臺灣博碩士論文加值系統

本研究的目的在透過整合性科技接受模型 (UTAUT) 與科技接受模型 (TAM) 對行為意向和顧客滿意的影響，探索越南接受行動銀行的過程。本研究調查問卷的編制乃經由驗證性因素分析 (CFA) 評估，並採用結構方程模型 (SEM) 檢驗理論模型和假設，以了解變量之間的統計關聯性。研究結果發現顧客滿意和行為意圖直接影響到手機銀行採用。此外績效期望、預期努力和感知易用性被認為是顧客使用行動銀行的最重要的前置因素。研究樣本包括200份有效問卷來自越南的大學、跨國企業之管理、財務和資訊管理部門。此研究發現可以提供業者未來發展行動銀行策略之參考。

The aims of this research explore the process of adoption of mobile banking in Viet Nam through the effects of pre-establish frameworks of the Unified theory of acceptance and use of technology model (UTAUT) and Technology acceptance model (TAM) on main predictors of behavioral intention and user satisfaction. The research questionnaire has been developed by confirm factor analysis (CFA) to assess the instruments and adopted structural equation modeling (SEM) was employed to test the theoretical model and hypotheses to understand the statistical associations among the variables. The finding of the proposed model mentioned that “User satisfaction” and “Behavioral intention” directly influence mobile banking adoption. Furthermore, “Performance expectancy”, “Effort expectancy” and “Perceived ease of use” were found to be the most important antecedents of user intention towards adopting of mobile banking. The sample consisted of 200 valid questionnaires were grossed by the respondent from the department of Vietnamese university, international business administration, finance, and information management. The result can be of reference to practitioners in Vietnam to develop mobile banking strategies.

ABSTRACT i
摘要 ii
ACKNOWLEDGEMENT iii
TABLE OF CONTENTS iv
LIST OF TABLES vi
LIST OF FIGURES vii
1. INTRODUCTION 1
1.1 Research background 1
1.2 Research objective 8
1.3 Research motivation 9
1.4 Research structure 9
2. LITERATURE REVIEW 10
2.1 M-banking concept framework 10
2.2 Unified theory of acceptance and use of technology (UTAUT) 13
2.3 Technology acceptance model (TAM) 19
3. METHODOLOGY 23
3.1 The research model and method design 23
3.2 Research hypothesis 27
3.2.1 TAM model 27
3.2.2 UTAUT model 28
3.3 Research process 30
3.3.1 Question design 30
3.3.2 Pilot test 30
3.3.3 Questionnaire distribution 31
3.3.4 Data collection 31
3.4 Statistical analysis 33
3.4.1 Listing and labeling of factor 33
3.4.2 Factor analysis 35
4. RESULTS AND DISCUSSION 39
4.1 Descriptive 39
4.2 Factor loading and cronbach’s alpha 42
4.3 Exploratory factor analysis (EFA) 45
4.4 Confirmatory factor analysis (CFA) 47
4.4.1 Reliability 47
4.4.2 Mean and standard deviation (SD) 49
4.5 Structural equation modeling (SEM) 50
4.6 Discussion 55
4.6.1 TAM 55
4.6.2 UTAUT 56
4.7 Implication 57
4.7.1 Theoretical implication 57
4.7.2 Managerial implication 58
5. CONCLUSION, LIMITATION AND FUTURE RESERACH 60
REFERENCES 62
APPENDIX A 77
APPENDIX B 80
APPENDIX C 85

Abdul Hamid, M.R., Amin, Hanudin A., Lada, S., Ahmad, N., (2007). A comparative analysis of Internet banking in Malaysia and Thailand. Journal of Internet Business, 4, 1–19.
Abubakar, F.M., Ahmed, H.B., (2012). The moderating effect of technology awareness on the relationship between UTAUT constructs and behavioral intention to use technology: a conceptual paper. Australia Journal Business Management Research, 3(2), 14–23.
Abushanab, E., & Pearson, J. M. (2007). Internet banking in Jordan: the unified theory of acceptance and use of technology (UTAUT) perspective. Journal of Systems and Information Technology, 9(1), 78-97.
Afshan, S., & Sharif, A. (2016). Acceptance of mobile banking framework in Pakistan. Telematics and Informatics, 33(2), 370–387.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 211(50), 179–211.
