在台灣電信已呈現高度密合、同時三大電信業者已寡佔大部份消費區塊的情況下，過去也有許多二類電信業者甚至如家樂福等零售品牌試圖加入與三大電信競爭，但結果都不如預期。本研究採用Bgane(1969)所提出的PPM延伸理論模型(Push-Pull-Mooring Model)，從推力效果(以滿意度與ARPU值為變數)、拉力效果(替代者吸引力為變數)與鎖住效果(轉換成本與慣性為變數)來分析各種變數與轉換意圖之間的交互影響作用，同時，也探討是否滿意度會受到轉換成本而對轉換意圖具有調節效果。以此來探討7-Mobile以一個電信市場的後進者，應該透過何種策略來提高電信既有用戶的轉換意圖。
本研究之對象為國內20歲以上擁有電信門號之民眾，總計回收樣本數為184份，扣除無效樣本1份後，實際有效樣本為183份。透過敘述性統計、信效度分析及結構方程模型(Structural Equation Modeling, SEM)中之偏最小平方估計法(Partial Least Square, PLS)進行分析，其主要研究結果如下：
1.	替代者吸引力對轉換意圖有顯著的正向影響。
2.	轉換成本對轉換意圖有顯著的負向影響。
3.	慣性對轉換意圖有顯著的負向影響。
緣此，本研究建議7-Mobile應該從提高替代者吸引力著手，運用統一超商強大的通路資源提出有別於其他電信業者的促銷方案，同時，訴求的主力消費者該為鎖住效果較低的用戶，較易驅動消費者的轉換意圖。

關鍵詞：PPM理論模型、滿意度、替代者吸引力、轉換成本、慣性、轉換意圖

The penetrate rate in Taiwan’s telecom market is very high; in the meantime, the top 3 carriers already dominate major market. Despite there are several ISR (Internet Simple Reseller), such as: Carrefour tried to step into the market to compete with top 3 carriers, yet the result is not as their expectation. The study adopt PPM model (Push-Pull-Mooring Model), which released by Bgane in 1969. It utilizes push effect (customer satisfaction and ARPU as variables), pull effect (alternative attractiveness as variable), and mooring effect (switching cost and habit as variables) to analysis the interactive from different variables and switching intention. In addition, the study also would like to investigate the moderating effect of switching costs on the customer satisfaction and switching intention. Based on the research result, to provide strategic thinking for 7-Mobile, as the telecom industrial late mover, how to increase the switching intention towards the current users of top 3 carriers? 
The research target current telecom consumers, which aged 20 or over. There are 184 questionnaires were issue. After removed one invalid sample, 183 valid samples were collected. Except descriptive statistics, validity analysis, and reliability analysis, partial least square method was applied to examine the proposed research framework. After the empirical research, the major findings as follows: 
1.	Alternative attractiveness has significant positive influence on switching intention.
2.	Switching cost has significant negative influence on switching intention.
3.	Habit has significant negative influence on switching intention.
Hence, the research suggests 7-Mobile should emphasis on how to increase alternative attractiveness, take advantage form 7-ELEVEN’s comprehensive channel resources to offer differential promotion campaign compare with other competitors. In the meantime, it should focus on those low loyalty consumers as their mooring effect weaker and more easy to increase switching intention.

