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研究生: 劉千綺
Liu, Chien-Chi
論文名稱: 校友關係管理架構之初探
A holistic strategic framework on ARM implementation
指導教授: 呂執中
Lyu, Jr-Jung
學位類別: 碩士
Master
系所名稱: 管理學院 - 工業與資訊管理學系
Department of Industrial and Information Management
論文出版年: 2010
畢業學年度: 98
語文別: 英文
論文頁數: 88
中文關鍵詞: 顧客關係管理校友募捐校友關係管理
外文關鍵詞: Customer Relationship Management (CRM), alumni donation, Alumni Relationship Management (ARM)
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  • 在國家財政吃緊的今天,教育預算捉襟見肘,政府能夠給予各大學院校之補助相當有限,因此各大學院校自籌經費支持校務運作已成必然趨勢。儘管有部份大學院校可以爭取到企業或財團法人經費上的支持,但校友募捐仍是大部分大學院校主要的經費來源。校友募捐既為各大學院校仰賴生存十分重要的一環,則如何和校友維繫良好關係、進而提升校友捐款意願之重要性便相形提高。
    校友相關文獻指出與校友培養良好且長久的關係對於增加校友捐款意願有著正向且顯著的影響。再者,文獻指出關係行銷手法可被運用於校友與母校之間長久關係的維繫上,此研究課題已成為近年來相當受到關注的新興研究領域。然而,以關係行銷為根基的校友募捐研究尚屬匱乏。
    綜合以上所述,此研究以『顧客關係管理』,從關係行銷衍伸而來之行銷手法,作為校友與母校長久關係發展的理論根基,提出一校友關係管理之架構並採用資料探勘手法- 模式樹將美國CAE組織所蒐集到之美國公私立大學校友募捐資料運用於模式樹之建構上。六種不同類別的校友募捐資料分別被建構成六棵模式樹,同時產出每棵模式樹所對應之相關係數。藉由分析模式樹之結構及其相關係數將校友資料轉換為有用之校友知識,進而發展出具參考價值之校友關係管理策略的具體建議。大學院校可以本研究所提出之校友關係管理架構為基礎,針對不同特徵族群之校友進行校友知識挖掘,並參考本研究所提出之校友關係管理策略的具體建議,發展出適合各族群之校友關係管理策略,以加深校友與母校之關係緊密度,以提升校友捐款之意願。

    State appropriations to higher education have declined relative to the rising costs of educating students and the ability of states to fund higher education. In this changing landscape of financing higher education, institutions of higher education are increasingly relying upon private support to keep their programs competitive. As charitable giving of alumni has always been the most significant source of revenue for higher education institutions, it becomes imperative for higher education institutions to cultivate a pool of loyal alumni donors.
    Existing studies of alumni reveal that cultivating a long- lasting relationship between alumni and their alma mater is significantly important to fostering alumni donors. In fact, long-term relationship between alumni donors and their alma mater has been studied from a relationship marketing perspective and has sparked a new interest in relational marketing. However, researches of alumni donation based on relational or marketing approach is still scarce.
    This research aims to explore the field of long-term relationship between alumni and university based on the concepts and principles of Customer Relationship Management (CRM), a relational marketing approach evolved from relationship marketing. A strategic framework of Alumni Relationship Management (ARM) is proposed and application of the proposed framework is demonstrated with model tree as the research methodology to analyze and transform alumni data of American higher education institutions into useful alumni knowledge. Based on the result of analysis, concrete suggestions for decision makers to develop ARM strategies are delineated at the end of the research.

    摘要 I ABSTRACT II ACKNOWLEDGEMENT III TABLE OF CONTENTS IV LIST OF TABLES VI LIST OF FIGURES VII CHAPTER 1 INTRODUCTION 1 1.1 RESEARCH BACKGROUND AND MOTIVATIONS 1 1.2 RESEARCH OBJECTIVES 3 1.3 RESEARCH LIMITATIONS 3 1.4 ORGANIZATION OF RESEARCH 3 CHAPTER 2 LITERATURE REVIEW 5 2.1 ALUMNI GIVING 5 2.2 CUSTOMER RELATIONSHIP MANAGEMENT (CRM) 12 2.2.1 Customer Knowledge and Customer Knowledge Competence 12 2.2.2 Knowledge Discovery 16 2.2.3 Knowledge Application 20 CHAPTER 3 RESEARCH FRAMEWORK AND METHODOLOGY 26 3.1 STRATEGIC FRAMEWORK ON ARM IMPLEMENTATION 26 3.1.1 Background of the strategic framework on ARM implementation 26 3.1.2. Development of the strategic framework on ARM implementation 30 3.2 METHODOLOGY 35 3.2.1. The Concept of Model tree 35 3.2.2. Data preprocessing 36 3.2.3. Construction of model tree 38 CHAPTER 4 DATA ANALYSIS 41 4.1 DATA PREPROCESSING 42 4.1.1 Description of selected attributes 42 4.1.2 Adjusted attributes 44 4.2 RESULTS AND EVALUATION 46 4.2.1 Results for Public Higher Education Institutions 47 4.2.2 Results for Private Higher Education Institutions 54 4.3 DISCUSSION 61 CHAPTER 5 CONCLUSIONS AND FUTURE DIRECTIONS 78 5.1 RESEARCH FINDINGS 80 5.2 FUTURE RESEARCH DIRECTIONS 82 REFERENCE 83

    Ahmed, S. (2004). Applications of Data Mining in Retail Business. IEEE Computer Society, 2( ), 455-459.