Akturan, U., & Tezcan, N. (2012). Mobile banking adoption of the youth market:
Perceptions and intentions. Marketing Intelligence and Planning, 30(4), 4.
Alapetite, A., Andersen, H. B., & Hertzum, M. (2009). Acceptance of speech recognition by physicians: a survey of expectations, experiences, and social influence. International Journal of Human-computer Studies, 67(1), 36-49.
Al-Gahtani, S. S., Hubona, G. S., & Wang, J. (2007). Information technology (IT) in Saudi Arabia: culture and the acceptance and use of IT. Information and Management, 44(8), 681-691.
Alsabawy, A. Y., Cater-Steel, A., & Soar, J. (2013). IT infrastructure services as a requirement for e-learning system success. Computers & Education, 69, 431-451.
Al-Somali, S.A., Gholami, R., Clegg, B., (2009). An investigation into the acceptance of online banking in Saudi Arabia. Technovation, 29 (2), 130–141.
Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological bulletin, 103(3), 411.
Anderson, J., (2010). M-banking in developing markets: competitive and regulatory implications. Information, 12 (1), 18–25.
Anus, S., Qureshi, F.A., Malik, S., Abbasi, A., Chaudhry, A., Mirza, S.N., (2011). Trust and initial acceptance of mobile banking in Pakistan. International Journal of Scientific and Engineering Research, 2(8).
Arbuckle, J. L., & Wothke, W. (1999). AMOS 4.0 Users Guide. Chicago: Smallwaters Corporation. Barlett, CA and Ghoshal, S.(2000) Transnational Management: Text, Cases, and Readings in Cross-Border Management, 704-17.
Babbie, E. (1992). The Practice of Social Research. California: Wadsworth.
Baptista G. & T. Oliveira (2015). “Understanding mobile banking: the unified theory of acceptance and use of technology combined with cultural moderators”. Computers in Human Behavior, 50, 418-430.
Bentler, P. M. (1990). Comparative fit indexes in structural models. Psychological bulletin, 107(2), 238.
Bentler, P. M., & Mooijaart, A. B. (1989). Choice of the structural model via parsimony: a rationale based on precision. Psychological bulletin, 106(2), 315.
Bhatiasevi, V., (2015). An extended UTAUT model to explain the adoption of mobile banking. Infinite Development, 0266666915570764.
Bhattacherjee, A., 2001b. An empirical analysis of the antecedents of electronic commerce service continuance. Decision Support Systems, 32 (2), 201–214.
Bohrnstedt, G. W. (1970). Significant tests and goodness of fit in the analysis of covariance. Attitude Measurement, Chicago: Rand McNally.
Boor, P. V. D., Oliveira, P., & Veloso, F. (2014). Users as innovators in developing countries: The global sources of innovation and diffusion in mobile banking services. Research Policy, 43, 1594–1607.
Brown, T. A. (2006). Confirmatory factor analysis for applied research. New York, NY: Guilford.
Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. Sage focus editions, 154, 136-136.
Bruce, T., (2010). Exploratory and Confirmatory Factor Analysis: Understanding Concepts. American Psychological Association, United States of America.
Byrne, B. M. (2013). Structural equation modeling with Mplus: Basic concepts, applications, and programming. Routledge.
Calisir, F., Gumussoy, C. A., & Bayram, A. (2009). Predicting the behavioral intention to use ERP systems: An extension of the technology acceptance model. Management Research News, 32(7), 597–613.
Capgemini (2013) World retail banking report. European Financial Management and Marketing Association.
Carmines, E. Y. Z. RA (1988), Reliability and validity assessment, Series Quantitative Applications in the social Sciences.
Casey, T., & Wilson-Evered, E. (2012). Predicting uptake of technology innovations in online family dispute resolution serviced: an application and extension of the UTAUT. Computers in Human Behavior, 28(6), 2034-2045.
Chang, C.P. (2011). Characteristics of Taiwan's IT industry. Retrieved from: http://www. npf.org.tw/1/8825.
Chang, I. C., Hwang, H. G., Hung, W. F., & Li, Y. C. (2007). Physicians’ acceptance of pharmacokinetics-based clinical decision support systems. Expert Systems with Applications, 33(2), 296-303.
Chen, F. F., Sousa, K. H., & West, S. G. (2005). Teacher's corner: Testing measurement invariance of second-order factor models. Structural equation modeling, 12(3), 471-492.
