Volume 10, Issue 7 (July 2023), Pages: 66-79
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Review Paper
Analyzing the factors influencing the adoption of cloud computing by SMEs using the SEM approach
Author(s):
Abdifatah Farah Ali 1, *, Abdikarim Abi Hassan 2, Husein Osman Abdullahi 1, Rusli Haji Abdulah 3
Affiliation(s):
1Faculty of Computing, SIMAD University, Mogadishu, Somalia
2Faculty of Engineering, SIMAD University, Mogadishu, Somalia
3Department of Software Engineering and Information System, University Putra Malaysia, Selangor, Malaysia
Full Text - PDF XML
* Corresponding Author.
Corresponding author's ORCID profile: https://orcid.org/0000-0003-4388-606X
Digital Object Identifier:
https://doi.org/10.21833/ijaas.2023.07.009
Abstract:
Cloud computing (CC) represents a third-generation computing platform that offers numerous benefits, including faster data transactions, cost advantages, elasticity, flexibility, and pay-per-use models, among others. However, CC adoption in developing nations, such as Somalia, is impeded by various challenges. This study aims to investigate the factors influencing CC adoption in small to medium-sized enterprises (SMEs) in Somalia. Data was collected from 195 ICT officials and experts in the SME domain in Mogadishu, Somalia, and analyzed using structural equation modeling (SEM). The results revealed that cost savings, firm size, top management support, and regulatory support significantly influence CC adoption in SMEs. Conversely, security concerns and competitive pressure showed no significant relationship with CC adoption. This study contributes to the literature by examining the technology, organization, and environment (TOE) framework in the context of CC adoption and provides valuable insights to inform policymaking and promote CC adoption in developing nations. Nonetheless, the study's limitation lies in its narrow focus on Somalia, and the generalizability of the results to other developing nations may be limited.
© 2023 The Authors. Published by IASE.
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Cloud computing, Technology adoption, TOE framework, SMEs
Article History: Received 3 December 2022, Received in revised form 1 May 2023, Accepted 16 May 2023
Acknowledgment
The work was funded by a research grant from the SIMAD University Centre for Research and Development, which the writers gratefully appreciate. The writers would also like to thank all of the research participants.
Compliance with ethical standards
Conflict of interest: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Citation:
Ali AF, Hassan AA, Abdullahi HQ, and Abdulah RH (2023). Analyzing the factors influencing the adoption of cloud computing by SMEs using the SEM approach. International Journal of Advanced and Applied Sciences, 10(7): 66-79
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Figures
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References (117)
- Abdollahzadegan A, Che Hussin AR, Moshfegh Gohary M, and Amini M (2013). The organizational critical success factors for adopting cloud computing in SMEs. Journal of Information Systems Research and Innovation, 4(1): 67-74. [Google Scholar]
- Aldossary M, Djemame K, Alzamil I, Kostopoulos A, Dimakis A, and Agiatzidou E (2019). Energy-aware cost prediction and pricing of virtual machines in cloud computing environments. Future Generation Computer Systems, 93: 442-459. https://doi.org/10.1016/j.future.2018.10.027 [Google Scholar]
- Ali A, Warren D, and Mathiassen L (2017). Cloud-based business services innovation: A risk management model. International Journal of Information Management, 37(6): 639-649. https://doi.org/10.1016/j.ijinfomgt.2017.05.008 [Google Scholar]
- Alkhater N, Wills G, and Walters R (2014). Factors influencing an organisation's intention to adopt cloud computing in Saudi Arabia. In the IEEE 6th International Conference on Cloud Computing Technology and Science, IEEE, Singapore, Singapore: 1040-1044. https://doi.org/10.1109/CloudCom.2014.95 [Google Scholar]
- Alshamaila Y, Papagiannidis S, and Li F (2013). Cloud computing adoption by SMEs in the north east of England: A multi‐perspective framework. Journal of Enterprise Information Management, 26(3): 250-275. https://doi.org/10.1108/17410391311325225 [Google Scholar]
- Al-Sharafi MA, Arshah RA, and Abu-Shanab EA (2019). Questionnaire development process to measure the SMEs' continuous use behavior towards cloud computing services. In the 8th International Conference on Software and Computer Applications, Association for Computing Machinery, Penang, Malaysia: 50-55. https://doi.org/10.1145/3316615.3316723 [Google Scholar]
