Asian Journal of Information Technology

Year: 2018
Volume: 17
Issue: 1
Page No. 60 - 78

Integrating User Satisfaction and Performance Impact with Technology Acceptance Model (TAM) to Examine the Internet Usage Within Organizations in Yemen

Authors : Osama Isaac, Zaini Abdullah, T. Ramayah, Ahmed M. Mutahar and Ibrahim Alrajawy

References

Al-Qeisi, K.I., 2009. Analyzing the use of UTAUT model in explaining an online behaviour: Internet banking adoption. http://www.researchgate.net/publication/49402230_Analyzing_the_use_of_UTAUT_model_in_explaining_an_online_behaviour_Internet_banking_adoption.

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 (ICPE7), December 1, 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  |  

Anonymous, 2016. Internet users as percentage of population. World Bank, Washington, USA.

Awang, Z., 2012. Structural Equation Modeling Using AMOS Graphic. Penerbit UiTM Press, Shah Alam, Malaysia, ISBN-13: 9789673634187, Pages: 167.

Barnes, S.J. and R.T. Vidgen, 2014. Technology socialness and Web site satisfaction. Technol. Forecasting Soc. Change, 89: 12-25.
Direct Link  |  

Baruch, Y. and B.C. Holtom, 2008. Survey response rate levels and trends in organizational research. Hum. Relat., 61: 1139-1160.
Direct Link  |  

Benedetto, D.C.A., R.J. Calantone and C. Zhang, 2003. International technology transfer: Model and exploratory study in the people's republic of China. Intl. Marketing Rev., 20: 446-462.
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  |  

Bhatiasevi, V. and C. Yoopetch, 2015. The determinants of intention to use electronic booking among young users in Thailand. J. Hospitality Tourism Manage., 23: 1-11.
Direct Link  |  

Bollen, K.A., 1990. Overall fit in covariance structure models: Two types of sample size effects. Psychol. Bull., 107: 256-259.
Direct Link  |  

Byrne, B.M., 2010. Structural Equation Modeling with AMOS: Basic Concepts, Applications and Programming. 2nd Edn., Routledge, Abingdon, UK., ISBN:9780805863734, Pages: 396.

Callum, K.M. and L. Jeffrey, 2013. The influence of students' ICT skills and their adoption of mobile learning. Austr. J. Educ. Technol., 29: 303-314.
Direct Link  |  

Cheng, Y.M., 2011. Antecedents and consequences of E‐learning acceptance. Inf. Syst. J., 21: 269-299.
CrossRef  |  Direct Link  |  

Cheng, Y.M., 2014. Exploring the intention to use mobile learning: The moderating role of personal innovativeness. J. Syst. Inf. Technol., 16: 40-61.
Direct Link  |  

Chin, W.W., 1998. Commentary: Issues and opinion on structural equation modeling. Manage. Inform. Syst. 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 Associates, Hillsdale, Michigan, Pages: 567.

Cudjoe, A.G., P.A. Anim and J.G.N.T. Nyanyofio, 2015. Determinants of mobile banking adoption in the Ghanaian banking industry: A case of access bank Ghana limited. J. Comput. Commun., 3: 1-19.
Direct Link  |  

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  |  

Dalcher, I. and J. Shine, 2003. Extending the new technology acceptance model to measure the end user information systems satisfaction in a mandatory environment: A bank's treasury. Technol. Anal. Strategic Manage., 15: 441-455.
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. Q., 13: 319-340.
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  |  

Doll, W.J. and G. Torkzadeh, 1998. Developing a multidimensional measure of system-use in an organizational context. Inf. Manage., 33: 171-185.
Direct Link  |  

Elkhani, N., S. Soltani and A.M. Nazir, 2014. The effects of transformational leadership and ERP system self-efficacy on ERP system usage. J. Enterprise Inf. Manage., 27: 759-785.
Direct Link  |  

Fagan, M.H., S. Neill and B.R. Wooldridge, 2008. Exploring the intention to use computers: An empirical investigation of the role of intrinsic motivation, extrinsic motivation and perceived ease of use. J. Comput. Inf. Syst., 48: 31-37.
Direct Link  |  

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.

Faqih, K.M., 2016. An empirical analysis of factors predicting the behavioral intention to adopt Internet shopping technology among non-shoppers in a developing country context: Does gender matter?. J. Retailing Consum. Serv., 30: 140-164.
Direct Link  |  

Farahat, T., 2012. Applying the technology acceptance model to online learning in the Egyptian universities. Procedia Soc. Behav. Sci., 64: 95-104.
Direct Link  |  

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  |  

Fusilier, M. and S. Durlabhji, 2005. An exploration of student internet use in India: The technology acceptance model and the theory of planned behaviour. Campus Wide Inf. Syst., 22: 233-246.
Direct Link  |  

Gardner, C. and D.L. Amoroso, 2004. Development of an instrument to measure the acceptance of internet technology by consumers. Proceedings of the 37th Annual Hawaii International Conference on System Sciences, January 5-8, 2004, IEEE, Big Island, Hawaii, pp: 1-10.

