本研究旨在探討影響捷運旅客持續使用「台北捷運 Go」App 的關鍵因素，運用資訊系統成功模式 (Information System Success Model, IS) 及科技接受模型 (Technology Acceptance Model, TAM) 作為理論基礎，分析資訊品質、系統品質、服務品質、知覺有用性、知覺易用性及知覺便利性對其持續使用意願的影響，以曾使用該 App 的旅客為研究對象。研究回收了605份有效問卷，並使用SPSS進行數據分析。進行描述性統計、獨立樣本t檢定、單因子變異數分析、皮爾森相關係數分析及多元迴歸分析，檢視各變數間的影響與關聯。
研究結果顯示，資訊品質、系統品質和服務品質對知覺有用性、知覺易用性及知覺便利性有顯著正向影響，且這三個知覺因素對持續使用意願有顯著正向影響。此外，知覺有用性在資訊品質與持續使用意願間具中介效果；知覺易用性在系統品質與持續使用意願間具中介效果；知覺便利性在服務品質與持續使用意願間具中介效果。
最後根據研究結果，建議「台北捷運 Go」App 開發業者應優化資訊品質、系統品質和服務品質，以提升使用者的知覺有用性、易用性和便利性，增強持續使用意願，並制定適應不同使用者需求策略，以應對不斷變化的市場需求和競爭環境。

This study aims to explore the key factors influencing MRT passengers' continuous use of the "Taipei MRT Go" App, analyzing the impact of information quality, system quality, service quality, perceived usefulness, perceived ease of use, and perceived convenience on their intention to continue using the App. The study targets passengers who have used the App, collecting 605 valid questionnaires and using SPSS for data analysis. Descriptive statistics, independent samples t-tests, one-way ANOVA, Pearson correlation, and multiple regression analyses were conducted to examine the effects and relationships among the variables.
The results show that information quality, system quality, and service quality significantly positively affect perceived usefulness, perceived ease of use, and perceived convenience, which in turn significantly positively influence continuous use intention. Additionally, perceived usefulness mediates the relationship between information quality and continuous use intention; perceived ease of use mediates the relationship between system quality and continuous use intention; and perceived convenience mediates the relationship between service quality and continuous use intention.
Finally, this study suggests that the developers of the "Taipei MRT Go" App should optimize information quality, system quality, and service quality to enhance users' perceived usefulness, ease of use, and convenience, thereby increasing continuous use intention. Furthermore, strategies should be developed to cater to different user needs to address the ever-changing market demands and competitive environment.

交通部（2023）。111年度交通年鑑。交通部全球資訊網。https://www.motc.Gov.tw/ch/App/yearbook_list?lang=ch&folderName=ch&id=21。
何中文（2012）。以資訊系統成功觀點探討影響App持續使用之因素［未出版之碩士論文］。正修科技大學。
何苔麗、徐慧霞、章家誠（2012）。手機應用程式服務使用態度及再購意願研究－以蘋果公司的 App Store 為例。中華科技大學學報，50，169-189。
https://doi.org/10.7095/JCUST.201201.0166
卓依臻（2021）。以資訊系統成功模式整合內部動機觀點探討行動銀行APP持續使用意圖［未出版之碩士論文］。朝陽科技大學。
徐欽祥、曾智檉、何篤光（2013）。以科技接受模型與資訊系統成功模式探討大專運動會官網使用意願。休閒運動保健學報，5，9-23。https://doi.org/10.6204/JRSHP.2013.05.02
柴康偉、歐瑋明、黃柏鈞、林明憲、陳定献、黃琮森、鄧富川 （2021）。蝦皮App使用者知覺有用性對使用態度之影響-以行動購物系統品質為干擾變數。管理資訊計算，10，1-10。https://doi.org/10.6285/MIC.202108/SP_02_10.0001
袁劍雲、邱天佑、關來成（2013）。使用者網站購物購買行為前置因素之研究：以轉換成本為調節變數。顧客滿意學刊，9(1)，1-22。
財團法人台灣網路資訊中心（2023）。2023年台灣網路報告。台灣網路報告官網。 https://report.twnic.tw/2023。
