Gender Effect on Cloud Computing Services Adoption by University Students: Case Study of Saudi Arabia

Abdulwahab Ali Almazroi, Eltahir Kabbar, Muawya Naser, Haifeng Shen


Cloud computing is a state of the art technology that provides services to individuals and organizations on demand via the Internet. Implementation of cloud services in an organization will lead to improved performance and reduced cost related to computing services. A number of previous studies suggest that there is a need to further investigate the role of gender on the adoption of cloud computing, especially in developing countries. The aim of this paper is to investigate the role of gender in the adoption of cloud computing services by university students in KSA. To meet the research objective an SEM study was conducted using responses from 451 Saudi higher education students to determine the role of gender on could computing acceptance in KSA context. The findings of this research show that there is a settle difference between female and male students where trust was found to be a significant determinant of behavioural intention for female students but not for their male counterparts. On the other hand, image was found to be a significant determinant of PU for male students but not for female students.


Cloud Computing; University Students; Acceptance Model; TAM; Higher education students

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Abu-Shanab, E., & Qasem, H. (2014). Cloud computing adoption: Brand equity impact on users’ choice. Saba Journal of Information Technology and Networking, 2(2), 63-80.

Agarwal, R., & Prasad, J. (1999). Are individual differences germane to the acceptance of new information technologies?. Decision Sciences, 30(2), 361-391.

Agudo-Peregrina, Á. F., Hernández-García, Á., & Pascual-Miguel, F. J. (2014). Behavioral intention, use behavior and the acceptance of electronic learning systems: Differences between higher education and lifelong learning. Computers in Human Behavior, 34, 301-314.

Al-Gahtani, S. S. (2004). Computer Technology Acceptance Success Factors in Saudi Arabia: An Exploratory Study. Journal of Global Information Technology Management, 7(1), 5-29. doi:10.1080/1097198X.2004.10856364

Al-Gahtani, S. S. (2014). Empirical investigation of E-learning acceptance and assimilation: A structural equation model. Applied Computing and Informatics, 12(1), 27-50.

Al-Jabri, I. M. (2014). The perceptions of adopters and non-adopters of cloud computing: Application of technology-organization-environment framework. Paper presented at the 14th International Conference on Electronic Business, Taipei, Taiwan.

AlCattan, R. F. (2014). Integration of cloud computing and web 2.0 collaboration technologies in E-learning. International Journal of Computer Trends and Technology 12(1), 46-55.

Alenezi, A. R., Karim, A., Malek, A., & Veloo, A. (2010). An empirical investigation into the role of enjoyment, computer anxiety, computer self-efficacy and internet experience in influencing the students' intention to use E-learning: A case study from Saudi Arabian governmental universities. Turkish Online Journal of Educational Technology, 9(4), 22-34.

Alhammadi, A., Stanier, C., & Eardley, A. (2015). The determinants of cloud computing adoption in Saudi Arabia. Paper presented at the Second International Conference on Computer Science & Engineering, Dubai, United Arab Emirates.

Alharbi, S. T. (2012). Users’ acceptance of cloud computing in Saudi Arabia: An extension of technology acceptance model. International Journal of Cloud Applications and Computing 2(2), 1-11.

Alharbi, S. T. (2014). Trust and acceptance of cloud computing: A revised UTAUT model. Paper presented at the 2014 International Conference on Computational Science and Computational Intelligence, Las Vegas, Nevada, USA.

Alotaibi, M. B. (2014). Exploring users’ attitudes and intentions toward the adoption of cloud computing in Saudi Arabia: An empirical investigation. Journal of Computer Science, 10(11), 2315-2329.

Alsaeed, N., & Saleh, M. (2015). Towards cloud computing services for higher educational institutions: Concepts & literature review. Paper presented at the 2015 International Conference on Cloud Computing (ICCC), Riyadh, Saudi Arabia.

Alsanea, M., & Wainwright, D. (2014). Identifying the determinants of cloud computing adoption in a government sector – A case study of Saudi organisation. International Journal of Business and Management Studies, 6(2), 29-43.