目錄
目錄....................................................................................................................................................I
表目錄...............................................................................................................................................II
圖目錄.............................................................................................................................................III
第一章 緒論	1
第一節	研究背景與動機	1
第二節	研究目的	2
第三節	研究流程	2
第二章 文獻回顧	4
第一節	電信產業概況	4
第二節 轉換意圖	9
第三節 PPM理論模型	10
第三章 研究方法	16
第一節	研究架構	16
第二節	研究假設	17
第三節	研究變數定義與衡量	17
第四節	研究與範圍	21
第五節	資料分析方法	21
第四章 資料分析	23
第一節	前測分析	23
第二節	樣本結構分析	24
第三節	研究變項之因果關係	27
第五章	結論與建議	34
第一節	研究結論與發現	34
第二節	管理意涵	35
第三節	研究限制	38
第四節	後續研究建議	38
參考文獻.......	39
附錄一 前測問卷	47
附錄二 正式問卷	50
表目錄
表2-1 台灣的MVNO業者	7
表2-2 各家電信業者網內互打比較	8
表3-1 轉換意圖操作定義與衡量問項	17
表3-2 滿意度操作定義與衡量問項	18
表3-3 每用戶平均貢獻值(ARPU)操作型定義與衡量問項	19
表3-4 替代者吸引力操作型定義與衡量問項	19
表3-5 轉換成本操作型定義與衡量問項	20
表3-6 關係慣性操作型定義與衡量問項	21
表4-1 各構面之信度值	24
表4-2 樣本結構分析	25
表4- 3 研究構面之信效度表	29
表4-4 相關係數矩陣表	30
表4-5 研究模型路徑分析結果	31
表4-6 轉換成本在滿意度與轉換意圖之階層迴歸分析彙整表	32
表4-7 轉換成本在關係慣性與轉換意圖之階層迴歸分析彙整表	33
表4-8 轉換成本在代替者吸引力與轉換意圖之階層迴歸分析彙整表	33
表5-1 本研究假說之驗證結果	34
圖目錄
圖1-1 本研究流程圖	3
圖2-1 消費者最常使用的電信門號	4
圖3-1 研究架構圖	16
圖3-2 電信企業利潤決定因素	18
圖4-1 本研究模型研究路徑圖	31

中文文獻
1.	王海平(2010)。顧客的轉換成本在顧客對電子商務企業忠誠的行程中的調節作用研究。浙江：浙江工商大學碩士論文。
2.	王慧萍(2005)。虛擬與實體的競爭 MVNO在3G市場之發展策略分析。 新通訊 2005年3月號 49 期「趨勢眺望」。取自：http://www.2cm.com.tw/markettrend_content.asp?sn=0701010388
3.	沈慶龍、李宜庭(2010)。探討轉換成本與轉換意圖之前因因子及其對顧客忠誠度之影響。第13屆科際整合管理研討會June 26, 271-288。
4.	林建發 (2006)。便利商店利用虛擬與實際通路結合之消費者使用分析。台中：靜宜大學EMBA論文。
5.	林泰安(2008)。消費者轉換行為之研究。遠東學報第二十五卷第一期。
6.	林沅駿(2009)。慣性與轉換成本在行動電話轉換意圖之角色。台北：銘傳大學管理研究所碩士論文。
7.	侯正裕，陳靜枝，陳鴻基，陳禹辰(2009)。以人口遷移理論探討線上遊戲之轉換。台北：台灣大學資訊管理所，東吳大學企業管理學系，中山管理評論。
8.	胡婉玲(2006)。消費者使用創新性、轉換成本與轉換意圖間關係之實證研究。行銷評論，秋季第3卷，第3期，頁399-422。
9.	徐靖銹(2010)。關係慣性之前置因素與結果。台中：東海大學國際貿易研究所碩士論文。
10.	馬欽海、李藝(2007)。顧客心理安全感對網路服務消費行為作用的實證研究。遼寧：東北大學工商管理學院，管理學報，2007 4 (6)。
11.	張會堂(2005)。行動電話號碼可攜性對顧客轉換意願之探討。台北：台灣科技大學管理研究所碩士論文。
12.	許鴻德(2011)。網內戶打免費及虛擬電信業者的崛起。手機王專題報導：http://www.sogi.com.tw/newforum/article_list.aspx?topic_ID=6174989
