Acceptance of Web-Based Training System Among Public Sector Employees

Authors

  • Huda Ibrahim School of Computing, Universiti Utara Malaysia, Malaysia
  • Thamer Ahmad AL-Rawashdeh Faculty of Science and Information Technology, Al-Zaytoonah University of Jordan, Jordan

DOI:

https://doi.org/10.32890/jict2014.13.5

Keywords:

Technology acceptance, web-based training system, public sector, UTAUT

Abstract

Applying web-based training system is highly preferable in meeting time constraints, however, its success is subject to users’ acceptance. Previous studies highlight human challenge as the most important barrier in the implementation of an ICT-based training system. Users tend to show resistance in using new technology and online approaches. They favour the traditional way such as the face-to-face method of training. This paper presents the results of a study conducted to assess the acceptance of a web-based training by public sector employees. The study applied the Unifi ed Theory of Acceptance and Use Technology (UTAUT) with the focus on three system characteristics; system flexibility, system enjoyment, and system interactivity. A total of 290 employees from the Jordanian Public Sector participated in the study. The fi ndings revealed that system fl exibility and system enjoyment have direct effects while system interactivity has an indirect effect on the employees’ intention to use the web-based training system. In addition, system flexibility is proven to have the strongest relationship to users’ intention to use the web-based training system.

 

References

http://jict.uum.edu.my/ Abbad, M. M., Morris, D., & Nahlik, C. (2009). Looking under the Bonnet: Factors affecting student adoption of e-Learning Systems in Jordan. International Review of Research in Open and Distance Learning, 10(2).

Advance Learning (2008). ICDL in the Middle East. Retrieved from http://www.eu.advancelearning.com

Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl, & J. Beckman (Eds.), Action-control: From cognition to behaviour (pp. 11−39). Heidelberg: Springer.

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179−211.

Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behaviour. New Jersey: Prentice-Hall.

Al-zahrani, M. E., & Goodwin, R. D. (2012).Towards a UTAUT-based model for the study of e government citizen acceptance in Saudi Arabia. World Academy of Science, Engineering and Technology, 64, 8−14.

Al-Rawashdeh, T. A. M. (2011). The extended UTAUT acceptance model of computer-based distance training system among public sector’s employees in Jordan (Unpublished doctoral dissertation). Universiti Utara Malaysia.

Bollen, K. A., & Laing, J. (1988). Some properties of Hoelter’s CN. Sociological Methods and Research, 16, 492−503.

Bollen, P. M. (1998). Structural equations with latent variables. New York: John Wiley & Sons.

Brown, K. G. (2001). Using computers to deliver training: Which employees learn and why? Personnel Psychology, 54(1), 271−296.

Browne, M. W., & Cudeck, R. (1993). Alternative ways of assessing model fit. In K. A. Bollen, Long testing structural equation models (pp. 136−162). Newbury Park, CA: Sage Publication.

Chatzoglou, P. D., Sarigiannidis, L., Vraimaki, E., & Diamantidis, E. (2009). Investigating Greek employees’ intention to use web-based training. Computers & Education, 53, 877–889. Journal of ICT, 13, 2014, pp: 87–

Chesney, T. (2006). An acceptance model for useful and fun information system. Interdisciplinary Journal of Humans in ICT Environment, 2(2), 225−235.

Conci, M., Pianesi, F., & Zancanaro, M. (2009). Useful, social and enjoyable: Mobile phone adoption by older people. Human-Computer Interaction – INTERACT 2009, Springer, 5726, 63−76. http://jict.uum.edu.my/

Dadayan, L., & Ferro, E. (2005). When technology meets the mind: A comparative study of the Technology Acceptance Model. International Conference on Electronic Government, 3591,137−144.

Davis, F. (1989). Perceived usefulness, perceived ease of use, and user acceptance. MIS Quarterly, Sep, 13(3), 318−323.

Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate data analysis (7th ed.). New Jersey: Pearson Education.

Hsia, J. W., & Tseng, A. H. (2008). An enhanced Technology Acceptance Model for e-learning systems in high-tech companies in Taiwan: Analyzed by structural equation modeling (pp. 39−44). International Conference on Cyberworlds.

Harfoushi, O., & Obiedat, R. (2013). E-training acceptance factors in business organizations. International Journal of Emerging Technologies in Learning, 6(2), 15−18.

ICDL US (2009). ICDL foundation. Retrieved from http://www.icdlus.com

Ivanovic, S., Mikinac, K., & Perman, L. (2011). CRM development in hospitality companies for the purpose of increasing the competitiveness in the tourist market. Journal of Economics, 2(1), 59–68.

Lim, B. C., Kian, H. S., & Kock, T. W. (2008). Acceptance of e-learning among distance learners: A Malaysian perspective. Proceedings of Ascilite Melbourne 2008, 541−551.

Marchewka, J., Liu, C., & Kostiwa, K. (2007). An application of the UTAUT model for understanding student perceptions using course management software. Communications of the IIMA, 7(2).

Najafabadi, M. O, Hosseini, S. J. F., & Mirdamadi, S. M. (2009). An ordinal factor analysis of requirements and challenges of information and communication technology system to train private agricultural insurance brokers in Iran. Journal of Information and Communication Technology, 8, 103−114.

Naidu, S. (2003). E-learning: A guidebook of principles, procedures and practices. Commonwealth of Learning. Commonwealth Educational Media Centre for Asia. Journal of ICT, 13, 2014, pp: 87–

Nanayakkara, C. (2005). A model of user acceptance of learning management systems: A study within tertiary institutions in New Zealand. International Journal of Learning, 13(12), 223−232.

Rogers, E. M. (1983). Diffusion of innovations (3rd ed.). New York: Free Press.

Sahin, I., & Shelley, M. (2008). Considering students’ perceptions: The http://jict.uum.edu.my/ distance education student satisfaction model. Educational Technology & Society, 11(3), 216–223.

Sheng, Z., Jue, Z., & Weiwei, T. (2008). Extending TAM for online learning systems: An intrinsic motivation perspective. Tsinghua Science and Technology, 13(3), 312−317.

Smith, T. D., & McMillan, B. F. (2001). A primer of model fit indices in structural equation model. Paper presented at the annual meeting of the southwest educational research association, February 1−3, New Orleans, LA.

Tan, S. (2011). How to increase your IT project success rate. Gartner Research: ID Number G00209668.

Taylor, S., & Todd, P. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144−176.

Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 124−143.

Venkatesh, V., & Morris, M.G. (2000). Why don’t men ever stop to ask for direction? Gender, social influence, and their role in technology acceptance and usage behavior. MIS Quarterly, 24(1), 115−139.

Venkatesh, V., Morris, M. G., Davis, G. B., K., & Davis, F., D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425−478.

Walczak, S., & Scott, J. E. (2009). Cognitive engagement with a multimedia ERP training tool: Assessing computer self-efficacy and technology acceptance. Information and Management, 46, 221−232.

Wang, T. S., & Jong, D. (2009). Students acceptance of web-based learning system. 2009 International Symposium on Web Information System and Application, 533−536.

Zikmund, W., G. (2003). Business research methods (7th ed.). Mason: Thomson/South-Western.

Downloads

Published

19-02-2014

How to Cite

Ibrahim, H., & AL-Rawashdeh, T. A. (2014). Acceptance of Web-Based Training System Among Public Sector Employees. Journal of Information and Communication Technology, 13, 87-107. https://doi.org/10.32890/jict2014.13.5

Research impact

Harvested 2026-09-06
0 citations recorded so far

Counts differ between services because each indexes a different body of literature. None of them is the whole picture.

Identifiers DOI 10.32890/jict2014.13.5

Most read articles by the same author(s)