A Conceptual Framework for the Adoption of Cloud Computing in a Higher Education Institutions
DOI:
https://doi.org/10.56294/dm2025431Keywords:
Cloud computing, Adoption, TOE model, Human factors, Jordanian higher educational institutionsAbstract
Today, with significant improvements of computing capacities, the world is witnessing significant technological advancements. Cloud computing especially, is increasingly becoming an advantageous tool, in developed countries especially, and these countries have invested substantially in cloud computing systems to enable the implementation of hi-tech advancements in many of their industries. On the other hand, in developing and underdeveloped countries, the adoption of cloud computing is still in the early stages; as can be observed, there has been some form of digital transformation of data systems in these countries. In Jordan, The factors affecting cloud computing adoption among higher education institutions were still underexplored, especially on the issues pertaining to cloud computing adoption. Therefore. Major factors with potential impact on user adoption of cloud computing were hence reviewed in this study. A conceptual framework of cloud computing adoption based on Extended Technology-Organizational-Environmental (TOE) framework by Tornatzky and Fleischer was proposed. The framework includes individual factors as the theoretical base for cloud computing adoption, to provide an inclusive comprehension on the factors that could affect behavioral intention and use of cloud computing.
References
1. Arpaci I. Understanding and predicting students' intention to use mobile cloud storage services. Computers in human behavior. 2016;58:150-7. DOI: https://doi.org/10.1016/j.chb.2015.12.067
2. Batista BG, Ferreira CHG, Segura DCM, Leite Filho DM, Peixoto MLM. A QoS-driven approach for cloud computing addressing attributes of performance and security. Future Generation Computer Systems. 2017;68:260-74. DOI: https://doi.org/10.1016/j.future.2016.09.018
3. Muzaffar T, Hussain H, Ali H, Ibrahim M, Daniya D. Understanding and Predicting Academic Performance Through Cloud Computing Adoption. Journal of Computers in Education. 2020(5):10.1007/s40692-018-0114-0.
4. Sutar S, Byranahallieraiah M, Shivashankaraiah K. A Dual-Objective Approach for Allocation of Virtual Machine with improved Job Scheduling in Cloud Computing. The International Arab Journal of Information Technology. 2024;21(1):46-56. DOI: https://doi.org/10.34028/iajit/21/1/4
5. Hussein LA, Hilmi MF. Cloud computing based e-learning in Malaysian universities. International Journal of Emerging Technologies in Learning (Online). 2021;15(8):4-20. DOI: https://doi.org/10.3991/ijet.v15i08.11798
6. Alsmadi AM, Ali Aloglah RM, Smadi AA, Alshabanah M, Alrajhi D, Alkhaldi H, et al. Fog computing scheduling algorithm for smart city. International Journal of Electrical & Computer Engineering (2088-8708). 2021;11(3):2219-28. DOI: https://doi.org/10.11591/ijece.v11i3.pp2219-2228
7. Owida HA, Moh’d BA-h, Turab N, Al-Nabulsi J, Abuowaida S. The Evolution and Reliability of Machine Learning Techniques for Oncology. International Journal of Online & Biomedical Engineering. 2023;19(8):110-29. DOI: https://doi.org/10.3991/ijoe.v19i08.39433
8. Rashid A, Chaturvedi A. Cloud computing characteristics and services: a brief review. International Journal of Computer Sciences and Engineering. 2019;7(2):421-6. DOI: https://doi.org/10.26438/ijcse/v7i2.421426
9. Eldalabeeh AR, AL-Shbail MO, Almuiet MZ, Bany Baker M, E'leimat D. Cloud-based accounting adoption in Jordanian financial sector. The Journal of Asian Finance, Economics and Business. 2021;8(2):833-49.
