本研究是以探討影響行動購物APP使用者透過智慧型手機持續使用行動購物APP的因素來當作研究的主題，並且本研究是使用「資訊系統接受後持續採用模式」當作研究模型的主要架構，然後整合「態度」、「習慣」和「愉悅感」這三個變數，來加以探討影響行動購物APP使用者透過智慧型手機持續使用行動購物APP的因素，因此本研究的模型架構總共有七個研究變數和十二個研究假說。
本研究是以問卷調查的方式進行研究，問卷的問項內容是根據相關的參考文獻的問卷的問項內容和研究變數的操作型定義來進行設計，並且設定研究對象和調查方式。研究對象主要是針對透過智慧型手機持續使用行動購物APP的使用者，調查方式是採用網路問卷的方式進行調查。最後總共回收了307份的問卷，而在刪除掉不要的問卷之後，總共有249份的有效問卷。
本研究是使用統計軟體對有效問卷的測量結果進行分析，分析後的研究結果顯示「確認」會正向影響「知覺有用性」和「滿意度」；「知覺有用性」會正向影響「滿意度」、「持續使用意圖」、「態度」和「習慣」；「滿意度」會正向影響「態度」和「持續使用意圖」；「愉悅感」會正向影響「習慣」和「持續使用意圖」；「態度」會正向影響「持續使用意圖」；以及「習慣」會正向影響「持續使用意圖」。

The subject of this study is to explore the factors which affects the continuous usage of mobile shopping APPs through the smartphones by end users. “A Post-Acceptance Model of IS Continuance” is adopted as a main framework of the research model which integrates the three variables of “Attitude”, “Habit”, and “Enjoyment”, and the research model structure of this study has a total of seven research variables and twelve research hypotheses.
This study is designed in the form of a questionnaire survey. The content of the questionnaire is designed according to the content of the questionnaire in the relevant references and the operational definition of the research variables, and the research object and the survey method are set. The object of this research is mainly for the users who use mobile shopping APPs(through smartphones) continuously ; the survey method is using the online questionnaires to conduct the surveys. In the end, a total of 307 questionnaires are recovered, and after deleting the invalid questionnaires, there are a total of 249 valid questionnaires.
This study uses the statistical software to analyze the measurement results of valid questionnaires, and the results of the analysis show that “Confirmation” positively influences “Perceived Usefulness” and “Satisfaction”; “Perceived Usefulness” positively influences “Satisfaction”, “Continuance Intention”, “Attitude”, and “Habit”; “Satisfaction” positively influences “Attitude” and “Continuance Intention”; “Enjoyment” positively influences “Habit” and “Continuance Intention”; “Attitude” positively influences “Continuance Intention”; and “Habit” positively influences “Continuance Intention”.

一、中文文獻
江義平、廖奕翔、吳佳惠（民105）。行動商務採用關鍵成功因素與其影響研究。電子商務研究，14，221-255。
林建廷、李元生（民101）。行動商務概論、實務與應用：無所不在的雲端運算、行動裝置、RFID與物聯網。臺北市：碁峰資訊股份有限公司。
范姜群暐（民101）。行動商務大未來。財金資訊季刊，72，2-6。
張春興（民101）。心理學概要（重修版）。臺北市：臺灣東華書局股份有限公司。
湯宗益、江啟惠（民101）。物流業使用行動商務接受度之研究。電子商務研究，10，269-296。

二、英文文獻
Aarts, H., & Dijksterhuis, A. (2000). Habits as knowledge structures: Automaticity in goal-directed behavior. Journal of personality and social psychology, 78(1), 53-63.
Aarts, H., Verplanken, B., & van Knippenberg, A. (1998). Predicting behavior from actions in the past: Repeated decision making or a matter of habit? Journal of Applied Social Psychology, 28, 1355-1374.
Abdel Hamid, J. (1987). Psychological studies of the Arab personality. Cairo, Egypt: World of Books.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179-211.
