PERTANIKA JOURNAL OF SCIENCE AND TECHNOLOGY

Cloud computing in governments has become an attraction to help enhance service delivery. Improving service delivery, productivity, transparency, and reducing costs necessitates governments to use cloud services. Since the publication of a review paper on cloud adoption elements in e-governments in 2015, cloud computing in governments has evolved into discussions of cloud service adoption factors. This paper concentrates on the adoption of cloud computing in governments, the benefits, models, and methodologies utilized, and the analysis techniques. Studies from 2010 up to 2020 have been investigated for this paper. This study has critically peer-reviewed articles that concentrate on cloud computing for electronic governments (e-Governments). It exhibits a systematic evaluation of the empirical studies focusing on cloud adoption studies in e-governments. This review work further categorizes the articles and exhibits novel research opportunities from the themes and unexhausted areas of these articles. From the reviewed articles, it has been observed that most of the articles have employed the quantitative approach, with few utilizing qualitative and mixed-method approaches. The results reveal that cloud computing adoption could help solve problems in learning, such as infrastructure issues, cost issues, and improve service delivery and transparency. This review gives more information on the future directions and areas that need attention, like the trust of cloud computing in e-governments.

• Al-Rawahna, A. S. M., Hung, C. W., & Chen, S. C. (2018). Readiness of government organizations for cloud-computing age: An empirical evidence from Jordan. Journal of Business and Management Sciences, 6(4), 152-162. https://doi.org/10.12691/jbms-6-4-3

• Al Hadwer, A., Tavana, M., Gillis, D., & Rezania, D. (2021). A systematic review of organizational factors impacting cloud-based technology adoption using technology-organization-environment framework. Internet of Things, 15, Article 100407. https://doi.org/10.1016/j.iot.2021.100407

• Al Mudawi, N., Beloff, N., & White, M. (2019). Cloud computing in government organizations-towards a new comprehensive model. In 2019 IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI) (pp. 1473-1479). IEEE Publishing. https://doi.org/10.1109/SmartWorld-UIC-ATC-SCALCOM-IOP-SCI.2019.00266

• Albugmi, A., Walters, R., & Wills, G. (2016). A framework for cloud computing adoption by Saudi government overseas agencies. In 2016 Fifth International Conference on Future Generation Communication Technologies (FGCT) (pp. 1-5). IEEE Publishing. https://doi.org/10.1109/FGCT.2016.7605063

• Alharbi, F., Atkins, A., & Stanier, C. (2016). Understanding the determinants of cloud computing adoption in Saudi healthcare organisations. Complex & Intelligent Systems, 2(3), 155-171. https://doi.org/10.1007/s40747-016-0021-9

• Ali, K. E., Mazen, S. A., & Hassanein, E. (2018a). A proposed hybrid model for adopting cloud computing in e-government. Future Computing and Informatics Journal, 3(2), 286-295. https://doi.org/10.1016/j.fcij.2018.09.001

• Ali, K. E., Mazen, S. A., & Hassanein, E. E. (2018b). Assessment of cloud computing adoption models in e-government environment. International Journal of Computational Intelligence Studies, 7(1), 67-92. https://doi.org/10.1504/IJCISTUDIES.2018.090168

• Ali, O., & Osmanaj, V. (2020). The role of government regulations in the adoption of cloud computing: A case study of local government. Computer Law & Security Review, 36, Article 105396. https://doi.org/10.1016/j.clsr.2020.105396

• Ali, O., Soar, J., & Yong, J. (2014). Impact of cloud computing technology on e-government. In International conference on information and software technologies (pp. 272-290). Springer. https://doi.org/10.1007/978-3-319-11958-8_22

• Ali, O., Soar, J., Yong, J., McClymont, H., & Angus, D. (2015). Collaborative cloud computing adoption in Australian regional municipal government: An exploratory study. In 2015 IEEE 19th International Conference on Computer Supported Cooperative Work in Design (CSCWD) (pp. 540-548). IEEE Publishing. https://doi.org/10.1109/CSCWD.2015.7231017

