Research Journal of Applied Sciences
205 - 223
Ahmad, T. B.T., K.B. Madarsha, A.M.H. Zainuddin, N. A.H. Ismail and M.S. Nordin, 2010. Faculty’s acceptance of computer based technology: Cross-validation of an extended model. Australas. J. Educ. Technol., 26: 268-279.Direct Link |
Aljukhadar, M., S Senecal and J. Nantel, 2014. Is more always better? Investigating the task-technology fit theory in an online user context. Inf. Manage., 51: 391-397.Direct Link |
Almatari, A., N. Iahad and A. Balaid, 2012. Factors influencing students â€TM intention to use m-learning. J. Inf. Syst. Res. Innovation, 2012: 1-8.
Alrajawy, I., N.M. Daud, O. Isaac and A. M. Mutahar, 2016. Mobile learning in yemen public universities: Factors influence student’s intention to use. Proceedings of the 7th International Conference on Postgraduate Education, December 01, 2016, Universiti Teknologi MARA , Shah Alam, Malaysia, pp: 1050-1064.
Anandarajan, M., M. Igbaria and U. Anakwe, 2002. IT acceptance in a less-developed country: A motivational factor perspective. Int. J. Inform. Manage., 22: 47-65.Direct Link |
Awang, Z., 2014. Structural Equation Modeling Using AMOS. Universiti Teknologi MARA Publication Center, Shah Alam, Malaysia,.
Baruch, Y. and B.C. Holtom, 2008. Survey response rate levels and trends in organizational research. Hum. Relat., 61: 1139-1160.Direct Link |
Bentler, P.M. and D.G. Bonnet, 1980. Significance tests and goodness of fit in the analysis of covariance structures. Psychol. Bull., 88: 588-606.CrossRef |
Bollen, K.A., 1990. Overall fit in covariance structure models: Two types of sample size effects. Psychol. Bull., 107: 256-259.Direct Link |
Bozorgkhou, N., 2015. An internet shopping user adoption model using an integrated TTF and UTAUT: Evidence from Iranian consumers. Manage. Sci. Lett., 5: 199-204.Direct Link |
Byrne, B.M., 2010. Structural Equation Modeling with AMOS: Basic Concepts, Applications and Programming. 2nd Edn., Routledge, New York, USA., ISBN-13: 9780805863734, Pages: 396.
Chan, F.K.Y., S.A. Brown, P.J. Hu and K.Y. Tam, 2010. Modeling citizen satisfaction with mandatory adoption of an E-Government technology. J. Assoc. Inf. Syst., 11: 519-549.
Chang, H.H., 2008. Intelligent agent's technology characteristics applied to online auctions task: A combined model of TTF and TAM. Technovation, 28: 564-577.Direct Link |
Chang, H.H., 2010. Task-technology fit and user acceptance of online auction. Intl. J. Hum. Comput. Stud., 68: 69-89.Direct Link |
Chen, C., 2013. Perceived risk, usage frequency of mobile banking services. Managing Serv. Qual. Intl. J., 23: 410-436.Direct Link |
Chen, C.C., J. Wu and S.C. Yang, 2006. The efficacy of online cooperative learning systems: The perspective of task-technology fit. Campus Wide Inf. Syst., 23: 112-127.Direct Link |
Chen, S.C., D.C. Yen and M.I. Hwang, 2012. Factors influencing the continuance intention to the usage of Web 2.0: An empirical study. Comput. Hum. Behav., 28: 933-941.Direct Link |
Cheng, D., G. Liu, C. Qian and Y.F. Song, 2008. Customer acceptance of Internet banking: Integrating trust and quality with UTAUT Model. Proceedings of the IEEE International Conference on Service Operations and Logistics and Informatics, IEEE/SOLI 2008, Vol. 1, October 12-15, 2008, IEEE, New York, USA., ISBN:978-1-4244-2012-4, pp: 383-388.
