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研究生:林玉珠
研究生(外文):Yu-Ju Lin
論文名稱:我國人壽保險業顧客購買保單類型之研究
論文名稱(外文):A Study on the Customers’ Purchases of Insurance Policies in Taiwan’s Life Insurance Industry
指導教授:黃金生黃金生引用關係
指導教授(外文):Chin-Sheng Huang
學位類別:博士
校院名稱:國立雲林科技大學
系所名稱:管理研究所博士班
學門:商業及管理學門
學類:企業管理學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:中文
論文頁數:95
中文關鍵詞:層級分析法模糊邏輯德菲法類神經網路因素分析人壽保險業
外文關鍵詞:AHPFuzzy logicDelphi techniqueNeural networkFactor analysisLife insurance industry
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人壽保險業務員在推薦顧客購買保單時,應依顧客不同的需求而給予購買建議。傳統上,壽險業務員大多憑藉著自己過去經驗、法則,甚至是主觀的認知給予顧客購買保單之建議,並無一套輔助之工具以協助其作決策。因此,本研究提出兩種決策模型,可以協助壽險業務員為其顧客推薦合適保單之購買。藉由使用本研究所建立的模型,壽險業務員在為顧客推薦保單購買建議時,可以有效地做出決策並消除其主觀的意見。
本研究根據不同的方法論建構兩種保單購買之決策模型,所探討之壽險保單類型共分為五大類,分別是人壽保險、年金保險、健康保險、傷害保險以及投資型保險,並以台灣某家保險公司300位保戶之購買記錄做為樣本資料。第一個決策模型是以專家知識為基礎,是結合層級分析法、模糊邏輯以及德菲法等之混合模型,其所建立的決策模型可提供使用者保單購買優先順序的建議。本模型首先運用德菲法選擇輸入變數、定義模糊表示式及產生評估法則,再利用模糊邏輯將原始輸入轉換為模糊變數,並將模糊變數輸入AHP中,最後將AHP計算的結果做為保單選擇之評估準則,並以樣本資料進行驗證。第二個決策模型是運用類神經網路做為保單購買決策之預測模型,並分成二個子模型探討: 整體保單類型與個別保單類型。其中,整體保單類型是以單一的類神經網路對五種保單類型同時做分類;而個別保單類型則是以五個類神經網路分別對五種保單類型做分類。本決策模型進一步依據保單購買目的,將健康保險與傷害保險依主約與附約二種購買型態,分別進行研究。本決策模型並利用因素分析法篩選重要的變數。
本研究經實證結果有以下的發現:
(一)透過德菲法之專家意見,有四個重要變數建議放入保單購買之決策模型中,分別為:年齡、年收入、教育程度以及風險偏好。
(二)在類神經網路模型中,個別保單類型分類準確率優於整體保單類型。
(三)在類神經網路模型中,年金保險、健康保險主約及傷害保險主約購買者,其分類準確率優於其他保單類型。
When life insurance agents recommend customers to buy an insurance policy, they should give purchase suggestions to the customers based on the different needs of the customers. Traditionally, life insurance agents give purchase recommendations by their own experiences, rules, and even subjective cognitions, without any auxiliary tool to help them make decisions. This study proposes two decision models for life insurance agents to determine appropriate insurance polices for their customers. By using the proposed models, the insurance agents can effectively make their decisions and remove their subjectively prejudiced opinions, when they give the purchase suggestions to their customers.

In this study, based on different methodologies, two types of decision models are built to determine the insurance policies. Five types of insurances are involved including life, annuity, health, accident, and investment-oriented insurances. Three hundred purchase records from an insurance company in Taiwan are used as samples. The first decision model is built based on the experts’ knowledge where a hybrid model of Analytic Hierarchy Process (AHP), fuzzy logic, and the Delphi technique is used to determine the purchase priorities of the five insurances. In this model, the Delphi technique is first employed to select inputs, define fuzzy expressions, and generate evaluation criteria. The fuzzy logic serves to map the original inputs to fuzzy variables. These fuzzy variables are then fed to AHP. The decision model is generated by the results of AHP and validated by the three hundred samples. The second decision model uses neural networks to determine the insurance polices. These neural networks are categorized into two sub-models: the integrated and the individual ones. The integrated sub-model uses a single neural network to classify the five insurances simultaneously. The individual sub-model utilizes five individual neural networks to classify the five insurances independently. Based on the purpose of insurance purchase, the health insurance and the accident insurance are furthermore categorized into two purchase types: primary insurance type and additional insurance type. Meanwhile, the factor analysis method is also utilized to select important variables in this decision model.

The findings of this study are drawn as follows:
1. Through the Delphi technique, four important variables are suggested to build the decision model of insurance purchase including age, annual income, educational level, and risk preference.
2. In the neural network model, the classification performance of the individual sub-model is better than that of the integrated one.
3. In the neural network model, the annuity insurance, health insurance (primary insurance type), and accident insurance (primary insurance type) have better classification results than others.
中文摘要 ..................................................................................................... i

英文摘要 ..................................................................................................... ii

誌謝 ..................................................................................................... iii

目錄 ..................................................................................................... iv

表目錄 ..................................................................................................... vi

圖目錄 ..................................................................................................... viii

第一章 緒論....................................................................................... 1
第一節 研究背景............................................................................... 1
第二節 研究動機與目的................................................................... 4
第三節 研究範圍與限制……..………………………..……..….… 6
第二章 文獻探討............................................................................... 7
第一節 保險購買行為....................................................................... 10
第二節 德菲法................................................................................... 15
第三節 層級分析法........................................................................... 17
第四節 模糊邏輯............................................................................... 19
第五節 類神經網路........................................................................... 22
第六節 因素分析法…………………..………………………….… 24
第三章 研究方法............................................................................... 26
第一節 德菲法................................................................................... 26
第二節 層級分析法…………........................................................... 28
第三節 模糊邏輯............................................................................... 33
第四節 類神經網路........................................................................... 35
第五節 因素分析法…………........................................................... 44
第四章 實證結果與分析…………................................................... 46
第一節 研究樣本…………………...…............................................ 46
第二節 層級分析法、模糊邏輯與德菲法混合模型……………… 51
第三節 類神經網路模型……........................................................... 62
第五章 結論與後續研究……........................................................... 73
第一節 結論…………....................................................................... 73
第二節 後續研究............................................................................... 76
參考文獻 …………………................................................................... 77
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