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International Journal of Science Annals, Vol. 6, No. 2, 2023
рrint ISSN: 2617-2682; online ISSN: 2707-3637; DOI:10.26697/ijsa

challenges of cloud computing in performance Kalema, B. M. (2022). Developing countries’
augmentation for pervasive computing [Paper continuance usage of e-services after COVID-19
presentation]. 2020 International Conference on in the 4IR era. In H. Twinomurinzi, N. Msweli, &
Electrical, Communication and Computer T. Mawela (Eds.), Proceedings of NEMISA
Engineering (ICECCE). Istanbul, Turkey. Summit and Colloquium 2022: Vol. 4. The Future
https://doi.org/10.1109/ICECCE49384.2020.9179462 of Work and Digital Skills (pp. 1-11). EasyChair.
Adler-Milstein, J., DesRoches, C. M., Kralovec, P., https://doi.org/10.29007/2cdm
Foster, G., Worzala, C., Charles, D., Searcy, T., & Katuu, S. (2018). Healthcare systems: Typologies,
Jha, A. K. (2015). Electronic health record framework models, and South Africa’s health
adoption in US hospitals: Progress continues, but sector. International Journal of Health
challenges persist, health affairs, 34(12), 2174- Governance, 23(2), 134-148,
2180. https://doi.org/10.1377/hlthaff.2015.0992 https://doi.org/10.1108/IJHG-10-2017-0054
Alipour, J., Mehdipour. Y., Karimi, A., & Sharifian, R. Khan, F. A., Alia, A., Abbas, H., & Haldar, N. H. (2014).
(2021). Affecting factors of cloud computing A cloud-based health care framework for security
adoption in public hospitals affiliated with and patients’ data privacy using wireless body
Zahedan University of Medical Sciences: A cross- area networks. Procedia Computer Science, 34,
sectional study in the Southeast of Iran. Digital 511–517. https://doi.org/10.1016/j.procs.2014.07.058
Health, 7. Maphumulo, W. T., & Bhengu, B. R. (2019). Challenges
https://doi.org/10.1177/20552076211033428 of quality improvement in the health care of South
Babbie, E. R. (2016). The practice of social research Africa post-apartheid: A critical review.
(14th ed.). Cengage Learning. Curationis, 42(1), Article 1901.
https://www.worldcat.org/title/The-practice-of- https://doi.org/10.4102/curationis.v42i1.1901
social-research/oclc/899217794 Massyn, N., Barron, P., Day, C., Ndlovu, N., &
Cohen, L., Manion, L., Morrison, K., & Morrison, R. B. Padarath, A. (Eds.). (2020). District health
(2018). Research methods in education (8th ed.). barometer 2018/19. Health Systems Trust.
Routledge. https://doi.org/10.4324/9781315456539 https://www.hst.org.za/publications/Pages/DIST
De Pietro, R., Wiarda, E., & Fleischer, M. (1990). The RICT-HEALTH-BAROMETER-201819.aspx
context for change: Organization, technology, and Rahim, N. N. A., Humaidi, N., Aziz, S. R. A., &
environment. In L. G. Tornatzky & M. Fleischer Zain, N. H. M. (2022). Moderating effect of
(Eds.), The processes of technological innovation technology readiness towards open and distance
(pp. 151-175). Lexington Books. learning (ODL) technology acceptance during
Djock, E. (2023). Trends & technologies shaping the COVID-19 pandemic. Asian Journal of
future of the ICT industry. ITONICS. University Education, 18(2), 406-421.
https://www.itonics-innovation.com/blog/trends- https://doi.org/10.24191/ajue.v18i2.17995
and-technologies-ict-industry Rahman, A.A.L., Islam, S., Kalloniatis, C., & Gritzalis,
Heale, R., & Twycross, A. (2015). Validity and reliability S. (2017). A risk management approach for a
in quantitative studies. Evidence-Based Nursing, sustainable cloud migration. Journal of Risk and
18(3), 66-67. https://doi.org/10.1136/eb-2015-102129 Financial Management, 10(4), Article 20.
Idoga, P. E., Toycan, M., Nadiri, H., & Celebi, E., (2019). https://doi.org/10.3390/jrfm10040020
Assessing factors militating against the Sadoughi, F., Ali, O., & Erfannia, L. (2020). Evaluating
acceptance and successful implementation of a the factors that influence cloud technology
cloud based health center from the healthcare adoption-comparative case analysis of health and
professionals’ perspective: A survey of hospitals non-health sectors: A systematic review. Health
in Benue state, northcentral Nigeria. BMC Informatics Journal, 26(2), 1363–1391.
Medical Informatics and Decision Making, 19, https://doi.org/10.1177/1460458219879340
Article 34 https://doi.org/10.1186/s12911-019-0751-x Singh, D., Sinha, S., & Thada, V. (2022). A novel
Kalema, B. M. (2013, August 29-31). The role of attribute based access control model with
moderating factors in ERP systems usage. 2013 application in IaaS cloud. Journal of Integrated
Third International Conference on Innovative Science and Technology, 10(2), 79-86.
Computing Technology (INTECH 2013) (pp. 166- https://www.pubs.iscience.in/journal/index.php/ji
172). IEEE. st/article/view/1424
https://doi.org/10.1109/INTECH.2013.6653699 Tripathi, S. (2018). Moderating effects of age and
Kalema, B. M., & Busobozi, V. V. (2020). Big data experience on the factors influencing the actual
analytics for data quality improvement to enhance usage of cloud computing. Journal of
evidence-based health care in developing International Technology and Information
countries. In M. Pant, T. Sharma, S. Basterrech, Management, 27(2), 121-158.
& C. Banerjee (Eds.), Performance of Integrated https://doi.org/10.58729/1941-6679.1373
Systems and Its Software Engineering Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer
Applications. Asset Analytics (pp. 29-42). acceptance and use of information technology:
Springer. https://doi.org/10.1007/978-981-13- Extending the unified theory of acceptance and
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