張宗榮（2012）。以整合性科技接受模式及沉浸理論探討App之使用行為模式：以行動社群App為例［未出版之碩士論文］。國立臺中教育大學。
許麗玲、徐村與、唐嘉偉、梁智勇（2010）。Blog體驗價值對使用者持續使用意圖之研究。資訊管理學報，17(4)，89-117。https://doi.org/10.6382/JIM.201010.0089
許麗玲、陳至柔、陳澔輝（2013）。雲端ERP系統服務品質與持續使用意願之研究。電子商務學報，15(2)，195-234。https://doi.org/10.6188/JEB.2013.15（2）.02
陳光華、楊政樺、林祈宏（2015）。服務便利性與企業信譽對高鐵 APP使用意願影響探討－兼論企業信譽的調節角色。運輸計劃季刊，44(3)，289-312。
陳至柔、吳如娟、林松江（2016）。雲端CRM系統持續使用意願之實證研究：整合任務-科技適配模式與體制理論。電子商務學報，18(1)，1-40。https://doi.org/10.6188/JEB.2016.18（1）.04
陳宜棻、蔡家文、謝昌隆、曾珮瑜（2015）。探討臺灣高速鐵路網路訂票系統之顧客使用意願。績效與策略研究，12(1)，1-26。https://doi.org/10.6736/JPSR.201503_12(1).0001
程琬萱（2014）。APP圖示視覺符號溝通與消費者下載決策關係：以遊戲類為例［未出版之碩士論文］。國立臺北科技大學。https://doi.org/10.6841/NTUT.2014.00563
黃姵嫙（2018）。綠色招募活動對組織人才吸引力之影響：以個人組織配適知覺為中介變數與個人環保態度為干擾變數［未出版之碩士論文］。東海大學。
楊治清、洪正明（2011）。運用修正版Delone and Mclean資訊系統成功模式探討影響行動輔修系統使用者滿意度之關鍵因素。電子商務研究，9(1)，61-78。
https://doi.org/10.29767/ECS.201103.0003
廖盈琦、王建富（2016）。企業行動商務推動之影響因素與經濟意涵。應用經濟論叢，100，183-216。
臺北大眾捷運股份有限公司（2023）。台北捷運Go App背景資料［未公開數據］。
臺北大眾捷運股份有限公司（2024）。台北捷運Go [行動裝置應用程式]。https://play.google.com/store/apps/details?id=tw.com.trtc.is.android05
蔣石蘭（2012）。智慧型手機使用者應用程式持續使用意圖之研究-以iPhone App Store為例［未出版之碩士論文］。華梵大學。
薛昭義、陳光華、陳培銘（2019）。Are You Ready？連鎖旅館行動應用軟體（APP）使用意願分析－從顧客觀點探討。觀光休閒學報，25(3)，247-273。https://doi.org/10.6267/JTLS.201912_25（3）.0001
Al Enezi, D. F., Al Fadley, A. A., & Al Enezi, E. G. (2022). Exploring the attitudes of instructors toward Microsoft Teams using the technology acceptance model. International Education Studies, 15(1), 123-135.https://doi.org/10.3390/su142113935
Albaom, M. A., Sidi, F., Jabar, M. A., Abdullah, R., Ishak, I., Yunikawati, N. A., Priambodo, M. P., Nusari, M. S., & Ali, D. A. (2022). The moderating role of personal innovativeness in tourists' intention to use web 3.0 based on updated information systems success model. Sustainability, 14(21), 1-35.https://doi.org/10.3390/su142113935
Aldholay, A., Isaac, O., Abdullah, Z., Abdulsalam, R., & Al-Shibami, A. H. (2018). An extension of Delone and McLean IS success model with self-efficacy. International Journal of Information and Learning Technology, 35(4), 285-304. https://doi.org/10.1108/IJILT-11-2017-0116
Angelina, R. J., Hermawan, A., & Suroso, A. I. (2019). Analyzing e-commerce success using DeLone and McLean model. Journal of Information Systems Engineering and Business Intelligence, 5(2), 156-162. https://doi.org/10.20473/jisebi.5.2.156-162
Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182.https://doi.org/10.1037/0022-3514.51.6.1173
Bentler, P. M., & Chou, C. P. (1987). Practical issues in structural modeling. Sociological Methods and Research, 16, 78-117.https://doi.org/10.1177/0049124187016001004
Berry, L. L., Seiders, K., & Grewal, D. (2002). Understanding service convenience. Journal of Marketing, 66(3), 1-17. https://doi.org/10.1509/jmkg.66.3.1.18505
Bhattacherjee, A. (2001). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32(2), 201-214.