Chew , A. A. (2006). The adoption of M-commerce in the United States. Honors thesis of California State University.
Chitungo, S. K., Munongo, S., (2013). Extending the technology acceptance model to mobile banking adoption in rural Zimbabwe. Journal of Business Administration and Education, 3(1), 51 – 79.
Chiu, C. M., & Wang, E. T. G. (2008). Understanding web-based learning continuance intention: the role of subjective task value. Information and Management, 45(3), 194-201.
Chung, Y., Song, T., & Park, J. (2012). Freeway booking policy: Public discourse and acceptability analysis. Transport Policy, 24, 223-231.
Chuttur, M., 2009. Overview of the technology acceptance model: origins. Development Future Direction Technology, 9, 23.
Citrix. (2013). Global survey shows that mobility is the priority for enterprises. Retrieved from: http://www.citrix.com.tw/news/845.
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: development of a measure and initial test. MIS Quarterly, 19(2), 189-211.
Craighead, C. W., Patterson, J. W., Roth, P. L., & Segars, A. H. (2006). Enabling the benefits of Supply Chain Management Systems: an empirical study of Electronic Data Interchange (EDI) in manufacturing. International Journal of Production Research, 44(1), 135-157.
Cruz, P., Neto, L.B.F., Muñoz-Gallego, P., Laukkanen, T., (2010). Mobile banking rollout in emerging markets: evidence from Brazil. International Journal of Bank Marketing, 28 (5), 342–371.
Curtis, L., Edwards, C., Fraser, K. L., Gudelsky, S., Holmquist, J., Thornton, K., (2010). Adoption of social media for public relations by nonprofit organizations. Public Relations Review, 36(1), 90-92.
Dabholkar, P. A., & Bagozzi, R. P. (2002). An attitudinal model of technology-based self-service: moderating effects of consumer traits and situational factors. Journal of the academy of marketing science, 30(3), 184-201.
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(1), 1111-1132.
Davis, F.D., (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.
Delbosc, A., & Currie, G. (2012). Choice and disadvantage in low-carb ownership households. Transport Policy, 23, 8-14.
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.
Devaraj, S., Fan, M., & Kohli, R., (2002). Antecedents of B2C channel satisfaction and preference: validating e-commerce metrics. Information Systems Research 13 (3), 316–333.
Docimini, G., & Palumbo, F. (2013). How to build an e-learning product: factors for student/customer satisfaction. Business Horizons, 56, 87–96.
Duyck, P., Pynoo, B., Devolder, P., Voet, T., Adang, L., & Ovaere, D. (2010). Monitoring the PACS implementation process in a large university hospital e discrepancies between radiologists and physicians. Journal of Digital Imaging, 23(1), 73-80.
Eckhardt, A., Laumer, S., & Weitzel, T. (2009). Who influences whom? Analyzing workplace referents’ social influence on its adoption and non-adoption. Journal of Information Technology, 24(1), 11-24.
Escobar-Rodríguez, T., & Carvajal-Trujillo, E. (2014). Online purchasing tickets for low-cost carriers: An application of the unified theory of acceptance and use of technology (UTAUT) model. Tourism Management, 43, 70-88.
Fishbein, M., & Ajzen, I., (1975). Belief, Attitudes, Intention and Behavior: An Introduction to Theory and Research. Addison-Wesley, Reading, MA.
Foon, Y. S., & Fah, B. C. Y. (2011). Internet banking adoption in Kuala Lumpur: an application of UTAUT model. International Journal of Business and Management, 6(4), 161.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 39-50.
Freeze, R. D., Alshare, K. A., Lane, P. L., & Wen, H. J. (2010) “IS success model in e-learning context based on students‟ perceptions.” Journal of Information Systems Education, 21(2), 173-184.
Gatignon, H., & Robertson, T. S. (1985). A propositional inventory for new diffusion research. Journal of Consumer Research, 11(4), 849-867.
Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS quarterly, 213-236.
Gu, J. C., Lee, S. C., & Suh, Y. H. (2009). Determinants of behavioral intention to mobile banking. Expert Systems with Applications, 36(9), 11605-11616.
Gupta, B., Dasgupta, S., & Gupta, A. (2008). Adoption of ICT in a government organization in a developing country: an empirical study. Journal of Strategic Information Systems, 17(2), 140-154.