    Arnett, D., German, S., & Hunt, S. (2003). The identity salience model of relationship marketing success: the case of nonprofit marketing. Journal of Marketing, 67(2), 89-105.
    Baade, R., & Sundberg, J. (1996). What determines alumni generosity? Economics of Education Review, 15(1), 75-81.
    Belfield, C., & Beney, A. (2000). What determines alumni generosity? Evidence for the UK. Education Economics, 8(1), 65-80.
    Bekkers, R., & Wiepking, P (2007). Generosity and philanthropy: A literature review.
    Bendoly, E. (2003). Theory and Support for Process Frameworks of Knowledge
    Discovery and Data Mining from ERP Systems, Information and
    Management, 40, 7, 639-647.
    Berry, M., & Linoff, G. (2004). Data mining techniques: for marketing, sales, and customer relationship management: Wiley New York.
    Bolloju, N., Khalifa, M. and Turban, E. (2002). Integrating Knowledge Management into Enterprise Environments for the Next Generation Decision Support, Decision Support Systems, 33, 2, 163-176.
    Bruggink, T., & Siddiqui, K. (1995). An Econometric Model of Alumni Giving: A Case Study for a Liberal Arts College. American Economist, 39(2), 53-60.
    Bryant, W., Jeon-Slaughter, H., Kang, H., & Tax, A. (2003). Participation in philanthropic activities: Donating money and time. Journal of Consumer Policy, 26(1), 43-73.
    Campbell, A. J. (2003). Creating Customer Knowledge Competence: Managing
    Customer Relationship Management Programs Strategically,
    Industrial Marketing Management, 32, 5, 375-383.
    Chen, Y., & Su, C. (2006). A Kano-CKM model for customer knowledge discovery. Total Quality Management & Business Excellence, 17(5), 589-608.
    Clotfelter, C. T.(2000). Alumni Giving to Elite Private Colleges and Universities.Working Paper. Duke University.
    Clotfelter, C.T.(2003). Alumni giving to elite private colleges and universities, Economics of Education Review, 22, 2, pp.109–120.
    Day, G. (1994). The capabilities of market-driven organizations. The Journal of Marketing, 58(4), 37-52.
    Davenport, T., & Klahr, P. (1998). Managing customer support knowledge. California Management Review, 40, 195-208.
    E. Ould-Ahmed-Vall, J., Woodlee, C., Yount, K., Doshi., & S. Abraham. (2007) Using
    model trees for computer architecture performance analysis of software
    applications, in IEEE International Symposium on Performance
    Analysis of Systems and Software (ISPASS), pp. 116–125.
    Giraud-Carrier, C., & Povel, O. (2003). Characterising data mining software. Intelligent Data Analysis, 7(3), 181-192.
    Gronroos, C. (1990). Relationship approach to marketing in service contexts: the marketing and organizational behavior interface. Journal of business research, 20(1), 3-11.
    Gummesson, E. (1987). The new marketing¡XDeveloping long-term interactive relationships. Long Range Planning, 20(4), 10-20.
    Gummesson, E. (2002). Relationship marketing in the new economy. Journal of Relationship Marketing, 1(1), 37-57.
    Harrison, W. (1995). College relations and fund-raising expenditures: Influencing the probability of alumni giving to higher education. Economics of Education Review, 14(1), 73-84.
    Heckman, R., & Guskey, A. (1998). The relationship between alumni and university: toward a theory of discretionary collaborative behavior. Journal of Marketing Theory and Practice, 6(2), 97-112.
    Hueston, F. (1992). Predicting alumni giving: A donor analysis test. Fund Raising Management, 23(5), 19-22.
    Hunt, E.B., Martin, J., Stone, P. (1996). Experiments in Induction. Academic Press, New York.
    Jackson, B. B. (1985). Build customer relationships that last. Harvard Business Review, 11, 120-128.
    Jiao, J., Zhang, Y., & Helander, M. (2006). A Kansei mining system for affective design. Expert Systems with Applications, 30(4), 658-673.
    Kalavathy, R., Suresh, R., & Akhila, R. (2007). KDD and data mining. Paper presented at the IET-UK International Conference on Information and Communication Technology in Electrical Sciences India.
    Kim, Y. (2006). Toward a successful CRM: variable selection, sampling, and
    ensemble, Decision Support Systems, vol. 41, no. 2, pp. 542-553.
    Korvas, R. (1984). The relationship of selected alumni characteristics and attitudes to alumni financial support at a private college. School of Education. University of Missouri-Kansas City.
    Leslie, L., & Ramey, G. (1988). Donor behavior and voluntary support for higher education institutions. The Journal of Higher Education, 59(2), 115-132.
