跳到主要內容

簡易檢索 / 詳目顯示

研究生: 范鈺鑫
Fan, Yu-Hsin
論文名稱: 行動銀行應用程式之服務品質與應用程式品質對於持續使用意願之影響
The Impact of Service Quality and Application Quality on the Continuance Intention of Mobile Bank Application
指導教授: 張欣綠
Chang, Hsin-Lu
口試委員: 王凱
Wang, Kai
戴基峯
Tai, Chi-Feng
學位類別: 碩士
Master
系所名稱: 商學院 - 資訊管理學系
Department of Management Information System
論文出版年: 2020
畢業學年度: 108
語文別: 英文
論文頁數: 66
中文關鍵詞: 行動銀行應用程式推敲可能性模型服務品質應用程式品質持續使用意願
外文關鍵詞: Mobile bank applications, Elaboration likelihood model, Service quality, App quality, Continuance intention
DOI URL: http://doi.org/10.6814/NCCU202001006
相關次數: 點閱:98下載:3
分享至:
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報

  • With the progress of technology, people have become accustomed to accessing in-formation or completing daily tasks on their smartphone applications to save time and avoid troubles. Therefore, banks have launched their mobile bank applications to pro-vide various financial services, such as transferring money, purchasing foreign currencies or funds and so on. However, many smartphone users download far more applications than they actually use. Additionally, as more and more competing banks launch similar applications, the switching cost becomes lower. Thus, how to make users will-ing to continue using mobile bank applications is a very critical topic for banks.
    In this study, we cooperate with First Bank, a top-ten bank in Taiwan, to examine factors that can persuade users to continue to use the mobile bank applications. We recruit its account users to test its newly launched application, iLEO. We classify the qualities of mobile bank applications into two kinds: service quality and app quality. Developed upon the elaboration likelihood model, we attempt to find out which quality-related cues are effective in persuading users to use iLEO continuously when considering individual differences, including self-efficacy and user involvement. The results are expected to help First Bank understand what cues are effective to persuade different users to use iLEO continuously and assist banks in planning different marketing events for different users.

    Chapter 1. Introduction 1
    Chapter 2. Literature Review 4
    2.1 Service Quality 4
    2.2 App Quality 6
    2.3 Elaboration Likelihood Model 9
    Chapter 3. Research Framework 11
    3.1 Research Framework 11
    3.2 Hypothesis 11
    3.2.1 Central Route 11
    3.2.2 Peripheral Route 12
    3.2.3 Self-efficacy 14
    3.2.4 User Involvement 15
    Chapter 4. Research Framework 16
    4.1 Research Methodology 16
    4.2 Measurement 29
    4.3 Data Collection 22
    Chapter 5. Model Analysis and Results 26
    5.1 Measurement Model Analysis 26
    5.2 Structural Model Analysis 31
    5.3 Group Analysis 33
    5.3.1 Grouping Based on Task Complexity 33
    5.3.2 Grouping Based on The Degree of Self-efficacy 35
    5.4 Summary 36
    Chapter 6. Discussion 38
    Chapter 7. Conclusion 40
    References 43
    Appendix A: Complete Questionnaire (English Version) 48
    Appendix B: Complete Questionnaire (Chinese Version) 56
    Appendix C: Complete Tasks (English Version) 65
    Appendix D: Complete Tasks (Chinese Version) 66

