Skip to main content
Log in

Cloud computing services adoption among higher education faculties: development of a standardized questionnaire

  • Published:
Education and Information Technologies Aims and scope Submit manuscript

Abstract

Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources including networks, servers, applications, and services. Our aim in this study was to develop and validate an instrument to investigate the determinants of cloud computing services (CCSs) based on Theory of Planned Behavior (TPB). A total of 240 faculty members in a medical university participated in this cross-sectional study. The development of the Theory of Planned Behavior-Cloud Computing Services use Questionnaire (TPB-CCSQ) began with a comprehensive review of literature. Content and construct validity, feasibilityو as well as reliability were assessed. Exploratory factor analysis indicated an optimal reduced solution with 30 items and 5 factors. The factors identified included Attitude toward CCSs use, Perceived Privacy/Security, Perceived Behavioral Control, Intention to use CCSs and Subjective Norms. The measurement model was found to be with a good fit to the data in the assumed model, and all sub-scales were found to be significant within an acceptable range. Our findings demonstrated validity, reliability, simplicity and functionality of the TPB-CCSQ. Information technology researchers, community agencies and educational organizations delivering CCSs may apply this instrument as a practical and useful tool to investigate the cognitive determinants of CCSs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Abdekhoda, M., Ahmadi, M., Dehnad, A., & Hosseini, A. (2014). Information technology acceptance in health information management. Methods of Information in Medicine, 53, 14–20.

    Article  Google Scholar 

  • Abdekhoda, M., Ahmadi, M., Dehnad, A., Noruzi, A., & Gohari, M. (2016). Applying electronic medical records in health care. Applied clinical informatics, 7, 341–354.

    Article  Google Scholar 

  • Abdekhoda, M., & Salih, K. M. (2017). Determinant factors in applying picture archiving and communication systems (PACS) in healthcare. Perspectives in Health Information Management, 14.

  • Aharony, N. (2015). An exploratory study on factors affecting the adoption of cloud computing by information professionals. The Electronic Library, 33, 308–323.

    Article  Google Scholar 

  • Ajzen, I. (1991). The theory of planned behavior. Organizational behavior and decision processes. Massachusetts: Academic Press. Inc.

    Google Scholar 

  • Alharthi, A., Yahya, F., Walters, R. J. & Wills, G. 2015. An overview of cloud services adoption challenges in higher education institutions.

  • Ali, M., Haidar, N., Ali, M. M., & Maryam, A. (2011a). Determinants of seat belt use among drivers in Sabzevar, Iran: A comparison of theory of planned behavior and health belief model. Traffic Injury Prevention, 12, 104–109.

    Article  Google Scholar 

  • Ali, M., Saeed, M. M. S., Ali, M. M., & Haidar, N. (2011b). Determinants of helmet use behaviour among employed motorcycle riders in Yazd, Iran based on theory of planned behaviour. Injury, 42, 864–869.

    Article  Google Scholar 

  • Aljenaa, E., Al-Anzi, F., & Alshayeji, M. (2011). Towards an efficient e-learning system based on cloud computing. In Proceedings of the second Kuwait conference on e-services and e-systems (p. 13). ACM.

  • Alshamaila, Y., Papagiannidis, S., & Li, F. (2013). Cloud computing adoption by SMEs in the north east of England: A multi-perspective framework. Journal of Enterprise Information Management, 26, 250–275.

    Article  Google Scholar 

  • Alshuwaier, F. A., Alshwaier, A. A., & Areshey, A. M. (2012). Applications of cloud computing in education. Computing and networking technology (ICCNT). In 8th international conference on, 2012. IEEE (pp. 26–33).

    Google Scholar 

  • Amoako-Gyampah, K., & Salam, A. F. (2004). An extension of the technology acceptance model in an ERP implementation environment. Information & Management, 41, 731–745.

    Article  Google Scholar 

  • Babazadeh, T., Nadrian, H., Banayejeddi, M., & Rezapour, B. (2016). Determinants of skin cancer preventive behaviors among rural farmers in Iran: An application of protection motivation theory. Journal of Cancer Education, 1–9.

