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    請使用永久網址來引用或連結此文件: http://ir.lib.ncu.edu.tw/handle/987654321/13071


    題名: 一個保險業的資料採擷應用--業務員的薪酬制度分析;A study on the application of data mining for an insurance company ─ a case for the evaluation of sales rep compensation
    作者: 陳錫畊;Shi-Keng Chen
    貢獻者: 資訊管理學系碩士在職專班
    關鍵詞: 決策樹;資料採擷;保險;Decision Tree;Data Mining;Insurance
    日期: 2003-06-14
    上傳時間: 2009-09-22 15:22:58 (UTC+8)
    出版者: 國立中央大學圖書館
    摘要: 論文摘要 一個保險業的資料採擷應用 --業務員的薪酬制度分析 指導教授:范錚強博士 研究生:陳錫 Abstract A study on the application of data mining for an insurance company ─ a case on the evaluation of sales rep compensation Advisor: Prof. C.K. Farn Student: Hsi Keng Chen Data mining is a comprehensive technique which combines information technique, analysis technique and industry know-how. With this technique, users can discover the hidden patterns in large volumes of data and transform such data into useful information and even business operating tactics. Nowadays, data mining is applied in many business fields. Business applications of data mining include profitability analysis, customer attraction, market segmentation, asset risk management, and cross selling etc.. This study applies data mining technique in the insurance industry. Insurance companies can use the results from prescription on sales’ behavior to expand their business performance. Data mining creates information assets that a company can leverage to achieve the business strategic objectives. The target company for this study is a traditional Taiwanese life insurance company. The management of the company believes that more sales rep contributes to higher revenues. Motivating sales rep is a difficult problem facing the management. The results of this data mining study can help to accomplish this goal. The results of this study are: there is significant relationship among performance, salary, position and tenure. As a result, it is suggested that tenure can be included as a factor in determining sales rep compensation. Keywords: Data Mining, Decision Tree, Insurance, Compensation
    顯示於類別:[資訊管理學系碩士在職專班 ] 博碩士論文

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