研究生: |
李沛家 Lee, Pei-Chia |
---|---|
論文名稱: |
以 PPM 理論探討顧客從實體銀行到網路銀行的轉換意圖 Exploring Customer Switching Intention From Physical to Online Banking - A Perspective of Push-Pull-Mooring Framework |
指導教授: |
黃瀞瑩
Ching-Ying, Huang |
學位類別: |
碩士 Master |
系所名稱: |
管理學院 - 企業管理學系 Department of Business Administration |
論文出版年: | 2022 |
畢業學年度: | 110 |
語文別: | 中文 |
論文頁數: | 82 |
中文關鍵詞: | 推力-拉力-維繫力理論 、網路銀行 、轉換意圖 |
外文關鍵詞: | Push-Pull-Mooring Theory, Online banking, Switching Intention |
相關次數: | 點閱:202 下載:48 |
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金融科技化(FinTech)使銀行營運型態有了許多重大的創新變革,網路銀行即是
在金融科技下所誕生的產物之一,可以提升服務效率、降低銀行營運成本以及使交
易不受時空限制。然而,如此便利的金融交易模式在臺灣的使用率卻只有四成多。
有鑑於此,本研究希望能找出影響國人從實體銀行到網路銀行轉換意圖的因素。此
外, 2019 年底COVID-19 的爆發讓全國陷入恐慌,許多生活模式開始改變,使電
子商務平台快速崛起。基於以上所述,本研究亦期望能了解疫情的爆發是否有使國
人對網路銀行出現轉換意圖。
而過去有關網路銀行的研究大多聚焦在「使用」與「接受」方面,但網路銀行的
使用不單只是對新型科技服務的採用,還需考量到舊有的實體服務模式會影響顧客對
新型服務的轉換意願。因此,本研究將以Moon (1995)所修正的推力-拉力-維繫力
理論(Push-Pull-Mooring Theory, PPM)為主要理論,探討實體銀行到網路銀行的轉換意
圖,並分別從推力對轉換意圖之影響、拉力對轉換意圖之影響、維繫力對轉換意圖之
影響、維繫力對推力與轉換意圖間之調節、維繫力對拉力與轉換意圖間之調節的五個
角度來探究顧客從實體銀行到網路銀行的轉換。
本研究之正式問卷所有問項皆採用Likert 七點量表衡量,共計收回554 份有效
問卷,並以AMOS 軟體進行結構方程模型(SEM)分析;以SPSS 進行樣本結構分
析、敘述性統計分析以及調節分析。本研究中五個假設的結果顯示,推力效果(等候
時間、主觀規範)會正向影響轉換意圖、拉力效果(知覺有用性、知覺易用性)會正向
影響轉換意圖、維繫力效果(慣性、轉換成本)會影響轉換意圖、維繫力效果對推力
效果與轉換意圖間的關係具有調節作用,但維繫力效果對拉力效果與轉換意圖間的
關係則不具有調節作用。
Online banking can enhance the efficiency of services and make transactions not limited by time and space, but the usage rate in Taiwan is just over 40%. In addition, the outbreak of COVID-19 sent the nation into a panic, and many lifestyles began to change, leading to the rapid rise of e-commerce platforms. In light of this, this study will identify the factors that influence the Taiwanese’ switching intention from physical bank to online banking.
While most studies on online banking have focused on “usage” in the past, the use of online banking also needs to take into account the impact of physical service style on customers' switching intention. Therefore, this study uses the Push-Pull-Mooring Theory (PPM) to examine the switching intention from physical bank to online banking.
In this study, we use online questionnaires to collect samples and received 554 valid questionnaires. We use AMOS to analyze SEM, and SPSS to analyze sample structure analysis, descriptive statistical analysis and moderated analysis. The results of this five hypotheses in the study showed that the push effect (waiting time, subjective norm) positively affected the switching intention, the pull effect (perceived usefulness, perceived ease of use) positively affected the switching intention, the mooring effect (inertia, switching cost) affected the switching intention, and the mooring effect moderated the relationship between the push effect and the switching intention. However, the mooring effect did not moderate the relationship between the pull effect and the switching intention.