Alshamaileh, Y. Y. (2013). An empirical investigation of factors affecting cloud computing adoption among SMEs in the north east of England. (PhD thesis), Newcastle University - Newcastle upon Tyne,

Arpaci, I. (2016). Understanding and predicting students' intention to use mobile cloud storage services. Computers in Human Behavior, 58, 150-157.

Behrend, T. S., Wiebe, E. N., London, J. E., & Johnson, E. C. (2011). Cloud computing adoption and usage in community colleges. Behaviour & Information Technology, 30(2), 231-240.

Borgman, H. P., Bahli, B., Heier, H., & Schewski, F. (2013). Cloudrise: Exploring cloud computing adoption and governance with the TOE framework. Paper presented at the 46th Hawaii International Conference on System Sciences, Maui, Hawaii,USA.

Burda, D., & Teuteberg, F. (2014). The role of trust and risk perceptions in cloud archiving— Results from an empirical study. The Journal of High Technology Management Research, 25(2), 172-187.

Cao, Y., Bi, X., & Wang, L. (2013). A study on user adoption of cloud storage service in China: A revised unified theory of acceptance and use of technology model. Paper presented at the 2013 International Conference on Information Science and Cloud Computing Companion, Guangzhou, China.

Carter, L., & Campbell, R. (2011). The impact of trust and relative advantage on internet voting diffusion. Journal of Theoretical and Applied Electronic Commerce Research, 6(3), 28-42.

CDW. (2011). From tactic to strategy: The CDW-G 2011 cloud computing tracking poll. Retrieved from

Chang, S. J., & Im, E.-O. (2014). A path analysis of internet health information seeking behaviors among older adults. Geriatric Nursing, 35(2), 137-141.

Clarke, R. (1999). A primer in diffusion of innovations theory. Retrieved from

Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: Development of a measure and initial test. MIS Quarterly, 19(2), 189-211.

Coursaris, C. K., van Osch, W., & Sung, J. (2013). A "cloud lifestyle": The diffusion of cloud computing applications and the effect of demographic and lifestyle clusters. Paper presented at the 46th Hawaii International Conference on System Sciences, Hawaii, USA.

Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches (3rd ed.): Sage Publications.

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982-1003.

Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1992). Extrinsic and intrinsic motivation to use computers in the workplace. Journal of Applied Social Psychology, 22(14), 1111-1132.

Faqih, K. M., & Jaradat, M.-I. R. M. (2015). Assessing the moderating effect of gender differences and individualism-collectivism at individual-level on the adoption of mobile commerce technology: TAM3 perspective. Journal of Retailing and Consumer Services, 22, 37-52.

González-Martínez, J. A., Bote-Lorenzo, M. L., Gómez-Sánchez, E., & Cano-Parra, R. (2015). Cloud computing and education: A state-of-the-art survey. Computers & Education, 80, 132-151.

Gupta, P., Seetharaman, A., & Raj, J. R. (2013). The usage and adoption of cloud computing by small and medium businesses. International Journal of Information Management, 33(5), 861-874.

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

Hashim, H. S., Hassan, Z. B., & Hashim, A. S. (2015). Factors influence the adoption of cloud computing: A comprehensive review. International Journal of Education and Research, 3(7), 295-306.

Heinssen, R. K., Glass, C. R., & Knight, L. A. (1987). Assessing computer anxiety: Development and validation of the computer anxiety rating scale. Computers in Human Behavior, 3(1), 49-59.

Hew, T.-S., & Kadir, S. L. S. A. (2016). Predicting the acceptance of cloud-based virtual learning environment: The roles of self determination and channel expansion theory. Telematics and Informatics, 33(4), 990-1013.

Huang, T. C.-K., Liu, C.-C., & Chang, D.-C. (2012). An empirical investigation of factors influencing the adoption of data mining tools. International Journal of Information Management, 32(3), 257-270.