Hair, J. F. Black, WC, Babin, BJ, & Anderson, RE (2010). Multivariate data analysis, 7.
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2006).Multivariate data analysis (Vol. 6). Upper Saddle River, NJ: Pearson Prentice Hall.
Halawi, L. A., McCarthy, R. V., & Aronson, J. E. (2008) “An empirical investigation of knowledge management system‟s success.” Journal of Computer Information Systems, 48(2), 121-135.
Hanafizadeh, P., Behboudi, M., Koshksaray, A.A., & Tabar, M.J.S., (2014). Mobile banking adoption by Iranian bank clients. Telematics Information, 31 (1), 62–78.
Hassanzadeh, A., Kanaani, F., & Elahi, S. (2012). A model for measuring e-learning systems success in universities. Expert Systems with Applications, 39, 10959–10966.
Hayashi, A., Chen, C., Ryan, T., & Wu, J., (2004). The role of social presence and the moderating role of computer self-efficacy in predicting the continuance usage of e-learning systems. Journal of Information Systems Education, 15 (2), 139–154.
Hinson, R.E., 2011. Banking the poor: the role of mobiles. Journal of Financial Services Marketing, 15 (4), 320–333.
Hsu, C. L., Wang, C. F., & Lin, J. C. C. (2011). Investigating customer adoption behaviors in mobile financial services. International Journal of Mobile Communications, 9(5), 477-494.
Hung, Y. H., Wang, Y. S., & Chou, S. C. T. (2007). User acceptance of e-government services. Kaohsiung: National Sun Yat-sen University.
Im, I., Hong, S., & Kang, M. S. (2011). An international comparison of technology adoption. Information & Management, 48(1), 1–8. http://dx.doi.org/10.1016/ j.im.2010.09.001.
Islam, A. K. M. (2014). Sources of satisfaction and dissatisfaction with a learning management system in the post-adoption stage: A critical incident technique approach. Computers in Human Behavior, 30, 249–261.
Islam, A. K. M. N. (2011). The determinants of the post-adoption satisfaction of educators with an e-learning system. Journal of Information Systems Education, 22(4), 319–332.
Islam, A.K.M.N., (2012). The role of perceived system quality as the educators’ motivation to continue e-learning system use. AIS Trans. Human–Computer Interaction, 4 (2), 25–44.
Juniper Research, (2013). Mobile banking handset & tablet market strategies, 2013–2017, Available at http://www.juniperresearch.com/reports/mobile_banking (accessed January 1, 2014).
Kazi, A.K., & Mannan, M.A., (2013). Factors Affecting Adoption of Mobile Banking in Pakistan: Empirical Evidence. Retrieved from: https://mpra.ub.unimuenchen.de/47922/1/MPRA_paper_47922.pdf.
Khalfan, A.M.S., Alrefaei, Y.S.Y., & Al-Hajery, M., (2006). Factors influencing the adoption of Internet banking in Oman: a descriptive case study analysis. International Journal of Financial Services Management, 1 (2), 155–172.
Kijsanayotin, B., Pannarunothai, S., & Speedie, S. M. (2009). Factors influencing health information technology adoption in Thailand’s community health centers: applying the UTAUT model. International Journal of Medical Informatics, 78(6), 404-416.
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, G., Shin, B., & Lee, H. G. (2009). Understanding dynamics between initial trust and usage intentions of mobile banking. Information Systems Journal, 19(3), 283–311. http://dx.doi.org/10.1111/j.1365-2575.2007.00269.x.
Kim, S. S., & Malhotra, N. K. (2005). “A Longitudinal Model of Continued IS Use: An Integrative View of Four Mechanisms Underlying Post-Adoption Phenomena,”. Management Science, 51(5), 741-755.
Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford publications.
Koenig-Lewis, N., Palmer, A., & Moll, A. (2010). Predicting young consumers’ take-up of mobile banking services. International Journal of Bank Marketing, 28(5), 410–432. http://dx.doi.org/10.1108/02652321011064917.
Koenig-Lewis, N., Palmer, A., & Moll, A. (2010). Predicting young consumers’ take-up of mobile banking services. International Journal of Bank Marketing, 28(5), 410–432. http://dx.doi.org/10.1108/02652321011064917.
Kuo, Y.-F., & Yen, S.-N. (2009). Towards an understanding of the behavioral intention to use 3G mobile value-added services. Computers in Human Behavior, 25, 103–110.