Ahmad, M., Iram, K., & Jabeen, G. (2020). Perception-based influence factors of intention to adopt COVID-19 epidemic prevention in China. Environmental research, 190, 109995.
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Prentice-Hall.
Al-Okaily, M., Alqudah, H., Matar, A., Lutfi, A., & Taamneh, A. (2020). Dataset on the
Acceptance of e-learning System among Universities Students' under the COVID-
19 Pandemic Conditions. Data in brief, 32, 106176.
Antón, C., Camarero, C., & Carrero, M. (2007). The mediating effect of satisfaction on consumers' switching intention. Psychology & Marketing, 24(6), 511-538.
Arner, D. W., Barberis, J., & Buckey, R. P. (2016). FinTech, RegTech, and the reconceptualization of financial regulation. Nw. J. Int'l L. & Bus., 37, 371.
Assael, H. (1998). Consumer behavior and marketing action. http://books.google.com/books?id=n2JaAAAAYAAJ
Bansal, H. S., Irving, P. G., & Taylor, S. F. (2004). A three-component model of customer to service providers. Journal of the Academy of Marketing Science, 32(3), 234-250.
Bansal, H. S., & Taylor, S. F. (1999). The service provider switching model (spsm) a model of consumer switching behavior in the services industry. Journal of service Research, 2(2), 200-218.
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.
Bendapudi, N., & Berry, L. L. (1997). Customers' motivations for maintaining relationships with service providers. Journal of Retailing, 73(1), 15-37. https://doi.org/https://doi.org/10.1016/S0022-4359(97)90013-0
Bernheim, B. D. (1994). A theory of conformity. Journal of political Economy, 102(5),
841-877.
Bloemer, J. M., & Kasper, H. D. (1995). The complex relationship between consumer
satisfaction and brand loyalty. Journal of economic psychology, 16(2), 311-329.
Bogue, D. J. (1969). Principles of demography. Wiley.
Boyle, P., Halfacree, K., & Robinson, V. (1998). Exploring Contemporary. Migration. Addison Wesley Longman Limited, Harlow.
Boyle, P., & Halfacree, K. (1999). Migration and gender in the developed world. Routledge London.
Chen, L.-d. (2008). A model of consumer acceptance of mobile payment. International Journal of Mobile Communications, 6(1), 32-52. https://doi.org/10.1504/IJMC.2008.015997
Chen, S., & Liu, L. (2008). Measure of ERP users' satisfaction. 2008 IEEE international
conference on service operations and logistics, and informatics.
Chen, Y., Shi, S., & Chow, W. S. (2016). Investigating users' extrinsic motivation for green personal computing. Journal of Computer Information Systems, 56(1), 70-78.
Clark, D. E., Knapp, T. A., & White, N. E. (1996). Personal and location‐specific
characteristics and elderly interstate migration. Growth and Change, 27(3), 327-
351.
Clemmer, E.C., & Schneider , B. (1989). Toward Understanding and Controlling Customer Dissatisfaction with Waiting. Working Paper. Cambridge MA: Marketing Science Institute, 89-115.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
de Vries, H., Dijkstra, M., & Kuhlman, P. (1988). Self-efficacy: the third factor besides
attitude and subjective norm as a predictor of behavioural intentions. Health education research, 3(3), 273-282. https://doi.org/10.1093/her/3.3.273
Estrella-Ramon, A., Sánchez-Pérez, M. and Swinnen, G. (2016). How customers’ offline experience affects the adoption of online banking. Internet Research.
https://doi.org/10.1108/IntR-03-2015-0092
Fornell, C. (1992). A national customer satisfaction barometer: The Swedish experience. Journal of Marketing, 56(1), 6-21.
Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS quarterly, 51-90.
Germani, G. (1965). Migration and Acculturation. In Handbook for Social Research in Urban Areas. Ed. Philip M. Hauser. Brussels, Belgium: UNESCO, 159-178.