• Alismaili, S. Z., Li, M., Shen, J., Huang, P., He, Q., & Zhan, W. (2020). Organisational-level assessment of cloud computing adoption: Evidence from the Australian SMEs. Journal of Global Information Management (JGIM), 28(2), 73-89. https://doi.org/10.4018/JGIM.2020040104

• Alkhalil, A., Sahandi, R., & John, D. (2017). An exploration of the determinants for decision to migrate existing resources to cloud computing using an integrated TOE-DOI model. Journal of Cloud Computing, 6(1), 1-20. https://doi.org/10.1186/s13677-016-0072-x

• AlKharusi, M. H., & Al-Badi, A. H. (2016). IT personnel perspective of the slow adoption of cloud computing in public sector: Case study in Oman. In 2016 3rd MEC International Conference on Big Data and Smart City (ICBDSC) (pp. 1-8). IEEE Publishing. https://doi.org/10.1109/ICBDSC.2016.7460364

• Alkhater, N., Wills, G., & Walters, R. (2014). Factors influencing an organisation’s intention to adopt cloud computing in Saudi Arabia. In 2014 IEEE 6th international conference on cloud computing technology and science (pp. 1040-1044). IEEE Publishing. https://doi.org/10.1109/CloudCom.2014.95

• Alkhwaldi, A., Kamala, M., & Qahwaji, R. (2017). From e-govemment to cloud-government: Challenges of Jordanian citizens’ acceptance for public services. In 2017 12th International Conference for Internet Technology and Secured Transactions (ICITST) (pp. 298-304). IEEE Publishing. https://doi.org/10.23919/ICITST.2017.8356405

• Alrashed, M. A., & Alotaibi, M. B. (2017). The role of trust in the acceptance of government cloud: An empirical study. International Journal of Technology Diffusion (IJTD), 8(3), 1-19. https://doi.org/10.4018/IJTD.2017070101

• Anuradha, M., Jayasankar, T., Prakash, N., Sikkandar, M. Y., Hemalakshmi, G., Bharatiraja, C., & Britto, A. S. F. (2021). IoT enabled cancer prediction system to enhance the authentication and security using cloud computing. Microprocessors and Microsystems, 80, Article 103301. https://doi.org/10.1016/j.micpro.2020.103301

• Attaran, M., & Woods, J. (2018). Cloud computing technology: A viable option for small and medium-sized businesses. Journal of Strategic Innovation & Sustainability, 13(2), 94-106.

• Avram, M. G. (2014). Advantages and challenges of adopting cloud computing from an enterprise perspective. Procedia Technology, 12, 529-534. https://doi.org/10.1016/j.protcy.2013.12.525

• Awa, H. O., Ojiabo, O. U., & Orokor, L. E. (2017). Integrated technology-organization-environment (TOE) taxonomies for technology adoption. Journal of Enterprise Information Management, 30(6), 893-921.

• Aziz, M. A., Abawajy, J., & Chowdhury, M. (2013). The challenges of cloud technology adoption in e-government. In 2013 International Conference on Advanced Computer Science Applications and Technologies (pp. 470-474). IEEE Publishing. https://doi.org/10.1109/ACSAT.2013.98

• Bayramusta, M., & Nasir, V. A. (2016). A fad or future of IT?: A comprehensive literature review on the cloud computing research. International Journal of Information Management, 36(4), 635-644. https://doi.org/10.1016/j.ijinfomgt.2016.04.006

• Chang, V., Kuo, Y. H., & Ramachandran, M. (2016). Cloud computing adoption framework: A security framework for business clouds. Future Generation Computer Systems, 57, 24-41. https://doi.org/10.1016/j.future.2015.09.031

• Chang, V., & Ramachandran, M. (2015). Towards achieving data security with the cloud computing adoption framework. IEEE Transactions on Services Computing, 9(1), 138-151. https://doi.org/10.1109/TSC.2015.2491281

• Choudrie, J., & Dwivedi, Y. K. (2005). Investigating the research approaches for examining technology adoption issues. Journal of Research Practice, 1(1), D1-D1.