13.	陳禹辰、侯正裕、尚榮安、陳靜枝、張翊宏(2009/12)。玩家為何轉換線上遊戲—人口遷徙理論觀點。電子商務學報，第十一卷第四期，頁723-752。
14.	陳藝妮，何緒軍(2010)。服務業中顧客轉換行為整合模型的實證研究。科學决策第12期，决策理論。
15.	陸海文、楊惠媚、陳依敏(2005)。行動通訊服務業顧客滿意度與顧客忠誠度之研究。經營管理論叢，第一期，第2卷， 2005 117-131頁。
16.	黃秀清，梁雄健(2005)。電信企業ARPU值分析。北京郵電大學經濟管理學院，第2期，第7卷，北京郵電大學學報(社會科學版)。
17.	黃峻瑋(2002)。行動通訊服務市場顧客保留因素之探討。新竹：交通管理科學研究所碩士論文。
18.	廖勝富(2010)。科技產品轉換模型-以智慧手機導航與可攜式車用導航為例。台北：台北大學EMBA碩士論文。
19.	劉宗其、吳立偉、黃吉村(2007)。關係慣性與轉換障礙對「滿意度─顧客留存關係之影響－以金融服務業為例。管理學報，第二十四卷第六期，671-687．
20.	德淑塔(2011)。顧客轉換行為之研究朝向以移動裝置購買: PPM 模型方法。台中：中興大學碩士學位論文。
21.	鄭士蘋，(2004)。其他選擇的吸引力、轉換成本和顧客 滿意對競爭市場中顧客忠誠之影響。輔仁管理評論，第十一卷第一期， 77-96頁。
22.	鄭鵬、馬耀峰、王潔潔、李君軼、楊敏(2010)。基於“推－拉”理論的美國旅遊者旅華流動影響因素研究。人文地理第5期總第115期。
23.	謝出本(2011)。消費者替代性選擇對顧客忠誠的影響研究。北京：中國科學技術大學碩士學位論文。
24.	Bill Hsu(2011)。PPM理論的延伸思考。　　http://hsulh.blogspot.com/2011/05/ppm.html 
英文文獻
1.	Alba, J. W., and Hutchinson J. W.(1987). Dimensions of consumer expertise, Journal of Consumer Research,13, 411-454.
2.	Anders Gustafsson, Michael D. Johnson, and Inger Roos.(2005).The effects of customer satisfaction, relationship commitment dimensions, and triggers on customer retention, American Marketing Association , 69, 210–218.
3.	Anderson, J.C. and Gerbing B.W. (1998). Structural equation modling in practice: A review and recommended two-step approach. Psychological Bulletin, 103, 411-423.
4.	Anto’n, C., Camarero, C. and Carrero, M. (2007). Analysing firms’ failures as determinants of consumer switching intentions: The effect of moderating factors, European Journal of Marketing, 41(1/2), 135-158.
5.	Assael, H. (1998). Consumer behavior and marketing action, Cincinnati, OH: Southwestern College Publishing.
6.	Athanassopoulos, A. D. (2000). Customer satisfaction cues to support market segmentation and explain switching behavior, Journal of business research,. 47,191-207.
7.	Bagne, D.J. (1969). Principles of Demography, New York.
8.	Bagozzi, Richard P. and Youjae Yi (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16, 74-94.
9.	Bansal, H S, Taylor, S F and James, Y (2005). Migrating’ to new service providers: toward a unifying framework of consumers’ switching behaviors, Journal of the Academy of Marketing Science, 33 (1), 96-115. 
10.	Barclay, D., Higgins, C., and Thompson, R. (1995). The Partial Least Squares (PLS) approach to causal modeling, personal computer adoption and use as an illustration. Technology Studies, 2(2), 285-309.
11.	Berry, L. L., Seiders K. and Grewal D. (2002). Understanding service convenience, Journal of Marketing, 66, 1-17.
12.	Blackwell, R. D., Miniard, P. W. and Engel J. F. (2001). Customer Behavior, New York: Dryden.
13.	Bloemer, J. and Ruyter, K. (1999). Customer Loyalty in high and low involvement service settings: The moderating impact of positive emotions, Journal of Marketing Management, 15, 315-330.
14.	Burnham, T. A., Frels, J. K. and Mahajan, V. (2003). Consumer switching costs: A topology, antecedent and consequences, Journal of the Academy of Marketing Science, 32(2), 213-217.
15.	Carrasco, R., Azcona, J. M. L. and Lopez-Salido, J. D. (2005). Consumer and Habits: Evidence from Panel Data, The Economic Journal, 115(500), 144-165.
16.	Chen, Y. and Richard, P. (2011). The role of habit in post-adoption switching of personal information technologies: An empirical investigation, Communications of the Association for Information Systems, 28, Artilce 35. http://aisel.aisnet.org/cais/vol28/iss1/35.
17.	Cheug, M. L., Chiu, P. Y. and Lee, K. O, (2010). Online Social networks: Why do students use Facebook? Computers in Human Behavior, 27, 1337-1343.
18.	Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In George A. Marcoulides (Ed.), Modern methods for business research, Lawrence Erlbaum Associates, 295-336.
19.	Chung, Y. F. (2011). Pull-and-suck effects in Taiwan mobile phone subscribers switching intentions, Telecommunications Policy, 35(2), 128-140. 
20.	Colgate, M., and Lang, B. (2001). Switching barriers in consumer markets: an investigationof the financial services industry. Journal of Consumer Marketing, 18(4), 332-347.
21.	Coulter, R. A., and Ligas, M. (2000). The long good-bye: The dissolution of customer-service provider relationships. Psychology and Marketing, 17(8), 669-695.