Lai, W. T., & Chen, C. F. (2011). Behavioral intentions of public transit passengers—The roles of service quality, perceived value, satisfaction, and involvement. Transport Policy, 18(2), 318-325.
Laukkanen, T., & Cruz, P. (2012, January). Cultural, individual and device-specific antecedents on mobile banking adoption: a cross-national study. InSystem Science (HICSS), 2012 45th Hawaii International Conference on (3170-3179). IEEE.
Laukkanen, T., (2007). Internet vs mobile banking: comparing customer value perceptions. Business Process Management Journal, 13 (6), 788–797.
Laukkanen, T., & Kiviniemi, V., (2010). The role of information in mobile banking resistance. International Journal of Bank Marketing, 28 (5), 372–388.
Laumer, S., Eckhardt, A., & Trunk, N. (2010). Do as your parents say? Analyzing IT adoption influencing factors for full and underage applicants. Information Systems Frontiers, 12(2), 169-183.
Lee, H., Harindranath, G., Oh, S., & Kim, D. J. (2014). Provision of mobile banking services from an actor–network perspective: Implications for convergence and standardization. Technological Forecasting & Social Change. http://dx.doi.org/ 10.1016/j.techfore.2014.02.007.
Lee, I., Choi, B., Kim, J., & Hon, S. J. (2007). Culture-technology fit: Effects of cultural characteristics on the post-adoption beliefs of mobile Internet users. International Journal of Electronic Commerce, 11(4), 11–51.
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, S., Shin, B., & Lee, H. G. (2009) “Understanding post-adoption usage of Mobile Data Services: The role of supplier-side variables.” Journal of the Associations of Information Systems, 10 (12), 860-888.
Lee, Y. H., Hsieh, Y. C., & Ma, C. H. (2011). A model of organizational employees’ learning systems acceptance. Knowledge-Based Systems, 24(3), 355–366.
Li, C.H. (2015). iT home (2015) survey of the CIO II: Analysis of enterprises' development trend. Retrieved from: http://www.ithome.com.tw/article/94146.
Liaw, S. S., Hatala, M., & Huang, H. M. (2010). Investigating acceptance toward mobile learning to assist individual knowledge management: Based on activity theory approach. Computers & Education, 54(2), 446–454.
Lin, H.-F. (2010). An empirical investigation of mobile banking adoption: The effect of innovation attributes and knowledge-based trust. International Journal of Information Management, 31(3), 252–260. http://dx.doi.org/10.1016/ j.ijinfomgt.2010.07.006.
Liyi Zhang, Jing Zhu & Quihua Liu (2012). A meta-analysis of mobile commerce adoption and the moderating effect of culture. Computers in Human Behavior, 28, 1902–1911.
Long Nguyen , Duc-Tho Nguyen & Tarlok Singh (2014). Effect of Trust on Customer Intention to use Electronic Banking in Vietnam. Proceedings of Global Business and Finance Research Conference, Marriott Hotel, Melbourne, Australia.
Lu , J., Yao, J. E., & Yu, C. S. (2005). Personal innovativeness, social influences and adoption of wireless Internet services via mobile technology. The Journal of Strategic Information Systems, 14(3), 245–268.
Luarn, P., & Lin, H. H. (2005). Toward an understanding of the behavioral intention to use mobile banking. Computers in human behavior, 21(6), 873-891.
Luo, X., Li, H., Zhang, J., & Shim, J. P. (2010). Examining multi-dimensional trust and multi-faceted risk in initial acceptance of emerging technologies: An empirical study of mobile banking services. Decision Support Systems, 49, 222–234.
MacCallum, R. C., Browne, M. W., & Sugawara, H. M. (1996). Power analysis and determination of sample size for covariance structure modeling.Psychological methods, 1(2), 130.
Mardikyan, S., Besiroglu, B., & Uzmaya, G. (2012). Behavioral intention towards the use of 3G technology. Communications of the IBIMA, 2012, 1.
Martins, C., Oliveira, T., & Popovicˇ, A. (2014). Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1–13. http://dx.doi.org/10.1016/j.ijinfomgt.2013.06.002.
Matos, J. C., & D’Aguiar, L. (2010). Measuring the evolution of monetary and financial services in Portugal. IPM17: Implementing the 1993 System of National Accounts, 283.