• Damanpour, F., Sanchez‐Henriquez, F., & Chiu, H. H. (2018). Internal and external sources and the adoption of innovations in organizations. British Journal of Management, 29(4), 712-730. https://doi.org/10.1111/1467-8551.12296

• Dash, S., & Pani, S. K. (2016). E-Governance paradigm using cloud infrastructure: Benefits and challenges. Procedia Computer Science, 85, 843-855. https://doi.org/10.1016/j.procs.2016.05.274

• Gangwar, H., Date, H., & Ramaswamy, R. (2015). Developing a cloud-computing adoption framework. Global Business Review, 16(4), 632-651. https://doi.org/10.1177/0972150915581108

• Garad, A., & Santoso, J. (2017). Analysis and design of cloud computing for e-government in Yemen. International Journal of Computer Engineering and Information Technology, 9(8), 166.

• Hadi, H., & Omar, M. (2021). Investigating the determinants of CC-SaaS adoption in Iraqi’s public organisations from the perspective of IT professionals. International Journal of Engineering and Technical Research, 14, 130-143.

• Hair, J. F., Ringle, C. M., & Sarstedt, M. (2013). Partial least squares structural equation modeling: Rigorous applications, better results and higher acceptance. Long Range Planning, 46(1-2), 1-12. https://doi.org/10.1016/j.lrp.2013.01.001

• Hair Jr, J. F., Sarstedt, M., Hopkins, L., & Kuppelwieser, V. G. (2014). Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research. European Business Review, 26(2), 106-121. https://doi.org/10.1108/EBR-10-2013-0128

• Hameed, M. A., Counsell, S., & Swift, S. (2012). A conceptual model for the process of IT innovation adoption in organizations. Journal of Engineering and Technology Management, 29(3), 358-390. https://doi.org/10.1016/j.jengtecman.2012.03.007

• Hosseini, S., Turhan, B., & Gunarathna, D. (2017). A systematic literature review and meta-analysis on cross project defect prediction. IEEE Transactions on Software Engineering, 45(2), 111-147. https://doi.org/10.1109/TSE.2017.2770124

• Hsu, P. F., Ray, S., & Li-Hsieh, Y. Y. (2014). Examining cloud computing adoption intention, pricing mechanism, and deployment model. International Journal of Information Management, 34(4), 474-488. https://doi.org/10.1016/j.ijinfomgt.2014.04.006

• Hwang, Y., Al-Arabiat, M., Shin, D. H., & Lee, Y. (2016). Understanding information proactiveness and the content management system adoption in pre-implementation stage. Computers in Human Behavior, 64, 515-523. https://doi.org/10.1016/j.chb.2016.07.025

• Ji, H., & Liang, Y. (2016). Exploring the determinants affecting e-government cloud adoption in China. International Journal of Business and Management, 11(4), 81-90. https://doi.org/10.5539/ijbm.v11n4p81

• Junior, L. P., Cunha, M. A., Janssen, M., & Matheus, R. (2020). Towards a framework for cloud computing use by governments: Leaders, followers and laggers. In The 21st Annual International Conference on Digital Government Research (pp. 155-163). ACM Publishing. https://doi.org/10.1145/3396956.3396989

• Kandil, A. M. N. A., Ragheb, M. A., Ragab, A. A., & Farouk, M. (2018). Examining the effect of TOE model on cloud computing adoption in Egypt. The Business & Management Review, 9(4), 113-123.

• Kitchenham, B., & Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering (Technical Report EBSE). Keele University.

• Kuiper, E., Van Dam, F., Reiter, A., & Janssen, M. (2014). Factors influencing the adoption of and business case for cloud computing in the public sector. In eChallenges e-2014 Conference Proceedings (pp. 1-10). IEEE Publishing.

• Kyriakou, N., Euripides, L., & Paraskevi, D. (2020). Factors affecting cloud storage adoption by Greek municipalities. In Proceedings of the 13th International Conference on Theory and Practice of Electronic Governance (pp. 244-253). ACM Publishing. https://doi.org/10.1145/3428502.3428537

• Lagzian, M., Hemmat, Z., Rashki, M., & Aghadavood, S. (2018). An investigation on effective factors of acceptance of cloud computing in iranian public services (No. 279). EasyChair.