10. Alzaabi NMI, Wahab E. Cloud Computing Adoption Factors Affecting Academic Performance in UAE Public Universities. International Journal of Sustainable Construction Engineering and Technology. 2023;14(2):214-22. DOI: https://doi.org/10.30880/ijscet.2023.14.02.022
11. Shana Z, Abulibdeh ESA. Cloud computing issues for higher education: Theory of acceptance model. International Journal of Emerging Technologies in Learning (iJET). 2017;12(11):168-84. DOI: https://doi.org/10.3991/ijet.v12i11.7473
12. Zhang W, Zhu Y. A new E-learning model based on elastic cloud computing for distance education. Eurasia Journal of Mathematics, Science and Technology Education. 2017;13(12):8393-403. DOI: https://doi.org/10.12973/ejmste/80800
13. Hiran KK, Henten A. An integrated TOE–DoI framework for cloud computing adoption in the higher education sector: case study of Sub-Saharan Africa, Ethiopia. International Journal of System Assurance Engineering and Management. 2020;11:441-9. DOI: https://doi.org/10.1007/s13198-019-00872-z
14. Alkhater N, Walters R, Wills G. An empirical study of factors influencing cloud adoption among private sector organisations. Telematics and Informatics. 2018;35(1):38-54. DOI: https://doi.org/10.1016/j.tele.2017.09.017
15. Yaokumah W, Amponsah RA. Examining the contributing factors for cloud computing adoption in a developing country. Cloud Security: Concepts, Methodologies, Tools, and Applications: IGI Global; 2019. p. 1663-85. DOI: https://doi.org/10.4018/978-1-5225-8176-5.ch082
16. Hoxha K, Aliko D. Cloud Computing Adoption in Albania: An Empirical Study. 5th International Conference on Recent Trends and Applications in Computer Science and Information Technology; Tirana, Albania2023. p. 7.
17. Bazel MA, Mohammed F, Ahmad M. A systematic review on the adoption of blockchain technology in the healthcare industry. EAI Endorsed Transactions on Pervasive Health and Technology. 2023;9(1):1-10. DOI: https://doi.org/10.4108/eetpht.v9i.2844
18. Pólvora A, Nascimento S, Lourenço JS, Scapolo F. Blockchain for industrial transformations: A forward-looking approach with multi-stakeholder engagement for policy advice. Technological Forecasting and Social Change. 2020;157:120091-109. DOI: https://doi.org/10.1016/j.techfore.2020.120091
19. Agbo CC, Mahmoud QH, Eklund JM, editors. Blockchain technology in healthcare: a systematic review. Healthcare; 2019: MDPI. DOI: https://doi.org/10.3390/healthcare7020056
20. Aznoli F, Navimipour NJ. Deployment strategies in the wireless sensor networks: systematic literature review, classification, and current trends. Wireless Personal Communications. 2017;95:819-46. DOI: https://doi.org/10.1007/s11277-016-3800-0
21. Gopalakrishnan S, Ganeshkumar P. Systematic reviews and meta-analysis: understanding the best evidence in primary healthcare. Journal of family medicine and primary care. 2013;2(1):9-14. DOI: https://doi.org/10.4103/2249-4863.109934
22. Mohammad OKJ. Recent trends of cloud computing applications and services in medical, educational, financial, library and agricultural disciplines. The 4th International Conference on Frontiers of Educational Technologies; NY, United States2018. p. 132-41. DOI: https://doi.org/10.1145/3233347.3233388
23. Okai S, Uddin M, Arshad A, Alsaqour R, Shah A. Cloud computing adoption model for universities to increase ICT proficiency. Sage Open. 2014;4(3):1-10. DOI: https://doi.org/10.1177/2158244014546461
24. Sabi HM, Uzoka F-ME, Langmia K, Njeh FN. Conceptualizing a model for adoption of cloud computing in education. International journal of information management. 2016;36(2):183-91. DOI: https://doi.org/10.1016/j.ijinfomgt.2015.11.010
25. Kayali M, Alaaraj S. Adoption of cloud based E-learning in developing countries: a combination a of DOI, TAM and UTAUT. International Journal of Contemporary Management and Information Technology. 2020;1(1):1-7.
