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研究生: 羅勻廷
Lo, Yun-Ting
論文名稱: 台灣行動支付分享意願因素之研究 - 以LINE Pay為例
Share intention of mobile payment in Taiwan -- Using LINE Pay as an example
指導教授: 盧希鵬
Hsi-Peng Lu
口試委員: 盧希鵬
Hsi-Peng Lu
黃世禎
Sun-Jen Huang
蕭國倫
Kuo-Lun Hsiao
學位類別: 碩士
Master
系所名稱: 管理學院 - 資訊管理系
Department of Information Management
論文出版年: 2019
畢業學年度: 107
語文別: 英文
論文頁數: 58
中文關鍵詞: 行動支付自我效能價值框架分享意願LINE Pay
外文關鍵詞: Mobile payment, Self-efficacy, Valence framework, Innovation Diffusion Theory, LINE Pay
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  • 隨著科技的快速發展,智慧型手機的使用已廣泛的應用於人們的生活中,而其便利性也影響到了許多人的生活習慣,行動支付這項創新的付費方式也從中融入了人們的生活當中。儘管台灣目前不論在政策上或是商業上都在積極推廣行動支付的使用,但使用行動支付作為付費方式的人數並沒有期望中的多,因此如何吸引潛在用戶使用行動支付成為台灣需面臨的主要問題。過去有許多關於行動支付的相關研究,但文獻中大部分都在探討使用者的使用意願及持續使用意願。由於台灣在地理環境上的便利性,使得人們在交易上習慣以舊有的現金及信用卡方式進行支付,若要吸引潛在用戶使用,藉由分享的方式可以快速增加不同族群間資訊的傳遞。故本研究將從不同的角度出發,去探討使用者的分享意願,以了解使用者願意分享行動支付這項服務的因素。以使用者自身的社會效能、科技效能為外部影響因子,並以知覺利益、知覺風險為中介變數,去探討人們分享行動支付的意願。
    本研究以量化的方式進行研究,並以LINE Pay作為問卷中的研究案例。從問卷分析中可以發現:(1) 根據創新接受程度的不同,對於分享意願的因素也會不同。早期採用者會因風險和利益而影響分享意願;主要及晚期採用者會因利益而影響分享意願,因此建議行動支付業者在早期推廣行動支付服務時應注重系統的穩定及安全性,未來再投入較多的優惠方案;(2) 早期、主要採用者會因自身的科技效能而影響知覺利益跟知覺風險,而晚期採用者除了科技效能外,也會因自身的社會效能影響知覺利益跟知覺風險。


    With the rapid development of technology, smartphones have been widely used in people's lives. The payment method of mobile payment has also been incorporated into people. Although Taiwan is currently actively promoting the use of mobile payments, the number of people using mobile payment is not much expected. Therefore, how to attract potential users using mobile payment has become a problem for Taiwan. There are many kinds of research explored the willingness and the willingness to continue to use mobile payment. Due to the geographical convenience of Taiwan, people used cash and credit card as their payment transaction. Through share intention, the information will transfer between different groups, and attract potential users. Therefore, this research will explore the willingness of users to share mobile payment from different perspectives. This research discusses the share intention of using mobile payment by applying “social efficacy” and “technology efficacy” as external factors, as well as “perceived benefit” and “perceived riskless” as intermediary variables.
    Through a qualitative method, this research adopted LINE Pay, a mobile payment application, as a research case in the questionnaire. After the literature review and analyzing the data, the cross-reference found that: (1) According to the degree of innovation diffusion, early adopters’ share intention will be affected by risks and benefits; major and latest adopters will be affected by benefit. Therefore, it is recommended that an enterprise should pay attention to the stability and security of the system in the stage of promoting mobile payment. (2) Early, main adopters will affect their perceived benefits and perceived riskless by technology efficacy. Latest adopters not only affect their perceived benefits and perceived riskless by technology efficacy, but also from social efficacy.

