臺灣博碩士論文加值系統

隨著智慧型手機與網路的普及化，人們的生活便利許多，消費者也不必親自前往金融機構，只要使用智慧型手機上的網路銀行APP即可轉帳、投資與完成各種金融交易。網路銀行發展到至今，其類型可分為三種：由實體銀行所發展的網路銀行、數位銀行和純網路銀行，本研究將這三種統稱為網路銀行。消費者有許多網路銀行可供挑選，因此，本研究的目的是了解消費者對於網路銀行的轉換意圖，使用推力-拉力-繫住力理論的各個構念來探討影響轉換意圖的重要因素。本研究以問卷調查法來蒐集研究資料，研究目標以18歲以上的消費者作為主要探討對象，以網路問卷在網路上發放並蒐集，總共回收252份問卷，有效問卷為220份。透過SPSS 29.0與SmartPLS 4.0軟體進行資料分析，研究結果顯示：推力效果(感知價值、不便利性)會正向影響消費者對於網路銀行之轉換意圖；拉力效果(感知有用性、感知易用性、替代品吸引力、個人創新、社會影響)會正向影響消費者對於網路銀行之轉換意圖；繫住力效果(慣性、信任、感知風險、轉換成本)會負向影響消費者對於網路銀行之轉換意圖。最後，本研究根據研究結果提出學術與實務建議。

With the widespread adoption of smartphones and the Internet, people's life has become much more convenient. Consumers no longer need to go to financial institutions in person. They can transfer money, invest, or complete various financial transactions by using Internet Banking apps on their smartphones. Internet Banking has evolved into three main types: traditional banks, digital bank, and Internet-Only Bank. This study collectively refers to these three types as Internet Banking. Given the wide range of Internet Banking available for consumers to choose from, the purpose of this study is to understand consumers' switching intention towards Internet Banking. Using the Push-Pull-Mooring (PPM) theory, this study explores the key factors influencing these switching intentions.
This study collected research data through a questionnaire survey method, targeting consumers aged 18 and above as the main subjects of investigation. The questionnaire was distributed and collected online, with a total of 252 responses received, of which 220 were valid. Data analysis was conducted using SPSS 29.0 and SmartPLS 4.0 software. The research findings indicate that push effects (perceived value, inconvenience) positively influence consumers' intention to switch to Internet Banking; pull effects (perceived usefulness, perceived ease of use, alternative attractiveness, personal innovativeness in IT, social influence) positively influence consumers' intention to switch to Internet Banking; and mooring effects (inertia, trust, perceived risk, switching cost) negatively influence consumers' intention to switch to Internet Banking. Finally, based on the research results, this study provides academic and practical recommendations.

摘要.......................................i
Abstract..................................ii
誌謝......................................iii
目錄......................................iv
表目錄.....................................vi
圖目錄....................................vii
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................................2
第二章 文獻探討.............................4
2.1 網路銀行................................4
2.1.1 由實體銀行所發展的網路銀行.............4
2.1.2 數位銀行(數位帳戶、數位存款帳戶)........6
2.1.3 純網路銀行............................7
2.2 推力-拉力-繫住力理論.....................8
2.3 感知價值...............................10
2.4 不便利性................................11
2.5 科技接受模式............................12
2.6 替代品吸引力............................13
2.7 個人創新...............................13
2.8 社會影響...............................14
2.9 慣性...................................15
2.10 信任..................................15
2.11 感知風險..............................16
2.12 轉換成本..............................17
第三章 研究方法.............................18
3.1 研究架構...............................18
3.2 研究假設................................19