26. Singh S, Chand D, editors. Trust evaluation in cloud based on friends and third party's recommendations. 2014 Recent Advances in Engineering and Computational Sciences (RAECS); 2014; Panjab University, Chandigarh, India: IEEE. DOI: https://doi.org/10.1109/RAECS.2014.6799600
27. Sabi HM, Uzoka F-ME, Langmia K, Njeh FN, Tsuma CK. A cross-country model of contextual factors impacting cloud computing adoption at universities in sub-Saharan Africa. Information Systems Frontiers. 2018;20:1381-404. DOI: https://doi.org/10.1007/s10796-017-9739-1
28. Al-Ramahi NM, Odeh M, Alrabie Z, Qozmar N. The TOEQCC framework for sustainable adoption of cloud computing at higher education institutions in the kingdom of Jordan. Sustainability. 2022;14(19):12744. DOI: https://doi.org/10.3390/su141912744
29. Atobishi T, Bahna M, Takács-György K, Fogarassy C. Factors affecting the decision of adoption cloud computing technology: The case of Jordanian business organizations. Acta Polytechnica Hungarica. 2021;18(5):131-54. DOI: https://doi.org/10.12700/APH.18.5.2021.5.9
30. Njenga K, Garg L, Bhardwaj AK, Prakash V, Bawa S. The cloud computing adoption in higher learning institutions in Kenya: Hindering factors and recommendations for the way forward. Telematics and Informatics. 2019;38:225-46. DOI: https://doi.org/10.1016/j.tele.2018.10.007
31. Hussein Alghushami A, Zakaria NH, Mat Aji Z. Factors influencing cloud computing adoption in higher education institutions of least developed countries: evidence from Republic of Yemen. Applied Sciences. 2020;10(22):8098-125. DOI: https://doi.org/10.3390/app10228098
32. Almaiah MA, Al-Khasawneh A. Investigating the main determinants of mobile cloud computing adoption in university campus. Education and Information Technologies. 2020;25:3087-107. DOI: https://doi.org/10.1007/s10639-020-10120-8
33. Asadi Z, Abdekhoda M, Nadrian H. Cloud computing services adoption among higher education faculties: development of a standardized questionnaire. Education and Information Technologies. 2020;25:175-91. DOI: https://doi.org/10.1007/s10639-019-09932-0
34. Ahmad N, Hoda N, Alahmari F. Developing a cloud-based mobile learning adoption model to promote sustainable education. Sustainability. 2020;12(8):3126. DOI: https://doi.org/10.3390/su12083126
35. Jaradat M, Ababneh HT, Faqih K, Nusairat NM. Exploring cloud computing adoption in higher educational environment: an extension of the UTAUT model with trust. International Journal of Advanced Science and Technology. 2020;29(5):8282-306.
36. Hiran KK, Henten A. An integrated TOE-DoI framework for cloud computing adoption in higher education: The case of Sub-Saharan Africa, Ethiopia. SoCTA 2018 of Soft Computing: Theories and Applications; Singapore: Springer; 2020. p. 1281-90. DOI: https://doi.org/10.1007/978-981-15-0751-9_117
37. Al Hadwer A, Tavana M, Gillis D, Rezania D. A systematic review of organizational factors impacting cloud-based technology adoption using Technology-organization-environment framework. Internet of Things. 2021;15:100407-17. DOI: https://doi.org/10.1016/j.iot.2021.100407
38. Song C-h, Sohn Y-w. The influence of dependability in cloud computing adoption. The Journal of Supercomputing. 2022;78(10):12159-201. DOI: https://doi.org/10.1007/s11227-022-04346-1
39. Shahbaz M, Zahid R. Probing the factors influencing cloud computing adoption in healthcare organizations: A three-way interaction model. Technology in Society. 2022;71:102139-71. DOI: https://doi.org/10.1016/j.techsoc.2022.102139
40. Sharma M, Gupta R, Acharya P, Jain K. Systems approach to cloud computing adoption in an emerging economy. International Journal of Emerging Markets. 2023;18(9):3283-308. DOI: https://doi.org/10.1108/IJOEM-04-2021-0501
41. Chen M, Wang H, Liang Y, Zhang G. Net and configurational effects of determinants on cloud computing adoption by SMEs under cloud promotion policy using PLS-SEM and fsQCA. Journal of Innovation & Knowledge. 2023;8(3):100388-409. DOI: https://doi.org/10.1016/j.jik.2023.100388
42. Ali AF, Abi Hassan A, Abdullahi HO, Abdulah RH. Analyzing the factors influencing the adoption of cloud computing by SMEs using the SEM approach. International Journal of Advanced and Applied Sciences. 2023;10(7):66-79. DOI: https://doi.org/10.21833/ijaas.2023.07.009
43. Lindawati ASL, Handoko BL, Joyceline I. Effect Of Technology Organization Environment And Individual Factors Towards Adoption Intention Of Cloud-Based Accounting Software In MSMES. Journal of Theoretical and Applied Information Technology. 2023;101(1):172-81.