  • Baek, J.-D. (2007). The effect of individual, organizational, and health care system factors on Physicians' information technology use. University of South Carolina.

  • Bhattacherjee, A., & Park, S. C. (2014). Why end-users move to the cloud: A migration-theoretic analysis. European Journal of Information Systems, 23, 357–372.

    Article  Google Scholar 

  • Botts, N., Thoms, B., Noamani, A., & Horan, T. A. (2010). Cloud computing architectures for the underserved: Public health cyberinfrastructures through a network of healthatms. 2010 43rd Hawaii international conference on system sciences (pp. 1–10). IEEE.

  • Buyya, R., Broberg, J., & Goscinski, A. M. (2010). Cloud computing: Principles and paradigms. John Wiley & Sons.

  • Carcary, M., Doherty, E., & Conway, G. (2014). The adoption of cloud computing by Irish SMEs-an exploratory study. Electronic Journal of Information Systems Evaluation, 17, 3.

    Google Scholar 

  • Chandra, D. G. & Borah, M. D. Cost benefit analysis of cloud computing in education. 2012 International Conference on Computing, Communication and Applications (ICCCA), 2012. IEEE, 1–6.

  • Clarke, R. (2010). Computing clouds on the horizon? Benefits and risks from the User's perspective. Bled eConference (Vol. 2).

    Google Scholar 

  • Cox, J. 2017. The world's most valuable brands revealed [Online]. INDEPENDENT. Available: https://www.independent.co.uk/news/business/news/worlds-most-valuable-brands-facebook-google-apple-amazon-a7556571.html. Accessed 2017.

  • 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, 1111–1132.

    Article  Google Scholar 

  • Devon, H. A., Block, M. E., Moyle-Wright, P., Ernst, D. M., Hayden, S. J., Lazzara, D. J., Savoy, S. M., & Kostas-Polston, E. (2007). A psychometric toolbox for testing validity and reliability. Journal of Nursing Scholarship, 39, 155–164.

    Article  Google Scholar 

  • Dignan, L. 2011. Virtualization [Online]. Available: https://www.zdnet.com/article/cloud-computing-market-241-billion-in-2020/ [Accessed].

  • Ding, Q., Li, X., Liu, Y. & Shi, Z. Research on remote collaborative engineering practices for Master of Software Engineering based on cloud computing environment. 2012 IEEE 25th conference on software engineering education and training (CSEE&T), 2012. IEEE, 110–114.

  • El-Ala, N. A., & Awad, W. (2012). Cloud computing for solving E-learning problems. Editorial Preface (p. 3).

    Google Scholar 

  • Gangwar, H., Date, H., & Ramaswamy, R. (2015). Understanding determinants of cloud computing adoption using an integrated TAM-TOE model. Journal of Enterprise Information Management, 28, 107–130.

    Article  Google Scholar 

  • Garrison, G., Rebman, J. R., M, C., & Kim, S. H. (2018). An identification of factors motivating individuals’ use of cloud-based services. Journal of Computer Information Systems, 58, 19–29.

    Article  Google Scholar 

  • Glanz, K., Rimer, B. K., & Viswanath, K. (2008). Health behavior and health education: Theory, research, and practice. John Wiley & Sons.

  • Goldberg, D. P., R, G., Sartorious, N., Ustun, T. B., Piccinelli, M., Gureje, O., & Rutter, C. (1997). The validity of two versions of the GHQ in the WHO study of mental illness in general health care. Psychological Medicine, 27, 191–197.

    Article  Google Scholar 

  • González-Martínez JA, B.-L. M., Gómez-Sánchez E, Cano-Parra R. 2015 Cloud computing and education: A state-of-the-art survey. Computers & Education, 80, 132–151.

  • Gorsuch, R. 1983. Factor analysis.

  • Hamzah, N. H., Mahmud, M., Zukri, S. M., Yaacob, W. F. W. & Yacob, J. The Awareness and Challenges of Cloud Computing Adoption on Tertiary Education in Malaysia. Journal of Physics: Conference Series, 2017. IOP Publishing, 012014.