    中文摘要 I Abstract II 致 謝 III Table of Contents IV List of Figures VI List of Tables VII 1 Introduction 1 1.1 Background and motivation 1 1.2 Research questions 3 1.3 Value of research 3 1.4 Overview 4 2 Literature Review 5 2.1 Mobile payment 5 2.2 Self-efficacy theory 7 2.3 Valence framework 8 2.4 Innovation diffusion theory 9 3 Proposed Model and Research Hypotheses 11 4 Methodology 14 4.1 Case description 14 4.2 Questionnaire 14 4.3 Sample 15 4.4 Data analysis 17 5. Result 24 6. Conclusion and Limitations 35 6.1. Conclusion and discussion 35 6.2. Theoretical implications 36 6.3. Practice recommendations 37 6.4. Limitations 38 6.5. Future research 38 References 39 Appendix. Questionnaire 46

    Alalwan, A. A., Dwivedi, Y. K., Rana, N. P., & Williams, M. D. (2016). Consumer adoption of mobile banking in Jordan: examining the role of usefulness, ease of use, perceived risk and self-efficacy. Journal of Enterprise Information Management, 29(1), 118-139.
    Bailey, A. A., Pentina, I., Mishra, A. S., & Ben Mimoun, M. S. (2017). Mobile payments adoption by US consumers: an extended TAM. International Journal of Retail & Distribution Management, 45(6), 626-640. doi:10.1108/ijrdm-08-2016-0144
    Bandura, A., & Schunk, D. H. (1981). Cultivating competence, self-efficacy, and intrinsic interest through proximal self-motivation. Journal of personality and social psychology, 41(3), 586.
    Bauer, H. H., Reichardt, T., Barnes, S. J., & Neumann, M. M. (2005). Driving consumer acceptance of mobile marketing: A theoretical framework and empirical study. Journal of electronic commerce research, 6(3), 181.
    Chandra, S., Srivastava, S. C., & Theng, Y.-L. (2010). Evaluating the role of trust in consumer adoption of mobile payment systems: An empirical analysis. CAIS, 27(29), 27.
    Chang, S. E., Shen, W. C., & Liu, A. Y. (2016). Why mobile users trust smartphone social networking services? A PLS-SEM approach. Journal of Business Research, 69(11), 4890-4895. doi:10.1016/j.jbusres.2016.04.048
    Chen, K. Y., & Chang, M. L. (2013). User acceptance of 'near field communication' mobile phone service: an investigation based on the 'unified theory of acceptance and use of technology' model. Service Industries Journal, 33(6), 609-623. doi:10.1080/02642069.2011.622369
    Chen, L.-d. (2008). A model of consumer acceptance of mobile payment. International Journal of Mobile Communications, 6(1), 32-52.
    Chu, R. J., & Chu, A. Z. (2010). Multi-level analysis of peer support, Internet self-efficacy and e-learning outcomes - The contextual effects of collectivism and group potency. Computers & Education, 55(1), 145-154. doi:10.1016/j.compedu.2009.12.011
    Dahlberg, T., Guo, J., & Ondrus, J. (2015). A critical review of mobile payment research. Electronic Commerce Research and Applications, 14(5), 265-284.
    Dahlberg, T., Mallat, N., Ondrus, J., & Zmijewska, A. (2008). Past, present and future of mobile payments research: A literature review. Electronic Commerce Research and Applications, 7(2), 165-181.
    De Kerviler, G., Demoulin, N. T., & Zidda, P. (2016). Adoption of in-store mobile payment: Are perceived risk and convenience the only drivers? Journal of Retailing and Consumer Services, 31, 334-344.
    de Kerviler, G., Demoulin, N. T. M., & Zidda, P. (2016). Adoption of in-store mobile payment: Are perceived risk and convenience the only drivers? Journal of Retailing and Consumer Services, 31, 334-344. doi:10.1016/j.jretconser.2016.04.011
    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.
    He, Y. J. (2013). Study of Magnetic Field Coupling Technologies in Activating RFID-SIM Card Mobile Payments. Wireless Personal Communications, 71(1), 243-254. doi:10.1007/s11277-012-0813-1
    Kankanhalli, A., Tan, B. C., & Wei, K.-K. (2005). Contributing knowledge to electronic knowledge repositories: An empirical investigation. MIS quarterly, 29(1).
    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.