• Li, G., Zhou, M., Feng, Z., Li, M., & Jiang, H. (2021). Research on key influencing factors of e-government cloud service satisfaction. Wireless Personal Communications, 1-19. https://doi.org/10.1007/s11277-021-08567-0

• Lian, J. W. (2015). Critical factors for cloud based e-invoice service adoption in Taiwan: An empirical study. International Journal of Information Management, 35(1), 98-109. https://doi.org/10.1016/j.ijinfomgt.2014.10.005

• Liang, Y., & Qi, G. (2017). The determinants of e-government cloud adoption: Multi-case analysis of China. International Journal of Networking and Virtual Organisations, 17(2-3), 184-201. https://doi.org/10.1504/IJNVO.2017.10004061

• Liang, Y., Qi, G., Wei, K., & Chen, J. (2017). Exploring the determinant and influence mechanism of e-Government cloud adoption in government agencies in China. Government Information Quarterly, 34(3), 481-495. https://doi.org/10.1016/j.giq.2017.06.002

• Liang, Y., Qi, G., Zhang, X., & Li, G. (2019). The effects of e-Government cloud assimilation on public value creation: An empirical study of China. Government Information Quarterly, 36(4), Article 101397. https://doi.org/10.1016/j.giq.2019.101397

• Lynn, T., Fox, G., Gourinovitch, A., & Rosati, P. (2020). Understanding the determinants and future challenges of cloud computing adoption for high performance computing. Future Internet, 12(8), Article 135. https://doi.org/10.3390/fi12080135

• Maluleka, S. M., & Ruxwana, N. (2016). Cloud computing as an alternative solution for South African public sector: A case for department of social development. In New Advances in Information Systems and Technologies (pp. 481-491). Springer. https://doi.org/10.1007/978-3-319-31232-3_45

• Mohammed, F., & Ibrahim, O. (2015a). Models of adopting cloud computing in the e-government context: A review. Jurnal Teknologi, 73(2), 51-59. https://doi.org/10.11113/jt.v73.4193

• Mohammed, F., & Ibrahim, O. B. (2015b). Drivers of cloud computing adoption for e-government services implementation. International Journal of Distributed Systems and Technologies (IJDST), 6(1), 1-14. https://doi.org/10.4018/ijdst.2015010101

• Mohammed, F., Ibrahim, O., & Ithnin, N. (2016). Factors influencing cloud computing adoption for e-government implementation in developing countries: Instrument development. Journal of Systems and Information Technology, 18(3), 297-327. https://doi.org/10.1108/JSIT-01-2016-0001

• Mohammed, F., Alzahrani, A. I., Alfarraj, O., & Ibrahim, O. (2017a). Cloud computing fitness for e-Government implementation: Importance-performance analysis. IEEE Access, 6, 1236-1248. https://doi.org/10.1109/ACCESS.2017.2778093

• Mohammed, F., Ibrahim, O., Nilashi, M., & Alzurqa, E. (2017b). Cloud computing adoption model for e-government implementation. Information Development, 33(3), 303-323. https://doi.org/10.1177/0266666916656033

• Mohammed, F., Olayah, F., Ali, A., & Gazem, N. A. (2020). The effect of cloud computing adoption on the sustainability of e-government services: A review. International Journal of Advanced Science and Technology, 29(5), 2636-2642.

• Mousa, M. A. S. (2020). Determinants of cloud based e-government in Libya. Journal of Critical Reviews, 7(13), 2239-2248.

• Nanos, I., Manthou, V., & Androutsou, E. (2019). Cloud computing adoption decision in E-government. In Operational Research in the Digital Era–ICT Challenges (pp. 125-145). Springer. https://doi.org/10.1007/978-3-319-95666-4_9

• Oguntala, G. A., Abd-Alhameed, P., Raed, A., Odeyemi, D., & Janet, O. (2017). Systematic analysis of enterprise perception towards cloud adoption in the African states: The Nigerian perspective. The African Journal of Information Systems, 9(4), Article 1.

• Park, H., & Choi, S. O. (2019). Digital innovation adoption and its economic impact focused on path analysis at national level. Journal of Open Innovation: Technology, Market, and Complexity, 5(3), Article 56. https://doi.org/10.3390/joitmc5030056

• Polyviou, A., & Pouloudi, N. (2015). Understanding cloud adoption decisions in the public sector. In 2015 48th Hawaii International Conference on System Sciences (pp. 2085-2094). IEEE Publishing. https://doi.org/10.1109/HICSS.2015.250

• Rogers, E. M. (2010). Diffusion of innovations. Simon and Schuster.

