This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.
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.AgarwalR.&PrasadJ.1998A conceptual and operational definition of personal innovativeness in the domain of information technologyInformation Systems Research9220421510.1287/isre.9.2.204Search in Google Scholar
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.AhmadS. Z.&KhalidK.2017The adoption of M-government services from the user’s perspectives: Empirical evidence from the United Arab EmiratesJournal of Information Management37536737910.1016/j.ijinfomgt.2017.03.008Search in Google Scholar
Ajzen, I., & Fishbein, M. (1980). Understanding Attitudes and Predicting Social Behavior. Englewood Cliffs, United States: Prentice-Hall.AjzenI.&FishbeinM.1980Understanding Attitudes and Predicting Social BehaviorEnglewood Cliffs, United StatesPrentice-HallSearch in Google Scholar
Akkucuk, U. (Ed.) (2014). Handbook of Research on Developing Sustainable Value in Economics. Finance and Marketing. United States: IGI Global.AkkucukUEd2014Handbook of Research on Developing Sustainable Value in Economics. Finance and MarketingUnited StatesIGI Global10.4018/978-1-4666-6635-1Search in Google Scholar
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/s10639-017-9587-0BazelaisP.DoleckT.&LemayD. J.2017Investigating the predictive power of TAM: A case study of CEGEP students’ intentions to use online learning technologiesEducation and Information Technologies2319311110.1007/s10639-017-9587-0Open DOISearch in Google Scholar
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.BrowneM. W.&CudeckR.1992Alternative ways of assessing model fitInBollenK. A.&LongJ. S.EdsTesting structural equation modelsNewbury Park, United StatesSage Publications10.1177/0049124192021002005Search in Google Scholar
Changchit, C., & Chuchuen, C. (2018). Cloud computing: An examination of factors impacting users’ adoption. Journal of Computer Information Systems, 58(1), 1-9.ChangchitC.&ChuchuenC.2018Cloud computing: An examination of factors impacting users’ adoptionJournal of Computer Information Systems5811910.1080/08874417.2016.1180651Search in Google Scholar
Charles, V., & Kumar, M. (2014). Performance Measurement and Management. Cambridge, United Kingdom: Scholars Publishing.CharlesV.&KumarM.2014Performance Measurement and ManagementCambridge, United KingdomScholars PublishingSearch in Google Scholar
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.2016.08.008ChintalapatiN.&DaruriV. S. K.2016Examining the Use of YouTube as a Learning resource in higher education: Scale development and Validation of TAM modelTelematics and Informatics34685386010.1016/j.tele.2016.08.008Open DOISearch in Google Scholar
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.CulnanM. J.1985The Dimensions of Perceived Accessibility to Information: Implications for the Delivery of Information Systems and ServicesJournal of the American Society of Information Sciences3630230810.1002/asi.4630360504Search in Google Scholar
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.DavisF. D.1986A Technology Acceptance Model for Empirically Testing New End-User Information Systems: Theory and ResultsCambridge, United StatesMIT Sloan School of ManagementSearch in Google Scholar
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease Of Use, And User Acceptance Of Information Technology. MIS Quarterly, 13(3), 319-340. doi: 10.2307/249008DavisF. D.1989Perceived Usefulness, Perceived Ease Of Use, And User Acceptance Of Information TechnologyMIS Quarterly13331934010.2307/249008Open DOISearch in Google Scholar
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.1993.1022DavisF. D.1993User Acceptance of Information Technology: System Characteristics, User Perceptions and Behavioral ImpactsInternational Journal of Man-Machine Studies38347548710.1006/imms.1993.1022Open DOISearch in Google Scholar
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.DavisF. D.BagozziR.&WarshawP.1989User acceptance of computer technology: a comparison of two theoretical modelsManagement Science358982100310.1287/mnsc.35.8.982Search in Google Scholar
Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research. Reading, United States: Addison-Wesley.FishbeinM.&AjzenI.1975Belief, Attitude, Intention, and Behavior: An Introduction to Theory and ResearchReading, United StatesAddison-WesleySearch in Google Scholar
Fornell, C., & Larcker, D. (1981). Evaluating structural equation models with unobservable variables and measurement errors. Journal of Marketing Research, 18, 39-50.FornellC.&LarckerD.1981Evaluating structural equation models with unobservable variables and measurement errorsJournal of Marketing Research18395010.1177/002224378101800104Search in Google Scholar
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.GroßM.2018Heterogeneity in consumers’ mobile shopping acceptance: A finite mixture partial least squares modelling approach for exploring and characterising different shopper segmentsJournal of Retailing and Consumer Services4081810.1016/j.jretconser.2017.09.002Search in Google Scholar
Hair, J. F., Black, B., Babin, B., Anderson, R. E., & Tatham, R. L. (2010). Multivariate Data Analysis. Prentice Hall International.HairJ. F.BlackB.BabinB.AndersonR. E.&TathamR. L.2010Multivariate Data AnalysisPrentice Hall InternationalSearch in Google Scholar
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.IgbariaM.ZinatelliN.CraggP.&CavayeA. L. M.1997Personal computing acceptance factors in small firms: A structural equation modelMIS Quarterly21327930510.2307/249498Search in Google Scholar
Karahanna, E., Agarwal, R., & Angst, C. M. (2006). Reconceptualizing compatibility beliefs in technology acceptance research. MIS Quarterly, 30(4), 781-804.KarahannaE.AgarwalR.&AngstC. M.2006Reconceptualizing compatibility beliefs in technology acceptance researchMIS Quarterly30478180410.2307/25148754Search in Google Scholar
