探討行動銀行提供線上視訊服務對使用意願的影響

以作者查詢圖書館館藏

、以作者查詢臺灣博碩士

、以作者查詢全國書目

、勘誤回報

、線上人數：68

、訪客IP：18.222.113.192

姓名

張淑萍(Shu-Ping Chang) 查詢紙本館藏

畢業系所

企業管理學系在職專班

論文名稱

探討行動銀行提供線上視訊服務對使用意願的影響

相關論文

★ 探討跨國企業在台子公司自主權與績效的關係	★ 以健康信念模式探討COVID-19對消費者騎乘自行車意圖的影響
★ 探討斜槓工作特性的對應關係及其對心理需求與職涯滿意度之影響	★ 建構雲端人臉辨識系統智能化勞安管理
★ 衡量台灣⾞⽤和⾮⾞⽤印刷電路板產業的營運效率變遷

檔案

[Endnote RIS 格式]

[Bibtex 格式]

[相關文章]

[文章引用]

[完整記錄]

[館藏目錄]

至系統瀏覽論文 (2024-12-31以後開放)

摘要(中)

線上視訊及直播已應用在不同的領域，而2020年新型冠狀病毒肺炎(COVID-19)疫情的影響，為避免人與人之間的接觸，許多經濟上的活動已以線上視訊或是行動支付作為主要媒介，另智慧型手機的普及加上網路5G環境的興起，更是提高線上視訊或直播的穩定性；在金融服務中，因金融服務涉及大量機密與敏感資訊，消費者係基於「信任」選擇與該銀行往來，故行動銀行提供線上視訊服務即是提供無法或避免至實體分行進行銀行業務的交易或諮詢服務缺口的解決方案之一。
本研究以DeLone和McLean資訊系統成功模型(2003)為研究基礎，加入「信任」以探討行動銀行加入線上視訊服務是否可使消費者信任行動銀行，提出九個假設並進行實證研究，使用的調查工具包括設計和管理229份問卷，並以結構方程模式(SEM)進行資料分析，研究結果表示：(1)系統品質及信任對於使用意願具有顯著影響、(2)服務品質、使用及信任對於使用者滿意度具有顯著影響、(3)系統品質需透過信任或是使用即可對使用者滿意度具有顯著影響；以總效果分析，信任在消費者使用行動銀行提供的線上視訊服務及影響消費者對於行動銀行提供的線上視訊服務的滿意度為主要關鍵，由此可知，業者若要推廣線上視訊服務，首先要獲得消費者之信任。

摘要(英)

Online video and live stream have been applied in different fields. In order to avoid the impact of the Coronavirus disease 2019 (COVID-19) in 2020, many economic activities have been replaced by online video or electronic payment in order to avoid contact between people. The popularity of smartphones and the rise of the 5G network environment have also improved the stability of online video or live stream. In financial services, consumers are based on ‘trust’ to choose their correspondent bank because financial services involve a large amount of confidential and sensitive information. So, the online video service provided by the mobile bank is one of the solutions to the inability or avoidance of the transaction or consulting service gap in the physical branch of the bank.
This research is based on the DeLone and McLean Information System Success Model (2003), adding ‘trust’ to discusses whether or not mobile banking provided online video services to make consumers trust mobile banks, put forward 9 hypotheses and conduct empirical research. The research tools include design and management of 229 questionnaires and the structural equation model (SEM) for data analysis. The research results show that: (1) System quality and trust have a significant impact on intention to use; (2) Service quality, usage and trust have a significant impact on user satisfaction; (3) System quality has a significant impact through trust or use. Based on the overall effect analysis, trust is the key whether consumers using mobile banking or not, and it also influencing consumers′ satisfaction with the online video services provided by mobile banking. It can be seen that, if service providers want to promote online video services, it must gain the trust of consumers first.

關鍵字(中)

★ 數位金融
★ 資訊系統成功模式
★ 視訊服務
★ 信任
★ 服務創新
★ 結構方程模式

關鍵字(英)

★ Digital finance
★ information system success model
★ Video banking
★ Trust
★ Service innovation
★ SEM

論文目次

中文摘要 I
ABSTRACT II
誌謝 III
目錄 IV
圖目錄 VI
表目錄 VII
第一章緒論 1
1-1研究背景與動機 1
1-2 研究目的 5
1-3 研究流程 7
第二章文獻探討 9
2-1 數位金融的發展 9
2-2 資訊系統成功模式 15
2-3 信任 26
2-4 視訊服務 28
第三章研究方法 30
3-1 研究架構 30
3-2 研究假說 31
3-3 變數定義及衡量 33
3-4 研究對象與研究設計 40
第四章研究結果 41
4-1 敘述性統計分析 41
4-2 信度與效度之分析 51
4-3 假說關係之驗證 60
第五章結論與建議 70
5-1 研究結論 70
5-2 研究建議 71
5-3 研究貢獻 73
5-4 研究限制 73
5-5 未來研究方向 74
參考文獻 76
附錄 86

