Abstract
This research is one of the first few to investigate the adoption and usage of cloud computing in higher education in the context of developing countries, in this case Thailand. It proposes extending the technology acceptance model to integrate subjective norm, perceived convenience, trust, computer self-efficacy, and software functionality in order to better understand the degree of influence that each has on the adoption of cloud in an educational setting. The instrument development was modified from past studies on technology adoption. Data was collected from two leading universities in Thailand, Mahidol University International College, and Thammasat University. Structural equation modeling was applied to the research, the results of which illustrated that perceived ease of use, perceived usefulness, intention to use, perceived convenience, trust, and software functionality have a statistically positive relationship towards the adoption of cloud computing. However, it is interesting to note that, contrary to most studies, computer self-efficacy and subjective norm did not posit a positive relationship. The research also presents the conclusions, which include a discussion of the findings, the academic and practical implications, and limitations.




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Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: a review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.
Agarwal, R., Sambamurthy, V., & Stair, R. M. (2000). The evolving relationship between general and specific computer self-efficacy: an empirical assessment. Information Systems Research, 11(4), 418–430.
Agarwal, R., & Prasad, J. (1998). A conceptual and operational definition of personal innovativeness in the domain of information technology. Information Systems Research, 9(2), 204–215.
Ajzen, I., & Fishbein, M. (1980). Understanding attitudes and predicting social behavior. Englewood Cliffs: Prentice Hall.
Al-Gahtani, S. (2001). The applicability of TAM outside North America: an empirical test in the United Kingdom. Information Resources Management Journal, 14(3), 37–46.
Amoako-Gyampah, K. (2007). Perceived usefulness, user involvement and behavioral intention: an empirical study of ERP implementation. Computers in Human Behavior, 23(3), 1232–1248.
Asavakovitkorn, K. (2014). Visualization & Cloud Computing. Available at: http://www.cisco.com/web/TH/about/articles/virtualisation.html. Accessed 9 Mar 2014.
Bandura, A. (1986). Social foundations of thought and action. Englewood Cliffs: Prentice Hall.
Bangkok Technology Forum, (2013). Available at: http://www.bangkoktechnologyforum.com/. Accessed 9 Mar 2014.
Bertrand, M., & Bouchard, S. (2008). Applying the technology acceptance model to VR with people who are favorable to its use. Journal of Cyber Therapy & Rehabilitation, 1(2), 200–210.
Bhatiasevi, V., & Krairit, D. (2013). Acceptance of opens source software amongst Thai users: an integrated model approach. Information Development, 29(4), 349–366.
Buyya, R., Yeo, C. S., & Venugopal, S. (2008). Market-oriented cloud computing: Vision, hype, and reality for delivering it services as computing utilities. Future Generation Computer Systems, 25(6), 599–616.
Cantu, A. (2011). The history and future of cloud computing. Available at: http://www.forbes.com/sites/dell/2011/12/20/the-history-and-future-of-cloud-computing/. Accessed Jan 10 2014.
Chang, C. C., Yan, C. F., & Tseng, J. H. (2012). Perceived convenience in an extended technology acceptance model: mobile technology and english learning for college students. Australasian Journal of Educational Technology, 28(5), 809–826.
Chun, W. (2012). What is cloud computing? Available at: https://developers.google.com/appengine/training/intro/whatiscc. Accessed 20 Dec 2013.
Cloud Security Alliance. (2013). Cloud Security Alliance and Electronic Government Agency (EGA) of Thailand partner to drive cloud computing adoption in the Association of Southeast Asian Nations. Available at: https://cloudsecurityalliance.org/media/news/csa-electronic-government-agency-ega-of-thailand-partner/ Accessed 15 Nov 2013.
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: development of a measure and initial test. MIS Quarterly, 19(2), 189–211.
Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13, 319–340.
Davis, F. D., Boozy, R. P., & Warsaw, P. R. (1989). User acceptance of computer technology: a comparison of two theoretical models. Management Science, 35(8), 982–1003.