Gounaris, S., & Stathakopoulos, V. (2004). Antecedents and consequences of brand
loyalty: An empirical study. Journal of brand Management, 11(4), 283-306.
Gray, D. M., D’Alessandro, S., Johnson, L. W., & Carter, L. (2017). Inertia in services: causes and consequences for switching. Journal of Services Marketing.
Grzybowski, L., & Nicolle, A. (2021). Estimating Consumer Inertia in Repeated Choices of Smartphones. The Journal of Industrial Economics, 69(1), 33-82.
Han, H., Kim, W., & Hyun, S. S. (2011). Switching intention model development: Role of service performances, customer satisfaction, and switching barriers in the hotel industry. International Journal of Hospitality Management, 30(3), 619-629.
Hightower Jr, R., Brady, M. K., & Baker, T. L. (2002). Investigating the role of the physical environment in hedonic service consumption: an exploratory study of sporting events. Journal of Business research, 55(9), 697-707.
Hooper, D., Coughlan, J., & Mullen, M. (2008). Evaluating model fit: a synthesis of the structural equation modelling literature. 7th European Conference on research
methodology for business and management studies.
Hou, A. C., Chern, C.-C., Chen, H.-G., & Chen, Y.-C. (2011). ‘Migrating to a new virtual world’: Exploring MMORPG switching through human migration theory.
Computers in Human Behavior, 27(5), 1892-1903.
Hsieh, J.-K., Hsieh, Y.-C., Chiu, H.-C., & Feng, Y.-C. (2012). Post-adoption switching
behavior for online service substitutes: A perspective of the push–pull–mooring
framework. Computers in Human Behavior, 28(5), 1912-1920.
Hsieh, P. J. (2016). An empirical investigation of patients’ acceptance and resistance toward the health cloud: the dual factor perspective. Computers in Human Behavior, 63, 959-969.
Hui, M. K., & Tse, D. K. (1996). What to tell consumers in waits of different lengths: An integrative model of service evaluation. Journal of Marketing, 60(2), 81-90.
Jackson, J. A. (1986a). Migration. Longman.
Jackson, J. A. (1986b). Migration In Aspects of Modern Sociology: Social Processes.
London and New York: Longman.
Jayawardhena, C., & Foley, P. (2000). Changes in the banking sector – the case of Internet banking in the UK. Internet Research, 10(1), 19-31. https://doi.org/10.1108/10662240010312048
Jones, M. A., Mothersbaugh, D. L., & Beatty, S. E. (2000). Switching barriers and
repurchase intentions in services. Journal of Retailing, 76, 259-274.
Jones, M. A., Mothersbaugh, D. L., & Beatty, S. E. (2002). Why customers stay: measuring the underlying dimensions of services switching costs and managing their differential strategic outcomes. Journal of Business research, 55(6), 441-450.
Katz, K. L., Larson, B. M., & Larson, R. C. (1991). Prescription for the Waiting-In-Line
Blues: Entertain, Enlighten, and Engage. Sloan Management Review, 32(2), 44.
Keaveney, S. M. (1995). Customer switching behavior in service industries: An exploratory study. Journal of Marketing, 59(2), 71-82.
Kim, B., & Kang, M. (2016). How user loyalty and nonconscious inertia influence the
continued use of mobile communications platforms. International Journal of Mobile Communications, 14(4), 387-410.
King, B. (2018). Bank 4.0: Banking Everywhere, Never at a Bank. John Wiley & Sons Inc.
Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford
publications.
Koch, J., Frommeyer, B., & Schewe, G. (2020). Online shopping motives during the
COVID-19 pandemic—lessons from the crisis. Sustainability, 12(24), 10247.
Kumar, P., Kalwani, M. U., & Dada, M. (1997). The impact of waiting time guarantees on customers' waiting experiences. Marketing science, 16(4), 295-314.
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.
Lai, J.-Y. & Wang, J. (2015). Switching attitudes of Taiwanese middle-aged and elderly patients toward cloud healthcare services: An exploratory study. Technological Forecasting and Social Change, 92, 155-167.
