因今日資訊科技的進步以及手機持有的普及化，行動商務已成為電子商務的延伸。而行動付款已成為行動商務的主要應用之一。在行動付款流程之中，消費者可藉由更快速、更便利的方式經由行動裝置完成付款動作，而商家亦能經由此付款機制完成請款的動作。因此，本研究之主要目的在探討一般消費者對於行動付款之認知及使用意願之影響因素，以科技任務配適度與延伸性科技接受模型為主要理論架構，作為探討付款任務、行動科技特性、任務-科技配適度、知覺可用性、相容性、知覺風險對消費者的行動付款使用意願之影響分析，總共回收有效問卷為297份。分析結果如下： (1)付款任務與行動科技特性有顯著的配適度，表示消費者認為行動科技能夠有效支援付款任務的達成。(2)知覺可用性和相容性皆會對採用態度產生正向的影響，其中相容性的影響程度較高，接下來為知覺可用性。(3)消費者特性之人口統計變數中，不同年齡對知覺風險、使用意願無顯著差異。(4)知覺風險對知覺可用性、使用意願並無直接的顯著效果，意即使用行動付款的考慮過程中並不會受到知覺風險而影響。由此可以發現，消費者認為目前的行動科技足以達成行動付款的任務，對行動付款的風險亦不顯著，證明現今消費者對於行動科技的瞭解程度是高的，即行動付款在台灣確是存在廣大的潛在使用者。雖然目前行動付款在台灣地區並未推出普及的服務，但根據過去研究與此研究之結果可得知，行動付款領域是未來電信、零售、金融等業者可以密切合作並考慮進入的市場。

Due to the advances in information technology and the high ownership of mobile phones today, mobile commerce has become an extension of e-commerce. Mobile payment, as one of the main mobile commercial applications, is also becoming a popular research topic. Using the process of mobile payment, consumers can pay by mobile device faster and more conveniently. The stores involved can also complete transactions using mobile technology. This study focuses on exploring the process of consumer behavioral intentions to use mobile payment by using task-technology fit (TTF) and the technology acceptance model (TAM) and considers other conditions that may impact consumer behavior, adding the diffusion of innovations theory (IDT) theory and perceived risk to complete the structure of this study. This study adopted 297 valid samples for analysis and assessed subject’s behavioral intention to use mobile payment under the effect of risks and compatibility. Shown as follows: (1) Consumers view payment tasks and the mobile technology characteristics as fit to complete mobile payment. (2) Both perceived usability and compatibility have a positive impact on behavioral intention to use mobile payment. (3) Perceived risks have little impact on perceived usability and behavioral intention; that is, perceived risks will not influence consumers’ evaluation processes with regard to using mobile payment. The development of mobile payment is still in the beginning stage. A successful mobile payment system has to be built on compact cooperation between telecommunication industries, banks, and retailers. New mobile payment solutions should be seamlessly integrated into consumer purchasing processes without requiring extraneous steps, equipment and training. The mobile payment experience should also be fun and should also help enhance the consumer’s lifestyle image.

BIBLIOGRAPHY
Aaker, D.A., Kumar, V., & Day, G.S, (2001). Marketing Research, 7th Ed., John Wiley and Sons, New York
Ahuja, M., & Carley, K., (1999). Network structure in virtual organizations, Organization Science, 10(6), 741-757.
Amberg, M., Fischer, S., & Schröder, M (2005). An evaluation framework for the acceptance of web-based aptitude tests. The Electronic Journal of Information Systems Evaluation, 8(3), 151-158
Ammenwerth E., Buchauer A., Bludau B., & Haux R., (2000). Mobile information and communication tools in the hospital, International Journal of Medical Informatics, 57(1), 21-40.
Anderson, J. C., & Gerbing, D. W. (1988). An updated paradigm for scale development incorporating unidimensionality and its assessment. Journal of Marketing Research, 25(2), 186-192.
Andriew S. L., (2008). Inter-consortia battles in mobile payments standardization, Electronic Commerce Research and Applications, 7, 202–213.
Au, Y.A. & Kauffman, R.J., (2008). The economics of mobile payments: Understanding stakeholder issues for an emerging financial technology application, Electronic Commerce Research and Applications, 7(2), 141–164.
