

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