22.	Eshghi, A., Haughton, D., and Topi, H. (2007). Determinants of customer loyalty in the wireless telecommunications industry, Telecommunications Policy, 31, 93-106.
23.	Fornell, C. and Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement errors, Journal of Marketing Research,18(1),39-50. 
24.	Fornell, C. (1992). A national customer satisfaction barometer: The swedish experience. Journal of Marketing, 56(1), 6-21.
25.	Fornell, C., and Cha, J. (1994). Partial least squares. In R. P. Bagozzi (Ed.), Advanced methods of marketing research (pp. 52-78). Cambridge, England: Blackwell.
26.	Fu, Jen-Ruei (2006). VISUAL PLS 1.04b1. http://www2.kuas.edu.tw/prof/fred/vpls/index.html.
27.	Garling, T., Fujii, S. and Boe, O. (2001). Empirical tests of a model of determinants of script-based driving choice, Transportation Research, 4, 89-102.
28.	Gefen, D. and Straub, D.W. (2005). A practical guide to factorial validity using PLS-graph: tutorial and annotated example. Communications of the Association for Information Systems, 16(5), 91-109.
29.	Gefen, D. Straub, D.W. and Boudreau, M.C. (2000). Structural equation modeling and regression: Guidelines for research practices. Communication of the Association for Information Systems, 7(4), 1-79
30.	Gruber, Harald (1998). An Investment of mobile telecommunications in the european union . Telecommunications Policy, 23, 521-538.
31.	Guiltinan, Josiph P. (1989). A Classitification of switching costs with implications for relationship marketing. In Terry L. Childers, Richard P. Bagozzi and J. Paul Peter. (Eds) 1989 AMA Winter Educators’ Conference: Marketing Theory and Practice. Chicage: American Marketing Association, 216-220.
32.	Hair, Jr., J.F., Black, W.C., Babin, B.J., and Anderson, R.E. (2010).  Multivariate data analysis, upper saddle river, new jersey, USA: Prentice Hall.
33.	Hair,J.F., Anderson, R.E., Tatham, R, L., and Black, W. C. (1998). Multivariate data analysis (5th ed.). Boston, MA: Pearson education Inc. 
34.	Heskett, J. L., Jones, T. O., Loveman, G. W., Jr Sasser, W. E. and Schlesinger, L. A. (1994). Putting the service-profit chain to work, Harvard Business Review, (Mar./Apr.), 164-174.
35.	Hidalgo, P., Manzur, E., Olavarrieta, S. and Farias, P. (2008). Customer retention and price matching: The AFPs case, Journal of Business Research, 61, 691–696.
36.	Hsieh, S. and Liu, L.C. (2005). The nature of switch cost: task set reconfiguration or carry-over effect? Cognitive Brain Research, 22, 165-175.
37.	Hu, W. L. and Hwang, I. S. (2006). Measuring the Effects of Consumer switching Costs on Switching Intention in Taiwan Mobile Telecommunication Services, The Journal of American Academy of Business, 9(1), 75-85.
38.	Hulland, J. (1999). Use of partial least squares in strategic management research: A review of four recent studies, Strategic Management Journal, 20(2), 195-204.
39.	Jolley, B., Mizerski, R. and Olaru, D.(2006). How habit and satisfaction affects player retention for online gambling, Journal of Business Research, 59,770-777 
40.	Jones, M. A., Mothersbaugh, D. L., & Beatty, S. E. (2000). Switching barrier and repurchase intantion in service, Journal of Retailing, 76(2), 259-274.
41.	Jones, M. A., Mothersbaugh, D. L., and Beatty, S. E. (2002). Why customers stay: Measuring the underlying dimensions of serviced switching costs and managing their differential strategic outcomes, Journal of Business Research, 55(6), 441-50.
42.	Keaveney, S. and Parthasarathy, M. (2001). Customer switching behaviour in online services: An exploratory study of the role of selected attitudinal, behavioural, and demographic factors, Journal of the Academy of Marketing Science, 29(4), 374-390.
43.	Kerin, Roger A., R. Rajan Varadarajan, and Robert A. Peterson (1992). First-Mover Advantage: A Synthesis, Conceptual Framework, and Research Propositions, Journal of Marketing, 56, 33-52.
44.	Kim Hee-Woong, Yoon-Seung Jeon, and Sujin Choi, Attractiveness of alternative in information system continuance: A case of WIMAX. The 11th International DSI and the 16th APDSI Joint Meeting, Taipei, Taiwan, July 12 – 16, 2011
45.	Kim, H. S. and Yoon, C. H. (2004). Determinants of subscriber churn and customer loyalty in Korean mobile telephone market, Telecommunications Policy, 28: 751-765.