Cheng, Y.M., 2011. Antecedents and consequences of E‐learning acceptance. Inf. Syst. J., 21: 269-299.CrossRef | Direct Link |
Cheung, R. and D. Vogel, 2013. Predicting user acceptance of collaborative technologies: An extension of the technology acceptance model for e-learning. Comput. Educ., 63: 160-175.CrossRef | Direct Link |
Cheung, W., M.K. Chang and V.S. Lai, 2000. Prediction of internet and world wide web usage at work: A test of an extended Triandis model. Decision Support Syst., 30: 83-100.CrossRef | Direct Link |
Chin, W.W., 1998. Commentary: Issues and opinion on structural equation modeling. MIS Q., 22: 7-16.Direct Link |
Cho, K.W., S.K. Bae, J.H. Ryu, K.N. Kim and C.H. An et al
., 2015. Performance evaluation of public hospital information systems by the information system success model. Healthcare Inf. Res., 21: 43-48.Direct Link |
Cohen, J., 1988. Statistical Power Analysis for the Behavioral Sciences. 2nd Edn., Lawrence Erlbaum, Hillsdale, New Jersey, USA., ISBN: 0-8058-6283-5, Pages: 128.
D'Ambra, J. and C.S. Wilson, 2004. Explaining perceived performance of the World Wide Web: Uncertainty and the task-technology fit model. Internet Res., 14: 294-310.Direct Link |
D'Ambra, J., C.S. Wilson and S. Akter, 2013. Application of the task-technology fit model to structure and evaluate the adoption of E-books by Academics. J. Assoc. Inf. Sci. Technol., 64: 48-64.CrossRef | Direct Link |
Daud, N.M., 2008. Factors determining intranet usage: An empirical study of middle managers in Malaysian port industry. Ph.D. Thesis, Multimedia University, Malaysia.
Davis, F.D., 1989. Perceived usefulness, perceived ease of use and user acceptance of information technology. MIS Quart., 13: 319-340.CrossRef | Direct Link |
DeLone, W.D. and E.R. McLean, 2003. The DeLone and McLean model of information systems success: A ten-year update. J. Manage. Inf. Syst., 19: 9-30.CrossRef | Direct Link |
DeLone, W.H. and E.R. McLean, 1992. Information systems success: The quest for the dependent variable. Inform. Syst. Res., 3: 60-95.CrossRef | Direct Link |
Dishaw, M.T. and D.M. Strong, 1999. Extending the technology acceptance model with task-technology fit constructs. Inform. Manage., 36: 9-21.CrossRef |
Falk, R.F. and N.B. Miller, 1992. A Primer for Soft Modeling. The University of Akron Press, Akron, Ohio, ISBN-13: 9780962262845, Pages: 103.
Fan, J.C. and K. Fang, 2006. ERP implementation and information systems success: A test of DeLone and McLean's model. Proceedings of the Conference on Technology Management for the Global Future, PICMET 2006, Vol. 3, July 8-13, 2006, IEEE, New York, USA., ISBN:1-890843-14-8, pp: 1272-1278.
Fang, S.F., 2014. Using UTAUT model to explore the user behavior of e-learning system in a public sector. Department of Communications, Stanford, California.
Fornell, C. and D.F. Larcker, 1981. Evaluating structural equation models with unobservable variables and measurement error. J. Market. Res., 18: 39-50.CrossRef | Direct Link |
Gefen, D., D.W. Straub and M.C. Boudreau, 2000. Structural equation modeling and regression: Guidelines for research practice. Commun. Assoc. Inform. Syst., 4: 1-77.Direct Link |
Glowalla, P. and A. Sunyaev, 2014. ERP system fit an explorative task and data quality perspective. J. Enterp. Inf. Manage., 27: 668-686.Direct Link |
Gonzalez, G.C., P.N. Sharma and D. Galletta, 2012. Factors influencing the planned adoption of continuous monitoring technology. J. Inf. Syst., 26: 53-69.Direct Link |
Goodhue, D.L. and R.L. Thompson, 1995. Task-technology fit and individual performance. MIS Q., 19: 213-236.CrossRef | Direct Link |
Hair, J.F., G.T.M. Hult, C.M. Ringle and M. Sarstedt, 2013. A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). SAGE Publication, Thousand Oaks, CA., USA., ISBN-13: 978-1452217444, Pages: 328.
Hair, Jr., J.F., W.C. Black, B.J. Babin and R.E. Anderson, 2010. Multivariate Data Analysis. 7th Edn., Prentice Hall, Upper Saddle River, NJ., ISBN-13: 9780138132637, Pages: 785.