Bagozzi, R.P., (1982). A field investigation of causal relations among cognitions, affect, intentions, and behavior, Journal of Marketing Research, 19(11), 562-584.
Bagozzi, R.P., & Yi, Y., (1988). On the evaluation of structural equation models, Journal of the Academy of Marketing Science, 16(1), 74-94.
Barki, H. & Pinsonneault, A., (2005). A model of organizational integration, implementation effort, and performance, Organization Science, 16(2), 165-179.
Bauer, A., (1976). Konsumentenentscheidungen als Risikoverhalten, Marketing-Soziologie, Karl-Gustav Specht and Günther Wiswede (eds.), Duncker Humblot, Berlin, 207-217.
Bauer, H., Barnes, S., Reichardt, T., & Neumann, M., (2005). Driving consumer acceptance of mobile marketing: a theoretical framework and empirical study, Journal of Electronic Commerce and Research, 6(3), 181-192.
Bauer, R., (1967). Consumer behavior as risk taking. In: Cox, D. (Ed.), Risk Taking and Information Handling in Consumer Behavior. Harvard University Press, Cambridge, MA.
Bell, S. J., Seigyoung, A., & Karen, S. (2005). Custome relationship dynamics: Service quality and customer loyalty in the context of varying levels of customer expertise and switching costs. Journal of the Academy of Marketing Science, 33 (2), 169-183.
Buhan, D., Cheong, Y.C., & Tan, C.-L., (2002). Payments in Mobile Commerce, Telecom Media Networks, Paris.
Burnham. T.A., Frels, J.K., & Mahajan, V., (2003). Consumer switching costs: a typology, antecedents, and consequences, Journal if the Academy of Marketing Science, 31(2), 109-126
Carlsson, C., Walden, P., Bouwman, H., (2006). Adoption of 3G+ services in Finland. International Journal of Mobile Communications, 4 (4), 369–385.
Casaló, L., Flavián, C., & Guinalíu, M., (2008). The role of perceived usability, reputation, satisfaction and consumer familiarity on the website loyalty formation process, Computers in Human Behavior, 24(2), 325–345
Chen, L., Gillenson, M.L., & Sherrell, D.L., (2002). Enticing online consumers: an extended technology acceptance perspective, Information and Management, 39(8), 705–719.
Chen, L.D., (2008). A model of consumer acceptance of mobile payment, International Journal of Mobile Communications, 6 (1), 32–52.
Cho V., (2006). A study of the roles of trusts and risks in information-oriented online legal services using an integrated model, Information and Management, 43(4), 502–520.
Clark, L., (2005). Shopping without cash: the emergence of the e-purse, Economic Perspectives , Fourth Quarter, 34–51
Clarke, I., (2001). Emerging value propositions for M-commerce, Journal of Business Strategies, 18 (2), 133- 149.
Constantiou, I.D., Damsgaard, J., Knutsen, L., (2006). Exploring perceptions & use of mobile services: user differences in an advancing market. International Journal of Mobile Communications, 4 (3), 231–247.
Cronbach, L., (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334.
Crowston, K., (2003). A taxonomy of organizational dependencies and coordination mechanisms. T.W. Malone, K. Crowston, and G.A. Herman, eds. Organizing Business Knowledge, 85-108.
Daft, R.L., & Macintosh, N.B., (1981). A tentative exploration into the amount and equivocality of information processing in organizational work-units, Administration Science Quarterly, 26(2) 207-224.
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, 7,165–181.
Dam, R., (2005). Mobile payments: Cash, credit or phone? Total Telecom Magazine, May 1, 42–43.
Davis, F.D., (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13 (3), 319–339.
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
de Ruyter, K., Wetzels, M. & Bloemer, J. (1998). On the relationships between perceived service quality, service loyalty and switching costs, International Journal of Service Industry Management, 9(5), 436-453.
Dewan, S.G. & Chen, L.D., (2005). Mobile payment adoption in the USA: a cross-industry, cross-platform solution. Journal of Information Privacy and Security, 1 (2), 4–28.
Dishaw, M.T. & Strong, D.M., (1999). Extending the technology acceptance model with task-technology fit constructs, Information and Management, 36 (1), 9-21.