44. Thavi R, Jhaveri R, Narwane V, Gardas B, Jafari Navimipour N. Role of cloud computing technology in the education sector. Journal of Engineering, Design and Technology. 2024;22(1):182-213. DOI: https://doi.org/10.1108/JEDT-08-2021-0417
45. Santos A, Martins J, Pestana P, Gonçalves R, São Mamede H, Branco F. Factors affecting cloud computing adoption in the education context-Systematic Literature Review. IEEE Access. 2024;12:71641 - 74. DOI: https://doi.org/10.1109/ACCESS.2024.3400862
46. Ifawoye OI, Ajayi BA, Chukwuemeka FN. Cloud Computing Adoption Models in Organizations: A Survey. International Journal of Research and Innovation in Applied Science. 2024;9(5):509-21. DOI: https://doi.org/10.51584/IJRIAS.2024.905045
47. Alsewie R, Md Johar MG, Hajamydeen AI. Framework for Cloud Computing Adoption in the Malaysian and Libyan Hospitality Industry. International Journal of Business Society. 2024;8(1):866-75. DOI: https://doi.org/10.30566/ijo-bs
48. Soleimani Nejad A, Doroudi F, Kamyab R. Assessment of the status and factors influencing the adoption of cloud computing in knowledge-based companies Case Study: Kerman Science and Technology Park. International Journal of Information Science and Management (IJISM). 2024;22(1):17-29.
49. Oliveira T, Thomas M, Espadanal M. Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors. Information & management. 2014;51(5):497-510. DOI: https://doi.org/10.1016/j.im.2014.03.006
50. Gebreslassie TW. E-Business Strategy to Adopt Electronic Banking Services in Ethiopia. Minnesota: Walden University; 2017.
51. Rajpurohit J, Sharma TK, Abraham A. Glossary of metaheuristic algorithms. International Journal of Computer Information Systems & Industrial Management Applications. 2017;9:181-205.
52. Alshamaila Y, Papagiannidis S, Li F. Cloud computing adoption by SMEs in the north east of England: A multi‐perspective framework. Journal of enterprise information management. 2013;26(3):250-75. DOI: https://doi.org/10.1108/17410391311325225
53. Hassan H, Nasir MHM, Khairudin N, Adon I. Factors influencing cloud computing adoption in small medium enterprises. Journal of Information and Communication Technology. 2017;16(1):21-41. DOI: https://doi.org/10.32890/jict2017.16.1.2
54. Tornatzky LG, Fleischer M. The processes of technological innovation. United States: Lexington Books, Lexington, Mass; 1990. 298 p.
55. Zhu K, Kraemer KL. Post-adoption variations in usage and value of e-business by organizations: cross-country evidence from the retail industry. Information systems research. 2005;16(1):61-84. DOI: https://doi.org/10.1287/isre.1050.0045
56. Oliveira T, Martins MF. Understanding e‐business adoption across industries in European countries. Industrial management & data systems. 2010;110(9):1337-54. DOI: https://doi.org/10.1108/02635571011087428
57. Al-Sharafi MA, AlAjmi Q, Al-Emran M, Qasem YA, Aldheleai YM. Cloud computing adoption in higher education: An integrated theoretical model. Recent Advances in Technology Acceptance Models and Theories. 2021:191-209. DOI: https://doi.org/10.1007/978-3-030-64987-6_12
58. Haneem F, Kama N, Taskin N, Pauleen D, Bakar NAA. Determinants of master data management adoption by local government organizations: An empirical study. International journal of information management. 2019;45:25-43. DOI: https://doi.org/10.1016/j.ijinfomgt.2018.10.007
59. Shree D, Singh RK, Paul J, Hao A, Xu S. Digital platforms for business-to-business markets: A systematic review and future research agenda. Journal of business research. 2021;137:354-65. DOI: https://doi.org/10.1016/j.jbusres.2021.08.031
60. Aligarh F, Sutopo B, Widarjo W. The antecedents of cloud computing adoption and its consequences for MSMEs’ performance: A model based on the Technology-Organization-Environment (TOE) framework. Cogent Business & Management. 2023;10(2):2220190-206. DOI: https://doi.org/10.1080/23311975.2023.2220190
61. Alshirah M, Lutfi A, Alshirah A, Saad M, Ibrahim N, Mohammed F. Influences of the environmental factors on the intention to adopt cloud based accounting information system among SMEs in Jordan. Accounting. 2021;7(3):645-54. DOI: https://doi.org/10.5267/j.ac.2020.12.013
62. Wu L, Chen J-L. A stage-based diffusion of IT innovation and the BSC performance impact: A moderator of technology–organization–environment. Technological Forecasting and Social Change. 2014;88:76-90. DOI: https://doi.org/10.1016/j.techfore.2014.06.015
63. Alraja MN, Imran R, Khashab BM, Shah M. Technological innovation, sustainable green practices and SMEs sustainable performance in times of crisis (COVID-19 pandemic). Information Systems Frontiers. 2022;24(4):1081-105. DOI: https://doi.org/10.1007/s10796-022-10250-z
64. Khayer A, Talukder MS, Bao Y, Hossain MN. Cloud computing adoption and its impact on SMEs’ performance for cloud supported operations: A dual-stage analytical approach. Technology in Society. 2020;60:101225-63. DOI: https://doi.org/10.1016/j.techsoc.2019.101225
65. Awa HO, Ojiabo OU, Orokor LE. Integrated technology-organization-environment (TOE) taxonomies for technology adoption. Journal of enterprise information management. 2017;30(6):893-921. DOI: https://doi.org/10.1108/JEIM-03-2016-0079
66. Venkatesh V, Thong JY, Xu X. Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS quarterly. 2012;36(1):157-78. DOI: https://doi.org/10.2307/41410412
67. Alshdaifat N, Rahman MNA. The effect of technological context on smart home adoption in Jordan. Indonesian Journal of Electrical Engineering and Computer Science. 2024;33(2):1186-95. DOI: https://doi.org/10.11591/ijeecs.v33.i2.pp1186-1195