參考文獻

1. Aboobucker, I., & Bao, Y. (2018). What obstruct customer acceptance of internet banking? Security and privacy, risk, trust and website usability and the role of moderators. The Journal of High Technology Management Research, 29(1), 109-123.
2. Adhikari, A. (June 2, 2014). IndusInd Bank launches video banking. Retrieved from https://www.businesstoday.in/sectors/banks/indusind-bank-launches-video-banking/story/206849.html
3. Ahn, T., Ryu, S., & Han, I. (2004). The impact of the online and offline features on the user acceptance of Internet shopping malls. Electronic Commerce Research and Applications, 3(4), 405-420.
4. Aldas-Manzano, J., Ruiz-Mafe, C., Sanz-Blas, S., & Lassala-Navarre, C. (2011). Internet banking loyalty: evaluating the role of trust, satisfaction, perceived risk and frequency of use. The Service Industries Journal, 31(7), 1165-1190.
5. Ali, M. (2010). Validating IS success model: Evaluation of Swedish e-Tax system. System, 3, 0.972.
6. Andoh-Baidoo, F. K., Villarreal, M. A., Liu, L. C., & Wuddah-Martey, P. (2010). An exploratory study to examine the success of electronic banking systems implementation in a developing nation. International Journal of Electronic Finance, 4(3), 221-235.
7. Baabdullah, A. M., Alalwan, A. A., Rana, N. P., Kizgin, H., & Patil, P. (2019). Consumer use of mobile banking (M-Banking) in Saudi Arabia: Towards an integrated model. International Journal of Information Management, 44, 38-52.
8. Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the academy of marketing science, 16(1), 74-94.
9. Barnes, S. J., & Corbitt, B. (2003). Mobile banking: concept and potential. International journal of mobile communications, 1(3), 273-288.
10. Bentler, P. M. (1982). Confirmatory factor analysis via noniterative estimation: A fast, inexpensive method. Journal of marketing research, 19(4), 417-424.
11. Bentler, P. M., & Bonett, D. G. (1980). Significance tests and goodness of fit in the analysis of covariance structures. Psychological bulletin, 88(3), 588.
12. Bentler, P. M., & Yuan, K.-H. (1999). Structural Equation Modeling with Small Samples: Test Statistics. Multivariate Behavioral Research, 34(2), 181-197. doi:10.1207/S15327906Mb340203
13. Bharati, P., & Chaudhury, A. (2004). An empirical investigation of decision-making satisfaction in web-based decision support systems. Decision support systems, 37(2), 187-197.
14. Boateng, H., Adam, D. R., Okoe, A. F., & Anning-Dorson, T. (2016). Assessing the determinants of internet banking adoption intentions: A social cognitive theory perspective. Computers in Human Behavior, 65, 468-478. doi:10.1016/j.chb.2016.09.017
15. Browne, M. W. (1993). Alternative ways of assessing model fit. Testing structural equation models.
16. Buhler, T., Neustaedter, C., & Hillman, S. (2013). How and why teenagers use video chat. Paper presented at the Proceedings of the 2013 conference on Computer supported cooperative work.
17. Chen, H.-J. (2010). Linking employees’e-learning system use to their overall job outcomes: An empirical study based on the IS success model. Computers & Education, 55(4), 1628-1639.
18. 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.
19. Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 319-340.
20. Davis, F. D. (1993). User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International journal of man-machine studies, 38(3), 475-487.
21. DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information systems research, 3(1), 60-95.
22. DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: a ten-year update. Journal of Management Information Systems, 19(4), 9-30.
23. DeLone, W. H., & McLean, E. R. (2004). Measuring e-commerce success: Applying the DeLone & McLean information systems success model. International Journal of electronic commerce, 9(1), 31-47.