McKinney, V., Yoon, K., & Zahedi, F. M. (2002) “The measurement of web customer satisfaction: an expectation-disconfirmation approach.” Information Systems Research, 13(3), 296-315.
Milton, C. L., Popovic, ˇ A., & Oliveira, T. (2013). Determinants of end-user acceptance of biometrics: Integrating the Big 3 of technology acceptance with privacy context. Decision Support Systems, 56, 103–114.
Mishra, V., & Bisht, S. S. (2013). Mobile banking in a developing economy: A customer-centric model for policy formulation. Telecommunications Policy, 37, 503–514.
Mohammadi, H., (2015). A study of mobile banking loyalty in Iran. Computer Human Behavior, 44, 35–47.
Mohd-Yusof, K., Helmi, S.A., & Phang F. A (2012). Creating a Constructively Aligned Learning Environment using Cooperative Problem-based Learning (CPBL) for a Typical Course, Regional Conference of Engineering Education, Seremban, Malaysia.
Muhammed, S.D., Jabbar, B.A., Mujahid, N., & Lakhan, G.R., (2013). An analysis of mobile banking acceptance by Pakistani customers. Development Country Study, 3 (6), 21–28.
Muthén, L. K., & Muthén, B. O. (2010). Mplus (version 6.1) Computer software]. Los Angeles, CA: Muthén & Muthén.
Muthen, L.K., & Muthen, B.O., (2010). Mplus Statistical Analysis with latent variables: User’s guide. Muthen & Muthen.
Nasri, W., & Charfeddine, L., (2012). Factors affecting the adoption of internet banking in Tunisia: an integration theory of acceptance model and theory of planned behavior. Journal of High Technology Management Research, 23 (1), 1–14.
Negash, S., Ryan, T., & Igvaria, M. (2003) “Quality and effectiveness in web-based customer support systems.” Information & Management, 40(8), 757-768.
Ngai, E. W. T., & Gunasekaran, A. (2007). A review for mobile commerce research and applications. Decision Support Systems, 43, 3–15.
Oliveira, T., Faria, M., Thomas, M.A., & Popovicˇ, A., (2014). Extending the understanding of mobile banking adoption: when UTAUT meets TTF and ITM. International Journal of Information Management, 34 (5), 689–703.
Park, J., Yang, S., & Lehto, X., (2007). Adoption of mobile technologies for Chinese consumers. Journal Electronic Commerce Research, 8 (3), 196–206.
Pikkarainen, T., Pikkarainen, K., & Karjaluoto, H., (2004). Consumer acceptance of online banking: an extension of the technology acceptance model. International Research: Electronic Network Application Policy, 14 (3), 224–235.
Pousttchi, K., & Schurig, M. (2004). Assessment of today’s mobile banking applications from the view of customer requirements. In Proceeding of the 37th Hawaii international conference on system sciences (1–10).
Rai, A., Lang, S.S., & Welker, R.B., (2002). Assessing the validity of IS success models: an empirical test and theoretical analysis. Information Systems Research, 13 (1), 50–69.
Revels, J., Tojib, D., & Tsarenko, Y. (2010). Understanding consumer intention to use mobile services. Australasian Marketing Journal (AMJ), 18(2), 74-80.
Riffai, M. M. M. A., Grantb, K., & Edgarc, D. (2012). Big TAM in Oman: exploring the promise of on-line banking, its adoption by customers and the challenges of banking in Oman. International Journal of Information Management, 32(3), 239- 250.
Riquelme, H.E., & Rios, R.E., (2010). The moderating effect of gender on the adoption of mobile banking. International Journal of Bank Marketing, 28 (5), 328–341.
Rogers, E. (1995). Diffusion of innovations. In. New York: Free Press.
San Martín, H., & Herrero, Á. (2012). Influence of the user’s psychological factor son the online purchase intention in rural tourism: integrating innovativeness to the UTAUT framework. Tourism Management, 33(2), 341-350.
Sanchez-Franco, M. J. (2009). The moderating effects of involvement on the relationships between satisfaction, trust and commitment in e-banking. Journal of Interactive Marketing, 23, 247–258.
Sapio, B., Turk, T., Cornacchia, M., Papa, F., Nicolo, E., & Livi, S. (2010). Building scenarios of digital television adoption: a pilot study. Technology Analysis and Strategic Management, 22(1), 43-63.