Ajzen, I. (2002). Residual effects of past on later behavior: Habituation and reasoned action perspectives. Personality and Social Psychology Review, 6(2), 107-122.
Albarracin, D., Zanna, M. P., Johnson, B. T., & Kumkale, G. T. (2005). Attitudes: Introduction and scope. In D. Albarracin, B. T. Johnson, & M. P. Zanna (Eds.), The handbook of attitudes (pp. 3-19). Mahwah, NJ: Lawrence Erlbaum.
Allport, G. W. (1935). Attitudes. In C. Murchison (Ed.), A handbook of social psychology (pp. 798-844). Worcester, MA: Clark University Press.
Al-maghrabi, T., Dennis, C., & Halliday, S. V. (2011). Antecedents of continuance intention towards e-shopping: The case of Saudi Arabia. Journal of Enterprise Information Management, 24(1), 85-111.
Anderson, E. W., & Sullivan, M. W. (1993). The antecedents and consequences of customer satisfaction for firms. Marketing science, 12(2), 125-143.
Babin, B. J., Darden, W. R., & Griffin, M. (1994). Work and/or fun: Measuring hedonic and utilitarian shopping value. Journal of consumer research, 20(4), 644-656.
Balasubramanian, S., Peterson, R. A., & Jarvenpaa, S. L. (2002). Exploring the implications of m-commerce for markets and marketing. Journal of the Academy of Marketing Science, 30(4), 348-361.
Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ: Prentice Hall.
Barnes, S. J. (2011). Understanding use continuance in virtual worlds: Empirical test of a research model. Information & Management, 48(8), 313-319.
Bhattacherjee, A. (2001a). An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32(2), 201-214.
Bhattacherjee, A. (2001b). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351-370.
Bolton, R. N., & Drew, J. H. (1991). A longitudinal analysis of the impact of service changes on customer attitudes. Journal of Marketing, 55(1), 1-9.
Bruner, G. C., & Kumar, A. (2005). Explaining consumer acceptance of handheld Internet devices. Journal of Business Research, 58(5), 553-558.
Campbell, J. Y., & Cochrane, J. H. (1999). By force of habit: A consumption-based explanation of aggregate stock market behavior. Journal of Political Economy, 107(2), 205-251.
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. In G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295-336). London, England: Lawrence Erlbaum Associates.
Chiu, C. M., Chang, C. C., Cheng, H. L., & Fang, Y. H. (2009). Determinants of customer repurchase intention in online shopping. Online Information Review, 33(4), 761-784.
Chopdar, P. K., & Sivakumar, V. J. (2019). Understanding continuance usage of mobile shopping applications in India: The role of espoused cultural values and perceived risk. Behaviour and Information Technology, 38(1), 42-64.
Dabholkar, P. A., Shepherd, C. D., & Thorpe, D. I. (2000). A comprehensive framework for service quality: An investigation of critical conceptual and measurement issues through a longitudinal study. Journal of retailing, 76(2), 139-173.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management science, 35(8), 982-1003.
Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111-1132.
DeVellis, R. F. (1991). Scale Development: Theory and Applications (Applied Social Research Methods Series, Vol. 26). Newbury Park, CA: Sage Publications.
Fornell, C. & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50.
Grøtnes, E. (2009). Standardization as open innovation: Two cases from the mobile industry. Information Technology & People, 22(4), 367-381.
Hajli, N., Shanmugam, M., Powell, P., & Love, P. E. D. (2015). A study on the continuance participation in on-line communities with social commerce perspective. Technological Forecasting and Social Change, 96, 232-241.
Hsiao, C. H., Chang, J. J., & Tang, K. Y. (2016). Exploring the influential factors in continuance usage of mobile social Apps: Satisfaction, habit, and customer value perspectives. Telematics and Informatics, 33(2), 342-355.
Hsu, C. L., & Lin, J. C. C. (2015). What drives purchase intention for paid mobile apps? - An expectation confirmation model with perceived value. Electronic Commerce Research and Applications, 14(1), 46-57.