Hou, C.K., 2012. Examining the effect of user satisfaction on system usage and individual performance with business intelligence systems: An empirical study of Taiwan's electronics industry. Intl. J. Inf. Manage., 32: 560-573.Direct Link |
Hsu, M. and C. Chiu, 2004. Internet self-efficacy and electronic service acceptance. Decision Support Syst., 38: 369-381.CrossRef |
Hu, L.T. and P.M. Bentler, 1999. Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Struct. Equat. Modell., 6: 1-55.CrossRef | Direct Link |
IMF., 2015. GDP per capita: Yemen vs, Neighbor Arab Countries. International Monetary Fund, Washington, USA.
Ifinedo, P., 2012. Technology acceptance by health professionals in Canada: An analysis with a modified UTAUT model. Proceedings of the 2012 45th Hawaii International Conference on System Science (HICSS), January 4-7, 2012, IEEE, New York, USA., ISBN:978-1-4577-1925-7, pp: 2937-2946.
Ifinedo, P., 2014. An examination of information technology assets and resources as antecedent factors to erp sysytem success. Proceedings of the 8th Mediterranean Conference on Information Systems (MCIS), September 3-5, 2014, Association for Information Systems, Atlanta, Georgia, USA., ISBN:978-88-6787-273-2, pp: 1-17.
Irick, M.L., 2008. Task-technology fit and information systems effectiveness. J. Knowl. Manage. Pract., 9: 1-5.Direct Link |
Isaac, O., Z. Abdullah, T. Ramayah, A.M. Mutahar and I. Alrajawy, 2016. Perceived usefulness, perceived ease of use, perceived compatibility and Net benefits: An empirical study of internet usage among employees in Yemen. Proceedings of the 7th International Conference on Postgraduate Education (ICPE7), Sep 8, 2016, Dewan Sri Budiman, Shah Alam, Malaysia, pp: 899-919.
James, L.R., S.A. Muliak and J.M. Brett, 1982. Causal Analysis: Models, Assumptions and Data. Sage, Beverly Hills, California,.
Joreskog, K. and D. Sorbom, 1993. LISREL 8: Structural Equation Modeling with the SIMPLIS Command Language. Scientific Software International Inc, Chicago, Illinois, ISBN:0-89498-033-5, Pages: 277.
Junglas, I., C. Abraham and R.T. Watson, 2008. Task-technology fit for mobile locatable information systems. Decis. Support Syst., 45: 1046-1057.Direct Link |
Kang, A., L. Barolli, J.D. Lee, J.H. Park and H.Y. Jeong, 2013. Information success model for learning system in cloud computing environment. Proceedings of the 2013 International Joint Conference on Awareness Science and Technology and Ubi-Media Computing (iCAST-UMEDIA), November 2-4, 2013, IEEE, Seoul, South Korea, ISBN: 978-1-4799-2364-9, pp: 764-768.
Kannan, V.R. and K.C. Tan, 2005. Just in time, total quality management and supply chain management: Understanding their linkages and impact on business performance. Omega, 33: 153-162.CrossRef | Direct Link |
Khayun, V. and P. Ractham, 2011. Measuring e-excise tax success factors: Applying the Delone and McLean information systems success model. Proceedings of the 44th Hawaii International Conference on System Sciences (HICSS) 2011, January 4-7, 2011, IEEE, California, USA., ISBN:978-1-4244-9618-1, pp: 1-10.
Kim, B.G., S.C. Park and K.J. Lee, 2008. A structural equation modeling of the internet acceptance in Korea. Electron. Commerce Res. Appl., 6: 425-432.Direct Link |
Kline, R.B., 2010. Principles and Practice of Structural Equation Modeling. 3rd Edn., The Guilford Press, New York, USA., ISBN-13: 9781606238769, Pages: 427.
Krejcie, R.V. and D.W. Morgan, 1970. Determining sample size for research activities. Educ. Psychol. Meas., 30: 607-610.CrossRef | Direct Link |
Kripanont, N., 2007. Examining a technology acceptance model of internet usage by academics within Thai Business Schools. Ph.D. Thsis, Victoria University, Melbourne, Australia.