Lee, E. S. (1966). A theory of migration. Demography, 3(1), 47-57.
Lee, K.-W., Tsai, M.-T., & Lanting, M. C. L. (2011). From marketplace to marketspace:
Investigating the consumer switch to online banking. Electronic Commerce
Research and Applications, 10(1), 115-125.
Lee, M.-C. (2009). Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefit. Electronic Commerce Research and Applications, 8(3), 130-141.
Lee, R., Murphy, J., & Neale, L. (2009). The interactions of consumption characteristics on social norms. Journal of Consumer Marketing.
Lewis, G.J. (1982). Human Migration: A Geographical Perspective. Routledge.
https://doi.org/10.4324/9781003183051
Li, C. Y. (2015). Switching barriers and customer retention: Why customers dissatisfied with online service recovery remain loyal. Journal of Service Theory and Practice.
Li, C. Y. (2018). Consumer behavior in switching between membership cards and mobile applications: The case of Starbucks. Computers in Human Behavior, 84, 171-184.
Liang, C.-C., & Wu, P.-C. (2015). Internet-banking customer analysis based on perceptions of service quality in Taiwan. Total Quality Management & Business
Excellence, 26(5-6), 550-568.
Lim, Y. J., Osman, A., Salahuddin, S. N., Romle, A. R., & Abdullah, S. (2016). Factors
influencing online shopping behavior: the mediating role of purchase intention. Procedia economics and finance, 35, 401-410.
Longino, 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.
Marakarkandy, B., Yajnik, N., & Dasgupta, C. (2017). Enabling internet banking adoption: An empirical examination with an augmented technology acceptance model (TAM). Journal of Enterprise Information Management.
Maroufizadeh, S., Zareiyan, A., & Sigari, N. (2014). Reliability and validity of Persian
version of perceived stress scale (PSS-10) in adults with asthma. Archives of
Iranian medicine, 17(5), 0-0.
Martins, C., Oliveira, T., & Popovič, A. (2014). Understanding the Internet banking
adoption: A unified theory of acceptance and use of technology and perceived risk
application. International journal of information management, 34(1), 1-13.
Moon, B. (1995). Paradigms in migration research: exploring'moorings' as a schema. Progress in human geography, 19(4), 504-524.
Moon, J.-W., & Kim, Y.-G. (2001). Extending the TAM for a World-Wide-Web context. Information & management, 38(4), 217-230.
Norberg, M., Stenlund, H., Lindahl, B., Andersson, C., Weinehall, L., Hallmans, G., &
Eriksson, J. W. (2007). Components of metabolic syndrome predicting diabetes: no
role of inflammation or dyslipidemia. Obesity, 15(7), 1875-1885.
Petersen, W. (1958). A general typology of migration. American sociological review, 23(3), 256-266.
Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: an extension of the technology acceptance model. Internet Research, 14(3), 224-235. https://doi.org/10.1108/10662240410542652
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.
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.
Pollak, R. A. (1970). Habit formation and dynamic demand functions. Journal of political Economy, 78(4, Part 1), 745-763.
Ranaweera, C., & Neely, A. (2003). Some moderating effects on the service quality customer retention link. International journal of operations & Production
management.
Ravenstein, E. G. (1885). The laws of migration. Journal of the statistical society of
London, 48(2), 167-235.
Safeena, R., Date, H., Hundewale, N., & Kammani, D. A. (2013). Combination of TAM and TPB in Internet banking adoption. International Journal of Computer Theory and Engineering, 5, 146-150. https://doi.org/10.7763/IJCTE.2013.V5.665
Schepers, J., & Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & management, 44(1), 90-103.
Shih, H.-P. (2004). Extended technology acceptance model of Internet utilization behavior. Information & management, 41(6), 719-729.
Sutherland, E. (2007). Mobile number portability. Info - The journal of policy, regulation and strategy for telecommunications, 9(4), 10-24. https://doi.org/10.1108/14636690710762101
Tan, M., & Teo, T. S. (2000). Factors influencing the adoption of Internet banking. Journal of the Association for information Systems, 1(1), 5.