Hunt, H. K. (1977). CS/D-Overview and Future Research Directions. In H. K. Hunt (Ed.), Conceptualization and Measurement of Consumer Satisfaction and Dissatisfaction (pp. 455-488). Cambridge, MA: Marketing Science Institute.
Jamalian, E., & Foukerdi, R. (2018). A hybrid data mining method for customer churn prediction. Engineering, Technology & Applied Science Research, 8(3), 2991-2997.
Jasperson, J., Carter, P. E., & Zmud, R. W. (2005). A comprehensive conceptualization of post-adoptive behaviors associated with information technology enabled work systems. MIS Quarterly, 29(3), 525-557.
Kleijnen, M., de Ruyter, K., & Wetzels, M. (2007). An assessment of value creation in mobile service delivery and the moderating role of time consciousness. Journal of Retailing, 83(1), 33-46.
Ko, E., Kim, E. Y., & Lee, E. K. (2009). Modeling consumer adoption of mobile shopping for fashion products in Korea. Psychology and Marketing, 26(7), 669-687.
Kosiur, D. R. (1997). Understanding electronic commerce. Redmond, WA: Microsoft Press.
Krotov, V., Junglas, I., & Steel, D. (2015). The mobile agility framework: An exploratory study of mobile technology enhancing organizational agility. Journal of Theoretical and Applied Electronic Commerce Research, 10(3), 1-7.
Lankton, N. K., Wilson, E. V., & Mao, E. (2010). Antecedents and determinants of information technology habit. Information & Management, 47(5-6), 300-307.
Lee, M. C. (2010). Explaining and predicting users’ continuance intention toward e-learning: An extension of the expectation-confirmation model. Computers & Education, 54(2), 506-516.
Lee, Y., & Kwon, O. (2011). Intimacy, familiarity and continuance intention: An extended expectation-confirmation model in web-based services. Electronic Commerce Research and Applications, 10(3), 342-357.
Liao, C., Palvia, P., & Chen, J. L. (2009). Information technology adoption behavior life cycle: Toward a Technology Continuance Theory (TCT). International Journal of Information Management, 29(4), 309-320.
Liao, C., Palvia, P., & Lin, H. N. (2006). The roles of habit and web site quality in e- commerce. International Journal of Information Management, 26(6), 469-483
Limayem, M., & Cheung, C. M. K. (2008). Understanding information systems continuance: The case of internet-based learning technologies. Information and Management, 45(4), 227-232.
Limayem, M., & Hirt, S. G. (2003). Force of habit and information systems usage: Theory and initial validation. Journal of the Association for Information Systems, 4(1), 65-97.
Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How habit limits the predictive power of intention: The case of information systems continuance. MIS Quarterly, 31(4), 705-737.
Maity, M., & Dass, M. (2014). Consumer decision-making across modern and traditional channels: E-commerce, m-commerce, in-store. Decision Support Systems, 61, 34-46.
Mouakket, S. (2015). Factors influencing continuance intention to use social network sites: The Facebook case. Computers in Human Behavior, 53, 102-110.
Nunnally, J. C. (1978). Psychometric Theory. New York, NY: McGraw-Hill.
Oliver, R. L. (1980). A cognitive model of the antecedents and consequences of satisfaction decisions. Journal of Marketing Research, 17(4), 460-469.
Oliver, R. L. (1981). Measurement and evaluation of satisfaction processes in retail settings. Journal of Retailing, 57(3), 25-48.
Oliver, R. L. (1993). Cognitive, affective, and attribute bases of the satisfaction response. Journal of Consumer Research, 20(3), 418-430.
Ouellette, J. A., & Wood, W. (1998). Habit and intention in everyday life: The multiple processes by which past behavior predicts future behavior. Psychological Bulletin, 124(1), 54-74.
Oulasvirta, A., Rattenbury, T., Ma, L., & Raita, E. (2012). Habit make smartphone use more pervasive. Personal and Ubiquitous Computing, 16(1), 105-114.