https://doi.org/10.1016/S0167-9236（01）00111-7Brown, L. G. (1989). The strategic and tactical implications of convenience in consumer product marketing. Journal of Consumer Marketing, 6(3), 13-19.https://doi.org/10.1108/EUM0000000002550
Chang, C. C., Tseng, K. H., Liang, C., & Yan, C. F. (2013). The influence of perceived convenience and curiosity on continuance intention in mobile English learning for high school students using PDAs. Technology, PedaGogy and Education, 22(3), 373-386. https://doi.org/10.1080/1475939X.2013.802991
Chang, H. H., & Lim, X. J. (2022). Effect of virtual reality on tourists' intention to visit a destination. Journal of Tourism and Leisure Studies, 28(1), 1-37. https://doi.org/10.6267/JTLS.202204_28（1）.0001
Chen, J., & Wang, S. (2022). The impact of AI and 5G on app development. Journal of Emerging Technologies, 15(2), 123-135. https://doi.org/10.3991/ijet.v17i01.28533
Ching, K. C., Hasan, Z. R. A., & Hasan, N. A. (2021). Factors influencing consumers in using Shopee for online purchase intention in east coast Malaysia. Universiti Malaysia Terengganu Journal of Undergraduate Research, 3(1), 45-56. https://doi.org/10.46754/umtjur.v3i1.191
Chiu, P. S., Chao, I. C., Kao, C. C., Pu, Y. H., & Huang, Y. M. (2016) . Implementation and evaluation of mobile e-books in a cloud bookcase using the information system success model. Library Hi Tech, 34(2), 207-223.https://doi.org/10.1108/LHT-12-2015-0113
Chou, C. H., Chiu, C. H., Ho, C. Y., & Lee, J. C. (2013, June). Understanding mobile apps continuance usage behavior and habit: An expectance-confirmation theory [Paper presentation]. Pacific Asia Conference on Information Systems (PACIS), Jeju Island, Korea.https://doi.org/10.1109/APCCAS.2012.6418976
Chowdhury, R. (2023). Impact of perceived convenience, service quality and security on consumers’ behavioural intention towards online food delivery services: The role of attitude as mediator. SN Business & Economics, 3(1), 1-23.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008
DeLone, W. H., & McLean, E. R. (1992). Information systems success: The quest for the dependent variable. Information Systems Research, 3(1), 60-95. https://doi.org/10.1287/isre.3.1.60
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.https://doi.org/10.1080/07421222.2003.11045748
Eryiğit, C., & Fan, Y. (2021). The effects of convenience and risk on e-loyalty through the mediating role of e-Service quality: A comparison for China and Turkey. Journal of International Consumer Marketing, 33(5), 613-626.https://doi.org/10.1080/08961530.2021.1879704
Fazio, R. H., & Zanna, M. P. (1981). Direct experience and attitude-behavior consistency. Advances in Experimental Social Psychology, 14, 161-202. https://doi.org/10.1016/S0065-2601(08)60372-X
Feng, T. T., Tien, C., Feng, Z. Y., & Lai, P. J. (2014). Web site quality and online trading influences on customer acceptance of securities brokers. Asia Pacific Management Review, 19(1), 25-45. https://doi.org/10.6126/APMR.2014.19.1.02
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.https://doi.org/10.2307/3151312
Frolick, M. N., & Chen, L.-D. (2004). Assessing m-commerce opportunities. Information Systems Management, 21(2), 53-61. https://doi.org/10.1201/1078/44118.21.2.20040301/80422.8
García-Fernández, J., Gálvez-Ruíz, P., Fernández-Gavira, J., Vélez-Colón, L., Pitts, B., & Bernal-García, A. (2018). The effects of service convenience and perceived quality on perceived value, satisfaction and loyalty in low-cost fitness centers. Sport Management Review, 21(3), 250-262.https://doi.org/10.1016/j.smr.2017.07.003
Hair, Jr. J. F., Anderson, R. E., Tatham, R, L. & Black, W. C. (1998). Multivariate data analysis (5th ed.). Prentice Hall.