Dowling, G. & Staelin, R., (1994). A model of perceived risk and intended risk-handling activity. Journal of Consumer Research, 21(1), 119-134.
Dunn, E. & Company, (2007). 2007 Mobile Financial Services Study. Edgar, Dunn and Company in cooperation with Mobile Payments World.
Featherman, M.S. & Pavlou, P.A., (2003). Predicting e-services adoption: a perceived risk facets perspective, International Journal of Human-Computer Studies, 59(4), 451-474.
Flavián C., Guinalíu M., Gurrea R., (2006). The role played by perceived usability, satisfaction and consumer trust on website loyalty, Information and Management, 43(1), 1-14.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18 (1), 39-50.
Fry, L.W., & Slocum, J.W., (1984). Technology, structure, and workgroup effectiveness: A test of a contingency model, Academy of Management Journal, 27(2), 221-246.
Gebauer J, Ginsburg M., (2009). Exploring the black box of task-technology fit. Communication of the ACM, 52(1), 130-135.
Gebauer J., Shaw, M.J., (2002). A Theory of Task-Technology Fit for Mobile Applications to Support Organizational Processes, University of Illinois at Urbana-Champaign, College of Business Working Paper, 02-1121.
Gebauer J., Tang Y., & Baimai C., (2008). User requirements of mobile technology: results from a content analysis of user reviews, Information Systems and e-Business Management, 6(4), 361-384.
Gebauer, J. & Shaw, M. J., (2004). Success factors and impacts of mobile business applications: results from a mobile e-procurement study, International Journal of Electronic Commerce, 8 (3), 19-41.
Gebauer, J. & Tang, Y., (2008). Applying the theory of task-technology fit to mobile technology: the role of user mobility, International Journal of Mobile Communications, 6(3), 321–344.
Gebauer, J., Shaw, M.J. & Gribbins, M., (2006). Task-technology fit for mobile information systems, University of Illinois at Urbana-Champaign, College of Business Working Paper, 06-0107.
Goodhue, D.L. & Thompson, R.L., (1995). Task-technology fit and individual performance, MIS Quarterly, 19 (2), 213-236.
Goodhue, D.L., (1995). Understanding user evaluations of information systems, Management Science, 41 (12), 1827-1844.
Goodhue, D.L., (1998). Development and measurement validity of a task–technology fit instrument for user evaluations of information systems, Decision Sciences, 29 (1), 105– 137.
Grewal, D., Gotlieb, J., Marmorstein, H., (1994). The moderating effects of message framing and source credibility on the price-perceived risk relationship. Journal of Consumer Research, 21, 145–153.
Gummesson, E., (1995). Relationship marketing: its role in the service economy. In W. Glynn and J.G. Barnes (eds), Understanding Services Management, Chichester, UK: Wiley, 244-268.
Hair, J, F., William, C. B., Barry, J. B., Anderson, R. E., & Tatham, R. L. (2006). Multivariate Data Analysis (6 ed.). Upper Saddle River, New Jersey: Pearson Education.
Hair, J.F., Anderson, R.E., Tatham, R.L., & Black, W.C., (1998). Multivariate Data Analysis (5ed.). Upper Seddle River, New Jersey, USA: Prentice-Hall International, Inc.
Hayashi, F. & Klee, E., (2003). Technology adoption and consumer payments: evidence from survey data, Review of Network Economics, 2 (2), 175–190.
Hyytinen, A. & Takalo, T., (2004). Preventing systemic crises through bank transparency, Economic Notes, 33 (2), 257–273.
Jarvenpaa, S.L., Lang, K.R., Takeda, Y., & Tuunainen, V.K., (2003). Mobile commerce at crossroads. Communications of the ACM, 46(12), 41-44.
Junglas, I.A., Watson, R.T., (2003). U-commerce: a conceptual extension of e-commerce and m-commerce, Proceedings of the Twenty-Fourth International Conference on Information Systems (ICIS 2003), Seattle, Washington, 667-677.
Karimi, J., Somers, T.M., & Gupta Y.P., (2004). Impact of environmental uncertainty and task characteristics on user satisfaction with data, Information Systems Research, 15(2), 175-193.