3.3 研究變數之操作型定義....................21
3.4 研究對象...............................26
3.5 問卷設計...............................26
第四章 資料分析.............................27
4.1 前測分析...............................27
4.2 敘述性統計分析.........................28
4.3 測量模式分析...........................31
4.3.1 正式問卷之信度分析....................35
4.3.2 正式問卷之效度分析....................36
4.4 結構模型分析與假設驗證..................42
第五章 結論與建議...........................45
5.1 研究結論...............................45
5.2 研究貢獻...............................47
5.2.1 學術貢獻.............................47
5.2.2 實務貢獻.............................47
5.3 研究限制...............................48
5.4 未來研究建議...........................49
參考文獻...................................50
附錄.......................................61
Extended Abstract.........................70

中文文獻
工商時報(2022)。疫情助攻 數位帳戶衝破1,385萬。https://www.ctee.com.tw/news/20221222700097-430301
中央銀行(2018)。6月21日央行理監事會後記者會參考資料。https://www.cbc.gov.tw/tw/cp-357-65706-BB65B-1.html
自由時報(2024)。〈財經週報-銀行業獲利〉三家純網銀仍虧損 力拚2025年損益兩平。https://ec.ltn.com.tw/article/paper/1628521
股感知識庫(2024)。數位帳戶是什麼？有哪些優缺點？與純網銀、網路銀行差在哪？https://www.stockfeel.com.tw/%E6%95%B8%E4%BD%8D%E5%AD%98%E6%AC%BE%E5%B8%B3%E6%88%B6-%E6%95%B8%E4%BD%8D%E5%B8%B3%E6%88%B6-%E6%AF%94%E8%BC%83-%E5%84%AA%E7%BC%BA%E9%BB%9E/
邱皓政(2011)。結構方程模式－LISREL/SIMPLIS 原理與應用(二版)。台北：雙葉。
金融監督管理委員會(2015)。打造數位化金融環境3.0全面啟動。https://www.fsc.gov.tw/ch/home.jsp?id=96&parentpath=0,2&mcustomize=news_view.jsp&dataserno=201501130003&toolsflag=Y&dtable=News
金融監督管理委員會(2019)。金管會公布純網路銀行許可設立名單。https://www.fsc.gov.tw/ch/home.jsp?id=96&parentpath=0,2&mcustomize=news_view.jsp&dataserno=201907300001&aplistdn=ou=news,ou=multisite,ou=chinese,ou=ap_root,o=fsc,c=tw&dtable=News
金融監督管理委員會(2019)。銀行受理客戶以網路方式開立數位存款帳戶作業範本部分條文修正對照表。
金融監督管理委員會(2023)。金融科技發展路徑圖(2.0)。
金融監督管理委員會(2024)。數位存款帳戶業務統計。https://www.banking.gov.tw/ch/home.jsp?id=591&parentpath=0,590&mcustomize=multimessage_view.jsp&dataserno=201911270001&dtable=Disclosure
侯正裕、陳靜枝(2012)。「網際遷移」─以人口遷移理論探索社交網站的轉換-舉Plurk為例。資訊管理學報，19(1)，105-132。https://doi.org/10.6382/JIM.201201.0105
侯正裕、陳靜枝、陳禹辰(2011)。「遷移到虛擬新世界」—以人口遷移理論探討MMORPG玩家的轉換。中山管理評論，19(1)，147-177。https://doi.org/10.6160/2011.03.01
蔡宜珍(2017)。探討消費者的轉換意圖及實際行為-以星巴克隨行卡及行動應用程式為例〔碩士論文，國立臺中科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0061-2706201722164600
鄧維兆、廖明宗、馬郁淇(2007)。網路銀行關鍵服務品質屬性確認-三因子理論與IPA之應用。品質學報，14(4)，351-365。
鄭鈞、邱兆民、梁定澎、徐士傑、陳怡蓁(2022)。以推力-拉力-繫住力理論探討消費者對純網銀之轉換意圖。中山管理評論，30(1)，3-36。
盧志敏(2001)。網路銀行的發展與影響，中央銀行季刊第二十三卷第一期。
謝凌立(2016)。從現金支付到行動支付——以PPM理論探討台灣消費者支付方式轉換意圖〔碩士論文，國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU201603392

英文文獻
Agarwal, R., & Karahanna, E. (2000). Time flies when you're having fun: Cognitive absorption and beliefs about information technology usage. MIS quarterly, 665-694.
Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information systems research, 9(2), 204-215.
Anderson, J. C., & Narus, J. A. (1990). A model of distributor firm and manufacturer firm working partnerships. Journal of marketing, 54(1), 42-58.
Bansal, H. S., Taylor, S. F., & St. 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.
Bauer, R. A. (1967). Consumer behavior as risk taking. Marketing: Critical perspectives on business and management,593, 13-21.
Berry, L. L., Seiders, K., & Grewal, D. (2002). Understanding service convenience. Journal of marketing, 66(3), 1-17.