Hair, Jr. J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (2010). Multivariate data analysis (7th ed.). Prentice Hall.
Hamid, A. A., Razak, F. Z. A., Bakar, A. A., & Abdullah, W. S. W. (2016). The effects of perceived usefulness and perceived ease of use on continuance intention to use E-Government. Procedia Economics and Finance, 35, 644-649.https://doi.org/10.1016/S2212-5671（16）00079-4
Hornik, J. (1984). Subjective vs. objective time measures: A note on the perception of time in consumer behavior. Journal of Consumer Research, 11(1), 615-618. https://doi.org/10.1086/208998
Hsia, H., Cheng, C., & Hong, L. (2013). An empirical study of users' continuance intention and word of mouth toward SNA (Social Network APP). In K. Phusavat (Ed.), Diversity, Technology, and Innovation for Operational Competitiveness: Proceedings of the 2013 International Conference on Technology Innovation and Industrial Management (pp. 29-31). ToKnowPress .
Hsu, M. H., Chang, C. M., Chu, K. K., & Lee, Y. J. (2014). Determinants of repurchase intention in online group-buying: The perspectives of DeLone & McLean IS success model and trust. Computers in Human Behavior, 36, 234-245.https://doi.org/10.1016/j.chb.2014.03.065
Jatimoyo, D., Rohman, F., & Djazuli, A. (2021). The effect of perceived ease of use on continuance intention through perceived usefulness and trust: A study on Klikindomaret service users in Malang City. International Journal of Research in Business and Social Science (2147-4478), 10(4), 430-437.https://doi.org/10.20525/ijrbs.v10i4.1223
Jiang, L., & Rosenbloom, B. (2005). Customer intention to return online: Price perception, attribute-level performance, and satisfaction unfolding over time. European Journal of Marketing, 39(1/2), 150-174. https://doi.org/10.1108/03090560510572061
Jin, L. Y., & Osman, A. (2014). Key drivers of purchase intention among undergraduate students a perspective of online shopping. International Journal of Economics, Commerce and Management, 2(11), 1-11.
Kang, M. J., & Hwang, Y. C. (2022). Exploring the factors affecting the continued usage intention of IoT-Based healthcare wearable devices using the TAM model. Sustainability, 14(19), 1-25. https://doi.org/10.3390/su141912492
Kaswengi, J., & Lambey-Checchin, C. (2020). How logistics service quality and product quality matter in the retailer-customer relationship of food drive-throughs: The role of perceived convenience. International Journal of Physical Distribution & Logistics Management, 50(5), 535-555.https://doi.org/10.1108/IJPDLM-01-2019-0036
Kline, R. B. (2005). Principles and practice of structural equation modeling (2nd ed.). Guilford Press.
LaTour, S. A., & Peat, N. C. (1980). The role of situationally-produced expectations, others' experiences, and prior experience in determining consumer satisfaction. Advances in Consumer Research, 7(1), 588-592.