- Alsmadi D and Prybutok V (2018). Sharing and storage behavior via cloud computing: Security and privacy in research and practice. Computers in Human Behavior, 85: 218-226. https://doi.org/10.1016/j.chb.2018.04.003 [Google Scholar]
- Armbrust M, Fox A, Griffith R, Joseph AD, Katz R, Konwinski A, and Zaharia M (2010). A view of cloud computing. Communications of the ACM, 53(4): 50-58. https://doi.org/10.1145/1721654.1721672 [Google Scholar]
- Assante D, Castro M, Hamburg I, and Martin S (2016). The use of cloud computing in SMEs. Procedia Computer Science, 83: 1207-1212. https://doi.org/10.1016/j.procs.2016.04.250 [Google Scholar]
- Asvija B, Eswari R, and Bijoy MB (2019). Security in hardware assisted virtualization for cloud computing: State of the art issues and challenges. Computer Networks, 151: 68-92. https://doi.org/10.1016/j.comnet.2019.01.013 [Google Scholar]
- Attaran M and Woods J (2019). Cloud computing technology: Improving small business performance using the Internet. Journal of Small Business and Entrepreneurship, 31(6): 495-519. https://doi.org/10.1080/08276331.2018.1466850 [Google Scholar]
- Bajenaru A (2010). Software-as-a-service and cloud computing, a solution for small and medium-sized companies: Bulletin of the Transilvania University of Brasov. Economic Sciences: Series V, 3(52): 173-184. [Google Scholar]
- Battleson DA, West BC, Kim J, Ramesh B, and Robinson PS (2016). Achieving dynamic capabilities with cloud computing: An empirical investigation. European Journal of Information Systems, 25: 209-230. https://doi.org/10.1057/ejis.2015.12 [Google Scholar]
- Benlian A and Hess T (2011). Opportunities and risks of software-as-a-service: Findings from a survey of IT executives. Decision Support Systems, 52(1): 232-246. https://doi.org/10.1016/j.dss.2011.07.007 [Google Scholar]
- Bishop M (2003). Computer security: Art and science. Addison Wesley Professional, Boston, USA. [Google Scholar]
- Borgman HP, Bahli B, Heier H, and Schewski F (2013). Cloudrise: exploring cloud computing adoption and governance with the TOE framework. In the 46th Hawaii International Conference on System Sciences, IEEE, Wailea, USA: 4425-4435. https://doi.org/10.1109/HICSS.2013.132 [Google Scholar]
- Bruque Camara S, Moyano Fuentes J, and Maqueira Marín JM (2015). Cloud computing, Web 2.0, and operational performance: The mediating role of supply chain integration. The International Journal of Logistics Management, 26(3): 426-458. https://doi.org/10.1108/IJLM-07-2013-0085 [Google Scholar]
- Buyya R, Broberg J, and Goscinski AM (2010). Cloud computing: Principles and paradigms. John Wiley and Sons, Hoboken, USA. https://doi.org/10.1002/9780470940105 [Google Scholar]
- Cegielski CG, Jones‐Farmer LA, Wu Y, and Hazen BT (2012). Adoption of cloud computing technologies in supply chains: An organizational information processing theory approach. The International Journal of Logistics Management, 23(2): 184-211. https://doi.org/10.1108/09574091211265350 [Google Scholar]
- Cervone HF (2010). An overview of virtual and cloud computing. OCLC Systems and Services: International Digital Library Perspectives, 26(3): 162-165. https://doi.org/10.1108/10650751011073607 [Google Scholar]
- Chae HC, Koh CE, and Park KO (2018). Information technology capability and firm performance: Role of industry. Information and Management, 55(5): 525-546. https://doi.org/10.1016/j.im.2017.10.001 [Google Scholar]
- Chen PY and Wu SY (2013). The impact and implications of on-demand services on market structure. Information Systems Research, 24(3): 750-767. https://doi.org/10.1287/isre.1120.0451 [Google Scholar]
- Chong AYL and Chan FT (2012). Structural equation modeling for multi-stage analysis on radio frequency identification (RFID) diffusion in the health care industry. Expert Systems with Applications, 39(10): 8645-8654. https://doi.org/10.1016/j.eswa.2012.01.201 [Google Scholar]
- Chong AYL, Lin B, Ooi KB, and Raman M (2009). Factors affecting the adoption level of c-commerce: An empirical study. Journal of Computer Information Systems, 50(2): 13-22. [Google Scholar]
- Cohen J (1988). Statistical power analysis for the behavioral sciences. 2nd Edition, Lawrence Erlbaum Associates, Hillsdale, USA. [Google Scholar]
- Crook CW and Kumar RL (1998). Electronic data interchange: A multi-industry investigation using grounded theory. Information and Management, 34(2): 75-89. https://doi.org/10.1016/S0378-7206(98)00040-8 [Google Scholar]