Bogue, D. J. (1969). Principles of demography.
Brown, L. G. (1990). Convenience in services marketing. Journal of Services Marketing, 4(1), 53-59.
Burnham, T. A., Frels, J. K., & Mahajan, V. (2003). Consumer switching costs: A typology, antecedents, and consequences. Journal of the Academy of marketing Science, 31(2), 109-126.
Caruana, A. (2003). The impact of switching costs on customer loyalty: A study among corporate customers of mobile telephony. Journal of Targeting, Measurement and Analysis for marketing, 12, 256-268.
Chang, E. C., & Tseng, Y. F. (2013). Research note: E-store image, perceived value and perceived risk. Journal of business research, 66(7), 864-870.
Chang, H. H., & Chen, S. W. (2008). The impact of customer interface quality, satisfaction and switching costs on e-loyalty: Internet experience as a moderator. Computers in Human Behavior, 24(6), 2927-2944.
Chang, H. H., Wong, K. H., & Li, S. Y. (2017). Applying push-pull-mooring to investigate channel switching behaviors: M-shopping self-efficacy and switching costs as moderators. Electronic Commerce Research and Applications, 24, 50-67.
Chang, Y. W., & Hsu, P. Y. (2019). An empirical investigation of organizations’ switching intention to cloud enterprise resource planning: a cost-benefit perspective. Information Development, 35(2), 290-302.
Chiang, H. S., & Chen, C. C. (2014). Exploring switch intention of users’ reading behaviour: An e-book reader case study. The Electronic Library, 32(4), 434-457.
Cox, D. F., & Rich, S. U. (1964). Perceived risk and consumer decision-making—the case of telephone shopping. Journal of marketing research, 1(4), 32-39.
Davis, F. D. (1986). A technology acceptance model for empirically testing new end-user information systems: Theory and results. Doctoral dissertation, Sloan School of Management, Massachusetts Institute of Technology.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management science, 35(8), 982-1003.
Deutsch, M., & Gerard, H. B. (1955). A study of normative and informational social influences upon individual judgment. The journal of abnormal and social psychology, 51(3), 629.
DeVellis, R. F. (1991). Scale Development: Theory and Applications. Newbury Park, Calif: Sage, 51-91.
Dimitriadis, S., & Kyrezis, N. (2010). Linking trust to use intention for technology‐enabled bank channels: The role of trusting intentions. Psychology and Marketing, 27(8), 799-820.
Dimitriadis, S., & Kyrezis, N. (2011). The effect of trust, channel technology, and transaction type on the adoption of self-service bank channels. The Service Industries Journal, 31(8), 1293-1310.
Fahmi, S., & Rohman, F. (2018). Factors affecting Indonesian consumers to switch, using mobile banking and internet banking service. KnE Social Sciences.
Farquhar, J. D., & Rowley, J. (2009). Convenience: a services perspective. Marketing theory, 9(4), 425-438.
Fornell, C. (1992). A national customer satisfaction barometer: The Swedish experience. Journal of marketing, 56(1), 6-21.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.
Gray, D. M., D’Alessandro, S., Johnson, L. W., & Carter, L. (2017). Inertia in services: causes and consequences for switching. Journal of Services Marketing, 31(6), 485-498.
Han, H., & Hyun, S. S. (2013). Image congruence and relationship quality in predicting switching intention: Conspicuousness of product use as a moderator variable. Journal of Hospitality and Tourism Research, 37(3), 303-329.
Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115-135.
Holbrook, M. B. (1999). Consumer value. A framework for analysis and research.
Hsu, C. L., & Lu, H. P. (2004). Why do people play on-line games? An extended TAM with social influences and flow experience. Information and management, 41(7), 853-868.
Huang, M. H., & Yu, S. (1999). Are consumers inherently or situationally brand loyal? —A set intercorrelation account for conscious brand loyalty and nonconscious inertia. Psychology and Marketing, 16(6), 523-544.
Hung, S. Y., Ku, C. Y., & Chang, C. M. (2003). Critical factors of WAP services adoption: an empirical study. Electronic commerce research and applications, 2(1), 42-60.
Jacoby, J. & Kaplan, L. B. (1972). ‘The components of perceived risk’, Advances in Consumer Research, 1(1),382–393.