  • Hippold, S. 2018. Gartner Forecasts Worldwide Public Cloud Revenue [Online]. September 12, 2018. Available: https://www.gartner.com/en/newsroom/press-releases/2018-09-12-gartner-forecasts-worldwide-public-cloud-revenue-to-grow-17-percent-in-2019 [Accessed].

  • Hussein, N. H., & Khalid, A. (2016). A survey of cloud computing security challenges and solutions. International Journal of Computer Science and Information Security, 14, 52.

    Google Scholar 

  • Jiao, B., Wang, H., An, S., & Fang, H. (2011). Research on distance collaborative activities for teacher education based on online video and cloud computing environment. 6th International Conference on Computer Science & Education (ICCSE), 2011. IEEE, 180–185.

  • Kline, R. (2005). Principles and practice of structural equation modeling. New York: 2nd The Guilford Press.

    MATH  Google Scholar 

  • Kumari, M., & Nath, R. (2015). Security concerns and countermeasures in cloud computing paradigm. Fifth International Conference on Advanced Computing & Communication Technologies (ACCT), 2015. IEEE, 534–540.

  • Lawshe, C. (1975). A qualitative approach to content. Personnel Psychology, 28, 63–575.

    Article  Google Scholar 

  • Lease, D. R. 2005. Factors influencing the adoption of biometric security technologies by decision making information technology and security managers.

    Google Scholar 

  • Lin, A., & Chen, N.-C. (2012). Cloud computing as an innovation: Percepetion, attitude, and adoption. International Journal of Information Management, 32, 533–540.

    Article  Google Scholar 

  • 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, 29–39.

    Article  Google Scholar 

  • Mchorney, C. A., & Tarlov, A. R. (1995). Individual-patient monitoring in clinical practice: Are available health status surveys adequate? Quality of Life Research, 4, 293–307.

    Article  Google Scholar 

  • Mell, P., & Grance, T. (2009). The NIST definition of cloud computing. National institute of standards and technology (Vol. 53, p. 50).

    Google Scholar 

  • Menard, P., Gatlin, R., & Warkentin, M. (2014). Threat protection and convenience: Antecedents of cloud-based data backup. Journal of Computer Information Systems, 55, 83–91.

    Article  Google Scholar 

  • Moradzadeh, R., N, M., Nadrian, H., Behrouzi, F., Keshavarz, T., & Golmohammadi, P. (2017). Validity and reliability of the Farsi version of the ECOS-16 questionnaire for females with osteoporosis. Eastern Mediterranean Health Journal., 23, 729–733.

    Article  Google Scholar 

  • Nadrian, H., S, N., Taghdisi, M. H., & Shojaeizadeh, D. (2014). Urban traffic-related determinants of health questionnaire (UTDHQ): An instrument developed for health impact assessments. Medical Journal of the Islamic Republic of Iran, 28, 84–95.

    Google Scholar 

  • Naveen Mishra, E. Z., PETR GORODETSKIY(GARTNER WEBINARS) 2017.

    Google Scholar 

  • Nunnally J. 1994. Psychometric Theory, New York:, Mc Graw-Hill Inc.

  • Orehovački, T., Etinger, D., & Babić, S. (2017). Perceived security and privacy of cloud computing applications used in educational ecosystem. 40th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO), 2017. IEEE, 717–722.

  • Oye, N., Iahad, N., & Rahim, N. A. (2014). The history of UTAUT model and its impact on ICT acceptance and usage by academicians. Education and Information Technologies, 19, 251–270.

    Article  Google Scholar 

  • Pourmajidi, W., Steinbacher, J., Erwin, T., & Miranskyy, A. (2017). On challenges of cloud monitoring. In Proceedings of the 27th annual international conference on computer science and software engineering. IBM Corp (pp. 259–265).

    Google Scholar 

  • Priyadarshinee, P., Raut, R. D., Jha, M. K., & Gardas, B. B. (2017). Understanding and predicting the determinants of cloud computing adoption: A two staged hybrid SEM-neural networks approach. Computers in Human Behavior, 76, 341–362.

    Article  Google Scholar 

  • Pyzik, L. (2012). Remote teaching and new testing method applied in higher education. Human–Computer Systems Interaction: Backgrounds and Applications 2. Springer.