Dishaw, M. T., & Strong, D. M. (1999). Extending the technology acceptance model with task-technology fit constructs. Information and Management, 36(1), 9–21.
Duffy, J. (2013). The best cloud storage solutions. Available at: http://www.pcmag.com/article2/0,2817,2413556,00.asp. Accessed 2 Feb 2014.
Ercan, T. (2010). Effective use of cloud computing in education institutions. Procedia Social and Behavioral Sciences, 2(2), 938–942.
EGA, e-Government Agency, (n.d.). Government cloud Service. Available at: http://www.ega.or.th/Content.aspx?m_id=94. Accessed 9 Mar 2014.
Fishbein, M., & Ajzen, I. (1975). Belief, attitude, intention and behavior: An introduction to theory and research. Reading: Addison-Wesley.
Fornell, C., & Larcker, D. (1981). Structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
Foster, I., Zhao, Y., Raicu, I., & Lu, S. (2008). Cloud computing and grid computing 360-degree compared. Grid Computing Environments Workshop, 2008, 1–10.
Gefen, D., Straub, D. W., & Boudreau, M. C. (2000). Structural equation modeling and regression: guidelines for research practice. Communication of AIS, 4(7), 2–77.
Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: an integrated model. MIS Quarterly, 27(1), 51–90.
Gerbing, D. W., & Anderson, J. C. (1988). An updated paradigm for scale development incorporating unidimensionality and its assessment. Journal of Marketing Research, 25(2), 186–192.
Guriting, P., & Ndubisi, N. O. (2006). Borneo online banking: evaluating customer perceptions and behavioral intention. Management Research News, 29(1/2), 6–15.
Hair, J. F., Jr., Anderson, R. E., Tatham, R. L., & Black, W. C. (1998). Multivariate data analysis (5th ed.). Upper Saddle River: Prentice Hall.
Hasan, B. (2007). Examining the effects of computer self-efficacy and system complexity on technology acceptance. Information Resources Management Journal, 20(3), 76–88.
Hatcher, L. (1994). A step-by-step approach to using the SAS system for factor analysis and structural equation modeling. Cary: SAS Institute, Inc.
Hsu, C. L., & Lu, H. P. (2004). Why do people play on-line games? An extended TAM with social influences and flow experience. Information and Management, 41(7), 853–868.
Hu, P. J., Chau, P. Y. K., Sheng, O. L., & Tam, K. Y. (1999). Examining the technology acceptance model using physician acceptance of telemedicine technology. Journal of Management Information Systems, 16(2), 91–112.
ISO-IEC 9126–1 (2001) Software engineering – Product quality – Part 1; quality model.
Keesookpun, C., and Mitomo, H. (2012). Cloud computing adoption and determining factors in different industries: A case study of Thailand. In: 19th ITS Biennial Conference 2012, Bangkok, Thailand, 18–21 November 2012.
Kim, H.-B., Kim, T., & Shin, S. W. (2009). Modeling roles of subjective norms and eTrust in customers’ acceptance of airline B2C eCommerce websites. Tourism Management, 30(2), 266–277.
Kim, C., Mirusmonov, M., & Lee, I. (2010). An empirical examination of factors influencing the intention to use mobile payment. Computers in Human Behavior, 26(3), 310–322.
Kim, J. B. (2012). An empirical study on consumer first purchase intention in online shopping: integrating initial trust and TAM. Electronic Commerce Research, 12(2), 125–150.
King, W. R., & He, J. (2006). A meta-analysis of the technology acceptance model. Information and Management, 43(6), 740–755.
Klopping, I. M., & McKinney, E. (2004). Extending the technology acceptance model and the task-technology fit model to consumer e-commerce. Information Technology, Learning, and Performance Journal, 22(1), 35–48.
Kunakornpaiboonsiri, T. (2012). Thai government launches new cloud service. Available at: http://www.futuregov.asia/articles/2012/feb/06/thai-government-launches-new-cloud-service/. Accessed 18 Nov 2013.
Lai, V. S., & Li, H. (2005). Technology acceptance model for Internet banking: an invariance analysis. Information and Management, 42(2), 373–386.