Pantano, E. (2013). Ubiquitous retailing innovative scenario: From the fixed point of sale to the flexible ubiquitous store. Journal of Technology Management & Innovation, 8(2), 84-92.
Prahalad, C. K., & Krishnan, M. S. (2008). The new age of innovation: Driving cocreated value through global networks. New York, NY: McGraw-Hill.
Sarkar, S., & Khare, A. (2018). Influence of expectation confirmation, network externalities, and flow on use of mobile shopping apps. International Journal of Human-Computer Interaction, 35(16), 1449-1460.
Shankar, V., Kleijnen, M., Ramanathan, S., Rizley, H., Holland, S., & Morrissey, S. (2016). Mobile shopper marketing: Key issues, current insights, and future research avenues. Journal of Interactive Marketing, 34, 37-48.
Shen, G. C. C. (2015). Users’ adoption of mobile applications: Product type and message framing’s moderating effect. Journal of Business Research, 68(11), 2317-2321.
Stone, M., Woodcock, N., & Wilson, M. (1996). Managing the change from marketing planning to customer relationship management. Long Range Planning, 29(5), 657-683.
Taylor, D. G., & Levin, M. (2014). Predicting mobile app usage for purchasing and information-sharing. International Journal of Retail & Distribution Management, 42(8), 759-774.
Thong, J. Y. L., Hong, S. J., & Tam, K. Y. (2006). The effects of post-adoption beliefs on the expectation-confirmation model for information technology continuance. International Journal of Human Computer Studies, 64(9), 799-810.
Tsalgatidou, A., & Pitoura, E. (2001). Business models and transactions in mobile electronic commerce: Requirements and properties. Computer Network, 37(2), 221-236.
Tse, D. K., & Wilton, P. C. (1988). Models of consumer satisfaction formation: An extension. Journal of Marketing Research, 25(2), 204- 212.
Tung, T., Jai, T. M., & Davis Burns, L. (2014). Attributes of apparel tablet catalogs: Value proposition comparisons. Journal of Fashion Marketing and Management, 18(3), 321-337.
van der Heijden, H. (2004). User acceptance of hedonic information systems. MIS Quarterly, 28(4), 695-704.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478.
Verplanken, B., Aarts, H., van Knippenberg, A., & Moonen, A. (1998). Habit versus planned behaviour: A field experiment. British Journal of Social Psychology, 37, 111-128.
Wang, R. J. H., Malthouse, E. C., & Krishnamurthi, L. (2015). On the go: How mobile shopping affects customer purchase behavior. Journal of Retailing, 91(2), 217-234.
Yang, K. (2010). Determinants of US consumer mobile shopping services adoption: Implications for designing mobile shopping services. Journal of Consumer Marketing, 27(3), 262-270.
Yang, K., & Kim, H. Y. (2012). Mobile shopping motivation: An application of multiple discriminant analysis. International Journal of Retail & Distribution Management, 40(10), 778-789.
Yeh, Y. S., & Li, Y. M. (2009). Building trust in m-commerce: Contributions from quality and satisfaction. Online Information Review, 33(6), 1066-1086.

三、網站資料
Yahoo看見數位行銷力（2022）。市調解析- 2020至2021年台灣網路行為趨勢觀察與比較。取自https://promo.campaign.yahoo.com.tw/b2b/b2bmarketing/page.php?u=a17fbddc-d586-4d83-815a-21e071532895。
資策會產業情報研究所（2020）。【網購大調查系列一】行動下單急追PC呈五五波 行動商務正式成為主流。取自https://mic.iii.org.tw/news.aspx?id=555。
資策會產業情報研究所（2021）。【零售電商消費者調查系列一】6成網友愛用蝦皮24h、momo　行動App購物冠軍為蝦皮　10大網購數位科技 消費者最重視電子支付、跨平台比價。取自https://mic.iii.org.tw/news.aspx?id=621&List=1。