朱永蕙、劉嘉麒（2016）。運用計畫行為理論探討環境關注對綠色民宿行為意向之研究。休閒與遊憩研究，8（2），97-111。
行政院（2017年12月06日）。賴揆：加速推動行動支付 盼2025年普及率達90%。行政院。https://www.ey.gov.tw/Page/9277F759E41CCD91/977b5339-f3a1-4882-9935-1f7ca0c075e0
李啓賢、陳宜清、何岫璁（2020）。以計畫行為理論探討商家維護場所消防設備堪用之行為意圖。科學與工程技術期刊，16（1），31-38。
李仲杰（2016）。以計畫行為理論探討消費者人格特質對炫耀性消費行為影響之研究-以智慧型手機為例（未出版之碩士論文）。國立臺灣師範大學，臺北市。
金融監督管理委員會（2024年1月9日）。金管會訂定我國非現金支付交易指標未來三年新目標值。金融監督管理委員會。https://www.fsc.gov.tw/ch/home.jsp?id=96&parentpath=0,2&mcustomize=news_view.jsp&dataserno=202401090002&toolsflag=Y&dtable=News
林宜隆、吳淑娟（2015）。行動支付之風險因子探討-以第三方支付為例。電腦稽核，32，97-111。
洪榮昭、傅惠筠（2012）。大專校院學生節能減碳行為意圖之研究。教育心理學報，44（2），373-387。
財團法人臺灣網路資訊中心（2023年8月29日）。2023臺灣網路報告。臺灣網路報告官網。https://report.twnic.tw/2023
財團法人資訊工業策進會產業情報研究所（2022年1月21日）。【行動支付大調查系列一】首選偏好度達50% 常用度逼近七成創新高 近六成消費者於疫情期間增加使用行動支付。MIC產業情報研究所。https://mic.iii.org.tw/news.aspx?id=617
財團法人資訊工業策進會產業情報研究所（2023年5月3日）。【行動支付大調查二】用戶款數集中度連年下降 36-45歲集中度最低 「藥局藥妝店、自營非連鎖餐飲」場域滲透率成長逾一成。MIC產業情報研究所。https://mic.iii.org.tw/news.aspx?id=639&List=49
陳怡如（2021）。消費者對行動支付使用意願之研究（未出版之碩士論文）。國立中興大學，臺中市。
黃俊豪（2018）。探討消費者由傳統信用卡轉換使用行動信用卡行為之研究（未出版之碩士論文）。淡江大學，新北市。
盧納特（2017）。行動支付大解構：掌握新消費習價。臺北市：四塊玉文創。
鍾政偉、蔣宇婷（2020）。以計畫行為理論探討社群媒體搜尋行為之研究-兼論社群媒體之差異比較。數據分析，15（4），69-101。
謝穎青（2018）。一機在手 樂活臺灣。臺灣經濟論衡，16（2），46-61。
Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and human decision processes, 50(2), 179-211.
Ajzen, I., & M., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs Prentice Hall.
Abdullah, F., & Ward, R. (2016). Developing a General Extended Technology Acceptance Model for E-Learning (GETAMEL) by analysing commonly used external factors. Computers in human behavior, 56, 238-256.
Azman, H. (2020). The factors that affecting consumer intention to utilize the electronic payment system in Malaysia. Journal of Technology Management and Technopreneurship (JTMT), 8(1), 129-138.
Alsmadi, A. A., Shuhaiber, A., Alhawamdeh, L. N., Alghazzawi, R., & Al-Okaily, M. (2022). Twenty years of mobile banking services development and sustainability: a bibliometric analysis overview (2000–2020). Sustainability, 14(17), 10630.
Bhattacherjee, A. (2000). Acceptance of e-commerce services: the case of electronic brokerages. IEEE Transactions on systems, man, and cybernetics-Part A: Systems and humans, 30(4), 411-420.
Bugembe, J. (2010). Perceived usefulness, perceived ease of use, attitude and actual usage of anew financial management system: A case of Uganda National Examinations Board (Doctoral dissertation, Makerere University).
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. psychometrika, 16(3), 297-334.