24. Dirgantari, P. D., Hidayat, Y. M., Mahphoth, M. H., & Nugraheni, R. (2020). Level of Use and Satisfaction of E-Commerce Customers in Covid-19 Pandemic Period: An Information System Success Model (ISSM) Approach. Indonesian Journal of Science and Technology, 5(2), 261-270.
25. Fernando, E. (2020). An Investigation Effective Factors Usage of Smartphone for Use Mobile Banking Services Case: Student University Customers. Paper presented at the 2020 International Conference on Information Management and Technology (ICIMTech).
26. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.
27. Futures, F. (1st December 2014). Barclays rolls out “anytime, anywhere” video banking. Retrieved from https://www.fintechfutures.com/2014/12/barclays-rolls-out-anytime-anywhere-video-banking/
28. Ganesan, S. (1994). Determinants of long-term orientation in buyer-seller relationships. Journal of marketing, 58(2), 1-19.
29. Gao, L., & Waechter, K. A. (2017). Examining the role of initial trust in user adoption of mobile payment services: an empirical investigation. Information Systems Frontiers, 19(3), 525-548.
30. Halawi, L. A., McCarthy, R. V., & Aronson, J. E. (2007). AN EMPIRICAL INVESTIGATION OF KNOWLEDGE MANAGEMENT SYSTEMS′SUCCESS. The Journal of Computer Information Systems, 48(2), 121.
31. Hanafizadeh, P., Behboudi, M., Koshksaray, A. A., & Tabar, M. J. S. (2014). Mobile-banking adoption by Iranian bank clients. Telematics and Informatics, 31(1), 62-78.
32. Hardianto, Z. I. P. (2019). Analysis and Design of User Interface and User Experience (UI/UX) E-Commerce Website PT Pentasada Andalan Kelola Using Task System Centered Design (TCSD) Method. Paper presented at the 2019 Fourth International Conference on Informatics and Computing (ICIC).
33. Hu, L. t., & Bentler, P. M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural equation modeling: a multidisciplinary journal, 6(1), 1-55.
34. Iivari, J. (2005). An empirical test of the DeLone-McLean model of information system success. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 36(2), 8-27.
35. Ives, B., Olson, M. H., & Baroudi, J. J. (1983). The measurement of user information satisfaction. Communications of the ACM, 26(10), 785-793.
36. Jana, S., Pande, A., Chan, A., & Mohapatra, P. (2013). Mobile video chat: issues and challenges. IEEE Communications Magazine, 51(6), 144-151.
37. Jarvenpaa, S. L., Tractinsky, N., & Saarinen, L. (1999). Consumer Trust in an Internet Store: a Cross-Cultural Validation. Journal of Computer-Mediated Communication, 5(2). doi:10.1111/j.1083-6101.1999.tb00337.x
38. Jerene, W., & Sharma, D. (2019). DETERMINANTS OF BANK CUSTOMER′S INTENTION TO ADOPT ELECTRONIC FINANCE TECHNOLOGIES IN ETHIOPIA: AN INTEGRATION OF TAM WITH FINANCIAL RISK, FINANCIAL TRUST, AND AWARENESS. Journal of Internet Banking and Commerce, 24(3), 1-18.
39. Kim, D., & Benbasat, I. (2003). Trust-related arguments in internet stores: A framework for evaluation. J. Electron. Commerce Res., 4(2), 49-64.
40. Kim, K. K., & Prabhakar, B. (2004). Initial trust and the adoption of B2C e-commerce: The case of internet banking. ACM SIGMIS Database: the DATABASE for Advances in Information Systems, 35(2), 50-64.
41. Lederer, A. L., Maupin, D. J., Sena, M. P., & Zhuang, Y. (2000). The technology acceptance model and the World Wide Web. Decision support systems, 29(3), 269-282.
42. Lee, K. C., & Chung, N. (2009). Understanding factors affecting trust in and satisfaction with mobile banking in Korea: A modified DeLone and McLean’s model perspective. Interacting with computers, 21(5-6), 385-392.
43. Likert, R. (1932). A technique for the measurement of attitudes. Archives of psychology.
44. Lin, H.-F., & Lee, G.-G. (2006). Determinants of success for online communities: an empirical study. Behaviour & Information Technology, 25(6), 479-488. doi:10.1080/01449290500330422
45. Lin, W.-R., Wang, Y.-H., & Hung, Y.-M. (2020). Analyzing the factors influencing adoption intention of internet banking: Applying DEMATEL-ANP-SEM approach. Plos one, 15(2), e0227852.