• Salam, N. R. A., & Ali, S. (2020). Determining factors of cloud computing adoption: A study of Indonesian local government employees. Journal of Accounting and Investment, 1(2), 312-333. https://doi.org/10.18196/jai.2102151

• Sallehudin, H., Aman, A. H. M., Razak, R. C., Ismail, M., Bakar, N. A. A., Fadzil, A. F. M., & Baker, R. (2020). Performance and key factors of cloud computing implementation in the public sector. International Journal of Business and Society, 21(1), 134-152. https://doi.org/10.33736/ijbs.3231.2020

• Sallehudin, H., Razak, R., Ismail, M., Fadzil, A., & Baker, R. (2019). Cloud computing implementation in the public sector: Factors and impact. Asia-Pacific Journal of Information Technology and Multimedia, 7(2-2), 27-42. https://doi.org/10.17576/apjitm-2018-0702(02)-03

• Scholtz, B., Govender, J., & Gomez, J. M. (2016). Technical and environmental factors affecting cloud computing adoption in the South African public sector. In International Conference on Information Resources Management (CONF-IRM) (pp. 1-14). AISeL.

• Senyo, P. K., Addae, E., & Boateng, R. (2018). Cloud computing research: A review of research themes, frameworks, methods and future research directions. International Journal of Information Management, 38(1), 128-139. https://doi.org/10.1016/j.ijinfomgt.2017.07.007

• Setiorini, A., Natasia, S. R., Wiranti, Y. T., & Ramadhan, D. A. (2021). Evaluation of the application of hospital management information system (SIMRS) in RSUD Dr. Kanujoso Djatiwibowo using the HOT-Fit method. In Journal of Physics: Conference Series (Vol. 1726, No. 1, p. 012011). IOP Publishing. https://doi.org/10.1088/1742-6596/1726/1/012011

• Shafique, M. A., Mahmood, Y., Hameed, K., Malik, B. H., Cheema, S. N., & Tabassum, S. (2017). Determinants impacting the adoption of e-government information systems and suggesting cloud computing migration framework. International Journal of Advanced Computer Science and Applications, 8(9), 173-182. https://doi.org/10.14569/IJACSA.2017.080925

• Sharma, M., Gupta, R., & Acharya, P. (2020). Analysing the adoption of cloud computing service: A systematic literature review. Global Knowledge, Memory and Communication, 70(1/2), 114-153. https://doi.org/10.1108/GKMC-10-2019-0126

• Shukur, B. S., Ghani, M. K. A., & Burhanuddin, M. (2018). An analysis of cloud computing adoption framework for Iraqi e-government. Culture, 9(8), 104-112. https://doi.org/10.14569/IJACSA.2018.090814

• Singh, P., Dwivedi, Y. K., Kahlon, K. S., Sawhney, R. S., Alalwan, A. A., & Rana, N. P. (2020). Smart monitoring and controlling of government policies using social media and cloud computing. Information Systems Frontiers, 22(2), 315-337. https://doi.org/10.1007/s10796-019-09916-y

• Sivapragash, C., Padmanaban, S., Eklas, H., Holm-Nielsen, J. B., & Hemalatha, R. (2019). Location-based optimized service selection for data management with cloud computing in smart grids. Energies, 12(23), 1-16. https://doi.org/10.3390/en12234517

• Sivapragash, C., Thilaga, S., & Kumar, S. S. (2012). Advanced cloud computing in smart power grid. In IET Chennai 3rd International Conference on Sustainable Energy and Intelligent Systems (SEISCON 2012) (pp. 356-361). IET Digital Library. https://doi.org/10.1049/cp.2012.2238

• Sivathanu, B. (2018). An empirical study of cloud-based e-governance services adoption in India. International Journal of Electronic Government Research (IJEGR), 14(1), 86-107. https://doi.org/10.4018/IJEGR.2018010105

• Sun, Y., & Jeyaraj, A. (2013). Information technology adoption and continuance: A longitudinal study of individuals’ behavioral intentions. Information & Management, 50(7), 457-465. https://doi.org/10.1016/j.im.2013.07.005

• Tornatzky, L. G., Fleischer, M., & Chakrabarti, A. K. (1990). Processes of technological innovation. Lexington books.