68. Croker TD. Formation of the Cloud: History, Metaphor, and Materiality. Blacksburg, Virginia: Virginia Tech; 2020.
69. Al-Hajri S, Echchabi A, Ayedh AM, Omar MMS. The Cloud Computing Systems' Adoption in the Higher Education Sector in Oman in Light of the COVID-19 Pandemic. International Journal of Evaluation and Research in Education. 2021;10(3):930-7. DOI: https://doi.org/10.11591/ijere.v10i3.21671
70. Jaradat Z, Shbail MA, Baker MB. Environmental and organisational factors affecting the adoption of enterprise resource planning systems in the Jordanian banking sector. International Journal of Business Information Systems. 2022;41(1):82-107. DOI: https://doi.org/10.1504/IJBIS.2022.126028
71. Shbail MOA, Jaradat Z, Baker MB, Almuiet M. Individual and technological factors affecting the adoption of enterprise resource planning systems in the Jordanian banking sector. International Journal of Business Information Systems. 2024;45(1):118-41. DOI: https://doi.org/10.1504/IJBIS.2024.135972
72. Sadoughi F, Ali O, Erfannia L. Evaluating the factors that influence cloud technology adoption—comparative case analysis of health and non-health sectors: A systematic review. Health informatics journal. 2020;26(2):1363-91. DOI: https://doi.org/10.1177/1460458219879340
73. Al-Hujran O, Al-Lozi EM, Al-Debei MM, Maqableh M. Challenges of cloud computing adoption from the TOE framework perspective. International Journal of E-Business Research (IJEBR). 2018;14(3):77-94. DOI: https://doi.org/10.4018/IJEBR.2018070105
74. Omar H, Owida HA, Abuowaida S, Alshdaifat N, Alazaidah R, Elsoud E, et al. ChatGPT: A New AI Tool for English Language Teaching and Learning among Jordanian Students. Kurdish studies. 2024;12(1):3628-37.
75. Asiaei A, Ab. Rahim NZ. A multifaceted framework for adoption of cloud computing in Malaysian SMEs. Journal of Science and Technology Policy Management. 2019;10(3):708-50. DOI: https://doi.org/10.1108/JSTPM-05-2018-0053
76. Jianwen C, Wakil K. A model for evaluating the vital factors affecting cloud computing adoption: Analysis of the services sector. Kybernetes. 2020;49(10):2475-92. DOI: https://doi.org/10.1108/K-06-2019-0434
77. AlBar AM, Hoque MR. Factors affecting the adoption of information and communication technology in small and medium enterprises: A perspective from rural Saudi Arabia. Information Technology for Development. 2019;25(4):715-38. DOI: https://doi.org/10.1080/02681102.2017.1390437
78. Low C, Chen Y, Wu M. Understanding the determinants of cloud computing adoption. Industrial management & data systems. 2011;111(7):1006-23. DOI: https://doi.org/10.1108/02635571111161262
79. Gangwar H, Date H, Ramaswamy R. Understanding determinants of cloud computing adoption using an integrated TAM-TOE model. Journal of enterprise information management. 2015;28(1):107-30. DOI: https://doi.org/10.1108/JEIM-08-2013-0065
80. Ji H, Liang Y. Exploring the determinants affecting e-government cloud adoption in China. International Journal of Business and Management. 2016;11(4):81-90. DOI: https://doi.org/10.5539/ijbm.v11n4p81
81. Senyo PK, Effah J, Addae E. Preliminary insight into cloud computing adoption in a developing country. Journal of enterprise information management. 2016;29(4):505-24. DOI: https://doi.org/10.1108/JEIM-09-2014-0094
82. Bhardwaj AK, Garg L, Garg A, Gajpal Y. E-learning during covid-19 outbreak: cloud computing adoption in Indian public universities. Computers, Materials & Continua. 2021;66(3):2471-92. DOI: https://doi.org/10.32604/cmc.2021.014099
83. Shirpoor M, Ranimi N. A Study of Organizational Changes that Occur to the Adoption of Cloud Computing Technologies in Organizations: Ministry of Communication and Information Technology in Afghanistan. Journal of Computer Science and Technology Studies. 2023;5(4):51-61. DOI: https://doi.org/10.32996/jcsts.2023.5.4.6
84. Kandil AMNA, Ragheb MA, Ragab AA, Farouk M. Examining the effect of TOE model on cloud computing adoption in Egypt. The Business & Management Review. 2018;9(4):113-23.