Kurniawan, B., 2010. Factors affecting customer satisfaction in purchase decision on ticket online: A case study in air Asia. Master Thesis, State Islamic University Syarif Hidayatullah, South Tangerang, Indonesia.
Lai, M., 2008. Technology readiness, internet self-efficacy and computing experience of professional accounting students. Campus-Wide Inf. Syst., 25: 18-29.Direct Link |
Larsen, T.J., A.M. Sorebo and O. Sorebo, 2009. The role of task-technology fit as users’ motivation to continue information system use. Comput. Hum. Behav., 25: 778-784.Direct Link |
Lederer, A.L., D.J. Maupin, M.P. Sena and Y. Zhuang, 2000. The technology acceptance model and the world wide web. Dec. Support Syst., 29: 269-282.CrossRef | Direct Link |
Lee, B.C., J.O. Yoon and I. Lee, 2009. Learner's acceptance of e-learning in South Korea: Theories and results. Comput. Educ., 53: 1320-1329.CrossRef | Direct Link |
Lee, D.Y. and M.R. Lehto, 2013. User acceptance of YouTube for procedural learning: An extension of the technology acceptance model. Comput. Educ., 61: 193-208.CrossRef | Direct Link |
Lee, K.C., S. Lee and J.S. Kim, 2005. Analysis of mobile commerce performance by using the task-technology fit. Proceedings of the IFIP TC8 Working Conference on Mobile Information Systems, September 15-17, 2004, Springer, Oslo, Norway, pp: 135-153.
Lee, S. and B.G. Kim, 2009. Factors affecting the usage of intranet: A confirmatory study. Comput. Hum. Behav., 25: 191-201.CrossRef | Direct Link |
Lee, Y.H., Y.C. Hsieh and C.Y. Ma, 2010. A model of organizational employees' e-learning systems acceptance. Knowledge Based Syst., 24: 355-366.CrossRef |
Lian, J.W., 2015. Critical factors for cloud based e-invoice service adoption in Taiwan: An empirical study. Int. J. Inf. Manage., 35: 98-109.Direct Link |
Lin, W.S. and C.H. Wang, 2012. Antecedences to continued intentions of adopting e-learning system in blended learning instruction: A contingency framework based on models of information system success and task-technology fit. Comput. Edu., 58: 88-99.CrossRef |
Liu, Y., H. Li and C. Carlsson, 2010. Factors driving the adoption of m-learning: An empirical study. Comput. Educ., 55: 1211-1219.CrossRef | Direct Link |
Lu, H.P. and Y.W. Yang, 2014. Toward an understanding of the behavioral intention to use a social networking site: An extension of task-technology fit to social-technology fit. Comput. Hum. Behav., 34: 323-332.
Lu, J., J.E. Yao and C.S. Yu, 2005. Personal innovativeness, social influences and adoption of wireless internet services via mobile technology. J. Strategic Inf. Syst., 14: 245-268.CrossRef |
Lwoga, T.E., 2013. Measuring the success of library 2.0 technologies in the African context: The suitability of the DeLone and McLean's model. Campus Wide Inf. Syst., 30: 288-307.Direct Link |
Makokha, M.W. and D.O. Ochieng, 2014. Assessing the success of ICT’s from a user perspective: Case study of coffee research foundation, Kenya. J. Manage. Strategy, 5: 46-54.Direct Link |
McFarland, D.J. and D. Hamilton, 2006. Adding contextual specificity to the technology acceptance model. Comput. Hum. Behav., 22: 427-447.Direct Link |
McGill, T.J. and J.E. Klobas, 2009. A task-technology fit view of learning management system impact. Comput. Educ., 52: 496-508.Direct Link |
Montesdioca, G.P.Z. and A.C.G. Macada, 2015. Measuring user satisfaction with information security practices. Comput. Secur., 48: 267-280.Direct Link |
Nikhashemi, S.R., L. Paim, F. Yasmin and A. Yousefi, 2013. Critical factors in determining customer satisfaction toward internet shopping in Malaysia. Intl. J. Bus. Manage. Invention, 2: 44-51.