King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information and Management, 43(6), 740-755.KingW. R.&HeJ.2006A meta-analysis of the technology acceptance modelInformation and Management43674075510.1016/j.im.2006.05.003Search in Google Scholar
Lai, V. S., & Li, H. (2000). Technology acceptance model for internet banking: An invariance analysis. Information and Management, 42(2), 373-386.LaiV. S.&LiH.2000Technology acceptance model for internet banking: An invariance analysisInformation and Management42237338610.1016/j.im.2004.01.007Search in Google Scholar
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: 10.1080/09537325.2015.1047757Liébana-CabanillasF.Ramos de LunaI.&Montoro-RíosF. J.2015User behaviour in QR mobile payment system: the QR Payment Acceptance ModelTechnology Analysis & Strategic Management2791031104910.1080/09537325.2015.1047757Open DOISearch in Google Scholar
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.v22i0.1651LimW. M.2018Dialectic Antidotes to Critics of the Technology Acceptance Model: Conceptual, Methodological, and Replication Treatments for Behavioural Modelling in Technology-Mediated EnvironmentsAustralasian Journal of Information Systems2211110.3127/ajis.v22i0.1651Open DOISearch in Google Scholar
Moon, J. W., & Kim, Y. G. (2001). Extending the TAM for a World-Wide-Web context. Information and Management, 38, 217-230.MoonJ. W.&KimY. G.2001Extending the TAM for a World-Wide-Web contextInformation and Management3821723010.1016/S0378-7206(00)00061-6Search in Google Scholar
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.ParkE.ChoY.HanJ.&KwonS. J.2017Comprehensive Approaches to User Acceptance of Internet of Things in a Smart Home EnvironmentIEEE Internet of Things Journal462342235010.1109/JIOT.2017.2750765Search in Google Scholar
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.ParkS. Y.2009An Analysis of the Technology Acceptance Model in Understanding University Students’ Behavioral Intention to Use e-LearningEducational Technology & Society123150162Search in Google Scholar
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.PrzechlewskiT.2012Modelowanie satysfakcji, użyteczności i wykorzystania oprogramowania Open Source [Modeling the satisfaction, usability and use of Open Source software]Gdańsk, PolandWydawnictwo Uniwersytetu GdańskiegoSearch in Google Scholar
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.RiceR. E.&ShookD.1988Access to, Usage of, and Outcomes from an Electronic Message SystemACM Transactions on Office Information Systems6325527610.1145/45945.214325Search in Google Scholar
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: 10.1145/3183586.3183600SangiN.ShuguangL.&SangiA. R.2018Robustness of factors influencing social media usage/adoption amongst SMEs in developing countries: A case of PakistanACM International Conference Proceeding Series10310910.1145/3183586.3183600Open DOISearch in Google Scholar
Sobh, T. (ed.), (2010). Innovations and Advances in Computer Sciences and Engineering. Switzerland: Springer Science & Business Media.SobhTed2010Innovations and Advances in Computer Sciences and EngineeringSwitzerlandSpringer Science & Business Media10.1007/978-90-481-3658-2Search in Google Scholar
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.TeoT. S. H.LimV. K. G.&LaiR. Y. C.1999Intrinsic and extrinsic motivation in internet usageOmega271253710.1016/S0305-0483(98)00028-0Search in Google Scholar
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.ThongJ. Y. L.HongW.&TamK.2002Understanding user acceptance of digital libraries: What are the roles of interface characteristics, organizational context, and individual differences?International Journal of Human-Computer Studies5721524210.1016/S1071-5819(02)91024-4Search in Google Scholar
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.Ul HassanM.IqbalA.&IqbalZ.2018Factors affecting the adoption of internet banking in Pakistan: An integration of technology acceptance model and theory of planned behaviourInternational Journal of Business Information Systems28334237010.1504/IJBIS.2018.092530Search in Google Scholar
Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315.VenkateshV.&BalaH.2008Technology acceptance model 3 and a research agenda on interventionsDecision Sciences39227331510.1111/j.1540-5915.2008.00192.xSearch in Google Scholar
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.xVenkateshV.&DavisF. D.1996A Model of the Antecedents of Perceived Ease of Use: Development and TestDecision Sciences27345148110.1111/j.1540-5915.1996.tb01822.xOpen DOISearch in Google Scholar
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46(2), 186-204.VenkateshV.&DavisF. D.2000A theoretical extension of the technology acceptance model: four longitudinal field studiesManagement Science46218620410.1287/mnsc.46.2.186.11926Search in Google Scholar
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.VenkateshV.MorrisM. G.DavisG. B.&DavisF. D.2003User acceptance of information technology: toward a unified viewMIS Quarterly27342547810.2307/30036540Search in Google Scholar
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.WaiI. S. H.NgS. S. Y.ChiuD. K. W.HoK. K. W.&LoP.2018Exploring undergraduate students’ usage pattern of mobile apps for educationJournal of Librarianship and Information Science501344710.1177/0961000616662699Search in Google Scholar
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.WuJ. H.&WangS. C.2005What drives mobile commerce? An empirical evaluation of the revised technology acceptance modelInformation and Management4271972910.1016/j.im.2004.07.001Search in Google Scholar
Zarantonello, L., & Pauwels-Delassus, V. (2015). The Handbook of Brand Management Scales. New York, United State: Taylor & Francis Group.ZarantonelloL.&Pauwels-DelassusV.2015The Handbook of Brand Management ScalesNew York, United StateTaylor & Francis Group10.4324/9781315813998Search in Google Scholar