Gefen, D. and E.E. Rigdon, 2011. An update and extension to SEM guidelines for administrative and social science research. MIS. Q., 35: 1-7.

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  |  

Ha, S. and L. Stoel, 2009. Consumer e-shopping acceptance: Antecedents in a technology acceptance model. J. Bus. Res., 62: 565-571.
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 Publications, Thousand Oaks, California, USA., Pages: 311.

Hair, J.F., W.C. Black, B.J. Babin and R.E. Anderson, 2010. Multivariate Data Analysis. 7th Edn., Prentice Hall, Upper Saddle River, New Jersey, USA., ISBN:9780138132637, Pages: 785.

Hayduk, L.A. and L. Littvay, 2012. Should researchers use single indicators, best indicators, or multiple indicators in structural equation models?. BMC. Med. Res. Method., 12: 1-17.
PubMed  |  Direct Link  |  

Hernandez, B., J. Jimenez and M.J. Martin, 2008. Extending the technology acceptance model to include the IT decision-maker: A study of business management software. Technovation, 28: 112-121.
Direct Link  |  

Hong, S., J.Y. Thong and K.Y. Tam, 2006. Understanding continued information technology usage behavior: A comparison of three models in the context of mobile internet. Decis. Support Syst., 42: 1819-1834.
CrossRef  |  Direct Link  |  

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  |  

Huang, E., 2008. Use and gratification in E-consumers. Internet Res., 18: 405-426.
Direct Link  |  

ILS., 2016. Internet users in the world. Internet Live Stats, New York, USA. http://www.internetlivestats.com/internet-users/.

Iqbal, S. and I.A. Qureshi, 2012. M-learning adoption: A perspective from a developing country. Int. Rev. Res. Open Distrib. Learn., 13: 147-164.
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. Mulaik and J.M. Brett, 1982. Causal analysis: Assumptions, Models and Data. Sage Publications, Beverly Hills, CA., ISBN-10: 0803918682.

Jan, A.U. and V. Contreras, 2011. Technology acceptance model for the use of information technology in universities. Comput. Human Behav., 27: 845-851.
CrossRef  |  Direct Link  |  

Jin, C.H., 2013. The effects of individual innovativeness on users’ adoption of internet content filtering software and attitudes toward children’s Internet use. Comput. Hum. Behav., 29: 1904-1916.
Direct Link  |  

Joo, J. and Y. Sang, 2013. Exploring Koreans’ smartphone usage: An integrated model of the technology acceptance model and uses and gratifications theory. Comput. Hum. Behav., 29: 2512-2518.
Direct Link  |  

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  |  

Kim, H.W., H.C. Chan and S. Gupta, 2007. Value-based adoption of mobile internet: An empirical investigation. Decis. Support Syst., 43: 111-126.
CrossRef  |  

Kim, S.H., 2014. A study on adoption factors of Korean smartphone users: A focus on TAM (Technology Acceptance Model) and UTAUT (Unified Theory of Acceptance and Use of Technology). Adv. Sci. Technol. Lett., 57: 27-30.
Direct Link  |  

Kline, R.B., 2010. Principles and Practice of Structural Equation Modeling. 3rd Edn., The Guilford Press, New York, USA.,.

Koksal, M.H., 2016. The intentions of Lebanese consumers to adopt mobile banking. Int. J. Bank Marketing, 34: 327-346.
Direct Link  |  

Konradt, U., T. Christophersen and U. Schaeffer-Kuelz, 2006. Predicting user satisfaction, strain and system usage of employee self-services. Intl. J. Hum. Comput. Stud., 64: 1141-1153.
Direct Link  |  

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.

Lee, B.C., J.O. Yoon and I. Lee, 2009. Learners’ 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. In: Mobile Information Systems, Lawrence, E., B. Pernici and J. Krogstie (Eds.). Springer, Boston, Massachusetts, ISBN:978-0-387-22851-8, pp: 135-153.

