ADOPTION OF MOBILE WEB AMONG UNIVERSITY STUDENTS IN MALAYSIA: A REVIEW
DOI:
https://doi.org/10.32890/jtom2017.12.1.2Keywords:
Mobile web, mobile technology, mobile devicesAbstract
This paper reviews major issues of mobile technology and mobile web usage among university students, including characteristics, importance and problems faced by university students when accessing web sites through mobile devices. This article also reviews the technology adoption models/theories that will best explain the adoption of IT/IS. The author identified Technology Acceptance Model (TAM) as the best model in explaining adoption of mobile web because TAM is the most suitable in explaining behavioural intention in the context of mobile devices. Mobile Web is the World Wide Web which is accessed through a mobile device such as laptop computer, smart phone or tablet. It establishes the entirety of the Internet and is not limited to webpages which have been specifically designed to be viewed through mobile devices. Distinctive features of mobile technology especially mobile web technology and its progressive impacts on information transfer and learning process has created many educational opportunities for higher education institutions. Although mobile devices are highly flexible, accessible and convenient, students are still facing great problems when they use mobile web for educational purpose.
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References
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Dillon, A., & Morris, M. G. (1996). User acceptance of new information technology: theories and models. Annual Review of Information Science and Technology, Vol. 31, 3–32.
Ferdousi, B., & Bari, J. (2015). Infusing Mobile Technology into Undergraduate Courses for Effective Learning. Procedia - Social and Behavioral Sciences, 176, 307–311. http://doi.org/10.1016/j.sbspro.2015.01.476
Fernandes, N., Rodrigues, A., Duarte, C., Hijon-Neira, R., & Carrico, L. (2014). Web Accessibility of Mobile and Desktop Representations. In Proceedings of BCS HCI (pp. 1–8).
Fernández-López, Ã., RodrÃguez-Fórtiz, M. J., RodrÃguez-Almendros, M. L., & MartÃnez-Segura, M. J. (2013). Mobile learning technology based on iOS devices to support students with special education needs. Computers & Education, 61, 77–90. http://doi.org/10.1016/j.compedu.2012.09.014
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
Goggin, G. (2012). Cell phone culture: Mobile technology in everyday life. Routledge.
Heo, J., Ham, D.-H., Park, S., Song, C., & Yoon, W. C. (2009). A framework for evaluating the usability of mobile phones based on multi-level, hierarchical model of usability factors. Interacting with Computers, 21(4), 263–275. http://doi.org/10.1016/j.intcom.2009.05.006
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Martin, F., Pastore, R., & Snider, J. (2012). Developing Mobile Based Instruction. TechTrends, 56(5), 46–51. http://doi.org/10.1007/s11528-012-0598-9
Moon, J., & Kim, Y. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38, 217–230. Retrieved from http://www.sciencedirect.com/science/article/pii/S0378720600000616
Park, E., & Ohm, J. (2014). Factors influencing users’ employment of mobile map services. Telematics and Informatics, 31(2), 253–265. http://doi.org/10.1016/j.tele.2013.07.002
Pollara, P. (2011). Mobile Learning in Higher Education: A Glimpse and a Comparison of Student and Faculty Readiness, Attitudes and Perceptions. Louisiana State University.
Raman, J. (2015). Mobile technology in nursing education: where do we go from here? A review of the literature. Nurse Education Today. http://doi.org/10.1016/j.nedt.2015.01.018
Razaque, A., & Elleithy, K. (2012). Interactive Prototypes for Mobile Collaborative Learning (MCL) to Substantiate Pedagogical Activities. International Journal of Interactive Mobile Technologies, 6(1), 16–24. http://doi.org/10.3991/ijim.v6i1.1808
Reychav, I., Dunaway, M., & Kobayashi, M. (2015). Understanding mobile technology-fit behaviors outside the classroom. Computers & Education, 87, 142–150. http://doi.org/10.1016/j.compedu.2015.04.005
Rogers, E. M. (1983). Diffusion of Innovtions. In Diffusion of innovations (Third edit). New York: The free press. Retrieved from http://hollis.harvard.edu/?itemid=%7Clibrary/m/aleph%7C006256656
Roudaki, A., Kong, J., & Yu, N. (2015). A classification of web browsing on mobile devices. Journal of Visual Languages & Computing, 26, 82–98. http://doi.org/10.1016/j.jvlc.2014.11.010
Tan, G. W.-H., Ooi, K.-B., Leong, L.-Y., & Lin, B. (2014). Predicting the drivers of behavioral intention to use mobile learning: A hybrid SEM-Neural Networks approach. Computers in Human Behavior, 36, 198–213. http://doi.org/10.1016/j.chb.2014.03.052
Taylor, S., & Todd, P. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144–176.
Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2), 273–315. http://doi.org/10.1111/j.1540-5915.2008.00192.x
Venkatesh, V., & Davis, F. D. (2000). A Theoretical Acceptance Extension Model : Field Four Studies of the Technology Longitudinal. Management Science, 46(2), 186–204.