Nistor, N., T. Lerche, A. Weinberger, C. Ceobanu and O. Heymann, 2014. Towards the integration of culture into the unified theory of acceptance and use of technology. Br. J. Educ. Technol., 45: 36-55.CrossRef | Direct Link |
Norzaidi, D.M. and S.M. Intan, 2009. Evaluating technology resistance and technology satisfaction on students performance. Campus Wide Inf. Syst., 26: 298-312.Direct Link |
Norzaidi, D.M., C.S. Choy, R. Murali and S.M. Intan, 2007. Intranet usage and managers performance in the port industry. Ind. Manage. Data Syst., 107: 1227-1250.Direct Link |
Norzaidi, M.D., S.C. Chong, R. Murali and M.I. Salwani, 2009. Towards a holistic model in investigating the effects of intranet usage on managerial performance: A study on Malaysian port industry. Maritime Policy Manage., 36: 269-289.CrossRef | Direct Link |
Ogara, S.O., C.E. Koh and V.R. Prybutok, 2014. Investigating factors affecting social presence and user satisfaction with mobile instant messaging. Comput. Hum. Behav., 36: 453-459.Direct Link |
Oliveira, T., M. Faria, M.A. Thomas and A. Popovic, 2014. Extending the understanding of mobile banking adoption: When UTAUT meets TTF and ITM. Intl. J. Inf. Manage., 34: 689-703.Direct Link |
Oyedemi, T.D., 2012. Digital inequalities and implications for social inequalities: A study of internet penetration amongst university students in South Africa. Telematics Inf., 29: 302-313.Direct Link |
PRC., 2013. Nations embrace internet & mobile technology. Pew Research Center, Washington, DC., USA. http://www.pewglobal.org/2014/02/13/emerging-nations-embrace-internet-mobile-technology/.
Pahnila, S., M. Siponen and X. Zheng, 2011. Integrating habit into UTAUT: The Chinese eBay case. Pac. Asia J. Assoc. Inf. Syst., 3: 1-30.Direct Link |
Pai, F.Y. and K.I. Huang, 2011. Applying the technology acceptance model to the introduction of healthcare information systems. Technol. Forecast. Social Change, 78: 650-660.CrossRef | Direct Link |
Parkes, A., 2013. The effect of task-individual-technology fit on user attitude and performance: An experimental investigation. Decis. Support Syst., 54: 997-1009.Direct Link |
Ramayah, T. and M.C. Lo, 2007. Impact of shared beliefs on perceived usefulness and ease of use in the implementation of an enterprise resource planning system. Manage. Res. News, 30: 420-431.CrossRef | Direct Link |
Ramayah, T., 2006. Course website usage does prior experience matter?. Wseas Trans. Inf. Sci. Appl., 3: 299-306.Direct Link |
Ramayah, T., J. Ignatius and B. Aafaqi, 2005. PC usage among students in a private institution of higher learning: The moderating role of prior experience. Educators Educ. J., 20: 131-152.Direct Link |
Roca, J.C., C.M. Chiu and F.J. Martinez, 2006. Understanding e-learning continuance intention: An extension of the technology acceptance model. Int. J. Hum. Comput. Stud., 64: 683-696.CrossRef | Direct Link |
Salisbury, W.D., R.A. Pearson, A.W. Pearson and D.W. Miller, 2001. Perceived security and World Wide Web purchase intention. Ind. Manage. Data Syst., 101: 165-177.Direct Link |
Schrier, T., M. Erdem and P. Brewer, 2010. Merging task-technology fit and technology acceptance models to assess guest empowerment technology usage in hotels. J. Hospitality Tourism Technol., 1: 201-217.Direct Link |
Sharma, S., S. Mukherjee, A. Kumar and W.R. Dillon, 2005. A simulation study to investigate the use of cutoff values for assessing model fit in covariance structure models. J. Bus. Res., 58: 935-943.CrossRef |
Shih, Y.Y. and C.Y. Chen, 2013. The study of behavioral intention for mobile commerce: Via integrated model of TAM and TTF. Qual. Quantity, 47: 1009-1020.CrossRef |
Shih, Y.Y. and K. Fang, 2004. The use of a decomposed theory of planned behavior to study Internet banking in Taiwan. Int. Res., 14: 213-223.CrossRef |
Singeh, W.F., A. Abrizah and A.K.N. Harun, 2013. Malaysian authors acceptance to self-archive in institutional repositories: Towards a unified view. Electron. Lib., 31: 188-207.Direct Link |