    Li, T., & Calantone, R. J. (1998). The impact of market knowledge competence on new product advantage: Conceptualization and empirical examination. Journal of Marketing, 62, 13– 29.
    Lilien, G., Rangaswamy, A., Van Bruggen, G., & Wierenga, B. (2002). Bridging the marketing theory-practice gap with marketing engineering. Journal of business research, 55(2), 111-121.
    Lindahl, W., & Winship, C. (1994). A logit model with interactions for predicting major gift donors. Research in Higher Education, 35(6), 729-743.
    Marakas,G. M. (1995). The discovery-learning DSS: allowing for discovery in the decision process, in: Proceedings of the 28thAnnual Hawaii International Conference on System Sciences, pp. 72–81.
    Martínez, L., Francisco.J., & Casillas, J. (2008). Marketing Intelligent Systems for
    consumer behaviour modelling by a descriptive induction approach based
    on Genetic Fuzzy Systems, Industrial Marketing Management, vol. In
    Press, Corrected Proof.
    McAlexander, J., & Koenig, H. (2001). University Experiences, the Student-College Relationship, and Alumni Support. Journal of Marketing for Higher Education, 10(3), 21-43.
    McAlexander, J., Koenig, H., & Schouten, J. (2005). Building a university brand community: The long-term impact of shared experiences. Journal of Marketing for Higher Education, 14(2), 61-79.
    McGuire, J. (2003). Integrating fund raising with academic planning and budgeting: Toward an understanding of strategic fund raising. Dissertations available from ProQuest.
    Mitra, S., Pal, S., & Mitra, P. (2002). Data mining in soft computing framework: A survey. IEEE Transactions on Neural Networks, 13(1), 3-14.
    Monks, J. (2003). Patterns of giving to one's alma mater among young graduates from selective institutions. Economics of Education Review, 22(2), 121-130.
    Ngai, E., Xiu, L., & Chau, D. (2009). Application of data mining techniques in customer relationship management: A literature review and classification. Expert Systems with Applications, 36(2), 2592-2602.
    Okunade, A. A. (1996). Graduate school alumni donations to academic funds-micro data evidence. American Journal of Economics and Sociology, 55, 213-229.
    Okunade, A., & Berl, R. (1997). Determinants of charitable giving of business school alumni. Research in Higher Education, 38(2), 201-214.
    O'Neil, J., & Schenke, M. (2006). An examination of factors impacting athlete alumni donations to their alma mater: a case study of a US university. International Journal of Nonprofit and Voluntary Sector Marketing, 12(1), 59-74.
    Paquette, S. (2006). Customer Knowledge Management. Encyclopedia of Knowledge Management, 90-96.
    Peterson, M., & Rajan, R. (1995). The Effect of Credit Market Competition on Firm-Creditor Relationships. Quarterly Journal of Economics 110.
    Prahalad, C. K. and G. Hamel (1990), The Core Competence of the Corporation,
    Harvard Business Review, May-June, 1990, 79-91.
    Quinlan, J. (1992). Learning with Continuous Classes. Paper presented at the In Proceedings of the Australian Joint Conference on Artificial Intelligence, Singapore.
    Ruta, Daiva & Virginija (2008). The Model of Creation of Customer Relationship Management (CRM) System. The economic conditions of enterprise functioning,3 (58).
    S.H. Thomke.(1998). Managing experimentation in the design of new products, Management Science 44, pp. 743–762.
    Shaw, M., Subramaniam, C., Tan, G., & Welge, M. (2001). Knowledge management and data mining for marketing. Decision Support Systems, 31(1), 127-137.
    Smith, H. A., & McKeen, J. D. (2005). Customer Knowledge Management: adding value for our customers. Communication of Association for Information Systems, (16),744-755.
    Stephen. H., & Steve. M. (2004). Using Model Trees to Characterize Computer Resource Usage, in 1st ACM SIGSOFT Workshop on Self-Managed Systems, pp. 80–84.
    Stutler, D., & Calvario, D. (1996). In alumni support, satisfaction matters. Fund Raising Management, 27(9), 12-13.
    Thomas, J., & Smart, J. (2005). The Relationship between Personal and Social Growth and Involvement in College and Subsequent Alumni Giving. Online Submission, 31.
    Turban, E., Aronson, J. E., Liang, T. P., & Sharda, R. (2007). Decision support and business intelligence systems : Pearson Education.
    Wang, Y., & Witten, I. (1997). Inducing model trees for continuous classes. Paper presented at the In Proceedings of the poster papers of the European Conference on Machine Learning, Prague.
    Wedgeworth, R. (2000). Donor relations as public relations: toward a philosophy of fund-raising. ILLINOIS, 48(3), 530-539.
    Weerts, D., & Ronca, J. (2009). Using classification trees to predict alumni giving for higher education. Education Economics, 17(1), 95-122.
    Wierenga, B., Van Bruggen, G., & Staelin, R. (1999). The success of marketing management support systems. Marketing Science, 18(3), 196-207.
    X. Hu, (1993). Conceptual Clustering and Concept Hierarchies in
    Knowledge Discovery, Simon Fraser University, Burnaby, BC.

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