    Kim, D. J., Ferrin, D. L., & Rao, H. R. (2009). Trust and satisfaction, two stepping stones for successful e-commerce relationships: A longitudinal exploration. Information systems research, 20(2), 237-257.
    Kreyer, N., Pousttchi, K., & Turowski, K. (2002). Standardized payment procedures as key enabling factor for mobile commerce. Paper presented at the International Conference on Electronic Commerce and Web Technologies.
    Kujala, S., Mugge, R., & Miron-Shatz, T. (2017). The role of expectations in service evaluation: A longitudinal study of a proximity mobile payment service. International Journal of Human-Computer Studies, 98, 51-61. doi:10.1016/j.ijhcs.2016.09.011
    Lee, H., Park, H., & Kim, J. (2013). Why do people share their context information on Social Network Services? A qualitative study and an experimental study on users' behavior of balancing perceived benefit and risk. International Journal of Human-Computer Studies, 71(9), 862-877. doi:10.1016/j.ijhcs.2013.01.005
    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, Z. W., Chan, T. K., Balaji, M., & Chong, A. Y.-L. (2018). Why people participate in the sharing economy: an empirical investigation of Uber. Internet Research, 28(3), 829-850.
    Lewis, W., Agarwal, R., & Sambamurthy, V. (2003). Sources of influence on beliefs about information technology use: An empirical study of knowledge workers. MIS quarterly, 657-678.
    Liébana-Cabanillas, F., Muñoz-Leiva, F., & Sánchez-Fernández, J. (2018). A global approach to the analysis of user behavior in mobile payment systems in the new electronic environment. Service Business, 12(1), 25-64.
    Liao, Y. J., He, Y. C., Li, F. G., & Zhou, S. J. (2018). Analysis of a mobile payment protocol with outsourced verification in cloud server and the improvement. Computer Standards & Interfaces, 56, 101-106. doi:10.1016/j.csi.2017.09.008
    Liebana-Cabanillas, F., de Luna, I. R., & Montoro-Rios, F. (2017). Intention to use new mobile payment systems: a comparative analysis of SMS and NFC payments. Economic Research-Ekonomska Istrazivanja, 30(1), 892-910. doi:10.1080/1331677x.2017.1305784
    Liebana-Cabanillas, F., de Luna, I. R., & Montoro-Rios, F. J. (2015). User behaviour in QR mobile payment system: the QR Payment Acceptance Model. Technology Analysis & Strategic Management, 27(9), 1031-1049. doi:10.1080/09537325.2015.1047757
    Liebana-Cabanillas, F., Molinillo, S., & Ruiz-Montanez, M. (2019). To use or not to use, that is the question: Analysis of the determining factors for using NFC mobile payment systems in public transportation. Technological Forecasting and Social Change, 139, 266-276. doi:10.1016/j.techfore.2018.11.012
    Lin, K.-Y., & Lu, H.-P. (2011). Why people use social networking sites: An empirical study integrating network externalities and motivation theory. Computers in Human Behavior, 27(3), 1152-1161.
    Lin, W. R., Wang, Y. H., & Shih, K. H. (2017). Understanding consumer adoption of mobile commerce and payment behaviour: an empirical analysis. International Journal of Mobile Communications, 15(6), 628-654. doi:10.1504/ijmc.2017.10005646
    Lopez, M. H., Felix, E. M., Ruiz, R. O., & Ortiz, O. G. (2016). Influence of social motivation, self-perception of social efficacy and normative adjustment in the peer setting. Psicothema, 28(1), 32-39. doi:10.7334/psicothema2015.135
    Lu, Y., Yang, S., Chau, P. Y., & Cao, Y. (2011). Dynamics between the trust transfer process and intention to use mobile payment services: A cross-environment perspective. Information & Management, 48(8), 393-403.
    Lu, Y. B., Yang, S. Q., Chau, P. Y. K., & Cao, Y. Z. (2011). Dynamics between the trust transfer process and intention to use mobile payment services: A cross-environment perspective. Information & Management, 48(8), 393-403. doi:10.1016/j.im.2011.09.006
    Ma, L., Zhang, X., & Ding, X. Y. (2018). Social media users' share intention and subjective well-being: An empirical study based on WeChat. Online Information Review, 42(6), 784-801. doi:10.1108/oir-02-2017-0058
    MIC. (2018). Mobile payment consumer survey in Taiwan - consumer analysis.