Lee, H., Choi, S. Y., & Kang, Y. S. (2009). Formation of e-satisfaction and repurchase intention: moderating roles of computer self-efficacy and computer anxiety. Expert Systems with Applications, 36(4), 7848–7859.
Lee, K. C., Kang, I., & Kim, J. S. (2007). Exploring the user interface of negotiation support systems from the user acceptance perspective. Computers in Human Behavior, 23(1), 220–239.
Lee, M. (2009). Predicting and explaining the adoption of online trading: an empirical study in Taiwan. Decision Support Systems, 47(2), 133–142.
Lee, Y. C. (2008). The role of perceived resources in online learning adoption. Computers & Education, 50(4), 1423–1438.
Lee, Y.-H., Hsieh, Y.-C., & Ma, C.-Y. (2011). A model of organizational employee’s e-learning systems acceptance. Knowledge-Based Systems, 24(3), 355–366.
Lee, Y., Kozar, K. A., & Larsen, K. R. T. (2003). The technology acceptance model: past, present, and future. Communications of the Association for Information Systems, 12(50), 752–780.
Lederer, A. L., Maupin, D. J., Sean, M. P., & Zhan, Y. (2000). The technology acceptance model and the world wide web. Decision Support Systems, 29(3), 269–282.
Legris, P., Ingham, J., & Collerette, P. (2003). Why people use information technology? A critical review of technology acceptance model. Information and Management, 40(3), 191–204.
Lu, J., Yu, C. S., Liu, C., & Yao, J. E. (2003). Technology acceptance model for wireless Internet. Internet Research: Electronic Networking Applications and Policy, 13(3), 206–219.
Lu, Y., Zhou, T., & Wang, B. (2009). Exploring Chinese users’ acceptance of instant messaging using the theory of planned behavior, the technology acceptance model, and the flow theory. Computers in Human Behavior, 25(1), 392–414.
Luarn, P., & Lin, H.-H. (2005). Toward the understanding of the behavior intention to use mobile banking. Computers in Human Behavior, 21(6), 873–891.
Ma, Q., & Liu, L. (2004). The technology acceptance model: a meta-analysis of empirical findings. Journal of Organizational and End User Computing, 16(1), 59–72.
Mathieson, K. (1991). Predicting user intentions comparing the technology acceptance model with the theory of planned behavior. Information Systems Research, 2(3), 173–191.
McCoy, S., Everard, A., & Jones, B. M. (2005). An examination of the technology acceptance model in Uruguay and the US: a focus on culture. Journal of Global Information Technology Management, 8(2), 27–45.
Mell, P. and Grance, T. (2011). The NIST Definition of Cloud Computing (Draft). National Institute of Standards and Technology Special Publication 800–145.
Moon, J.-W., & Kim, Y.-G. (2001). Extending the TAM for a world-wide-web context. Information and Management, 38(4), 217–230.
Ministry of ICT (2009). The second Thailand Information and Communication Technology Master Plan (2009–2013). Available at: http://www.mict.go.th/download/Master_Plan.pdf. Accessed 21 Jan 2013.
Murah, M. Z. (2011). Teaching and learning cloud computing. Procedia Social and Behavioral Sciences, 59(17), 157–163.
Numnonda, T. (2011a). Public/Private Cloud Security Trend and Awareness, Asia Cloud Computing Association. Available at: http://www.slideshare.net/softwarepark/publicprivate-cloud-securtiy-trends-awareness. Accessed 20 Dec 2013.
Numnonda, T. (2011b). Cloud Computing: Situation in Thailand. Available at: http://www.slideshare.net/softwarepark/cloud-computing-situation-inthailand?utm_source=slideshow02&utm_medium=ssemail&utm_campaign=share_slideshow_loggedout Accessed 21 Dec 2013.
Numnonda, T. (2013a). Cloud Computing: kub karn chain garn nai ong-korn thang thang (Usage in different organizations). Available at: http://www.slideshare.net/thananum/cloud-computing-14525835. Accessed 20 Dec 2013.
