University Staff Adaption: An Empirical Study using the Unified Theory of Acceptance and Use of Technology and Extended Technology Acceptance Model II (Northern Border University, Saudi Arabia)


  • Wael Sh. Basri Dr. Wael Sh. Basri Northern Border University, College of Business Administration College of Business Administration, ArAr. Saudi Arabia


Saudi Arabia, Academic Staff, MIS, TAM, UTAUT, Education and ICT Adaption


Whenever institutions aspire to implement ICT systems, there are preliminary considerations to ponder for overall success. This paper examine ICT from the context of Northern Border University in Saudi Arabia, the paper has identified user variables for acceptance of ICT as performance expectancy, effort expectancy, social influence, facilitating conditions, age, voluntariness of use, experience and training of the users. This paper has discussed each variable before concluding with affirmation of the Technology Acceptance Model (TAM2) under Unified Theory of Acceptance and Use of Technology (UTAUT) as a recommendation for all University leaders to adopt. The considerations of these variables are alive to possibilities that different institutions could be having unique challenges. However, the UTAUT is really a baseline for such institutions with room for modifications.

Author Biography

Wael Sh. Basri, Dr. Wael Sh. Basri Northern Border University, College of Business Administration College of Business Administration, ArAr. Saudi Arabia

Assistance Professor

Business administration

Information Technology managemnt

Dean of Admission and Registeration

Northern Border University


• Al-Gahtani, S. (2001). The applicability of TAM outside North America: an empirical test in the United Kingdom. Information Resources Management Journal , 2 (Jul/Sep), 37-46.

• Bakkabulindi, F. (2011). Individual Characteristics as Correlates of Use of ICT in Makerere University. International Journal of Computing and ICT Research , 5 (2), 38-45.

• Basri, W. & Suliman, M. (2012). Factors Affecting Information Communication Technology Acceptance in Public Organizations in Saudi Arabia. International Journal of Computer Science and Information Security , 10 (2), 118-139.

• Bolaji, O. & Babajide, A. (2003). Perception of lecturers and service teachers towards the use of communication media in teaching pure and applied science related disciplines. the 44 Annual STAN Conferences (pp. 23 – 40). Lagos: roceedings of Conference.

• Carmines, E. & McIver, J. (1981). Analyzing models with unobserved variables: Analysis of Covariance structures. In &. E. G. W. Bohrnstedt, Social measurement: Current issues (Vol. 10, pp. 65-115). Beverly Hills, CA: Sage Publications.

• Chismar, W. & Patton, S. (2003). Does the Extended Technology Acceptance Model Apply to Physicians. the 36th Hawaii International Conference on System Sciences. Hawaii : HICSS.

• Fishbein, M. & Ajzen, I. (1975). Belief, Attitude, Intention, and Behavior: In An Introduction to Theory and Research. Reading. MA: Addison- Wesley.

• Gefen, D.& Straub, D. (2000). The relative importance of perceived ease of use in IS adoption: A study of e-commerce adoption. Journal of the Association for Information Systems , 1 (8), 1-28.

• Hair, J., Black, W., Babin, B. & Anderson, R. (2010). Structural Equation Modeling in Multivariate Data Analysis (7th Edition ed.). Saddle Rive, NJ: Prentice Hall.

• Jong-Ae, K. (2005). User acceptance of web-based subscription databases: extending the technology acceptance model. Unpublished Doctoral Dissertation . Tallahassee, Florida, USA: The Florida State University.

• Kozma, R. (2005). National policies that connect ICT-based education reform to economic and social development. Human Technology , 1 (2), 117-156.

• Lane. M & Stagg. A. (2014). UNIVERSITY STAFF ADOPTION OF IPADS: AN EMPIRICAL STUDY USING AN EXTENDED TECHNOLOGY ACCEPTANCE MODEL. Australasian Journal of Information Systems , 18 (3), 53 -74.

• Lea, M., Rogers, P. & Postmes, T. (2002). SIDE-VIEW: evaluation of a system to develop team players and improve productivity in internet collaborative learning groups. British Journal of Educational Technology , 33 (1), 53-63.

• Ma, Q. & Liu, L. (2004). The technology acceptance model: Ameta Analysis of Empirical Findings. Journal of Organizational and End User Computing , 16 (1), 59–72.

• Matyokurehwa, k. (2013). Challenges faced in Implementing ICT in Higher Learning Institutions. A Botswana perspective. International Journal for Infonomics (IJI) , 6 (1/2), 708 -712.

• McDonald, R. & Ho, M. (2002). Principles and Practice in Reporting Structural Equation Analyses. Psychological Methods , 7 (1), 64-82.

• Mischel, W. (2009). From Personality and Assessment (1968) to Personality Science, 2009. Journal of Research in Personality (Special Issue: Personality and Assessment 40 years later) , 43 (2), 82 – 290.

• Moralex- Gomez, D. & Melesse, M. (1998). Utilizing Information and Communication Technologies for Development: Social dimensions. Information Technology for Development , 8 (1), 3-13.

• Mullins, L. (2002). Management and Organization Behavior. London, UK: Pitman.

• Pajo, A. & Wallace, C. (2001). Barriers to the uptake of web-based technology by university teachers. Journal of Distance Education , 16 (1), 70-84.


• Rogers, E. (2003). Diffusion of innovations. New York, US: Free Press.

• Schiffman, L. & Kanuk, L. (2004). Consumer Behaviour. New Delhi, India: Prentice - Hall of India.

• Sife, A. S. (2007). New technologies for teaching and learning: Challenges for higher learning institutions in developing countries. International journal of Education and Development using Information and Communication Technology , 3 (2), 57-67.

• Taylor, S. & Todd, P. (1995). Assessing IT usage: The Role of Prior Experience. MIS Quarterly , 19 (4), 561-570.

• Venkatesh, D. &. (2003). User acceptance of information technology: Towards a unified view. MIS Quarterly , 27 (3), 425-478.

• Viswanath, V. & Fred D. . (2000). A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal. Management Science , 46 (2), 186-204.

• Wei-Tsong, W. & Chao-Yueh, L. (2004). The Application of the Technology Acceptance Model: A New way to Evaluate Information system success. University of Albany, Albany: Association Research and Travel grants Review Board.

• Wexler, J. (2001). Why computer users accept new systems. MIT Sloan Management Review , 42 (3), 17-20.

• ye, N. , Iahad, N. & Rabin, Z. (2011). A Model of ICT Acceptance and Use for Teachers in Higher Education Institutions. International Journal of Computer Science & Communication Networks , 1 (1), 22-40.

• Zeithaml, V., Parasuraman, A. & Malhotra, A. (2002). Service quality delivery through Web sites: a critical review of extant knowledge. Journal of the Academy of Marketing Science , 30 (4), 362-375.

• Zhang, P., Li, N. & Sun, H. . (2006). Affective Quality and Cognitive Absorption: Extending Technology Acceptanc e Research. Paper presented at the The Hawaii International Conference on System Sciences. Hawaii : International Conference on System Sciences 2006.

• Zmud, R. (2000). The Pinnaflex. Retrieved Jun 15, 2015, from Framing the Domains of IT Management : Projecting the Future...Through the Past:




How to Cite

Basri, W. S. (2015). University Staff Adaption: An Empirical Study using the Unified Theory of Acceptance and Use of Technology and Extended Technology Acceptance Model II (Northern Border University, Saudi Arabia). Asian Journal of Business and Management, 3(5). Retrieved from