Jahangir, N., & Begum, N. (2008). The role of perceived usefulness, perceived ease of use, security and privacy, and customer attitude to engender customer adaptation in the context of electronic banking. African journal of business management, 2(2), 32.
Jones, M. A., Mothersbaugh, D. L., & Beatty, S. E. (2000). Switching barriers and repurchase intentions in services. Journal of retailing, 76(2), 259-274.
Keaveney, S. M. (1995). Customer switching behavior in service industries: An exploratory study. Journal of marketing, 59(2), 71-82.
Kelman, H. C. (1958). Compliance, identification, and internalization three processes of attitude change. Journal of conflict resolution, 2(1), 51-60.
Kemp, S. (2023). Digital 2023: Taiwan. Datareportal. https://datareportal.com/reports/digital-2023-taiwan
Kerlinger, F. N. (1986). Foundations of Behavioral Research (Holt, Rinehart & Winston, New York, NY).
Khazaei, A., Manjiri, H., Samiey, E., & Najafi, H. (2014). The effect of service convenience on customer satisfaction and behavioral responses in bank industry. International Journal of Basic Sciences and Applied Research, 3(1), 16-23.
Kim, H. W., Chan, H. C., & Gupta, S. (2007). Value-based adoption of mobile internet: an empirical investigation. Decision support systems, 43(1), 111-126.
Kim, S. S. (2009). The integrative framework of technology use: An extension and test. Mis Quarterly, 513-537.
King, B. (2012). Bank 3.0: Why banking is no longer somewhere you go but something you do. John Wiley and Sons.
King, B. (2018). Bank 4.0: Banking everywhere, never at a bank. John Wiley and Sons.
Koskosas, I. (2011). The pros and cons of internet banking: a short review. Business excellence and management, 1(1), 49-58.
Lai, J. Y., Debbarma, S., & Ulhas, K. R. (2012). An empirical study of consumer switching behaviour towards mobile shopping: a Push–Pull–Mooring model. International Journal of Mobile Communications, 10(4), 386-404.
Latané, B. (1981). The psychology of social impact. American psychologist, 36(4), 343.
Lee, J. M., & Kim, H. J. (2020). Determinants of adoption and continuance intentions toward Internet-only banks. International Journal of Bank Marketing, 38(4), 843-865.
Lee, Y. K., Ahn, W. K., & Kim, K. (2008). A study on the moderating role of alternative attractiveness in the relationship between relational benefits and customer loyalty. International Journal of hospitality and tourism administration, 9(1), 52-70.
Li, M. L., Lin, S. P., Chan, Y. H., & Wu, C. H. (2021). Customer Involvement Facets Stimulating Customers' Intention to Use Internet-Only Bank Services in China: The Extension of Perceived Risk-Value Model. Journal of Organizational and End User Computing (JOEUC), 33(5), 74-97.
Lin, C. N., & Wang, H. Y. (2017). Understanding users’ switching intentions and switching behavior on social networking sites. Aslib Journal of Information Management, 69(2), 201-214.
Longino Jr, C. F. (1992). The forest and the trees: micro-level considerations in the study of geographic mobility in old age. In elderly migration and population redistribution, 23-34.
Lu, H. P., & Gustafson, D. H. (1994). An empirical study of perceived usefulness and perceived ease of use on computerized support system use over time. International journal of information management, 14(5), 317-329.
Magalhaes, S. H. D. J. P. (2009). The differential effects of switching costs and attractiveness of alternatives on customer loyalty (Master's thesis, Universidade NOVA de Lisboa (Portugal)).
Mayer, R. C., Davis, J. H., & Schoorman, F. D. (1995). An integrative model of organizational trust. Academy of management review, 20(3), 709-734.
McKnight, D. H., & Chervany, N. L. (2001). What trust means in e-commerce customer relationships: An interdisciplinary conceptual typology. International journal of electronic commerce, 6(2), 35-59.
McKnight, D. H., Cummings, L. L., & Chervany, N. L. (1998). Initial trust formation in new organizational relationships. Academy of Management review, 23(3), 473-490.
Milutinović, V., Horvat, Z., Mihanović, M., Stefanović, M., Dingarac, D., Vujović, I., ... & Patricelli, F. (2003). E-Banking Nuts and Bolts. Mastering E-Business Infrastructure, 171-204.