Klee, E., (2006). Families’ use of payment instruments during a decade of change in the US payment system, Working Paper, Board of Governors of the Federal Reserve System, Washington, DC.
Kreps, M., (1990). A Course in Microeconomic Theory, Princeton University Press, Princeton, NJ.
Kreyer, N., Pousttchi, K., Turowski, K., (2003). Mobile payment procedures. e-Service Journal, 2 (3), 7–22.
Kruppa, S., (2001). Mobile Payment. Beyond the M-Commerce Hype, Stuttgart.
Lee, C.C., Cheng, H.K., Cheng, H.H., (2007). An empirical study of mobile commerce in insurance industry: task technology fit and individual differences, Decision Support Systems, 43(1), 95-110.
Lee, K.C., Lee, S., & Kim, J.S., (2005). Analysis of mobile commerce performance by using the task-technology fit, Mobile Information Systems, 158 ,135-153.
Liang, T.P., & Wei, C.P., (2004). Introduction to the special issue: mobile commerce applications, International Journal of Electronic Commerce, 8(3), 7-17.
Lim, K. & Benbasat, I., (2000). The effect of multimedia on perceived equivocality and perceived usefulness of information systems, MIS Quarterly, 24 (3), 449-471.
Lin H., Choong Y., Salvendy G., (1997). A proposed index of usability: a method for comparing the relative usability of different software systems, Behaviour and Information Technology, 16(4–5), 267–278.
Majchrzak, A., Malhotra, A., & John, R., (2005). Perceived individual collaboration know-how development through information technology-enabled contextualization: evidence from distributed teams, Information Systems Research, 16(1), 9-27.
Mallat, N., (2007). Exploring consumer adoption of mobile payments - A qualitative study, Journal of Strategic Information Systems, 16(4), 413-432,
Mallat, N., Rossi, M., Tuunainen, V.K., (2004). Mobile banking services. Communications of the ACM, 47 (5), 42–46.
Malone, T.W., & Crowston, K., (1994). The interdisciplinary study of coordination, ACM Computing Surveys, 26(1), 87-119.
McKitterick, D. & Dowling, J., (2003). State of the art review of mobile payment technology, Technical Report, TCD-CS-2003-24.
Menke, L. & de Lussanet, M., (2006). SMS-based mobile payment: popular with the young. Forrester Research.
Mester, L.J., (2003). Changes in the use of electronic means of payment: 1995–2001, Federal Reserve Bank of Philadelphia Business Review, v3Q, 18–20.
Mitchell, V.W., (1992). Understanding consumers’ behavior: can perceived risk theory help? Management Decision, 30(2), 26–31.
Mitchell, V.W., (1999). Consumer perceived risk: conceptualizations and models", Journal of Marketing, 33(1), 163-196.
Miyazaki, A.D. & Fernandez, A., (2001). Consumer perceptions of privacy and security risks for online shopping, Journal of Consumer Affairs, 35(1), 27-44.
Moore, G.C. & Benbasat I., (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation, Information Systems Research, 2(3), 193-222.
Nielsen, J., (2005). Usability 101. <http://www.useit.com/alertbox/20030825.html>.
Nunnally, J.C., (1978). Psychometric theory (2ed), New York: McGraw-Hill
Nysveen, H., Pedersen, P. E., Thorbjørnsen, H., (2005). Intentions to use mobile services: antecedents and cross-service comparisons, Journal of the Academy of Marketing Science, 33 (3), 330-346.
Ondrus, J. & Pigneur, Y., (2006). Towards a holistic analysis of mobile payments: a multiple perspectives approach. Electronic Commerce Research and Applications, 5 (3), 246–257.
Ondrus, J. & Pigneur, Y., (2007). Cross-industry preferences for development of mobile payments in Switzerland. Electronic Markets, 17 (2), 142–152.
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.
Perrow, C., (1967). A Framework for the comparative analysis of organizations, American Sociological Review, 32(2), 194-208.
Pousttchi K., (2008). A modeling approach and reference models for the analysis of mobile payment use cases, Electronic Commerce Research and Applications,7 , 182–201.
Ramaseshan, B., & Tsao, H.Y. (2007). Moderating effects of the brand concept on the relationship between brand personality and perceived quality. Journal of Brand Management, 14(6), 458-466.
