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題名 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作者 范鈺鑫
Fan, Yu-Hsin貢獻者 張欣綠
Chang, Hsin-Lu
范鈺鑫
Fan, Yu-Hsin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
Mobile bank applications
Elaboration likelihood model
Service quality
App quality
Continuance intention日期 2020 上傳時間 3-Aug-2020 17:36:13 (UTC+8) 摘要 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. 參考文獻 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.00305Chiu, 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.xDevaraj, 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-07-2016-0256Fornell, 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/10.2307/3151312Gan, 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.2016.05.007Gefen, 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.01605Gefen, 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.00407Gorla, 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.2010.05.001Hair 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-10-2013-0128Hajiheydari, 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.2018100102Henseler, 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)0000020014Hoehle, 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/2015/39.2.08Hulland, 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.2009.10.013Kim, 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/s10796-010-9267-8Kim, 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.00056Lowry, 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/MIS0742-1222240408Parasuraman, 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_En3qjvd1Bo5k9fwPeng, 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-05-2014-0132Petty, 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)60214-2Review 24. 39+ Smartphone Statistics You Should Know in 2019 Retrieved January29 2020, from https://review42.com/smartphone-statisticsSeddon, 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.8.3.240Statista. App Users Spend 77% of Their Time on Their Top 3 Apps RetrievedSeptember 30 2019, from https://www.statista.com/chart/3835/top-10-app-usage/?fbclid=IwAR2nqjzTjVri8-cuAO3VR-Zs-YlwZit9AzTfcY7Ckw6Q3VrTBL6LjDQOEPoStoyanov, 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.3422Sussman, 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.14.1.47.14767Tam, 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.1050.0058Yang, 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/s10257-015-0274-7Zhou, 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.2012.03.021Zhou, 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 描述 碩士
國立政治大學
資訊管理學系
107356023資料來源 http://thesis.lib.nccu.edu.tw/record/#G0107356023 資料類型 thesis dc.contributor.advisor 張欣綠 zh_TW dc.contributor.advisor Chang, Hsin-Lu en_US dc.contributor.author (Authors) 范鈺鑫 zh_TW dc.contributor.author (Authors) Fan, Yu-Hsin en_US dc.creator (作者) 范鈺鑫 zh_TW dc.creator (作者) Fan, Yu-Hsin en_US dc.date (日期) 2020 en_US dc.date.accessioned 3-Aug-2020 17:36:13 (UTC+8) - dc.date.available 3-Aug-2020 17:36:13 (UTC+8) - dc.date.issued (上傳時間) 3-Aug-2020 17:36:13 (UTC+8) - dc.identifier (Other Identifiers) G0107356023 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/130980 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 資訊管理學系 zh_TW dc.description (描述) 107356023 zh_TW dc.description.abstract (摘要) 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. en_US dc.description.tableofcontents Chapter 1. Introduction 1Chapter 2. Literature Review 42.1 Service Quality 42.2 App Quality 62.3 Elaboration Likelihood Model 9Chapter 3. Research Framework 113.1 Research Framework 113.2 Hypothesis 113.2.1 Central Route 113.2.2 Peripheral Route 123.2.3 Self-efficacy 143.2.4 User Involvement 15Chapter 4. Research Framework 164.1 Research Methodology 164.2 Measurement 294.3 Data Collection 22Chapter 5. Model Analysis and Results 265.1 Measurement Model Analysis 265.2 Structural Model Analysis 315.3 Group Analysis 335.3.1 Grouping Based on Task Complexity 335.3.2 Grouping Based on The Degree of Self-efficacy 355.4 Summary 36Chapter 6. Discussion 38Chapter 7. Conclusion 40References 43Appendix A: Complete Questionnaire (English Version) 48Appendix B: Complete Questionnaire (Chinese Version) 56Appendix C: Complete Tasks (English Version) 65Appendix D: Complete Tasks (Chinese Version) 66 zh_TW dc.format.extent 1896809 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0107356023 en_US dc.subject (關鍵詞) 行動銀行應用程式 zh_TW dc.subject (關鍵詞) 推敲可能性模型 zh_TW dc.subject (關鍵詞) 服務品質 zh_TW dc.subject (關鍵詞) 應用程式品質 zh_TW dc.subject (關鍵詞) 持續使用意願 zh_TW dc.subject (關鍵詞) Mobile bank applications en_US dc.subject (關鍵詞) Elaboration likelihood model en_US dc.subject (關鍵詞) Service quality en_US dc.subject (關鍵詞) App quality en_US dc.subject (關鍵詞) Continuance intention en_US dc.title (題名) 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 zh_TW dc.title (題名) The Impact of Service Quality and Application Quality on the Continuance Intention of Mobile Bank Application en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) 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.00305Chiu, 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.xDevaraj, 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-07-2016-0256Fornell, 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/10.2307/3151312Gan, 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.2016.05.007Gefen, 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.01605Gefen, 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.00407Gorla, 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.2010.05.001Hair 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-10-2013-0128Hajiheydari, 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.2018100102Henseler, 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)0000020014Hoehle, 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/2015/39.2.08Hulland, 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.2009.10.013Kim, 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/s10796-010-9267-8Kim, 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.00056Lowry, 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/MIS0742-1222240408Parasuraman, 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_En3qjvd1Bo5k9fwPeng, 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-05-2014-0132Petty, 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)60214-2Review 24. 39+ Smartphone Statistics You Should Know in 2019 Retrieved January29 2020, from https://review42.com/smartphone-statisticsSeddon, 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.8.3.240Statista. App Users Spend 77% of Their Time on Their Top 3 Apps RetrievedSeptember 30 2019, from https://www.statista.com/chart/3835/top-10-app-usage/?fbclid=IwAR2nqjzTjVri8-cuAO3VR-Zs-YlwZit9AzTfcY7Ckw6Q3VrTBL6LjDQOEPoStoyanov, 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.3422Sussman, 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.14.1.47.14767Tam, 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.1050.0058Yang, 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/s10257-015-0274-7Zhou, 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.2012.03.021Zhou, 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 zh_TW dc.identifier.doi (DOI) 10.6814/NCCU202001006 en_US