    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 & Management, 43(3), 350-363.
    Nambiar, S., & Lu, C.-T. (2005). M-payment solutions and m-commerce fraud management. In Advances in security and payment methods for mobile commerce (pp. 192-213): IGI Global.
    Ogbanufe, O., & Kim, D. J. (2018). Comparing fingerprint-based biometrics authentication versus traditional authentication methods for e-payment. Decision support systems, 106, 1-14.
    Oliveira, T., Thomas, M., Baptista, G., & Campos, F. (2016). Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology. Computers in Human Behavior, 61, 404-414. doi:10.1016/j.chb.2016.03.030
    Ooi, K.-B., & Tan, G. W.-H. (2016). Mobile technology acceptance model: An investigation using mobile users to explore smartphone credit card. Expert Systems with Applications, 59, 33-46.
    Park, J., Amendah, E., Lee, Y., & Hyun, H. (2019). M-payment service: Interplay of perceived risk, benefit, and trust in service adoption. Human Factors and Ergonomics in Manufacturing & Service Industries, 29(1), 31-43. doi:10.1002/hfm.20750
    Park, J., Amendah, E., Lee, Y., & Hyun, H. (2019). M‐payment service: Interplay of perceived risk, benefit, and trust in service adoption. Human Factors and Ergonomics in Manufacturing & Service Industries, 29(1), 31-43.
    Rogers, E. M. (2010). Diffusion of innovations: Simon and Schuster.
    Ryu, H.-S. (2018). What makes users willing or hesitant to use Fintech?: the moderating effect of user type. Industrial Management & Data Systems, 118(3), 541-569.
    Shao, Z., Zhang, L., Li, X., & Guo, Y. (2019). Antecedents of trust and continuance intention in mobile payment platforms: The moderating effect of gender. Electronic Commerce Research and Applications, 33, 100823.
    Singh, N., Srivastava, S., & Sinha, N. (2017). Consumer preference and satisfaction of M-wallets: a study on North Indian consumers. International Journal of Bank Marketing, 35(6), 944-965. doi:10.1108/ijbm-06-2016-0086
    Su, P., Wang, L., & Yan, J. (2018). How users’ Internet experience affects the adoption of mobile payment: a mediation model. Technology Analysis & Strategic Management, 30(2), 186-197.
    Torres, R., & Gerhart, N. (2019). Mobile Proximity Usage Behaviors Based on User Characteristics. Journal of Computer Information Systems, 59(2), 161-170. doi:10.1080/08874417.2017.1320954
    Tsai, M. T., & Cheng, N. C. (2010). Programmer perceptions of knowledge-sharing behavior under social cognitive theory. Expert Systems with Applications, 37(12), 8479-8485. doi:10.1016/j.eswa.2010.05.029
    Tzou, R.-C., & Lu, H.-P. (2009). Exploring the emotional, aesthetic, and ergonomic facets of innovative product on fashion technology acceptance model. Behaviour & Information Technology, 28(4), 311-322.
    Wipawayangkool, K., & Teng, J. T. C. (2019). Profiling knowledge workers' knowledge sharing behavior via knowledge internalization. Knowledge Management Research & Practice, 17(1), 70-82. doi:10.1080/14778238.2018.1557798
    Xiao, L., Farooq, U., Carroll, J. M., & Rosson, M. B. (2013). The development of community members' roles in partnership research projects: An empirical study. Journal of the American Society for Information Science and Technology, 64(11), 2340-2353.
    Yang, H. L., & Lin, S. L. (2019). The reasons why elderly mobile users adopt ubiquitous mobile social service. Computers in Human Behavior, 93, 62-75. doi:10.1016/j.chb.2018.12.005
    Yang, Y., Liu, Y., Li, H., & Yu, B. (2015). Understanding perceived risks in mobile payment acceptance. Industrial Management & Data Systems, 115(2), 253-269.
    Zhou, T. (2013). An empirical examination of continuance intention of mobile payment services. Decision support systems, 54(2), 1085-1091.

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