A Study of Establishing a Decision Support System for Customer Satisfaction Analysis 張煒嵩、陳偉星
E-mail: [email protected]
ABSTRACT
In recent years, the concept of customer relationship management has gradually been noticed in most enterprise organizations. Also, customer satisfaction has always played an important role in customer relation management. Customers would decide their level of satis-faction according to heir preference and subjective consciousness to-ward enterprises. Therefore, the success or failure of an enterprise is directly proportional to the level of customer satisfaction. However, at present, there is lack of an effective decision support tool that inte-grate product sale and the quality management to analyze customer satisfaction, thus, it is difficult to analyze the customers' authentic sat-isfaction and their willingness for re-buying. The propose of thesis is to establish complete customer satisfaction analysis system. Our theoretic basis is based on making use of multi-criteria satisfaction analysis (MUSA) to observe customer satisfaction from the whole customers and linguistic additive majority aggregation (LAMA) to ob-serve Customer Satisfaction for the individual customer. In this way, we establish a decision support system for customer satisfaction analysis.
Keywords : decision support system, customer satisfaction analysis , multi-criteria satisfaction analysis , linguistic additive majority aggre-gation
Table of Contents
封面內頁 簽名頁 授權書...iii 中文摘要...v ABSTRACT...vi 誌謝...vii 目
錄...viii 圖目錄...xi 表目
錄...xiii 第一章 緒論...1 1.1 研究背景與動 機...1 1.2 研究目的...2 1.3 研究流
程...3 第二章 文獻探討...4 2.1 顧客滿意度的定 義...4 2.2 顧客滿意度的衡量...6 第三章 研究方
法...11 3.1 研究架構...11 3.2 多準則滿意度分析 法(MUSA)...13 3.2.1 MUSA基本原理...13 3.2.2 MUSA求解整體流 程...13 3.2.3 總體滿意度與個別指標滿意度...15 3.2.4 順序變量轉與數值變 量...16 3.2.5 求解思維 - 序列迴歸模式之建立...17 3.2.6 線性規劃基本數學模型之 建立...17 3.2.7 次佳解模型之建立(對偶)...22 3.2.8 各項滿意度指
標...24 3.2.9 決策支援圖...28 3.3 多數語意合成
法(LAMA)...31 3.3.1 個別客戶總體滿意度之模糊集合概念...31 3.3.2 LAMA基本原 理...33 3.3.3 LAMA與推導性總體滿意度的關係...34 3.3.4 LAMA應用
於MUSA之求解...36 3.4 顧客滿意度分析系統介紹...38 3.4.1 系統架 構...38 3.4.2 系統開發工具...39 3.4.3 系統模
組...40 3.4.4 資料庫表單定義...42 3.4.5 使用者介面介
紹...43 3.4.6 環境設定與問卷資料輸入介紹...45 3.4.7 敘述性統計以及信度分 析介紹...46 3.4.8 MUSA各項指標計算...47 3.4.9 MUSA各項決策
圖...48 第四章 個案分析與探討...53 4.1 資料蒐集與處 理...53 4.1.1 信度分析與敘述性統計...53 4.2 顧客滿意度指標分 析...55 4.2.1 基本MUSA 模型求解滿意度指標...55 4.2.2 MUSA模型 加 入LAMA模型求解...57 4.2.3 決策圖分析...58 第五章 結論與未來研究方 向...65 5.1 結論...65 5.2 未來研究方
向...65 參考文獻...67 REFERENCES
[1] Oliver Richaard L. (1980),“A Cognitive Model of the Ante-cede nts and Conseqences of Satisfaction Decisions,” Journal of Marketing
Research,Vol.17, No.11, pp.460-469.
[2] Reichheld, F.E. and W.E. Sasser Jr. (1990),“Zero-Defections Quality comes to services,” Harvard Business Review, Sep-tember-October, pp.
105-111.
[3] Bolton, R. N. and J. H. Drew (1991), “A Multistage Model of Customers’Assessments of Service Quality and Value,”Journal of Consumer Research, pp.375-384.
[4] ohnson, M.D.and Fornell, C. (1991),“A Framework for Com-paring Customer Satisfaction Across Individuals and Product Categories,”
Journal of Economic Psychology, Vol.12, No.3, pp.267-286.
[5] Kolter, p. (1991), Marketing Management-Analysis, Planning, Implementation and Control , 7th edition, NJ:Prentice-Hall.
[6] Brown, T.J., G.A. Chruchill and J.P. Peter (1991),“Improving the Measurement of Service,” Journal of Retailing, Vol.69-1, pp.127-139.
[7] Fornell, C. (1992),“A National Customer Satisfaction Barome-ter:The Swedish Experience,” Journal of Marketing, Vol.56, No.1, pp.6-21.
[8] Engel, James f., Roger d. Blackwell, and pull W. Miniard (1993),Consumer Behavior, 7th ed., New York, NY: The Dryden, p.559.
[9] Kolter, P., Leong, S. M., Ang, S. H. and Tan, C. T. (1996), Mar-keting Management: An Asian Perspective, pp.617-620.
[10] Day, Ralph L. (1997), “Extending the Concept of Consumer Satisfaction, ” Atlanta: Association for Consumer Research, Vol.4, pp.149-154.
[11] Czepiel, John A. (1974) , Perspective on Consumer Satisfaction, AMA Conference Proceedings, pp.119-123.
[12] Grigoroudis E. and Siskos Y. (2002), Preference disaggregation for measuring and analysing customer satisfaction: The MUSA method, European Journal of Operational Research, 143, pp148-170.
[13] A.Parasurama, Valarie A. Zeithaml, and Leonard L. Berry (1996),“Reassessment of Expectation as a Comparison Stan-dard in Measuring Service Quality: Implications for Future Re-search,” Journal of Marketing, Vol.58, pp.111-124.
[14] Erevelles, S. & Leavitt (1992), “A Comparison of Current Mod-els of Consumer Satisfaction/Dissatisfaction.” Journal of Con-sumer Satisfaction, Dissatisfaction and Complaining Behavior, Vol. 5, pp. 194-114.
[15] Holbrook, M.B., (1983). “Using a structural model of halo ef-fect to assess perceptual distortion due to affective overtones,” Journal of Consumer Research, Vol. 10, pp. 247-252.
[16] Fornell, C. (1992), A National Customer Satisfaction Barometer: The Swedish Experience. Journal of Marketing, Vol.55, pp1-21.
[17] Fornell, C., M. D. Johnson (1996), et al. The American Cus-tomer Satisfaction Index: Nature, Purpose and Findings. Journal of Marketing, Vol.60(4), pp 7-18.
[18] ECSI technical committee. (1998). European customer satisfac-tion index: foundation and structure for harmonized national pi-lot projects, report prepared for the ECSI steering committee, Octber.
[19] Pelaez J. I. and Dona J. M., (2003), “LAMA: A Linguistic Ag-gregation of Majority Additive Operator,” International Journal in Artificial Intelligence. Vol. 18, 7, pp. 809-820.
[20] Wei-Shing Chen and Wei-Shung Chang (2004), Customer Seg-mentation Using Satisfaction Demanding Analysis , Interna-tional Journal of Electronic Business Management, Vol. 2, No. 4, pp. 219-227.