Lee, M.C., 2009. Factors influencing the adoption of internet banking: An integration of TAM and TPB with perceived risk and perceived benefits. Electron. Commerce Res. Applic., 8: 130-141.
CrossRef  |  Direct Link  |  

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.N. Hsu, 2011. Adding innovation diffusion theory to the technology acceptance model: Supporting employees' intentions to use E-learning systems. J. Educ. Technol. Soc., 14: 124-137.
Direct Link  |  

Lee, Y.H., Y.C. Hsieh and C.Y. Ma, 2011. A model of organizational employees’E-learning systems acceptance. Knowl. Based Syst., 24: 355-366.

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  |  

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  |  

Luarn, P. and H.H. Lin, 2005. Toward an understanding of the behavioral intention to use mobile banking. Comput. Hum. Behav., 21: 873-891.
CrossRef  |  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  |  

Mbogo, M., 2010. The impact of mobile payments on the success and growth of micro-business: The case of M-Pesa in Kenya. J. Lang. Technol. Entrepreneurship Afr., 2: 182-203.
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  |  

Mutahar, A.M., N.M. Daud, T. Ramayah, L. Putit and O. Isaac et al., 2016. The role of trialability, awareness, perceived ease of use and perceived usefulness in determining the perceived value of using mobile banking in Yemen. Proceedings of the 7th International Conference on Postgraduate Education (ICPE7), December 1, 2016, Universiti Teknolo gi MARA (UiTM), Shah Alam, Malaysia, pp: 884-898.

Nasri, W. and L. Charfeddine, 2012. Factors affecting the adoption of internet banking in Tunisia: An integration theory of acceptance model and theory of planned behavior. J. High Technol. Manage. Res., 23: 1-14.
CrossRef  |  

Negahban, A. and C.H. Chung, 2014. Discovering determinants of users perception of mobile device functionality fit. Comput. Hum. Behav., 35: 75-84.
Direct Link  |  

Negroponte, N., 2014. A 30-year history of the future. TED, South Dakota, USA. https://www.ted.com/talks/nicholas_negroponte_a_30_year_history_of_the_future.

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. and M.I. Salwani, 2009. Evaluating technology resistance and technology satisfaction on student's performance. Campus-Wide Inf. Syst., 26: 298-312.
CrossRef  |  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  |  

Nunnally, J.C. and I.H. Bernstein, 1994. Psychometric Theory. 3rd Edn., McGraw-Hill, New York, USA.

Park, Y. and J.V. Chen, 2007. Acceptance and adoption of the innovation use of smartphone. Ind. Manage. Data Syst., 107: 1349-1365.
CrossRef  |  Direct Link  |  

Parveen, F. and A. Sulaiman, 2008. Technology complexity, personal innovativeness and intention to use wireless internet using mobile devices in Malaysia. Intl. Rev. Bus. Res. Pap., 4: 1-10.
Direct Link  |  

Peng, W., R.A. Ratan and L. Khan, 2015. Ebook uses and class performance in a college course. Proceedings of the 2015 48th Hawaii International Conference on System Sciences (HICSS), January 5-8, 2015, IEEE, Kauai, HawaiiI, USA., ISBN:978-1-4799-7367-5, pp: 63-71.

Phua, P.L., S.L. Wong and R. Abu, 2012. Factors influencing the behavioural intention to use the internet as a teaching-learning tool in home economics. Procedia Soc. Behav. Sci., 59: 180-187.
Direct Link  |  

Pinho, C.M.R.J. and A.M. Soares, 2011. Examining the technology acceptance model in the adoption of social networks. J. Res. Interact. Marketing, 5: 116-129.
Direct Link  |  

Rahman, M.A., X. Qi and M.T. Islam, 2016. Banking access for the poor: Adoption and strategies in rural areas of Bangladesh. J. Econ. Financial Stud., 4: 1-10.
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. and N.M. Suki, 2006. Intention to use mobile PC among MBA students: Implications for technology integration in the learning curriculum. Unitar E. J., 1: 30-39.
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  |  

Rana, N.P., Y.K. Dwivedi, M.D. Williams and V. Weerakkody, 2015. Investigating success of an E-government initiative: Validation of an integrated IS success model. Inf. Syst. Front., 17: 127-142.
CrossRef  |  Direct Link  |  

Rehman, M., V. Esichaikul and M. Kamal, 2012. Factors influencing E-government adoption in Pakistan. Transforming Government People Process Policy, 6: 258-282.
Direct Link  |  

Revels, J., D. Tojib and Y. Tsarenko, 2010. Understanding consumer intention to use mobile services. Aust. Marketing J., 18: 74-80.
CrossRef  |  

Ridley, M., 2010. When ideas have sex. TED, New York, USA. http://www.ted.com/talks/matt_ridley_when_ideas_have_sex/transcript#t-103000.