Dahlberg, T., Guo, J., & Ondrus, J. (2015). A critical review of mobile payment research. Electronic commerce research and applications, 14(5), 265-284.
Fu, H. P., Chang, T. S., Wang, C. N., Hsu, H. P., Liu, C. H., & Yeh, C. Y. (2022). Critical factors affecting the introduction of mobile payment tools by microretailers. Technological Forecasting and Social Change, 175, 121319.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50.
Guielford, J. P. (1965). A psychometric approach to creativity. In H. Anderson (Ed.). Creativity in childhood and adolescence (pp. 348-369). Palo Alto, California: Science and Behavior Books.
Hair, J. F. Jr., Anderson, R. E., Tatham, R. L., & Black, W. C. (2010) . Multivariate data analysis (7th ed.) . Englewood Cliffs, NJ: Prentice Hall.
Hoa, N. T., Hien, L. M., & Lien, V. T. P. (2019). Studying the factors affecting online payment decision: A case of vietnamese customers. Journal of Management Information and Decision Sciences, 22(1), 43-54.
Immanuel, D. M., & Dewi, Y. K. (2020). Mobile Payment Adoption Intention During Pandemic COVID-19 in Indonesia. Journal of Information System and Technology Management, 5(19), 60-76.
Jena, R. K. (2022). Investigating and predicting intentions to continue using mobile payment platforms after the COVID-19 pandemic: An empirical study among retailers in India. Journal of Risk and Financial Management, 15(7), 314.
Jung, J.-H., Kwon, E., & Kim, D. H. (2020). Mobile payment service usage: U.S. consumers’ motivations and intentions. Computers in Human Behavior Reports, 1, 100008. https://doi.org/10.1016/j.chbr.2020.100008
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.
Koenig-Lewis, N., Marquet, M., Palmer, A. (2015). Enjoyment and social influence: predicting mobile payment adoption. The Service Industries Journal, 35(10), 537–554. https://doi.org/10.1080/02642069.2015.1043278
Liébana-Cabanillas, F., Ramos de Luna, I., & Montoro-Ríos, F. J. (2015). User behaviour in QR mobile payment system: the QR Payment Acceptance Model. Technology Analysis & Strategic Management, 27(9), 1031-1049.
Liu, Y., Luo, J., & Zhang, L. (2021). The effects of mobile payment on consumer behavior. Journal of Consumer Behaviour, 20(3), 512-520.
Lian, J.-W., & Li, J. (2021). The dimensions of trust: An investigation of mobile payment services in Taiwan. Technology in Society, 67, 101753. https://doi.org/10.1016/j.techsoc.2021.101753
Lai, P. C. (2017). Security as an extension to TAM model: Consumers' intention to use a singleplatform E-Payment. Asia-Pacific Journal of Management Research and Innovation, 13(3-4), 110-119.
Norng, S. (2022). Factors influencing mobile banking adoption in Cambodia: The structuring of TAM, DIT, and trust with TPB. Asian Journal of Business Research Volume, 12(3).
Oney, E., Guven, G. O., & Rizvi, W. H. (2017). The determinants of electronic payment systems usage from consumers' perspective. Economic research-Ekonomska istraživanja, 30(1),394-415.
Ooi, K. B., & Tan, G. W. H. (2022). Guest editorial: The impact of COVID-19 pandemic on mobile payment. International Journal of Bank Marketing, 40(5), 937-938.
Rahman, M., Ismail, I., & Bahri, S. (2020). Analysing consumer adoption of cashless payment in Malaysia. Digital Business, 1(1), 100004.
Slade, E. L., Dwivedi, Y. K., Piercy, N. C. (2015). Modeling Consumers’ Adoption Intentions of Remote Mobile Payments in the United Kingdom: Extending UTAUT with Innovativeness, Risk, and Trust. Psychology & Marketing, 32(8), 860–873. https://doi.org/10.1002/mar.20823
Sánchez, R. A., & Hueros, A. D. (2010). Motivational factors that influence the acceptance of Moodle using TAM. Computers in human behavior, 26(6), 1632-1640.
Tan, M., & Teo, T. S. (2000). Factors influencing the adoption of Internet banking. Journal of the Association for information Systems, 1(1), 5.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS quarterly, 425-478.