Numnonda, T. (2013b). Cloud for M-Learning. Available at: http://www.slideshare.net/imcinstitute/cloud-for-mlearning. Accessed 9 Mar 2014.
Numnonda, T. (2013c). Prayook chai cloud computing sumrub ong-korn (Adapting Cloud Computing for Organization). Available at: http://www.slideshare.net/imcinstitute/cloud-computing-19987871. Accessed 9 Mar 2014.
Nunnally, J. (1978). Psychometric theory. New York: McGraw-Hill.
National Science and Technology development Agency (2013). Yuttakarn Kub Kluen Cloud Computing nai Prathed Thai (Cloud computing strategy in Thailand). Available at: http://www.nstda.or.th/news/10753-nectec. Accessed 9 Mar 2014.
Obe, O. O., & Balogu, V. F. (2007). Practice, trends, and challenges of mobile commerce in Nigeria. Information Technology Journal, 6(3), 448–456.
Okazaki, S., Skapa, R., & Grande, I. G. (2008). Capturing global youth: mobile gaming in the U.S., Spain, and the Czech Republic. Journal of Computer-Mediated Communication, 13(4), 827–855.
Ong, C. S., & Lai, J. Y. (2006). Gender differences in perceptions and relationships among dominants of e-learning acceptance. Computers in Human Behavior, 22(5), 816–829.
Ong, C. S., Lai, J., & Wang, Y. S. (2004). Factors affecting engineers’ acceptance of asynchronous e-learning systems in high-tech companies. Information and Management, 41(6), 795–804.
Pituch, K. A., & Lee, Y. K. (2006). The influence of system characteristic on e-learning use. Computers & Education, 47(2), 222–244.
Pornwasin, A. (2013). SMEs to fuel cloud computing. Available at: http://www.nationmultimedia.com/technology/SMEs-to-fuel-cloud-computing-30200740.html. Accessed 13 Jan 13, 2014.
Roca, J. C., Chiu, C. M., & Martinez, F. J. (2006). Understanding e-learning continuance intention: an extension of the technology acceptance model. International Journal of Human-Computer Studies, 64(8), 683–696.
Rogers, E. M. (1983). Diffusion of innovation (3rd ed.). New York: Free Press.
Rose, G., & Straub, D. (1998). Predicting general IT use: applying TAM to the Arabic World. Journal of Global Information Management, 6(3), 39–46.
Saade, R. G., & Bahli, B. (2005). The impact of cognitive absorption on perceived usefulness and perceived ease of use in on-line learning: an extension of the technology acceptance model. Information and Management, 42(2), 317–327.
Saade, R. G., & Kira, D. (2009). Computer anxiety in e-learning: the effect of computer self-efficacy. Journal of Information Technology Education, 8, 177–191.
Sanchez Franco, M. J. (2010). WebCT – the quasimoderating effect of perceived affective quality on an extending technology acceptance model. Computers & Education, 54(1), 37–46.
Sanchez, R. A., & Hueros, A. D. (2010). Motivational factors that influence the acceptance of moodle using TAM. Computers in Human Behavior, 26(6), 1632–1640.
Sang, S., Lee, J. D., & Lee, J. (2009). E-government adoption in ASEAN: the case of Cambodia. Internet Research, 19(5), 517–533.
Scalater, N. (2009). Cloudworks. eLearning in the Cloud. Available at: http://cloudworks.ac.uk/cloud/view/2430/. Accessed 2 Jan 2013.
Schepers, J., & Wetzels, M. (2007). A meta-analysis of the technology acceptance model: investigating subjective norm and moderation effects. Information and Management, 44(1), 90–103.
Schofield, J. W. (1975). Effect of norms, public disclosure, and need for approval on volunteering behavior consistent with attitudes. Journal of Personality and Social Psychology, 31, 1126–1133.
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.
Shyu, S. H.-P., & Huang, J.-H. (2011). Elucidating usage of e-government learning: a perspective of the extended technology acceptance model. Government Information Quarterly, 28(4), 491–502.
Software Park Thailand, (2014). Available at http://www.swpark.or.th/component/seminar/?task=3&cid=130. Accessed 9 Mar 2014.