  • 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, 80–97.

    Article  Google Scholar 

  • Safeena, R., Date, H., Hundewale, N., & Kammani, A. (2013). Combination of TAM and TPB in internet banking adoption. International Journal of Computer Theory and Engineering, 5, 146.

    Article  Google Scholar 

  • Sahin, I. (2006). Detailed review of Rogers' diffusion of innovations theory and educational technology-related studies based on Rogers' theory. TOJET: The Turkish Online. Journal of Educational Technology, 5.

  • Shawish, A., & Salama, M. (2014). Cloud computing: Paradigms and technologies. Inter-cooperative collective intelligence: Techniques and applications. Springer.

  • Shiau, W.-L., & Chau, P. Y. (2014a). To use a tree or a forest in behavioral intention. In Proceedings of the 18th Pacific Asia conference on information systems (PACIS 2014). Association for Information Systems (AIS).

  • Shiau, W.-L., & Chau, P. Y. (2014b). To use a tree or a Forest in behavioral intention. PACIS, 248.

  • Shiau, W.-L., & Chau, P. Y. (2016). Understanding behavioral intention to use a cloud computing classroom: A multiple model comparison approach. Information & Management, 53, 355–365.

    Article  Google Scholar 

  • Shih, Y.-Y., & Fang, K. (2004). The use of a decomposed theory of planned behavior to study internet banking in Taiwan. Internet Research, 14, 213–223.

    Article  Google Scholar 

  • Shroff, R. H., & Keyes, C. J. (2017). A proposed framework to understand the intrinsic motivation factors on university students’ behavioral intention to use a mobile application for learning. Journal of Information Technology Education: Research, 16, 143–168.

    Article  Google Scholar 

  • Sultan, N. (2010). Cloud computing for education: A new dawn? International Journal of Information Management, 30, 109–116.

    Article  Google Scholar 

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

    Article  Google Scholar 

  • Thomas, P. (2011). Cloud computing: A potential paradigm for practising the scholarship of teaching and learning. The Electronic Library, 29, 214–224.

    Article  Google Scholar 

  • Thompson, R. L., Higgins, C. A., & Howell, J. M. (1991). Personal computing: Toward a conceptual model of utilization. MIS Quarterly, 15, 125–143.

    Article  Google Scholar 

  • Toopchian, A., S, K., Babazadeh, T., Allahverdipour, H., & Nadrian, H. (2017). Development and psychometric properties of a condom use and its cognitive determinants questionnaire (CUCDQ). Open access Macedonian journal of medical sciences., 15 (p. 79).

    Google Scholar 

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

    Article  Google Scholar 

  • Wang, L., Von Laszewski, G., Younge, A., He, X., Kunze, M., Tao, J., & Fu, C. (2010). Cloud computing: A perspective study. New Generation Computing, 28, 137–146.

    Article  MATH  Google Scholar 

  • Winston, T. G. (2015). An empirical investigation of privacy and security concerns on doctors’ and nurses’ behavioral intentions to use RFID in hospitals. Nova Southeastern University.

  • Yari, A., H, N., Rashidian, H., Nedjat, S., Esmaeilnasab, N., Doroudi, R., & Hoursan, H. (2014). Psychometric properties of the Persian version of social capital questionnaire in Iran. Medical Journal of the Islamic Republic of Iran, 28, 17–27.

    Google Scholar 

Download references

Acknowledgements

The authors acknowledge all participants collaborated in this study.

This study was supported by TUOMS.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mohammadhiwa Abdekhoda.

Ethics declarations

Ethical approval

The ethics committee of the Tabriz University of Medical Sciences reviewed and approved the study protocol (Ethics code: TBZMED.REC.1396.324). All the study participants were informed about the aim of the study and were assured of the privacy of the records. All participants signed a consent form.

Conflict of interest

The authors declare that there is no conflict of interest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Asadi, Z., Abdekhoda, M. & Nadrian, H. Cloud computing services adoption among higher education faculties: development of a standardized questionnaire. Educ Inf Technol 25, 175–191 (2020). https://doi.org/10.1007/s10639-019-09932-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10639-019-09932-0

Keywords

Navigation