Taylor, S. (1994). Waiting for service: The relationship between delays and evaluations of service. Journal of Marketing, 58(2), 56-69. https://doi.org/10.2307/1252269
Venkatesh, V., & Davis, F. D. (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies. Management science, 46(2),
186-204. https://doi.org/10.1287/mnsc.46.2.186.11926
Wan, C., Shen, G. Q., & Choi, S. (2017). Experiential and instrumental attitudes: Interaction effect of attitude and subjective norm on recycling intention. Journal of Environmental Psychology, 50, 69-79.
Wang, L., Luo, X. R., Yang, X., & Qiao, Z. (2019). Easy come or easy go? Empirical
evidence on switching behaviors in mobile payment applications. Information &
Management, 56(7), 103150.
Wolpert, J. (1965). Behavioral Aspects of the Decision to Migrate?. Papers of the Regional Science Association, 15, 159-169.
Wolpert, J. (1966). Migration as an Adjustment to Environmental Stress. Journal of Social Issues, 22, 92-102.
Wu, J.-H., & Wang, S.-C. (2005). What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model. Information & management, 42(5), 719-729.
Xu, X., Wang, S., & Yu, Y. (2020). Consumer’s intention to purchase green furniture: Do health consciousness and environmental awareness matter?. Science of the Total Environment, 704, 135275.
Yaghoubi, N.-M., & Bahmani, E. (2010). Factors affecting the adoption of online banking: An integration of technology acceptance model and theory of planned behavior. International journal of business and management, 5(9), 159-165.
Ye, C., & Potter, R. (2011). The Role of Habit in Post-Adoption Switching of Personal Information Technologies: An Empirical Investigation. Communications of the Association for Information Systems, 28. https://doi.org/10.17705/1CAIS.02835
Zhou, Y., Wei, J., Meng, F., & Jiang, F. (2015). Influential factors and user behavior of mobile reading. Journal of Intelligent Systems, 24(2), 223-234.
李國瑋. (2016). 科技接受或轉換?科技轉換模式的初探與驗證. 電子商務學報, 18(2),
183-223. https://doi.org/10.6188/jeb.2016.18(2).02
金融監督管理委員會銀行局 (2012)。個人網路銀行業務服務定型化契約範本。金融
監督管理委員會主管法規共用系統。
https://law.fsc.gov.tw/LawContent.aspx?media=print&id=GL000599
金融監督管理委員會銀行局 (2022)。金融統計指標。
https://www.banking.gov.tw/ch/home.jsp?id=157&parentpath=0,4&mcustomize=bs
tatistics_view.jsp&serno=201105120001
財團法人臺灣網路資訊中心 (2017)。臺灣頻寬網路使用調查報告。
https://www.twnic.tw/download/200307/20170721e.pdf
財團法人臺灣網路資訊中心 (2020)。臺灣網路報告。
https://www.twnic.tw/doc/twrp/202012e.pdf
陳禹辰, 侯正裕, 尚榮安, 陳靜枝, & 張翊宏. (2009). 玩家為何轉換線上遊戲-人口遷
徙理論觀點. 電子商務學報, 11(4), 723-751.
國家發展委員會 (2021)。國家數位發展研究報告。
https://ws.ndc.gov.tw/Download.ashx?u=LzAwMS9hZG1pbmlzdHJhdG9yLzEwL2
NrZmlsZS8wZTBiMjM5OC04ZWQxLTQwYzQtYTM5ZS05ZjMzOWRiNjZlMT
YucGRm&n=5ZyL5a625pW45L2N55m85bGV56CU56m25aCx5ZGK57ay6aCB5
4mIMDEwNk9LX0ZpbmFsLnBkZg%3d%3d&icon=.pdf
謝人俊、林耀傑 (2020, May)。數位金融環境下銀行經營型態的演變與對策。
https://www.tpefx.com.tw/uploads/download/tw/8.%20The%20evolution%20and%
20countermeasures%20of%20bank%20management%20pattern%20in%20the%20
digital%20financial%20environment.pdf