- Demirkan H and Delen D (2013). Leveraging the capabilities of service-oriented decision support systems: Putting analytics and big data in cloud. Decision Support Systems, 55(1): 412-421. https://doi.org/10.1016/j.dss.2012.05.048 [Google Scholar]
- Doherty E, Carcary M, and Conway G (2015). Migrating to the cloud: Examining the drivers and barriers to adoption of cloud computing by SMEs in Ireland: An exploratory study. Journal of Small Business and Enterprise Development, 22(3): 512-527. https://doi.org/10.1108/JSBED-05-2013-0069 [Google Scholar]
- EIU (2015). Ascending cloud: The adoption of cloud computing in five industries. The Economist Intelligence Unit, London, UK. [Google Scholar]
- El-Gazzar R, Hustad E, and Olsen DH (2016). Understanding cloud computing adoption issues: A Delphi study approach. Journal of Systems and Software, 118: 64-84. https://doi.org/10.1016/j.jss.2016.04.061 [Google Scholar]
- Fatima S and Ahmad S (2019). An exhaustive review on security issues in cloud computing. KSII Transactions on Internet and Information Systems, 13(6): 3219-3237. https://doi.org/10.3837/tiis.2019.06.025 [Google Scholar]
- Fornell C and Larcker DF (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 18(3): 382–388. https://doi.org/10.1177/002224378101800313 [Google Scholar]
- Gangwar H, Date H, and Ramaswamy R (2015). Understanding determinants of cloud computing adoption using an integrated TAM-TOE model. Journal of Enterprise Information Management, 28(1): 107-130. https://doi.org/10.1108/JEIM-08-2013-0065 [Google Scholar]
- Gans J, Hervé M, and Masri M (2023). Economic analysis of proposed regulations of cloud services in Europe. European Competition Journal. https://doi.org/10.1080/17441056.2023.2228668 [Google Scholar]
- Garrison G, Kim S, and Wakefield RL (2012). Success factors for deploying cloud computing. Communications of the ACM, 55(9): 62-68. https://doi.org/10.1145/2330667.2330685 [Google Scholar]
- Gold AH, Malhotra A, and Segars AH (2001). Knowledge management: An organizational capabilities perspective. Journal of Management Information Systems, 18(1): 185-214. https://doi.org/10.1080/07421222.2001.11045669 [Google Scholar]
- Grossman RL (2009). The case for cloud computing. IT Professional, 11(2): 23-27. https://doi.org/10.1109/MITP.2009.40 [Google Scholar]
- Gupta P, Seetharaman A, and Raj JR (2013). The usage and adoption of cloud computing by small and medium businesses. International Journal of Information Management, 33(5): 861-874. https://doi.org/10.1016/j.ijinfomgt.2013.07.001 [Google Scholar]
- Hair JF, Ringle CM, and Sarstedt M (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2): 139-152. https://doi.org/10.2753/MTP1069-6679190202 [Google Scholar]
- Hair JF, Ringle CM, and 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 [Google Scholar]
- Hair Jr JF, Hult GTM, Ringle C, and Sarstedt M (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications, Thousand Oaks, USA. [Google Scholar]
- Henseler J, Ringle CM, and Sarstedt M (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43: 115-135. https://doi.org/10.1007/s11747-014-0403-8 [Google Scholar]
- Hogan M, Liu F, Sokol A, and Tong J (2011). NIST cloud computing standards roadmap. NIST Special Publication, 35: 6-11. https://doi.org/10.6028/NIST.SP.500-291v1 [Google Scholar]
- Ifinedo P (2011). Internet/e‐business technologies acceptance in Canada's SMEs: An exploratory investigation. Internet Research, 21(3): 255-281. https://doi.org/10.1108/10662241111139309 [Google Scholar]
- Iyer B and Henderson JC (2010). Preparing for the future: Understanding the seven capabilities cloud computing. MIS Quarterly Executive, 9(2): 117-131. [Google Scholar]
- Jede A and Teuteberg F (2015). Integrating cloud computing in supply chain processes. Journal of Enterprise Information Management, 28(6): 872-904. https://doi.org/10.1108/JEIM-08-2014-0085 [Google Scholar]
- Kasemsap K (2015). The role of cloud computing adoption in global business. In: Chang V, Walters RJ, and Wills G (Eds.), Delivery and adoption of cloud computing services in contemporary organizations: 26-55. IGI Global, Pennsylvania, USA. https://doi.org/10.4018/978-1-4666-8210-8.ch002 [Google Scholar]
- Khorshed MT, Ali AS, and Wasimi SA (2012). A survey on gaps, threat remediation challenges and some thoughts for proactive attack detection in cloud computing. Future Generation Computer Systems, 28(6): 833-851. https://doi.org/10.1016/j.future.2012.01.006 [Google Scholar]
- Kline RB (2015). Principles and practice of structural equation modeling. Guilford Publications, New York, USA. [Google Scholar]