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  |  

Ryan, C. and U. Rao, 2008. Holiday users of the internet ease of use, functionality and novelty. Intl. J. Tourism Res., 10: 329-339.
CrossRef  |  Direct Link  |  

Safar-Hasim, M. and A. Salman, 2010. Factors affecting sustainability of internet usage among youth. Electron. Lib., 28: 300-313.
Direct Link  |  

Sanchez, R.A. and A.D. Hueros, 2010. Motivational factors that influence the acceptance of Moodle using TAM. Comput. Hum. Behav., 26: 1632-1640.
CrossRef  |  Direct Link  |  

Sekaran, U. and R. Bougie, 2013. Research Methods for Business: A Skill-Building Approach. 6th Edn., John Wiley & Sons, Hoboken, New Jersey, USA., ISBN:9781119942252, Pages: 436.

Seliaman, M.E. and M.S.A. Turki, 2012. Mobile learning adoption in Saudi Arabia. Intl. J. Comput. Electr. Autom. Control Inf. Eng., 6: 1129-1131.
Direct Link  |  

Sharma, S.K. and J.K. Chandel, 2013. Technology acceptance model for the use of learning through websites among students in Oman. Intl. Arab J. E. Technol., 3: 44-49.
Direct Link  |  

Shih, H.P., 2004. Extended technology acceptance model of Internet utilization behavior. Inform. Manage., 41: 719-729.
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  |  

Singh, N., G. Fassott, M.C.H. Chao and J.A. Hoffmann, 2006. Understanding international web site usage: A cross-national study of German, Brazilian and Taiwanese online consumers. Int. Marketing Rev., 23: 83-97.
CrossRef  |  

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, London, UK., ISBN:9780205956227, Pages: 1024.

Tarhini, A., K. Hone and X. Liu, 2013. User acceptance towards web-based learning systems: Investigating the role of social, organizational and individual factors in European higher education. Procedia Comput. Sci., 17: 189-197.
Direct Link  |  

Tarhini, A., T. Elyas, M.A. Akour and Z. Al-Salti, 2016. Technology, demographic characteristics and E-learning acceptance: A conceptual model based on extended technology acceptance model. Higher Educ. Stud., 6: 72-89.
Direct Link  |  

Tarhini, A., T. Teo and T. Tarhini, 2016. A cross-cultural validity of the E-learning Acceptance Measure (ElAM) in Lebanon and England: A confirmatory factor analysis. Educ. Inf. Technol., 21: 1269-1282.
Direct Link  |  

Teo, T.S.H., V.K.G. Lim and R.Y.C. Lai, 1999. Intrinsic and extrinsic motivation in internet usage. Omega, 27: 25-37.
CrossRef  |  Direct Link  |  

Tucker, L.R. and C. Lewis, 1973. A reliability coefficient for maximum likelihood factor analysis. Psychometrika, 38: 1-10.
CrossRef  |  Direct Link  |  

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., 2000. Determinants of perceived ease of use: Integrating control, intrinsic motivation and emotion into the technology acceptance model. Inform. Syst. Res., 11: 342-365.
CrossRef  |  Direct Link  |  

Venkatesh, V., J.Y. Thong, F.K. Chan, P.J.H. Hu and S.A. Brown, 2011. Extending the two‐stage information systems continuance model: Incorporating UTAUT predictors and the role of context. Inf. Syst. J., 21: 527-555.
CrossRef  |  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  |  

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  |  

Wang, Y.S., 2008. Assessing E‐commerce systems success: A respecification and validation of the DeLone and McLean model of IS success. Inf. Syst. J., 18: 529-557.
CrossRef  |  Direct Link  |  

Wessels, L. and J. Drennan, 2010. An investigation of consumer acceptance of M-banking. Int. J. Bank Marketing, 28: 547-568.
CrossRef  |  

Wixom, B.H. and P.A. Todd, 2005. A theoretical integration of user satisfaction and technology acceptance. Inform. Syst. Res., 16: 85-102.
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  |  

Xinli, H., 2015. Effectiveness of information technology in reducing corruption in China: A validation of the DeLone and McLean information systems success model. Electron. Lib., 33: 52-64.
Direct Link  |  

Yalcinkaya, R., 2007. Police officers' adoption of information technology: A case study of the Turkish POLNET system. Ph.D Thesis, University of North Texas, Denton, Texas.

Yayla, A.A. and Q. Hu, 2007. User acceptance of E-commerce technology: A meta-analytic comparison of competing models. Proceedings of the 15th International Conference on ECIS Information Systems, June 7-9, 2007, University of St. Gallen, St. Gallen, Switzerland, pp: 179-190.

Design and power by Medwell Web Development Team. © Medwell Publishing 2022 All Rights Reserved