Misra, S., Pedada, K., & Sinha, A. (2022). A theory of marketing’s contribution to customers’ perceived value. Journal of Creating Value, 8(2), 219-240.
Moon, B. (1995). Paradigms in migration research: exploring'moorings' as a schema. Progress in human geography, 19(4), 504-524.
Mun, Y. Y., Jackson, J. D., Park, J. S., & Probst, J. C. (2006). Understanding information technology acceptance by individual professionals: Toward an integrative view. Information and management, 43(3), 350-363.
Nimako, S. G., & Ntim, B. A. (2013). Construct specification and misspecification within the application of push-pull-mooring theory of switching behaviour. Journal of Business and Management Sciences, 1(5), 83-95.
Oliver, R. L. (1993). Cognitive, affective, and attribute bases of the satisfaction response. Journal of consumer research, 20(3), 418-430.
Parasuraman, A., & Grewal, D. (2000). The impact of technology on the quality-value-loyalty chain: a research agenda. Journal of the academy of marketing science, 28(1), 168-174.
Peter, J. P., & Ryan, M. J. (1976). An investigation of perceived risk at the brand level. Journal of marketing research, 13(2), 184-188.
Ping Jr, R. A. (1993). The effects of satisfaction and structural constraints on retailer exiting, voice, loyalty, opportunism, and neglect. Journal of retailing, 69(3), 320-352.
Pires, G., Stanton, J., & Eckford, A. (2004). Influences on the perceived risk of purchasing online. Journal of Consumer Behaviour: An International Research Review, 4(2), 118-131.
Polites, G. L., & Karahanna, E. (2012). Shackled to the status quo: The inhibiting effects of incumbent system habit, switching costs, and inertia on new system acceptance. MIS quarterly, 21-42.
Porter, M. E. (1980). Competitive Strategy: Techniques for Analyzing Industries and Competitors. New York: Free Press.
Quoquab, F., Mohammad, J., Yasin, N. M., & Abdullah, N. L. (2018). Antecedents of switching intention in the mobile telecommunications industry: a partial least square approach. Asia Pacific Journal of Marketing and Logistics, 30(4), 1087-1111.
Ramayah, T., & Ignatius, J. (2005). Impact of perceived usefulness, perceived ease of use and perceived enjoyment on intention to shop online. ICFAI Journal of Systems Management (IJSM), 3(3), 36-51.
Rogers, E. M. (1995). Diffusion of innovation (4th Ed.). New York: The Free Press.
Roselius, T. (1971). Consumer rankings of risk reduction methods. Journal of marketing, 35(1), 56-61.
Rumelt, R. P. (1995). Inertia and transformation. In Resource-based and evolutionary theories of the firm: Towards a synthesis (pp. 101-132). Boston, MA: Springer US.
Rusbult, C. E. (1980). Commitment and satisfaction in romantic associations: A test of the investment model. Journal of experimental social psychology, 16(2), 172-186.
Sánchez-Fernández, R., & Iniesta-Bonillo, M. Á. (2007). The concept of perceived value: a systematic review of the research. Marketing theory, 7(4), 427-451.
Sánchez-Fernández, R., Iniesta-Bonillo, M. Á., & Holbrook, M. B. (2009). The Conceptualisation and Measurement of Consumer Value in Services. International Journal of Market Research, 51(1), 1-17.
Sarstedt, M., Hair Jr, J. F., Cheah, J. H., Becker, J. M., & Ringle, C. M. (2019). How to specify, estimate, and validate higher-order constructs in PLS-SEM. Australasian marketing journal, 27(3), 197-211.
Schul, P. L., Lamb Jr, C. W., & Little Jr, T. E. (1981). A path analysis of the intrachannel conflict process. In AMA Summer Educators’ Conference Proceedings, American Marketing Association, Chicago, IL (pp. 39-42).
Seiders, K., Berry, L. L., & Gresham, L. G. (2000). Attention, retailers! How convenient is your convenience strategy? MIT Sloan Management Review, 41(3), 79.
Shuval, J.T. (1982). Migration and stress. In L. Gold-berger and S. Breznitz, editors, Handbook of stress: theoretical and clinical aspects. New York: Free Press,677-91.