46. Lunt, P. (1995). Besting the big boys with video banking. American Bankers Association. ABA Banking Journal, 87(10), 28.
47. Marinkovic, V., & Obradovic, V. (2015). Customers’ emotional reactions in the banking industry. International journal of bank marketing.
48. Mashhour, A. (2008). A Framework for Evaluating the Effectiveness of Information Systems at Jordan Banks: An Empirical Study. Journal of Internet Banking and Commerce, 13(1).
49. McDonald, R. P., & Marsh, H. W. (1990). Choosing a multivariate model: Noncentrality and goodness of fit. Psychological bulletin, 107(2), 247.
50. McKnight, D. H., Choudhury, V., & Kacmar, C. (2002a). Developing and validating trust measures for e-commerce: An integrative typology. Information systems research, 13(3), 334-359.
51. McKnight, D. H., Choudhury, V., & Kacmar, C. (2002b). The impact of initial consumer trust on intentions to transact with a web site: a trust building model. The Journal of Strategic Information Systems, 11(3-4), 297-323.
52. 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.
53. Moorhead, P. (2016/8/30). Vidyo Aims To Disrupt Video Banking After Seeing Success In Healthcare And Defense. Retrieved from https://www.forbes.com/sites/patrickmoorhead/2016/08/30/vidyo-aims-to-disrupt-video-banking-after-seeing-success-in-healthcare-and-defense/?sh=3c717a4d5e4a
54. Nelson, R. R., Todd, P. A., & Wixom, B. H. (2005). Antecedents of information and system quality: an empirical examination within the context of data warehousing. Journal of Management Information Systems, 21(4), 199-235.
55. Nugroho, Y., & Prasetyo, A. (2018). Assessing information systems success: a respecification of the DeLone and McLean model to integrating the perceived quality. Problems and Perspectives in Management, 16(1), 348.
56. Parasuraman, A., Zeithaml, V. A., & Berry, L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. 1988, 64(1), 12-40.
57. Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1985). A conceptual model of service quality and its implications for future research. Journal of marketing, 49(4), 41-50.
58. Parasuraman, A., Zeithaml, V. A., & Malhotra, A. (2005). ES-QUAL: A multiple-item scale for assessing electronic service quality. Journal of service research, 7(3), 213-233.
59. Pitt, L. F., Watson, R. T., & Kavan, C. B. (1995). Service quality: a measure of information systems effectiveness. MIS quarterly, 173-187.
60. Riantama, I. G. E., Suardhika, N., & Yuesti, A. (2020). Financial technology application success in the 4.0 Era. International Journal of Psychosocial Rehabilitation, 24(9), 2948-2962.
61. Romi, I. M. (2013). Testing Delone and Mclean’s Model in Financial Institutions.
62. Sabherwal, R., Jeyaraj, A., & Chowa, C. (2006). Information system success: Individual and organizational determinants. Management science, 52(12), 1849-1864.
63. Sandjojo, N., & Wahyuningrum, T. (2015). Measuring e-learning systems success: Implementing D & M is success model. Paper presented at the 2015 4th International Conference on Interactive Digital Media (ICIDM).
64. Sharma, S. K., & Sharma, M. (2019). Examining the role of trust and quality dimensions in the actual usage of mobile banking services: An empirical investigation. International Journal of Information Management, 44, 65-75.
65. SKINNER, C. (2014). 數位銀行－銀行數位轉型策略指南: 台灣金融研訓院.
66. Strong, R. (2018). Video Banking ICT Adoption. Available at SSRN 3099802.
67. Tam, C., & Oliveira, T. (2016). Understanding the impact of m-banking on individual performance: DeLone & McLean and TTF perspective. Computers in Human Behavior, 61, 233-244.
68. Tam, C., & Oliveira, T. (2017). Understanding mobile banking individual performance: The DeLone & McLean model and the moderating effects of individual culture. Internet Research.