Robben, M., (2001). ePayment: Old Brooms Still Sweep Best, Electronic Commerce Infos Net (ECIN), Dortmund.
Roca, J.C., Chiu, C.M., Martínez, F.J., (2006). Understanding e-learning continuance intention: An extension of the technology acceptance model, International Journal of Human-Computer Studies, 64(8), 683-696.
Rochet, J.C. & Tirole, J., (2003). Platform competition in two-sided markets, Journal of the European Economic Association, 1 (4), 990– 1029.
Rogers, E.M., (1995). The Diffusion of Innovations, 4th ed. New York: Free Press.
Roy M., Dewit O., Aubert B., (2001). The impact of interface usability on trust in web retailers, Internet Research: Electronic Networking Applications and Policy, 11(5), 388–398.
Siau, K., Lim, E.P., & Shen, Z., (2001). Mobile Commerce: Promises, Challenges and Research Agenda, Journal of Database Management, 12(3), 4-13.
Simon, S.M., (1994). Customers’ risk perceptions of electronic payment systems, International Journal of Bank Marketing, 12(8), 26-39.
Smith, H.J., Milberg, S.J. & Burke, S.J., (1996). Information privacy: measuring individuals’ concerns about organizational practices, MIS Quarterly, 20(2), 167–196.
Stavins, J., (2001). Effect of consumer characteristics on the use of payment instruments, New England Economic Review, Q3, 19–31.
Straub, D.W., (1989). Validating instruments in MIS research. MIS Quarterly, 13(2), 147-170.
Suh, B. & Han, I., (2003). The impact of customer trust and perception of security control on the acceptance of electronic commerce, Informational Journal of Electronic Commerce, 7(3), 135–161.
Tacchi, S., (2008). Mobile payments challenges and opportunities in retail banking, Mobile payments challenges in retail banking, 2 (2), 159-166.
Taga, K., & Karlsson, J., (2005). Little Global M-Payment Update, February 6, 2006, from http://www.adl.com/industries/time/order_mpayments_m_i.php.
Thompson, J.D., (1967). Organizations in Action. McGraw-Hill, New York.
Tornatzky, L. G. & Klein, K. J., (1982). Innovation characteristics and innovation adoption -implementation: a meta-analysis of findings, IEEE Trans. Engineering Management, 29(1), 28-43.
Wageman, R. & Gordon, F., (2005). As the twig is bent: how group values shape emergent task interdependence in groups, Organization Science, 16(6), 687-700.
Van de Ven, A.H., & Ferry, D.L., (1980). Measuring and Assessing Organizations. Series on Organizational Change, Wiley, New York.
Weise, G. (1975). Psychologische Leistungstests, Hogrefe, Göttingen, Germany
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.
Venkatesh, V., Ramesh, V., & Massey, A.P., (2003). Understanding Usability in Mobile Commerce. Communications of the ACM, 46(12), 53-56.
Vijayasarathy, L., (2004). Predicting consumer intentions to use on-line shopping: the case for an augmented technology acceptance model, Information and Management, 41(6), 747-762.
Wu, J. H., & Wang, S.C., (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information & Management, 42(5), 719–729.
Xie, J. & Shugan, S.M., (2001). Electronic tickets, smart cards, and online prepayments: when and how to advance sell, Marketing Science, 20 (3), 219-243.
Yuan, Y., & Zhang, J., (2003). Towards an appropriate business model for m-commerce, International Journal of Mobile Communications, 1(1/2), 35-56.
Zigurs, I. & Buckland, B.K., (1998). A theory of task/technology fit and group support systems effectiveness, MIS Quarterly, 22 (3), 313-334.
Zigurs, I. & Khazanchi, D., (2008). From profiles to patterns: A new view of task-technology fit, Information Systems Management, 25(1), 8-13.
陳孟敏, (2007). 行動電話用戶數, 工業技術研究院,　2006 產業經濟與趨勢研究中心, http://www.iek.itri.org.tw/internet/domain/Domain_DiagramDetail.aspx?domain_id=-1andnotesid=D6FA5AAFCDFDB375482573B00011E3AFandpage=4andtype=table