46.	Kim, K. A., Park, J. S., Kim, J. J. and Koh, J. (2011). Why do customers keep or switch their mobile telecommunication service provider? New Challenges for Intelligent Information and Database Systems Studies in Computational Intelligence, 351, 349-362.
47.	Kim, M. K., Park, M.C. and Jeong, D. H. (2004). The effect of customer satisfaction and switching barrier on customer loyalty in Korean mobile telecommunication services, Telecommunications Policy, 28, 145-149.
48.	Klemperer, P. (1988). Welfare effects of entry into market with switching cost, Journal of Industrial Economics, 37(2), 159-165.
49.	Lee, J., Lee, J. and Feick, L. (2001). The impact of switching costs on the customer-loyalty link: Mobile phone service in France, Journal of Service Marketing, 15(1), 35-48     
50.	Liao, C., Paliva, P. and Lin, H. N. (2006). The Roles of habit and site quality in E-Commerce, International Journal of Information Management, 26(6), 469-483.
51.	Lui, S. M. (2005). Impacts of information technology commoditization: Selected studies from ubiquitous information service, Ph.D. Thesis, Hong Kong University of science and technology. 
52.	Manrai L.A. and Manrai, A. K. (2007). A field study of customers’ switching behavior for bank services, Journal of Retailing and Consumer Services, 14,208-215.
53.	McDougall, G. and Levesque, T. (2000).Customer satisfaction with service：Putting perceived value into the equation, Journal of Service Marketing, 14(5), 392-408. 
54.	Medina, M. Q., and Chaparro, J. P. (2007/2008). The impact of the human element in the information systems quality for decision making and user satisfaction, The Journal of Computer Information Systems, 48(2), 44-53.
55.	Morgan, R. M., and Hunt, S. D. (1994). The commitment-trust theory of relationship marketing, Journal of Marketing, 58(3), 20-38.
56.	Nunnally, J. C. (1978). Psychometric theory. New York: McGraw-Hill
57.	Nunnally,J. C. and Bernstein, I.H.(1994). Psychometric theory (3rd ed.). New York: McGraw-Hill. 
58.	Oliver, R. L. (1999). Whence consumer loyalty? Journal of Marketing, 63, 33-44.
59.	Olsen, S. O. (2007). Repurchase Loyalty: The role of involvement and satisfaction, Psychology & Marketing, 24(4), 315-341.
60.	Patterson, P. G., and Smith T. (2003). A Cross-Cultural Study of switching barriers and propensity to stay with service providers. Journal of Retailing, 79, P107-120.
61.	Pavlou, P.A. and Fygenson, M. (2006). Understanding and predicting electronic commerce adoption: An extension of the theory of planned behavior, MIS Quarterly, 30 (1), 115-143.
62.	Ranaweera, C. and Prabhu, J. (2003). The influence of satisfaction, trust and switching barriers on customer retention in a continuous purchasing setting, International Journal of Service Industry Management, 14(4), 374-395.
63.	Sang, S., Lee, J. D. and Lee, J. (2010). E-government adoption in Cambodia: A partial least squares approach. Transforming Government: People, Process, and Policy, 4(2),138-157.
64.	Sharma, N., and Patterson, P. G. (2000). Switching costs, alternative attractiveness and experience as moderators of relationship commitment in professional, consumer services, International Journal of Service Management, 11(5), 470-90.
65.	Shin, D. H. and Kim, W. Y. (2008). Forecasting customer switching intention in mobile service: An exploratory study of predictive factors in mobile number portability, Technological Forecasting and Social Change, 75(6), 854-874.
66.	Spreng, R.A., MacKenzie S.B.,and Olshavsky R.W.(1996). A reexamination of the determinants of consumer satisfaction, Journal of Marketing, 60, 15-32.
67.	Sutherland, E. (2007). Mobile number portability, info , 9(4) 10-24.
68.	Verplanken, B. and Aarts, H. (1999). Habit, attitudes, and planned behavior: Is habit an empty construct or an interesting case of goal-directed behavior, European Review of Social Psychology, 10, 101–134.
69.	Yanamandram, V. and White, L. (2006). Switching barriers in business-to-business services: A qualitative study, International Journal of Service Industry Management, 17(2), 158-192.