Schaupp, L. C., Carter, L., & McBride, M. E. (2010). E-file adoption: a study of US taxpayers’ intentions. Computers in Human Behavior, 26(4), 636-644.
Schepers, J., & Wetzels, M. (2007). A meta-analysis of the technology acceptance model: Investigating subjective norm and moderation effects. Information & Management, 44(1), 90-103.
Schierz, P. G., Schilke, O., & Wirtz, B. W. (2010). Understanding consumer acceptance of mobile payment services: An empirical analysis. Electronic commerce research and applications, 9(3), 209-216.
Schubert, P. (2002). Extended web assessment method (EWAM): Evaluation of electronic commerce from the customer’s viewpoint. International Journal of Electronic Commerce, 7(2), 51–80.
Seddon, P.B., (1997). A respecification and extension of the DeLone and McLean model of IS success. Information Systems Research, 8 (3), 240–253.
Shaikh, A.A., & Karjaluoto, H., (2015). Mobile banking adoption: a literature review. Telematics Information, 32 (1), 129–142.
Singh, T., & Kaur, M., (2012). Internet banking: a content analysis of selected Indian public and private sector banks’ online portals. Journal of Internet Banking and Commerce, 17 (1).
Sohail, M.S., & Al-Jabri, I.M., (2014). Attitudes towards mobile banking: are there any differences between users and non-users? Behaviour & Information Technology, 33 (4), 335– 344.
Sohrabi, B., Vanani, I. R., Tahmasebipur, K., & Fazli, S. (2012). An exploratory analysis of hotel selection factors: A comprehensive survey of Tehran hotels.International Journal of Hospitality Management, 31(1), 96-106.
Sripalawat, J., Thongmak, M., & Ngramyarn, A., (2011). M-banking in metropolitan Bangkok and a comparison with other countries. Journal of Computer Information Systems, 51 (3), 67–76.
Steiger, J. H. (1990). Structural model evaluation and modification: An interval estimation approach. Multivariate behavioral research, 25(2), 173-180.
Sumak, B., Hericko, M., & Punik, M., (2011). A meta-analysis of e-learning technology acceptance: the role of user types and e-learning technology types. Computers in Human Behavior, 27 (6), 2067–2077.
Sutanonpaiboon, J., & Pearson, A. M. (2006). E-commerce adoption: perceptions of managers/owners of small and medium-sized enterprises (SMEs) in Thailand. Journal of Internet Commerce, 5(3), 53-82.
Sykes, T. A., Venkatesh, V., & Gosain, S. (2009). Model of acceptance with peer support: a social network perspective to understand employees’ system use. MIS Quarterly, 33(2), 371-393.
Taylor, S., & Tood, P. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6, 144–177.
Thakur, R. (2014). What keeps mobile banking customers loyal?. International Journal of Bank Marketing, 32(7), 628-646.
Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15(1), 124–143.
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.
Thye Goh, T., Mohd Suki, N., & Fam, K. (2014). Exploring a consumption value model for Islamic mobile banking adoption. Journal of Islamic Marketing, 5(3), 344-365.
Tiwari, R. (2007). In S. Buse (Ed.), The mobile commerce prospects A strategic analysis of opportunities in the banking sector. Hamburg, Deutschland: Hamburg University Press.
Tuttle, S.W., Lowe, D.B., & Moulton, B., (2011). A survey of issues and approaches to remote laboratory adoption by teacher-academics. In: FIE ‘11 Proceedings of the 2011 Frontiers in Education Conference.
Udo, G., Bagchi, K. K., & Kirs, P. J. (2011). Using SERVQUAL to assess the quality of learning experience. Computers in Human Behavior, 27, 1272–1283.
Van Acker, V., & Witlox, F. (2010). Car ownership as a mediating variable in car travel behavior research using a structural equation modeling approach to identify its dual relationship. Journal of Transport Geography, 18(1), 65-74.
Van der Heijden, H., (2004). User acceptance of hedonic information systems. MIS Quart., 695–704.
Van Raaij, E. M., & Schepers, J. J. L. (2008). The acceptance and use of a virtual learning environment in China. Computers & Education, 50(3), 838-852.
Venkatesh, V., & Davis, F. D. (2000). “A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies,” Management Science, 46(2), 186-204.
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., 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.