Smith, C.D. and J.T. Mentzer, 2010. Forecasting task-technology fit: The influence of individuals, systems and procedures on forecast performance. Intl. J. Forecasting, 26: 144-161.Direct Link |
Son, H., Y. Park, C. Kim and J.S. Chou, 2012. Toward an understanding of construction professional's acceptance of mobile computing devices in South Korea: An extension of the technology acceptance model. Autom. Constr., 28: 82-90.CrossRef | Direct Link |
Steiger, J.H., 1990. Structural model evaluation and modification: An interval estimation approach. Multivariate Behav. Res., 25: 173-180.CrossRef | Direct Link |
Straub, D., M. Keil and W. Brenner, 1997. Testing the technology acceptance model across cultures: A three country study. Inform. Manage., 33: 1-11.CrossRef |
Straub, D., M. Limayem and E. Karahanna-Evaristo, 1995. Measuring system usage: Implications for IS theory testing. Manage. Sci., 41: 1328-1342.CrossRef | Direct Link |
Sun, P., R. Tsai, G. Finger, Y. Chen and D. Yeh, 2008. What drives a successful e-learning? An empirical investigation of the critical factors influencing learner satisfaction. Comput. Educ., 50: 1183-1202.CrossRef | Direct Link |
Sun, Y. and S. Mouakket, 2015. Assessing the impact of enterprise systems technological characteristics on user continuance behavior: An empirical study in China. Comput. Ind., 70: 153-167.Direct Link |
Tabachnick, B.G. and L.S. Fidell, 2012. Using Multivariate Statistics. 6th Edn., Pearson Education, Boston, MA., ISBN-13: 9780205849574, Pages: 983.
Tobias, O. and M. Kairu, 2015. Relationship between human characteristics and adoption of project management information system in non-governmental organizations’ projects in Nakuru Town (Kenya). Intl. J. Intell. Inf. Syst., 4: 16-26.CrossRef | Direct Link |
Torkzadeh, G. and T.P.V. Dyke, 2001. Development and validation of an Internet self-efficacy scale. Behav. Inf. Technol., 20: 275-280.Direct Link |
Tucker, L.R. and C. Lewis, 1973. A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38: 1-10.CrossRef |
Urbach, N. and F. Ahlemann, 2010. Structural equation modeling in information systems research using partial least squares. J. Inf. Technol. Theory Applic., 11: 5-40.Direct Link |
Venkatesh, V. and M.G. Morris, 2000. Why don't men ever stop to ask for directions? Gender, social influence and their role in technology acceptance and usage behavior. MIS Quart., 24: 115-139.CrossRef | Direct Link |
Venkatesh, V., J.Y. Thong and X. Xu, 2012. Consumer acceptance and use of information technology: Extending the unified theory of acceptance and use of technology. MIS. Q., 36: 157-178.Direct Link |
Venkatesh, V., M.G. Morris, G.B. Davis and F.D. Davis, 2003. User acceptance of information technology: Toward a unified view. MIS Quart., 27: 425-478.CrossRef | Direct Link |
Vogiatzi, M., 2015. The use of ICT technologies enhances employees’ performance in the Greek hotel industry. Intl. J. Econ. Finance Manage. Sci., 3: 43-56.
Wang, Y.S. and Y.W. Liao, 2008. Assessing eGovernment systems success: A validation of the DeLone and McLean model of information systems success. Govt. Inform. Quart., 25: 717-733.CrossRef | Direct Link |
Wu, J.H. and Y.M. Wang, 2006. Measuring KMS success: A respecification of the DeLone and McLean's model. Inform. Manage., 43: 728-739.CrossRef | Direct Link |
Yu, C.S., 2012. Factors affecting individuals to adopt mobile banking: Empirical evidence from the UTAUT model. J. Electron Commerce Res., 13: 104-121.
Zhao, L., Y. Lu, B. Wang and W. Huang, 2011. What makes them happy and curious online? An empirical study on high school students’ Internet use from a self determination theory perspective. Comput. Educ., 56: 346-356.Direct Link |
Zhou, T., Y. Lu and B. Wang, 2010. Integrating TTF and UTAUT to explain mobile banking user adoption. Comput. Hum. Behav., 26: 760-767.CrossRef |