    趙珮晴, & 余民寧. (2018). 未來職業意圖受 [情境] 影響? 以社會認知生涯理論分析. 257–290. https://doi.org/10.6209/JORIES.201809Bhattacherjee, A., & Sanford, C. (2006). Influence Processes for Information Technology Acceptance: An Elaboration Likelihood Model. 30(4), 805–825.
    Cheung, C. M. Y., Sia, C. L., & Kuan, K. K. Y. (2012). Is this review believable? A study of factors affecting the credibility of online consumer reviews from an ELM perspective. Journal of the Association of Information Systems, 13(8), 618–635. https://doi.org/10.17705/1jais.00305
    Chiu, C. M., Chiu, C. S., & Chang, H. C. (2007). Examining the integrated influence of fairness and quality on learners’ satisfaction and Web-based learning continuance intention. Information Systems Journal, 17(3), 271–287. https://doi.org/10.1111/j.1365-2575.2007.00238.x
    Devaraj, S., M. Fan, R. K. (2002). “Antecedents of B2C Channel Satisfaction and Preference: Validating e-Commerce Metrics,” Information Systems Research. (July 2019).
    Fang, Y. H. (2017). Exploring task-service fit and usefulness on branded applications continuance. Journal of Services Marketing, 31(6), 574–588. https://doi.org/10.1108/JSM-07-2016-0256
    Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39. https://doi.org/10.2307/3151312
    Gan, C. L., & Balakrishnan, V. (2017). Enhancing classroom interaction via IMMAP - An Interactive Mobile Messaging App. Telematics and Informatics, 34(1), 230–243. https://doi.org/10.1016/j.tele.2016.05.007
    Gefen, D., & Straub, D. (2005). A Practical Guide To Factorial Validity Using PLS-Graph: Tutorial And Annotated Example. Communications of the Association for Information Systems, 16, 91–109. https://doi.org/10.17705/1cais.01605
    Gefen, D., Straub, D., & Boudreau, M.-C. (2000). Structural Equation Modeling and Regression: Guidelines for Research Practice. Communications of the Association for Information Systems, 4(October). https://doi.org/10.17705/1cais.00407
    Gorla, N., Somers, T. M., & Wong, B. (2010). Organizational impact of system quality, information quality, and service quality. Journal of Strategic Information Systems, 19(3), 207–228. https://doi.org/10.1016/j.jsis.2010.05.001
    Hair Jr, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM). Practical Assessment, Research and Evaluation, 21(1), 1–16. https://doi.org/10.1108/ebr-10-2013-0128
    Hajiheydari, N., Hernandez-Carrion, J. R., & Ashkani, M. (2018). Mobile application diffusion and success: An interpretative approach to influential factors. International Journal of E-Services and Mobile Applications, 10(4), 18–39. https://doi.org/10.4018/IJESMA.2018100102
    Henseler, J., Ringle, C. M., & Sinkovics, R. R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20(January), 277–319. https://doi.org/10.1108/S1474-7979(2009)0000020014
    Hoehle, H., & Venkatesh, V. (2015). Mobile application usability: Conceptualization and instrument development. MIS Quarterly: Management Information Systems, Vol. 39, pp. 435–472. https://doi.org/10.25300/MISQ/2015/39.2.08
    Hulland, J. (1999). USE OF PARTIAL LEAST SQUARES (PLS) IN STRATEGIC MANAGEMENT RESEARCH: A REVIEW OF FOUR RECENT STUDIES. 18(May), 1998.
    Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310–322. https://doi.org/10.1016/j.chb.2009.10.013
    Kim, D. J., & Hwang, Y. (2012). A study of mobile internet user’s service quality perceptions from a user’s utilitarian and hedonic value tendency perspectives. Information Systems Frontiers, 14(2), 409–421. https://doi.org/10.1007/s10796-010-9267-8
    Kim, H.-W., Xu, Y., & Koh, J. (2004). A Comparison of Online Trust Building Factors between Potential Customers and Repeat Customers. Journal of the Association for Information Systems, 5(10), 392–420. https://doi.org/10.17705/1jais.00056
    Lowry, P. B., Vance, A., Moody, G., Beckman, B., & Read, A. (2008). Explaining and predicting the impact of branding alliances and web site quality on initial consumer trust of E-commerce web sites. Journal of Management Information Systems, 24(4), 199–224. https://doi.org/10.2753/MIS0742-1222240408
    Parasuraman, A., & Zeithaml, V. (1988). SERVQUAL: a multiple-item scale for measuring consumer perceptions of service …. Retailing: Critical …. Retrieved from http://books.google.co.uk/books?hl=en&lr=&id=Rt96wAigg2oC&oi=fnd&pg=PA140&dq=over+50%27s+consumer+behaviour&ots=pPv45yAHvK&sig=AL2ewACQwL3_En3qjvd1Bo5k9fw
    Peng, K. F., Chen, Y., & Wen, K. W. (2014). Brand relationship, consumption values and branded app adoption. Industrial Management and Data Systems, 114(8), 1131–1143. https://doi.org/10.1108/IMDS-05-2014-0132
    Petty, R. E., & Cacioppo, J. T. (1986). The elaboration likelihood model of persuasion. Advances in Experimental Social Psychology, 19(C), 123–205. https://doi.org/10.1016/S0065-2601(08)60214-2
    Review 24. 39+ Smartphone Statistics You Should Know in 2019 Retrieved January 29 2020, from https://review42.com/smartphone-statistics
    Seddon, P. B. (1997). A Respecification and Extension of the DeLone and McLean Model of IS Success. Information Systems Research, Vol. 8, pp. 240–253. https://doi.org/10.1287/isre.8.3.240
    Statista. App Users Spend 77% of Their Time on Their Top 3 Apps Retrieved
    September 30 2019, from https://www.statista.com/chart/3835/top-10-app-usage/?fbclid=IwAR2nqjzTjVri8-cuAO3VR-Zs-YlwZit9AzTfcY7Ckw6Q3VrTBL6LjDQOEPo
    Stoyanov, S. R., Hides, L., Kavanagh, D. J., Zelenko, O., Tjondronegoro, D., & Mani, M. (2015). Mobile App Rating Scale: A New Tool for Assessing the Quality of Health Mobile Apps. JMIR MHealth and UHealth, 3(1), e27. https://doi.org/10.2196/mhealth.3422
    Sussman, S. W., & Siegal, W. S. (2003). Informational influence in organizations: An integrated approach to knowledge adoption. Information Systems Research, 14(1), 47–65. https://doi.org/10.1287/isre.14.1.47.14767
    Tam, K. Y., & Ho, S. Y. (2005). Web personalization as a persuasion strategy: An elaboration likelihood model perspective. Information Systems Research, 16(3), 271–291. https://doi.org/10.1287/isre.1050.0058
    Yang, S. (2016). Role of transfer-based and performance-based cues on initial trust in mobile shopping services: a cross-environment perspective. Information Systems and E-Business Management, 14(1), 47–70. https://doi.org/10.1007/s10257-015-0274-7
    Zhou, T. (2012). Understanding users’ initial trust in mobile banking: An elaboration likelihood perspective. Computers in Human Behavior, 28(4), 1518–1525. https://doi.org/10.1016/j.chb.2012.03.021
    Zhou, T. (2013). An empirical examination of continuance intention of mobile payment services. Decision Support Systems, 54(2), 1085–1091. https://doi.org/10.1016/j.dss.2012.10.034

    QR CODE
    :::