• Tsaravas, C., & Themistocleous, M. (2011, May 30-31). Cloud computing and Egovernment: A literature review. In European, Mediterranean & Middle Eastern Conference on Information Systems (pp. 154-164). Athens, Greece.

• Tuli, S., Tuli, S., Tuli, R., & Gill, S. S. (2020). Predicting the growth and trend of COVID-19 pandemic using machine learning and cloud computing. Internet of Things, 11, Article 100222. https://doi.org/10.1016/j.iot.2020.100222

• Tweneboah-Koduah, S., Endicott-Popovsky, B., & Tsetse, A. (2014). Barriers to government cloud adoption. International Journal of Managing Information Technology, 6(3), 1-16. https://doi.org/10.5121/ijmit.2014.6301

• Vaidya, S., Shah, N., Virani, K., & Devadkar, K. (2020). A survey: Mobile cloud computing in education. In 2020 5th International Conference on Communication and Electronics Systems (ICCES) (pp. 655-659). IEEE Publishing. https://doi.org/10.1109/ICCES48766.2020.9138053

• Vu, K., Hartley, K., & Kankanhalli, A. (2020). Predictors of cloud computing adoption: A cross-country study. Telematics and Informatics, 52, Article 101426. https://doi.org/10.1016/j.tele.2020.101426

• Wahsh, M. A., & Dhillon, J. S. (2015a). An investigation of factors affecting the adoption of cloud computing for E-government implementation. In 2015 IEEE Student Conference on Research and Development (SCOReD) (pp. 323-328). IEEE Publishing. https://doi.org/10.1109/SCORED.2015.7449349.

• Wahsh, M. A., & Dhillon, J. S. (2015b). A systematic review of factors affecting the adoption of cloud computing for E-government implementation. Journal of Engineering and Applied Sciences, 10(23), 17824-17832.

• Wang, C., Li, S., Cheng, T., & Li, B. (2020). A construction of smart city evaluation system based on cloud computing platform. Evolutionary Intelligence, 13(1), 119-129. https://doi.org/10.1007/s12065-019-00259-w

• Wisdom, J. P., Chor, K. H. B., Hoagwood, K. E., & Horwitz, S. M. (2014). Innovation adoption: A review of theories and constructs. Administration and Policy in Mental Health and Mental Health Services Research, 41(4), 480-502. https://doi.org/10.1007/s10488-013-0486-4

• Wohlin, C. (2014). Guidelines for snowballing in systematic literature studies and a replication in software engineering. In Proceedings of the 18th international conference on evaluation and assessment in software engineering (pp. 1-10). ACM Publishing. https://doi.org/10.1145/2601248.2601268

• Wu, J., Ding, F., Xu, M., Mo, Z., & Jin, A. (2016). Investigating the determinants of decision-making on adoption of public cloud computing in e-government. Journal of Global Information Management (JGIM), 24(3), 71-89. https://doi.org/10.4018/JGIM.2016070104

• Yadegaridehkordi, E., Nilashi, M., Shuib, L., Nasir, M. H. N. B. M., Asadi, S., Samad, S., & Awang, N. F. (2020). The impact of big data on firm performance in hotel industry. Electronic Commerce Research and Applications, 40, Article 100921. https://doi.org/10.1016/j.elerap.2019.100921

• Yusof, M. M., Kuljis, J., Papazafeiropoulou, A., & Stergioulas, L. K. (2008). An evaluation framework for Health Information Systems: Human, organization and technology-fit factors (HOT-fit). International Journal of Medical Informatics, 77(6), 386-398. https://doi.org/10.1016/j.ijmedinf.2007.08.011

• Zhang, H. (2020). The application of cloud computing in government management. In IOP Conference Series: Materials Science and Engineering (Vol. 750, No. 1, p. 012166). IOP Publishing. https://doi.org/10.1088/1757-899X/750/1/012166