Ibrahim, M. S., Salleh, N., & Misra, S. (2015). Empirical studies of cloud computing in education: A systematic literature review. Paper presented at the The 15th International Conference on Computational Science and Its Applications, Alberta, Canada.

Irshad, M. B. M., & Johar, M. G. M. (2015). A study of undergraduate use of cloud computing applications: Special reference to Google Docs. European Journal of Computer Science and Information Technology, 3(4), 22-32.

Isaila, N. (2014). Cloud computing in education. Knowledge Horizons-Economics, 6(2), 100-103.

Jiang, J. J., Hsu, M. K., Klein, G., & Lin, B. (2000). E‐commerce user behavior model: An empirical study. Human Systems Management, 19(4), 265-276.

Kumar, S., & Murthy, O. (2013). Cloud computing for universities: A prototype suggestion and use of cloud computing in academic institutions. International Journal of Computer Applications, 70(14), 1-6.

Lai, J.-Y., Kan, C.-W., & Ulhas, K. R. (2013). Impacts of employee participation and trust on E-business readiness, benefits, and satisfaction. Information Systems and e-Business Management, 11(2), 265-285.

Li, Y., & Chang, K.-c. (2012). A study on user acceptance of cloud computing: A multi-theoretical perspective. Paper presented at the Eighteenth Americas Conference on Information Systems, Washington, USA.

Liu, J. (2013). E-learning in english classroom: Investigating factors impacting on ESL (english as second language) college students' acceptance and use of the modular object-oriented dynamic learning environment (Moodle). (Master thesis), Iowa State University - Ames, Iowa, USA,

Low, C., Chen, Y., & Wu, M. (2011). Understanding the determinants of cloud computing adoption. Industrial Management & Data Systems, 111(7), 1006-1023.

Mary, M., & Pauline, R. (2004). The impact of trust on the technology acceptance model in business to consumer E-commerce. In K.-P. Mehdi (Ed.), Innovations Through Information Technology (pp. 921-924). London: Idea Group Publishing.

Mathieson, K. (1991). Predicting user intentions: Comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3), 173-191.

Militaru, G., Niculescu, C., & Teaha, C. (2013). Critical success factors for cloud computing adoption in higher education institutions: A theoretical and empirical investigation. Paper presented at the International Conference of Management and Industrial Engineering, Bucharest, Romania.

Ministry of Communications and Information Technology. (2014). $29 billion, the size of Saudi Arabia's investments in cloud. Retrieved from

Ministry of Communications and Information Technology. (2015). Cloud computing gains traction in KSA and UAE. Retrieved from

Mokhtar, S. A., Ali, S. H. S., Al-Sharafi, A., & Aborujilah, A. (2013). Cloud computing in academic institutions. Paper presented at the 7th International Conference on Ubiquitous Information Management and Communication, Kota Kinabalu, Malaysia.

Moore, G. C., & Benbasat, I. (1991). Development of an instrument to measure the perceptions of adopting an information technology innovation. Information Systems Research, 2(3), 192-222.

Nguyen, T. D., Nguyen, T. M., Pham, Q.-T., & Misra, S. (2014). Acceptance and use of E-learning based on cloud computing: The role of consumer innovativeness. Paper presented at the International Conference on Computational Science and Its Applications, Guimarães, Portugal.

Nulty, D. D. (2008). The adequacy of response rates to online and paper surveys: What can be done? Assessment & Evaluation in Higher Education, 33(3), 301-314.

Okai, S., Uddin, M., Arshad, A., Alsaqour, R., & Shah, A. (2014). Cloud computing adoption model for universities to increase ICT proficiency. SAGE Open, 4(3), 215-234.

Opala, O. J., & Rahman, S. M. (2013). An exploratory analysis of the influence of information security on the adoption of cloud computing. Paper presented at the 8th International Conference on System of Systems Engineering, Wailea-Makena, Hawaii, USA.

Pallant, J. (2011). SPSS survival manual: A step by step guide to data analysis using SPSS (4th ed.). Australia: Allen & Unwin.