85. Amron M, Noh NM. Technology acceptance model (TAM) for analysing cloud computing acceptance in higher education institution (HEI). IOP Conference Series: Materials Science and Engineering; United Kingdom: IOP Publishing; 2021. p. 012036. DOI: https://doi.org/10.1088/1757-899X/1176/1/012036
86. Juma MK, Tjahyanto A. Challenges of cloud computing adoption model for higher education level in Zanzibar (the case study of Suza and Zu). The Fifth Information Systems International Conference 2019 Surabaya, Indonesia2019. p. 1046-54. DOI: https://doi.org/10.1016/j.procs.2019.11.215
87. Gangwar H, Date H, Ramaswamy R. Developing a cloud-computing adoption framework. Global Business Review. 2015;16(4):632-51. DOI: https://doi.org/10.1177/0972150915581108
88. van de Weerd I, Mangula IS, Brinkkemper S. Adoption of software as a service in Indonesia: Examining the influence of organizational factors. Information & management. 2016;53(7):915-28. DOI: https://doi.org/10.1016/j.im.2016.05.008
89. Rehman MH, Rajkumar M. Buying Behavior of Organizations for Software Products: Influence of Environmental Factors. Restaurant Business. 2019;118(10):252-71. DOI: https://doi.org/10.26643/rb.v118i10.9321
90. Kumar D, Samalia HV, Verma P. Factors influencing cloud computing adoption by small and medium-sized enterprises (SMEs) in India. Pacific Asia Journal of the Association for Information Systems. 2017;9(3):25-48. DOI: https://doi.org/10.17705/1pais.09302
91. Lutfi A, Saad M, Almaiah MA, Alsaad A, Al-Khasawneh A, Alrawad M, et al. Actual use of mobile learning technologies during social distancing circumstances: Case study of King Faisal University students. Sustainability. 2022;14(12):7323-41. DOI: https://doi.org/10.3390/su14127323
92. Rogers E. Diffusion of innovations, 5th edn Tampa. 5th edition ed. New York: Free Press; 2003.
93. Lumsden JR, Gutierrez A. Understanding the determinants of cloud computing adoption within the UK. European, Mediterranean and Middle Eastern Conference on Information Systems (EMCIS) UK2013.
94. Sayginer C, Ercan T. Understanding determinants of cloud computing adoption using an integrated diffusion of innovation (doi)-technological, organizational and environmental (toe) model. Humanities & Social Sciences Reviews. 2020;8(1):91-102. DOI: https://doi.org/10.18510/hssr.2020.8115
95. Lian J-W, Yen DC, Wang Y-T. An exploratory study to understand the critical factors affecting the decision to adopt cloud computing in Taiwan hospital. International journal of information management. 2014;34(1):28-36. DOI: https://doi.org/10.1016/j.ijinfomgt.2013.09.004
96. Atobishi TQA. Adoption Factors of Cloud Computing Technology. Hungary: Szent István University; 2020.
97. Alharbi F, Atkins A, Stanier C. Strategic framework for cloud computing decision-making in healthcare sector in Saudi Arabia. The seventh international conference on ehealth, telemedicine, and social medicine; Lisbon, Portugal2015. p. 138-44.