Steddum, J. (2013). A brief history of cloud computing. Available at: http://blog.softlayer.com/2013/virtual-magic-the-cloud/. Accessed 12 Jan 2014.
Straub, D. W., Keil, M., & Brenner, W. H. (1997). Testing the technology acceptance model across cultures: a three country study. Information and Management, 33(1), 1–11.
Sultan, N. (2010). Cloud computing for education: a new dawn? International Journal of Information Management, 30(2), 109–116.
SYS-CON Media Inc. (2008). Twenty Experts Define Cloud Computing, Available at: http://cloudcomputing.sys-con.com/read/612375-p. Accessed 15 Jan 2014.
Taylor, S., & Todd, P. A. (1995). Accessing IT usage: the role of prior experience. MIS Quarterly, 19(2), 560–570.
Teo, T., Lim, V., & Lai, R. (1999). Intrinsic and extrinsic motivation in internet usage. OMEGA: International Journal of Management Science, 27(1), 25–37.
Tung, F. C., Chang, S. C., & Chou, C. M. (2008). An extension of trust and TAM model with IDT in the adoption of the electronic logistics information system in HIS in the medical industry. International Journal of Medical Informatics, 77(5), 324–335.
Van Slyke, C., Belanger, F., & Comunale, C. (2004). Factors influencing the adoption of web-based shopping: the impact of trust. The Database for Advances in Information Systems, 35(2), 32–49.
Vaquero, L. M. Rodero-Merino, L. Caceres, J. and Lindner, M. (2009). A Break in the Clouds: Towards a Cloud Definition. ACM Sigcomm Computer Communication Review, 11(4).
Venkatesh, V., & Davis, F. D. (1996). A model of the antecedents of perceived ease of use: development and test. Decision Sciences, 27(3), 451–481.
Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: four longitudinal field studies. Management Science, 46(2), 186–204.
Wang L, Tao J, Kunze M, Castellanos A, Kramer D, and Karl W. (2008). Scientific cloud computing: early definition and experience, The 10th IEEE International Conference on High Performance Computing and Communications, pp. 825–830.
Winkler, V. (J.R.) (2011). Introduction to cloud computing and security. In: Securing the cloud: Cloud Computer Security Techniques and Tactics, 1–27.
Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information and Management, 42(5), 719–729.
Wu, L., & Chen, J. L. (2005). An extension of trust and TAM model with TPB in the initial adoption of on-line tax: an empirical study. International Journal of Human-Computer Studies, 62(6), 784–808.
Yarbrough, A. K., & Smith, T. B. (2007). Technology acceptance among physicians: a new take on TAM. Medical Care Research and Review, 62(6), 650–672.
Yoon, C., & Kim, S. (2007). Convenience and TAM in a ubiquitous computing environment: the case of wireless LAN. Electronic Commerce Research and Applications, 6(1), 102–112.
Yu, J., Ha, I., Choi, M., & Rho, J. (2005). Extending the TAM for t-commerce. Information and Management, 42(7), 965–976.
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This paper was funded by the Mahidol University International College (MUIC) SEED grant.
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Appendix
1.1 Instruction
This questionnaire is to study users’ behavior relating to the acceptance of Dropbox/Google Docs among users. The questionnaire aims at college students who use cloud computing for educational purposes both inside and outside the classroom. Information provided in this questionnaire will be kept confidential by the researcher. The researcher would like to thank the participants for their cooperation and time.
1.1.1 Section 1

1.1.2 Section 2
Please tell us your opinion about Dropbox/Google Docs by indicating whether you agree or disagree with the below statements. Please circle the number (from 1–7) which best represent your opinion where 1 means you strongly disagree with the statement and 7 means you strongly agree with the statement.
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Bhatiasevi, V., Naglis, M. Investigating the structural relationship for the determinants of cloud computing adoption in education. Educ Inf Technol 21, 1197–1223 (2016). https://doi.org/10.1007/s10639-015-9376-6
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DOI: https://doi.org/10.1007/s10639-015-9376-6