Park, S.-T., Park, E.-M., Seo, J.-H., & Li, G. (2015). Factors affecting the continuous use of cloud service: Focused on security risks. Cluster Computing, 19(1), 485-495.

Pavlou, P. (2001). Integrating trust in electronic commerce with the technology acceptance model: Model development and validation. Paper presented at the Seventh Americas Conference on Information Systems, Boston, USA.

Pavlou, P. A. (2003). Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model. International Journal of Electronic Commerce, 7(3), 101-134.

Pikkarainen, T., Pikkarainen, K., Karjaluoto, H., & Pahnila, S. (2004). Consumer acceptance of online banking: An extension of the technology acceptance model. Internet Research, 14(3), 224-235.

Ratten, V. (2015). Factors influencing consumer purchase intention of cloud computing in the United States and Turkey: The role of performance expectancy, ethical awareness and consumer innovation. EuroMed Journal of Business, 10(1), 80-97.

Ratten, V. (2016). Continuance use intention of cloud computing: Innovativeness and creativity perspectives. Journal of Business Research, 69(5), 1737-1740.

Rui, G. (2007). Information systems innovation adoption among organizations - A match-based framework and empirical studies. (PhD thesis), National University of Singapore - Singapore,

Sabi, H. M., Uzoka, F.-M. E., Langmia, K., & Njeh, F. N. (2016). Conceptualizing a model for adoption of cloud computing in education. International Journal of Information Management, 36(2), 183-191.

Saunders, M. N., Lewis, P., & Thornhill, A. (2009). Research methods for business students (5th ed.). London: Prentice Hall.

Sekaran, U. (2003). Research methods for business: A skill building approach (4th ed.). USA: John Wiley & Sons, Inc.

Shin, D.-H. (2013). User centric cloud service model in public sectors: Policy implications of cloud services. Government Information Quarterly, 30(2), 194-203.

Tan, M., & Lin, T. T. (2012). Exploring organizational adoption of cloud computing in Singapore. Paper presented at the 19th ITS Biennial Conference, Bangkok, Thailand.

Tan, X., & Kim, Y. (2011). Cloud computing for education: A case of using Google Docs in MBA group projects. Paper presented at the 2011 International Conference on Business Computing and Global Informatization, Shanghai, China.

Tashkandi, A., & Al-Jabri, I. M. (2015). Cloud computing adoption by higher education institutions in Saudi Arabia. Paper presented at the 2015 International Conference on Cloud Computing, Riyadh, Saudi Arabia.

Tashkandi, A. N., & Al-Jabri, I. M. (2015). Cloud computing adoption by higher education institutions in Saudi Arabia: An exploratory study. Cluster Computing, 18(4), 1527-1537.

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

Trenz, M., Huntgeburth, J. C., & Veit, D. (2013). The role of uncertainty in cloud computing continuance: Antecedents, mitigators, and consequences. Paper presented at the 21st European Conference on Information Systems, Utrecht, Netherlands.

Van der Schyff, K., & Krauss, K. E. (2014). Higher education cloud computing in South Africa: Towards understanding trust and adoption issues. South African Computer Journal, 55, 40-55.

Venkatesh, V. (2000). Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model. Information Systems Research, 11(4), 342-365.

Venkatesh, V., & Bala, H. (2008). Technology acceptance model 3 and a research agenda on interventions. Decision Sciences, 39(2), 273-315.

Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186-204.

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

Wang, C.-S., & Huang, Y.-M. (2015). Acceptance of cloud services in face-to-face computer-supported collaborative learning: A comparison between single-user mode and multi-user mode. Innovations in Education and Teaching International, 53(6), 637-648.

White Baker, E., Al‐Gahtani, S. S., & Hubona, G. S. (2007). The effects of gender and age on new technology implementation in a developing country: Testing the theory of planned behavior (TPB). 20(4), 352-375. doi:doi:10.1108/09593840710839798


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