98. Premkumar G, Roberts M. Adoption of new information technologies in rural small businesses. Omega. 1999;27(4):467-84. DOI: https://doi.org/10.1016/S0305-0483(98)00071-1
99. Lynn T, Fox G, Gourinovitch A, Rosati P. Understanding the determinants and future challenges of cloud computing adoption for high performance computing. Future Internet. 2020;12(8):135-52. DOI: https://doi.org/10.3390/fi12080135
100. Ali O, Shrestha A, Osmanaj V, Muhammed S. Cloud computing technology adoption: an evaluation of key factors in local governments. Information Technology & People. 2021;34(2):666-703. DOI: https://doi.org/10.1108/ITP-03-2019-0119
101. Buyya R, Yeo CS, Venugopal S, Broberg J, Brandic I. Cloud computing and emerging IT platforms: Vision, hype, and reality for delivering computing as the 5th utility. Future Generation Computer Systems. 2009;25(6):599-616. DOI: https://doi.org/10.1016/j.future.2008.12.001
102. Lin A, Chen N-C. Cloud computing as an innovation: Percepetion, attitude, and adoption. International journal of information management. 2012;32(6):533-40. DOI: https://doi.org/10.1016/j.ijinfomgt.2012.04.001
103. Bradford M, Florin J. Examining the role of innovation diffusion factors on the implementation success of enterprise resource planning systems. International journal of accounting information systems. 2003;4(3):205-25. DOI: https://doi.org/10.1016/S1467-0895(03)00026-5
104. Tsai M-C, Lee W, Wu H-C. Determinants of RFID adoption intention: Evidence from Taiwanese retail chains. Information & management. 2010;47(5-6):255-61. DOI: https://doi.org/10.1016/j.im.2010.05.001
105. Suki NM. Subscribers’ intention towards using 3G mobile services. Journal Of Economics and Behavioral Studies. 2011;2(2):67-75. DOI: https://doi.org/10.22610/jebs.v2i2.223
106. Park JK, Yang S, Lehto X. Adoption of mobile technologies for Chinese consumers. Journal Of Electronic Commerce Research. 2007;8(3):196-206.
107. Davis FD. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly. 1989;13(3):319-40. DOI: https://doi.org/10.2307/249008
108. Khayer A, Jahan N, Hossain MN, Hossain MY. The adoption of cloud computing in small and medium enterprises: a developing country perspective. VINE Journal of Information and Knowledge Management Systems. 2021;51(1):64-91. DOI: https://doi.org/10.1108/VJIKMS-05-2019-0064
109. Peng CH, Hsu CF, Tseng YH. Student User Acceptance Behavior of M-Commerce in Taiwan. International Conference on Management; Bangkok2011.
110. Moghavvemi S, Salleh NAM, Zhao W, Mattila M. The entrepreneur's perception on information technology innovation adoption: An empirical analysis of the role of precipitating events on usage behavior. Innovation: Management, Policy & Practice. 2012;14(2):231-46. DOI: https://doi.org/10.5172/impp.2012.14.2.231
111. Nusir M, Alshirah M, Alghsoon R. Investigating smart city adoption from the citizen’s insights: empirical evidence from the Jordan context. PeerJ Computer Science. 2023;9:e1289. DOI: https://doi.org/10.7717/peerj-cs.1289
112. Mohammad AH. The effects of usability and accessibility for e-government services on the end-user satisfaction. International Journal of Interactive Mobile Technologies. 2020;14(13):78-90. DOI: https://doi.org/10.3991/ijim.v14i13.14659
113. Davis FD. User acceptance of information technology: system characteristics, user perceptions and behavioral impacts. International Journal of Man-Machine Studies. 1993;38 (3):475-87. DOI: https://doi.org/10.1006/imms.1993.1022
114. Koivumäki T, Ristola A, Kesti M. The perceptions towards mobile services: an empirical analysis of the role of use facilitators. Personal and ubiquitous computing. 2008;12(1):67-75. DOI: https://doi.org/10.1007/s00779-006-0128-x
115. Sreenivasan J, Noor MNM. A conceptual framework on mobile commerce acceptance and usage among Malaysian consumers: the influence of location, privacy, trust and purchasing power. WSEAS Transactions on Information Science and Applications. 2010;7(5):661-70.
116. Zhou T, Lu Y, Wang B. Integrating TTF and UTAUT to explain mobile banking user adoption. Computers in Human Behavior. 2010;26(4):760-7. DOI: https://doi.org/10.1016/j.chb.2010.01.013
117. Kaufman LM. Data security in the world of cloud computing. IEEE Security & Privacy. 2009;7(4):61-4. DOI: https://doi.org/10.1109/MSP.2009.87
118. Amini M. The factors that influence on adoption of cloud computing for small and medium enterprises. Malaysia: Universiti Teknologi Malaysia; 2014.