Wang, H. W., & Wang, S. H. (2010). User acceptance of mobile internet based on the unified theory of acceptance and use of technology: investigating the determinants and gender differences. Social Behavior & Personality: An International Journal, 33(3), 415-426.
Wang, Y. S., & Liao, Y. W. (2008). Assessing eGovernment systems success: A validation of the DeLone and McLean model of information systems success. Government Information Quarterly, 25(4), 717-733.
Wang, Y. S., & Shih, Y. W. (2009). Why do people use information kiosks? A validation of the unified theory of acceptance and use of technology. Government Information Quarterly, 26(1), 158-165.
Wang, Y. S., Lin, H. H., & Luarn, P.(2006). Predicting consumer intention to use mobile service. Information Systems Journal, 16, 157–179.
Wang, Y. S., Wu, M. C., & Wang, H. Y. (2009). Investigating the determinants and age and gender differences in the acceptance of mobile learning. British Journal of Educational Technology, 40(1), 92-118.
Wen, C. H., Lan, L., & Cheng, H. L. (2005). Structural equation modeling to determine passenger loyalty toward intercity bus services. Transportation Research Record: Journal of the Transportation Research Board, (1927), 249-255.
Wessels, L., Drennan, J., (2010). An investigation of consumer acceptance of M-banking. International Journal of Bank Marketing, 28 (7), 547–568.
Williams, M. D., Rana, N. P., Dwivedi, Y. K., & Lal, B. (2011). Is UTAUT really used or just cited for the sake of it? A systematic review of citations of UTAUT’s originating article. In 19th European conference on information systems, Helsinki.
Wonglimpiyarat, J. (2014). Competition and challenges of mobile banking: A systematic review of major bank models in the Thai banking industry. Journal of High Technology Management Research, 25, 123–131.
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.
Wu, W. Y., & Li, C. Y. (2007). A contingency approach to incorporate human, emotional and social influence into a TAM for KM programs. Journal of Information Science, 33(3), 275–297.
Wu, Y. L., Tao, Y. H., & Yang, P. C. (2008). The use of the unified theory of acceptance and use of technology to confer the behavioral model of 3G mobile telecommunication users. Journal of Statistics and Management Systems, 11(5), 919-949.
Wymer, S. A., & Regan, E. A. (2005). Factors influencing e-commerce adoption and use by small and medium businesses. Electronic Markets, 15(4), 438-453.
Xu, H., & Gupta, S. (2009). The effects of privacy concerns and personal innovativeness on potential and experienced customers’ adoption of location-based services. Electronic Markets, 19(2-3), 137-149.
Yang, A. S. (2009). Exploring adoption difficulties in mobile banking services. Canadian Journal of Administrative Sciences-Revue Canadienne Des Sciences De L Administration, 26, 136–149.
Yu, C.S., (2012). Factors affecting individuals to adopt mobile banking: empirical evidence from the UTAUT model. Journal Electronic Commerce Research, 13 (2), 104–121.
Yu, Z., Yan, H., & Cheng, T.C.E., (2001). Benefits of information sharing with supply chain partnerships. Industrial Management & Data Systems, 101 (3), 114– 119.
Zhang, L., Zhu, J., & Liu, Q. (2012). A meta-analysis of mobile commerce adoption and the moderating effect of culture. Computers in Human Behavior, 28(5), 1902–1911. http://dx.doi.org/10.1016/j.chb.2012.05.008.
Zhou, T. (2012). Examining mobile banking user adoption from the perspectives of trust and flow experience. Information Technology & Management, 13, 27–37.
Zhou, T. (2013a). An empirical examination of continuance intention of mobile payment services. Decision Support Systems, 54, 1085-1091. 119.
Zhou, T. (2013b). An empirical examination of the determinants of mobile purchase. Personalized Ubiquitous Computing Journal, 17, 187-195.
Zhou, T., (2011). An empirical examination of initial trust in mobile banking. Internet Research, 21 (5), 527–540. http://dx.doi.org/10.1108/ 10662241111176353.
Zhou, T., (2012). Understanding users’ initial trust in mobile banking: an elaboration likelihood perspective. Computers in Human Behavior, 28 (4), 1518–1525.
Zhou, T., Lu, Y., & Wang, B. (2010). Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior, 26(4), 760–767. HTTP:// dx.doi.org/10.1016/j.chb.2010.01.013.