Lee, C., & Wan, G. (2010). Including subjective norm and technology trust in the technology acceptance model: A case of e-ticketing in China. ACM SIGMIS Database: The DATABASE for Advances in Information Systems, 41(4), 40-51.https://doi.org/10.1145/1899639.1899642
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.https://doi.org/10.1016/j.elerap.2008.11.006
Liébana-Cabanillas, F., Singh, N., Kalinic, Z., & Carvajal-Trujillo, E. (2021). Examining the determinants of continuance intention to use and the moderating effect of the gender and age of users of NFC mobile payments: A multi-analytical approach. Information Technology and Management, 22, 133-161.https://doi.org/10.1007/s10799-021-00328-6
Lin, Y. (2023). Urban transportation evolution and its impact on daily life. Transportation Research Journal, 20(1), 45-58.
Martono, S., Nurkhin, A., Mukhibad, H., Anisykurlillah, I., & Wolor, C. W. (2020). Understanding the employee's intention to use information system: Technology acceptance model and information system success model Approach. The Journal of Asian Finance, Economics and Business, 7(10), 1007-1013.https://doi.org/10.13106/jafeb.2020.vol7.no10.1007
Mohammadi, H. (2015). Investigating users’ perspectives on e-learning: An integration of TAM and IS success model. Computers in Human Behavior, 45, 359-374. https://doi.org/10.1016/j.chb.2014.07.044
Muqtadiroh, F. A., Herdiyanti, A., Wicaksono, I., & Usagawa, T. (2019). Analysis of factors affecting continuance intention of e-learning adoption in lecturers’ perspectives. IOP Conference Series: Materials Science and Engineering, 588, 1-9.https://doi.org/10.1088/1757-899X/588/1/012022
Myung, J., & Kim, B. (2022). The effects of service quality of medical information O2O platform on continuous use intention: Case of South Korea. Information, 13(10), 1-17. https://doi.org/10.3390/info13100486
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). McGraw-Hill.
Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction. Journal of Marketing Research, 17(4), 460-469. https://doi.org/10.2307/3150499
Olivia, M., & Marchyta, N. K. (2022). The influence of perceived ease of use and perceived usefulness on E-wallet continuance intention: Intervening role of customer satisfaction. Jurnal Teknik Industri, 24(1), 13-22.https://doi.org/10.9744/jti.24.1.13-22
Osatuyi, B., & Turel, O. (2019). Social motivation for the use of social technologies: An empirical examination of social commerce site users. Internet Research, 29(1), 24-45.
Ouyang, Y., Tang, C., Rong, W., Zhang, L., Yin, C., & Xiong, Z. (2017). Task-technology fit aware expectation-confirmation model towards understanding of MOOCs continued usage. In T. Bui (Ed.), Proceedings of the 50th Hawaii International Conference on System Sciences (pp. 174-183). University of Hawaii.https://doi.org/10.24251/HICSS.2017.020
Parasuraman, A., Zeithaml, V. A., & Berry, L. L. (1988). SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. Journal of Retailing, 64(1), 12-40.
Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), 101-134.https://doi.org/10.1080/10864415.2003.11044275
Petter, S., DeLone, W., & McLean, E. R. (2008). Measuring information systems success: Models, dimensions, measures, and interrelationships. European Journal of Information Systems, 17(3), 236-263.https://doi.org/10.1057/ejis.2008.15
Prasetyo, Y. T., Ong, A. K. S., Concepcion, G. K. F., Navata, F. M. B., Robles, R. A. V., TomaGos, I. J. T., Young, M. N., Diaz, J. F. T., Nadlifatin, R., & Redi, A. A. N. P. (2021) . Determining factors affecting acceptance of e-learning platforms during the COVID-19 pandemic: Integrating extended technology acceptance model and DeLone & McLean IS success model. Sustainability, 13(15), 1-16.https://doi.org/10.3390/su13158365
Rafique, H., Almagrabi, A. O., Shamim, A., Anwar, F., & Bashir, A. K. (2020). Investigating the acceptance of mobile library Applications with an extended technology acceptance model (TAM). Computers & Education, 145, 1-13.https://doi.org/10.1016/j.compedu.2019.103732
Reynaldo, R., Suprapto, W., & Jani, Y. (2020). Service convenience and service quality to customer satisfaction among the shipping expeditions. SHS Web of Conferences, 76, 1-7.https://doi.org/10.1051/shsconf/20207601043
Saprikis, V., & Avlogiaris, G. (2021). Factors that determine the adoption intention of direct mobile purchases through social media Apps. Information, 12(11), 449-470. https://doi.org/10.3390/info12110449
Scherer, R., Siddiq, F., & Tondeur, J. (2020). All the same or different? Revisiting measures of teachers' technology acceptance. Computers & Education, 143, 1-17.https://doi.org/10.1016/j.compedu.2019.103656
Siegfried, N., Winkler, N., & Benlian, A. (2020). Do bad experiences loom larger than Good ones? The role of prior purchase experiences on the effectiveness of IS certifications. Journal of Decision Systems, 29(2), 79-101.https://doi.org/10.1080/12460125.2020.1766235
Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. In S. Leinhardt (Ed.), Sociological Methodology (pp. 290-312). Jossey-Bass.https://doi.org/10.2307/270723
Sobel, M. E. (1986). Some new results on indirect effects and their standard errors in covariance structure models. In N. Tuma (Ed.), Sociological methodology (pp. 159-186). American Sociological Association.https://doi.org/10.2307/270922
Susanto, A., Chang, Y., & Ha, Y. (2016). Determinants of continuance intention to use the smartphone banking services: An extension to the expectation-confirmation model. Industrial Management & Data Systems, 116(3), 508-525
Taylor, S., & Todd, P. (1995). Assessing IT usage: The role of prior experience. MIS Quarterly, 19(4), 561-570.https://doi.org/10.2307/249633
Taylor, S., Smith, A., & Johnson, R. (2011). The early development of mobile applications. Journal of Mobile Technology, 6(2), 123-134.
Tseng, C. H., Hsu, C. H., Liu, J. W., & Wang, C. T. (2022). The impact of online teaching in behavior intention for college students in Taiwan. Frontiers in Psychology, 13, 1-12.https://doi.org/10.3389/fpsyg.2022.911262
Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: Development and test. Decision Sciences, 27(3), 451-481.https://doi.org/10.1111/j.1540-5915.1996.tb01822.x
Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS Quarterly, 36(1), 157-178.https://doi.org/10.2307/41410412
Wang, R. Y., & Strong, D. M. (1996). Beyond accuracy: What data quality means to data consumers. Journal of Management Information.Systems,12(4), 5-33.https://doi.org/10.1080/07421222.1996.11518099
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, 529-557.https://doi.org/10.1111/j.1365-2575.2007.00268.x
Wangpipatwong, S., Chutimaskul, W., & Papasratorn, B. (2008). Understanding citizen's continuance intention to use e Government website: A composite view of technology acceptance model and computer self-efficacy. Electronic Journal of E-Government, 6(1), 55-64.
Xu, F., Huang, S. S., & Li, S. (2019). Time, money, or convenience: What determines Chinese consumers’ continuance usage intention and behavior of using tourism mobile Apps? International Journal of Culture, Tourism and Hospitality Research, 13(3), 288-302.https://doi.org/10.1108/IJCTHR-04-2018-0052
Zhao, Y., Wang, H., Guo, Z., Huang, M., Pan, Y., & Guo, Y. (2022) . Online reservation intention of tourist attractions in the COVID-19 context: An extended technology acceptance model. Sustainability, 14(16), 1-17.https://doi.org/10.3390/su141610395
Zhu, Y., Wei, Y., Zhou, Z., & Jiang, H. (2022). Consumers’ continuous use intention of O2O E-commerce platform on community: A value Co-creation perspective. Sustainability, 14(3), 1-12.https://doi.org/0.3390/SU14031666