119. Al-Jabri IM. The perceptions of adopters and non-adopters of cloud computing: application of technology-organization-environment framework. The 14th International Conference of Electronic Business; Taipei, Taiwan2014.
120. Kiratu LW. Digitization Readiness Assessment in Public Organizations a Case of Kenya National Examinations Council. Kenya: University of Nairobi; 2020.
121. Shea CM, Jacobs SR, Esserman DA, Bruce K, Weiner BJ. Organizational readiness for implementing change: a psychometric assessment of a new measure. Implementation science. 2014;9(1):1-15. DOI: https://doi.org/10.1186/1748-5908-9-7
122. Weiner BJ, Amick H, Lee S-YD. Conceptualization and measurement of organizational readiness for change: a review of the literature in health services research and other fields. Medical care research and review. 2008;65(4):379-436. DOI: https://doi.org/10.1177/1077558708317802
123. Trivedi H. Cloud adoption model for governments and large enterprises. Cambridge, MA: Massachusetts Institute of Technology; 2013.
124. Gutierrez A, Boukrami E, Lumsden R. Technological, organisational and environmental factors influencing managers’ decision to adopt cloud computing in the UK. Journal of enterprise information management. 2015;28(6):788-807. DOI: https://doi.org/10.1108/JEIM-01-2015-0001
125. Lee S, Kim K-j. Factors affecting the implementation success of Internet-based information systems. Computers in human behavior. 2007;23(4):1853-80. DOI: https://doi.org/10.1016/j.chb.2005.12.001
126. Pan M-J, Jang W-Y. Determinants of the adoption of enterprise resource planning within the technology-organization-environment framework: Taiwan's communications industry. Journal of Computer information systems. 2008;48(3):94-102.
127. Jambekar AB, Pelc KI. Managing a manufacturing company in a wired world. International journal of information technology and management. 2002;1(1):131-41. DOI: https://doi.org/10.1504/IJITM.2002.001192
128. Zhu K, Kraemer KL, Dedrick J. Information technology payoff in e-business environments: An international perspective on value creation of e-business in the financial services industry. Journal of management information systems. 2004;21(1):17-54. DOI: https://doi.org/10.1080/07421222.2004.11045797
129. Aboelmaged MG. Predicting e-readiness at firm-level: An analysis of technological, organizational and environmental (TOE) effects on e-maintenance readiness in manufacturing firms. International journal of information management. 2014;34(5):639-51. DOI: https://doi.org/10.1016/j.ijinfomgt.2014.05.002
130. AlGhamdi R, Nguyen A, Nguyen J, Drew S. Factors influencing E-commerce Adoption by Retailers in Saudi Arabia. International Conference on Internet Studies; Kuala Lumpur, Malaysia2012. p. 1-15. DOI: https://doi.org/10.1002/j.1681-4835.2011.tb00335.x
131. Zhu K, Kraemer KL, Xu S. The process of innovation assimilation by firms in different countries: a technology diffusion perspective on e-business. Management science. 2006;52(10):1557-76. DOI: https://doi.org/10.1287/mnsc.1050.0487
132. Sastararuji D, Hoonsopon D, Pitchayadol P, Chiwamit P. Cloud accounting adoption in Thai SMEs amid the COVID-19 pandemic: An explanatory case study. Journal of Innovation and Entrepreneurship. 2022;11(1):43-68. DOI: https://doi.org/10.1186/s13731-022-00234-3
133. Agarwal R, Prasad J. A conceptual and operational definition of personal innovativeness in the domain of information technology. Information systems research. 1998;9(2):204-15. DOI: https://doi.org/10.1287/isre.9.2.204
134. Liang T-P, Liu C-C, Wu C-H. Can social exchange theory explain individual knowledge-sharing behavior? A meta-analysis. Twenty Ninth International Conference on Information Systems; Paris2008. p. 1-19.
135. AlKharusi MH, Al-Badi AH, editors. IT personnel perspective of the slow adoption of cloud computing in public sector: Case study in Oman. 2016 3rd MEC International Conference on Big Data and Smart City (ICBDSC); 2016; Muscat, Oman: IEEE. DOI: https://doi.org/10.1109/ICBDSC.2016.7460364
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Saleh Alqatan, Mohammad Alshirah, Mohammad Bany Baker, Hayel Khafajeh, Suhaila Abuowaida (Author)
This work is licensed under a Creative Commons Attribution 4.0 International License.
The article is distributed under the Creative Commons Attribution 4.0 License. Unless otherwise stated, associated published material is distributed under the same licence.
