References
- Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204-215.
- Ahmad, S. Z., & Khalid, K. (2017). The adoption of M-government services from the user’s perspectives: Empirical evidence from the United Arab Emirates. Journal of Information Management, 37(5), 367-379.
- Ajzen, I., & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behavior. Englewood Cliffs, United States: Prentice-Hall.
- Akkucuk, U. (Ed.) (2014). Handbook of Research on Developing Sustainable Value in Economics. Finance and Marketing. United States: IGI Global.
- Bazelais, P., Doleck, T., & Lemay, D. J. (2017). Investigating the predictive power of TAM: A case study of CEGEP students’ intentions to use online learning technologies. Education and Information Technologies, 23(1), 93-111. doi: 10.1007/s10639-017-9587-0
- Browne, M. W., & Cudeck, R. (1992). Alternative ways of assessing model fit. In: K. A. Bollen & J. S. Long (Eds.), Testing structural equation models. Newbury Park, United States: Sage Publications.
- Changchit, C., & Chuchuen, C. (2018). Cloud computing: An examination of factors impacting users’ adoption. Journal of Computer Information Systems, 58(1), 1-9.
- Charles, V., & Kumar, M. (2014). Performance Measurement and Management. Cambridge, United Kingdom: Scholars Publishing.
- Chintalapati, N., & Daruri, V. S. K. (2016). Examining the Use of YouTube as a Learning resource in higher education: Scale development and Validation of TAM model. Telematics and Informatics, 34(6), 853-860. doi: 10.1016/j.tele.2016.08.008
- Culnan, M. J. (1985). The Dimensions of Perceived Accessibility to Information: Implications for the Delivery of Information Systems and Services. Journal of the American Society of Information Sciences, 36, 302-308.
- Davis, F. D. (1986). A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and Results. Cambridge, United States: MIT Sloan School of Management.
- Davis, F. D. (1989). Perceived Usefulness, Perceived Ease Of Use, And User Acceptance Of Information Technology. MIS Quarterly, 13(3), 319-340. doi: 10.2307/249008
- Davis, F. D. (1993). User Acceptance of Information Technology: System Characteristics, User Perceptions and Behavioral Impacts. International Journal of Man-Machine Studies, 38(3), 475-487. doi: 10.1006/ imms.1993.1022
- Davis, F. D., Bagozzi, R., & Warshaw, P. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982-1003.
- Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, United States: Addison-Wesley.
- Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement errors. Journal of Marketing Research, 18, 39-50.
- Groß, M. (2018). Heterogeneity in consumers’ mobile shopping acceptance: A finite mixture partial least squares modelling approach for exploring and characterising different shopper segments. Journal of Retailing and Consumer Services, 40, 8-18.
- Hair, J. F., Black, B., Babin, B., Anderson, R. E., & Tatham, R. L. (2010). Multivariate Data Analysis. Prentice Hall International.
- Igbaria, M., Zinatelli, N., Cragg, P., & Cavaye, A. L. M. (1997). Personal computing acceptance factors in small firms: A structural equation model. MIS Quarterly, 21(3), 279-305.
- Karahanna, E., Agarwal, R., & Angst, C. M. (2006). Reconceptualizing compatibility beliefs in technology acceptance research. MIS Quarterly, 30(4), 781-804.
- King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information and Management, 43(6), 740-755.
- Lai, V. S., & Li, H. (2000). Technology acceptance model for internet banking: An invariance analysis. Information and Management, 42(2), 373-386.
- 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. doi: 10.1080/09537325.2015.1047757
- Lim, W. M. (2018). Dialectic Antidotes to Critics of the Technology Acceptance Model: Conceptual, Methodological, and Replication Treatments for Behavioural Modelling in Technology-Mediated Environments. Australasian Journal of Information Systems, 22, 1-11. doi: 10.3127/ajis.v22i0.1651
- Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information and Management, 38, 217-230.
- Park, E., Cho, Y., Han J., & Kwon, S. J. (2017). Comprehensive Approaches to User Acceptance of Internet of Things in a Smart Home Environment. IEEE Internet of Things Journal, 4(6), 2342-2350.
- Park, S. Y. (2009). An Analysis of the Technology Acceptance Model in Understanding University Students’ Behavioral Intention to Use e-Learning. Educational Technology & Society, 12(3), 150-162.
- Przechlewski, T. (2012). Modelowanie satysfakcji, użyteczności i wykorzystania oprogramowania Open SourceModeling the satisfaction, usability and use of Open Source software Gdańsk, Poland: Wydawnictwo Uniwersytetu Gdańskiego.
- Rice, R. E., & Shook, D. (1988). Access to, Usage of, and Outcomes from an Electronic Message System. ACM Transactions on Office Information Systems, 6(3), 255-276.
- Sangi, N., Shuguang, L., & Sangi, A. R. (2018). Robustness of factors influencing social media usage/adoption amongst SMEs in developing countries: A case of Pakistan. ACM International Conference Proceeding Series, 103-109. doi: 10.1145/3183586.3183600
- Sobh, T. (ed.), (2010). Innovations and Advances in Computer Sciences and Engineering. Switzerland: Springer Science & Business Media.
- Teo, T. S. H., Lim, V. K. G., & Lai, R. Y. C. (1999). Intrinsic and extrinsic motivation in internet usage. Omega, 27(1), 25-37.
- Thong, J. Y. L., Hong, W., & Tam, K. (2002). Understanding user acceptance of digital libraries: What are the roles of interface characteristics, organizational context, and individual differences? International Journal of Human-Computer Studies, 57, 215-242.
- Ul Hassan, M., Iqbal, A., & Iqbal, Z. (2018). Factors affecting the adoption of internet banking in Pakistan: An integration of technology acceptance model and theory of planned behaviour. International Journal of Business Information Systems, 28(3), 342-370.
- Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315.
- 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. doi: 10.1111/ j.1540-5915.1996.tb01822.x
- 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.
- Wai I. S. H., Ng S. S. Y., Chiu D. K. W., Ho K. K. W., & Lo P. (2018). Exploring undergraduate students’ usage pattern of mobile apps for education. Journal of Librarianship and Information Science, 50(1), 34-47.
- Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information and Management, 42, 719-729.
- Zarantonello, L., & Pauwels-Delassus, V. (2015). The Handbook of Brand Management Scales. New York, United State: Taylor & Francis Group.