Venkatesh, V., & Morris, G. M. (2000). Why don’t men ever stop to ask for direction? Gender, social influence and their role in technology acceptance and usage behaviour. MIS Quarterly, 24(1), 115–137.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. Management Information Systems, 27(3), 425–478.
Wangpipatwong, S., Chutimaskul, W., & Papasratorn, B. (2008). Understanding citizen’s continuance intention to use e-government website: A composite view of technology acceptance model and computer self-efficacy. Electronic Journal of E-Government, 6(1), 55–64. Retrieved from http://unpan1.un.org/intradoc/groups/public/documents/apcity/unpan045451.pdf
Weiss, S. (2002). Handheld Usability. John Wiley & Sons.
Wu, C.-S., Cheng, F.-F., Yen, D. C., & Huang, Y.-W. (2011). User acceptance of wireless technology in organizations: A comparison of alternative models. Computer Standards & Interfaces, 33(1), 50–58. http://doi.org/10.1016/j.csi.2010.03.002
Yu, N., & Kong, J. (2015). User experience with web browsing on small screens: Experimental investigations of mobile-page interface design and homepage design for news websites. Information Sciences. http://doi.org/10.1016/j.ins.2015.06.004
Ajzen, I. (1991). The Theory of Planned Behavior. Organizational Behavior and Human Decision Processes, 50, 179–211.
Al-Khalifa, H. S. (2014). A framework for evaluating university mobile websites. Online Information Review, 38(2), 166–185. http://doi.org/10.1108/OIR-12-2012-0231
Al-najjar, G. M. (2012). Mobile Information Systems: An Empirical Analysis of the Determinants of Mobile Commerce Acceptance in Jordan. Universiti Utara Malaysia.
Alzaza, N. S. (2012). Mobile Learning Services Acceptance Model among Malaysian Higher Education Students. Universiti Utara Malaysia.
Babu, B. R., Jeyshankar, R., & Rao, P. N. (2010). Websites of Central Universities in India: A Webometric Analysis. DESIDOC Journal of Library & Information Technology, 30(4), 33–43. http://doi.org/10.14429/djlit.30.458
Churchill, D., Fox, B., & King, M. (2012). Study of Affordances of iPads and Teachers’ Private Theories. International Journal of Information and Education Technology, 2(3), 251–254. http://doi.org/10.7763/IJIET.2012.V2.122
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quaterly, 13(3), 319–340.
Dillon, A., & Morris, M. G. (1996). User acceptance of new information technology: theories and models. Annual Review of Information Science and Technology, Vol. 31, 3–32.
Ferdousi, B., & Bari, J. (2015). Infusing Mobile Technology into Undergraduate Courses for Effective Learning. Procedia - Social and Behavioral Sciences, 176, 307–311. http://doi.org/10.1016/j.sbspro.2015.01.476
Fernandes, N., Rodrigues, A., Duarte, C., Hijon-Neira, R., & Carrico, L. (2014). Web Accessibility of Mobile and Desktop Representations. In Proceedings of BCS HCI (pp. 1–8).
Fernández-López, Ã., RodrÃguez-Fórtiz, M. J., RodrÃguez-Almendros, M. L., & MartÃnez-Segura, M. J. (2013). Mobile learning technology based on iOS devices to support students with special education needs. Computers & Education, 61, 77–90. http://doi.org/10.1016/j.compedu.2012.09.014
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading, MA: Addison-Wesley.
Goggin, G. (2012). Cell phone culture: Mobile technology in everyday life. Routledge.