Skinner, C. (2014). Digital bank: Strategies to launch or become a digital bank. Marshall Cavendish International Asia Pte Ltd.
Stewart, K. J. (2003). Trust transfer on the world wide web. Organization science, 14(1), 5-17.
Stone, R. N., & Grønhaug, K. (1993). Perceived risk: Further considerations for the marketing discipline. European Journal of marketing, 27(3), 39-50.
Suleiman Awwad, M., & Awad Neimat, B. (2010). Factors affecting switching behavior of mobile service users: The case of Jordan. Journal of Economic and Administrative Sciences, 26(1), 27-51.
Sun, Y., Liu, D., Chen, S., Wu, X., Shen, X. L., & Zhang, X. (2017). Understanding users' switching behavior of mobile instant messaging applications: An empirical study from the perspective of push-pull-mooring framework. Computers in Human Behavior, 75, 727-738.
Sweeney, J. C., & Soutar, G. N. (2001). Consumer perceived value: The development of a multiple item scale. Journal of retailing, 77(2), 203-220.
Von Weizsäcker, C. C. (1984). The costs of substitution. Econometrica: Journal of the Econometric Society, 1085-1116.
Wang, N., Shen, X. L., & Sun, Y. (2013). Transition of electronic word-of-mouth services from web to mobile context: A trust transfer perspective. Decision support systems, 54(3), 1394-1403.
Wieringa, J. E., & Verhoef, P. C. (2007). Understanding customer switching behavior in a liberalizing service market: an exploratory study. Journal of Service Research, 10(2), 174-186.
Woodruff, R.B. (1997) Customer Value: The Next Source of Competitive Advantage. Journal of the Academy of Marketing Science, 25, 139-153.
Yale, L., & Venkatesh, A. (1986). Toward the construct of convenience in consumer research. Advances in consumer research, 13(1), 403-408.
Yao, X., Phang, C. W., & Ling, H. (2015). Understanding the influences of trend and fatigue in individuals' SNS switching intention. In 2015 48th Hawaii International Conference on System Sciences (pp. 324-334). IEEE.
Ye, D., Liu, F., Cho, D., & Jia, Z. (2022). Investigating switching intention of e-commerce live streaming users. Heliyon, 8(10).
Yen, Y. X., & Horng, D. J. (2010). Effects of satisfaction, trust and alternative attractiveness on switching intentions in industrial customers. International Journal of Management and Enterprise Development, 8(1), 82-101.
Yoon, C., & Lim, D. (2021). Customers’ intentions to switch to internet-only banks: Perspective of the push-pull-mooring model. Sustainability, 13(14), 8062.
Yuen, K. F., Ng, W. H., & Wang, X. (2023). Switching intention in the online crowdsourced delivery environment: The influence of a platform's technological characteristics and relational bonding strategies. Technology in Society, 72, 102167.
Zeithaml, V. A. (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. Journal of marketing, 52(3), 2-22.
Zengyan, C., Yinping, Y., & Lim, J. (2009). Cyber migration: An empirical investigation on factors that affect users' switch intentions in social networking sites. In 2009 42nd Hawaii International Conference on System Sciences (pp. 1-11). IEEE.
Zhang, K. Z., Cheung, C. M., Lee, M. K., & Chen, H. (2008). Understanding the blog service switching in Hong Kong: an empirical investigation. In Proceedings of the 41st annual Hawaii international conference on system sciences (HICSS 2008) (pp. 269-269). IEEE.
Zhang, R., Wang, K., Chen, K., & Rong, R. (2007, August). Customer switching intention in service industries and the effect of customer perceived value. In 2007 IEEE International Conference on Service Operations and Logistics, and Informatics (pp. 1-6). IEEE.
Zhang, Y., Chen, X., Liu, X., & Zhu, N. (2018). Exploring trust transfer between internet enterprises and their affiliated internet-only banks: An adoption study of internet-only banks in China. Chinese Management Studies, 12(1), 56-78.
Zhou, T. (2016). Examining user switch between mobile stores: A push-pull-mooring perspective. Information Resources Management Journal (IRMJ), 29(2), 1-13.
朴聖圭(2019)。關於線上購物網站的服務失敗嚴重性, 顧客抱怨處理滿意度與轉換意圖關係中信任所起的媒介效果的研究。 지역산업연구,42(4), 211-233.