69. Tiwari, R., Buse, S., & Herstatt, C. (2007). Mobile services in banking sector: the role of innovative business solutions in generating competitive advantage. Technology and Innovation Managment Working Paper(48).
70. Urbach, N., Smolnik, S., & Riempp, G. (2010). An empirical investigation of employee portal success. The Journal of Strategic Information Systems, 19(3), 184-206.
71. Wang, Y. S. (2008). Assessing e‐commerce systems success: a respecification and validation of the DeLone and McLean model of IS success. Information systems journal, 18(5), 529-557.
72. Wu, J.-H., & Wang, Y.-M. (2006). Measuring KMS success: A respecification of the DeLone and McLean′s model. Information & Management, 43(6), 728-739.
73. Yadav, A. (2016). Factors influencing the usage of mobile banking among customers. IUP Journal of Bank Management, 15(4), 7.
74. Yousafzai, S., Pallister, J., & Foxall, G. (2009). Multi-dimensional role of trust in Internet banking adoption. The Service Industries Journal, 29(5), 591-605.
75. Yousafzai, S. Y., Pallister, J. G., & Foxall, G. R. (2005). Strategies for building and communicating trust in electronic banking: A field experiment. Psychology & Marketing, 22(2), 181-201.
76. Yu, P. L., Balaji, M., & Khong, K. W. (2015). Building trust in internet banking: a trustworthiness perspective. Industrial Management & Data Systems.
77. Zhao, Y., & Bacao, F. (2021). How Does the Pandemic Facilitate Mobile Payment? An Investigation on Users’ Perspective under the COVID-19 Pandemic. International Journal of Environmental Research and Public Health, 18(3), 1016.
78. Zhou, T. (2012). Understanding users’ initial trust in mobile banking: An elaboration likelihood perspective. Computers in Human Behavior, 28(4), 1518-1525. doi:10.1016/j.chb.2012.03.021
79. Zhu, D. H., Lan, L. Y., & Chang, Y. P. (2017). Understanding the Intention to Continue Use of a Mobile Payment Provider: An Examination of Alipay Wallet in China. International Journal of Business and Information, 12(4), 369-390. doi:http://dx.doi.org/10.6702/ijbi.2017.12.4.2
80. Zhu, J. D.-S., & Lin, C.-T. (2010). The antecedents and consequences of e-service quality for online banking. Social Behavior and Personality: an international journal, 38(8), 1009-1018.
81. 台灣金融研訓院. (2020). 台灣金融生活調查. Retrieved from 台灣金融研訓院:
82. 吳亞馨, 朱素玥, & 方文昌. (2008). 網路購物信任與科技接受模式之實證研究. 資訊管理學報, 頁, 123-152.
83. 吳家豪. (2020). 電商雙11單日銷售額破30億元創歷年新高. Retrieved from https://money.udn.com/money/story/5612/5010311
84. 李顯正. (2018). 金融科技概論: 新陸書局股份有限公司.
85. 李顯儀. (2018). 數位金融與金融科技: 全華圖書股份有限公司.
86. 周采嫻. (2016). 以媒體豐富性與媒體同步性探討運用視訊會議探視長輩之意圖. 交通大學管理學院資訊管理學程學位論文, 1-95.
87. 拓墣產業研究所. (2011). 行動雲端新浪潮：智慧型手機商機俏.
88. 林信亨. (2020/04). 疫情之下的遠距科技應用商機.
89. 林政賢. (2020). 2020 全球智慧型手機發展趨勢. 光連: 光電產業與技術情報(146), 40-44.
90. 林朝源, & 秦儀庭. (2012). PZB 服務品質模型探討服務品質與顧客滿意度之研究. Paper presented at the 彰雲嘉大學校院聯盟 2012 年學術研討會 (101/12/07) 2012-12-07 2012-12-07 大葉大學.
91. 范姜群暐. (2012/09). 行動商務大未來. 財金資訊季刊(NO.72).
92. 財團法人台灣網路資訊中心. (2020). 台灣網路報告. Retrieved from 財團法人台灣網路資訊中心:
93. 國立清華大學秘書處. (2017). 「心電支付」清華團隊發現來自新心的秘密. Retrieved from https://www.nthu.edu.tw/hotNews/content/537
94. 張偉豪. (2011). SEM 論文寫作不求人, 台北: 鼎茂圖書出版股份有限公司.
95. 曹孝義. (2002). 即時互動式視訊與遠端服務系統應用於電子教學環境之研究.
96. 陳正昌、程炳林. (2002). SPSS, SAS, BMDP統計軟體在多變量統計上的應用. 台北: 五南圖書出版公司.
97. 陳順宇. (2005). 多變量分析: 華泰書局.
98. 曾名慧. (2019). 影響消費者對純網路銀行使用意圖之研究.
99. 黃伃君. (2021/04/15). 臉書測試第二款約會軟體！4分鐘快速視訊配對用戶. Retrieved from https://newtalk.tw/news/view/2021-04-15/564125
100. 黃芳銘. (2004). 結構方程模式理論與應用, 台北市: 五南.
101. 勤業眾信聯合會計師事務所. (2021). 勤業眾信通訊. Retrieved from 勤業眾信聯合會計師事務所:
102. 楊筱筠. (2021/04/25). 數位帳戶戰純網銀躍新勢力. Retrieved from https://money.udn.com/money/story/5612/5411706
103. 劉曉薇. (2019). 純網路銀行對銀行業的影響研析. 彰銀資料, 68.
104. 蔡敏姿. (2020). 天貓雙11戰報十天業績2兆. Retrieved from https://udn.com/news/story/7333/5008119
105. 賴郁淇. (2008). 探討Podcasting採用因素與使用行為之研究. (碩士). 國立政治大學, 台北市. Retrieved from https://hdl.handle.net/11296/9mrs77

指導教授

張東生曹壽民(Dong-Shang Chang Shou-Min Tsao)

審核日期

2021-6-23

推文