Heo, J., Ham, D.-H., Park, S., Song, C., & Yoon, W. C. (2009). A framework for evaluating the usability of mobile phones based on multi-level, hierarchical model of usability factors. Interacting with Computers, 21(4), 263–275. http://doi.org/10.1016/j.intcom.2009.05.006
Hsieh, J.-K., Hsieh, Y.-C., Chiu, H.-C., & Yang, Y.-R. (2014). Customer Response to Web Site Atmospherics: Task-relevant Cues, Situational Involvement and PAD. Journal of Interactive Marketing, 28(3), 225–236. http://doi.org/10.1016/j.intmar.2014.03.001
Huff, K. C. (2015). The comparison of mobile devices to computers for web-based assessments. Computers in Human Behavior, 49, 208–212. http://doi.org/10.1016/j.chb.2015.03.008
Johnson, T., & Seeling, P. (2013). Desktop and Mobile Web Page Comparison: Characteristics, Trends, and Implications. Communications Magazine, IEEE, 1–14. Retrieved from http://arxiv.org/abs/1309.1792
Kroski, E. (2008). On the Move with the Mobile Web: Libraries and Mobile Technologies. Library technology reports (Vol. 44). Retrieved from http://eprints.rclis.org/15024/1/mobile_web_ltr.pdf
Lin, J. C.-C., & Lu, H. (2000). Towards an understanding of the behavioural intention to use a web site. International Journal of Information Management, 20(3), 197–208. http://doi.org/10.1016/S0268-4012(00)00005-0
Male, G., & Pattinson, C. (2011). Enhancing the quality of e-learning through mobile technology: A socio-cultural and technology perspective towards quality e-learning applications. Campus-Wide Information Systems, 28(5), 331–344. http://doi.org/10.1108/10650741111181607
Martin, F., Pastore, R., & Snider, J. (2012). Developing Mobile Based Instruction. TechTrends, 56(5), 46–51. http://doi.org/10.1007/s11528-012-0598-9
Moon, J., & Kim, Y. (2001). Extending the TAM for a World-Wide-Web context. Information & Management, 38, 217–230. Retrieved from http://www.sciencedirect.com/science/article/pii/S0378720600000616
Park, E., & Ohm, J. (2014). Factors influencing users’ employment of mobile map services. Telematics and Informatics, 31(2), 253–265. http://doi.org/10.1016/j.tele.2013.07.002
Pollara, P. (2011). Mobile Learning in Higher Education: A Glimpse and a Comparison of Student and Faculty Readiness, Attitudes and Perceptions. Louisiana State University.
Raman, J. (2015). Mobile technology in nursing education: where do we go from here? A review of the literature. Nurse Education Today. http://doi.org/10.1016/j.nedt.2015.01.018
Razaque, A., & Elleithy, K. (2012). Interactive Prototypes for Mobile Collaborative Learning (MCL) to Substantiate Pedagogical Activities. International Journal of Interactive Mobile Technologies, 6(1), 16–24. http://doi.org/10.3991/ijim.v6i1.1808
Reychav, I., Dunaway, M., & Kobayashi, M. (2015). Understanding mobile technology-fit behaviors outside the classroom. Computers & Education, 87, 142–150. http://doi.org/10.1016/j.compedu.2015.04.005
Rogers, E. M. (1983). Diffusion of Innovtions. In Diffusion of innovations (Third edit). New York: The free press. Retrieved from http://hollis.harvard.edu/?itemid=%7Clibrary/m/aleph%7C006256656
Roudaki, A., Kong, J., & Yu, N. (2015). A classification of web browsing on mobile devices. Journal of Visual Languages & Computing, 26, 82–98. http://doi.org/10.1016/j.jvlc.2014.11.010
Tan, G. W.-H., Ooi, K.-B., Leong, L.-Y., & Lin, B. (2014). Predicting the drivers of behavioral intention to use mobile learning: A hybrid SEM-Neural Networks approach. Computers in Human Behavior, 36, 198–213. http://doi.org/10.1016/j.chb.2014.03.052
Taylor, S., & Todd, P. (1995). Understanding information technology usage: A test of competing models. Information Systems Research, 6(2), 144–176.
Venkatesh, V., & Bala, H. (2008). Technology Acceptance Model 3 and a Research Agenda on Interventions. Decision Sciences, 39(2), 273–315. http://doi.org/10.1111/j.1540-5915.2008.00192.x
Venkatesh, V., & Davis, F. D. (2000). A Theoretical Acceptance Extension Model : Field Four Studies of the Technology Longitudinal. Management Science, 46(2), 186–204.
Venkatesh, V., & Morris, G. M. (2000). Why don’t men ever stop to ask for direction? Gender, social influence and their role in technology acceptance and usage behaviour. MIS Quarterly, 24(1), 115–137.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. Management Information Systems, 27(3), 425–478.
Wangpipatwong, S., Chutimaskul, W., & Papasratorn, B. (2008). Understanding citizen’s continuance intention to use e-government website: A composite view of technology acceptance model and computer self-efficacy. Electronic Journal of E-Government, 6(1), 55–64. Retrieved from http://unpan1.un.org/intradoc/groups/public/documents/apcity/unpan045451.pdf
Weiss, S. (2002). Handheld Usability. John Wiley & Sons.
Wu, C.-S., Cheng, F.-F., Yen, D. C., & Huang, Y.-W. (2011). User acceptance of wireless technology in organizations: A comparison of alternative models. Computer Standards & Interfaces, 33(1), 50–58. http://doi.org/10.1016/j.csi.2010.03.002
Yu, N., & Kong, J. (2015). User experience with web browsing on small screens: Experimental investigations of mobile-page interface design and homepage design for news websites. Information Sciences. http://doi.org/10.1016/j.ins.2015.06.004
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Published
27-06-2017
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Thaneshan, L., Yamin, F. M., & Othman, S. N. (2017). ADOPTION OF MOBILE WEB AMONG UNIVERSITY STUDENTS IN MALAYSIA: A REVIEW. Journal of Technology and Operations Management, 12(1), 11–20. https://doi.org/10.32890/jtom2017.12.1.2
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