- Kranz JJ, Hanelt A, and Kolbe LM (2016). Understanding the influence of absorptive capacity and ambidexterity on the process of business model change–The case of on‐premise and cloud‐computing software. Information Systems Journal, 26(5): 477-517. https://doi.org/10.1111/isj.12102 [Google Scholar]
- Lee OK, Sambamurthy V, Lim KH, and Wei KK (2015). How does IT ambidexterity impact organizational agility? Information Systems Research, 26(2): 398-417. https://doi.org/10.1287/isre.2015.0577 [Google Scholar]
- Lian JW, Yen DC, and Wang YT (2014). An exploratory study to understand the critical factors affecting the decision to adopt cloud computing in Taiwan hospital. International Journal of Information Management, 34(1): 28-36. https://doi.org/10.1016/j.ijinfomgt.2013.09.004 [Google Scholar]
- Lin A and Chen NC (2012). Cloud computing as an innovation: Percepetion, attitude, and adoption. International Journal of Information Management, 32(6): 533-540. https://doi.org/10.1016/j.ijinfomgt.2012.04.001 [Google Scholar]
- Lin G, Fu D, Zhu J, and Dasmalchi G (2009). Cloud computing: IT as a service. IT Professional, 11(2): 10-13. https://doi.org/10.1109/MITP.2009.22 [Google Scholar]
- Lippert SK and Govindarajulu C (2006). Technological, organizational, and environmental antecedents to web services adoption. Communications of the IIMA, 6(1): 147-160. https://doi.org/10.58729/1941-6687.1303 [Google Scholar]
- Liu S, Chan FT, Yang J, and Niu B (2018). Understanding the effect of cloud computing on organizational agility: An empirical examination. International Journal of Information Management, 43: 98-111. https://doi.org/10.1016/j.ijinfomgt.2018.07.010 [Google Scholar]
- Liu S, Yang Y, Qu WG, and Liu Y (2016). The business value of cloud computing: The partnering agility perspective. Industrial Management and Data Systems, 116(6): 1160-1177. https://doi.org/10.1108/IMDS-09-2015-0376 [Google Scholar]
- Low C, Chen Y, and Wu M (2011). Understanding the determinants of cloud computing adoption. Industrial Management and Data Systems, 111(7): 1006-1023. https://doi.org/10.1108/02635571111161262 [Google Scholar]
- Lowry PB, D’Arcy J, Hammer B, and Moody GD (2016). “Cargo Cult” science in traditional organization and information systems survey research: A case for using nontraditional methods of data collection, including Mechanical Turk and online panels. The Journal of Strategic Information Systems, 25(3): 232-240. https://doi.org/10.1016/j.jsis.2016.06.002 [Google Scholar]
- Lu Y and Ramamurthy K (2011). Understanding the link between information technology capability and organizational agility: An empirical examination. MIS Quarterly, 35(4): 931-954. https://doi.org/10.2307/41409967 [Google Scholar]
- Lu Y, Xu X, and Xu J (2014). Development of a hybrid manufacturing cloud. Journal of Manufacturing Systems, 33(4): 551-566. https://doi.org/10.1016/j.jmsy.2014.05.003 [Google Scholar]
- Luo X, Gurung A, and Shim JP (2010). Understanding the determinants of user acceptance of enterprise instant messaging: An empirical study. Journal of Organizational Computing and Electronic Commerce, 20(2): 155-181. https://doi.org/10.1080/10919391003709179 [Google Scholar]
- Luo X, Zhang W, Li H, Bose R, and Chung QB (2018). Cloud computing capability: Its technological root and business impact. Journal of Organizational Computing and Electronic Commerce, 28(3): 193-213. https://doi.org/10.1080/10919392.2018.1480926 [Google Scholar]
- Makena JN (2013). Factors that affect cloud computing adoption by small and medium enterprises in Kenya. International Journal of Computer Applications Technology and Research, 2(5): 517-521. https://doi.org/10.7753/IJCATR0205.1003 [Google Scholar]
- Marston S, Li Z, Bandyopadhyay S, Zhang J, and Ghalsasi A (2011). Cloud computing: The business perspective. Decision Support Systems, 51(1): 176-189. https://doi.org/10.1016/j.dss.2010.12.006 [Google Scholar]
- Mell P and Grance T (2011). The NIST definition of cloud computing. NIST Special Publication 800-145, National Institute of Standards and Technology, Gaithersburg, USA. https://doi.org/10.6028/NIST.SP.800-145 [Google Scholar]
- Misra SC and Mondal A (2011). Identification of a company’s suitability for the adoption of cloud computing and modelling its corresponding return on investment. Mathematical and Computer Modelling, 53(3-4): 504-521. https://doi.org/10.1016/j.mcm.2010.03.037 [Google Scholar]
- Mourtzis D and Vlachou E (2016). Cloud-based cyber-physical systems and quality of services. The TQM Journal, 28(5): 704-733. https://doi.org/10.1108/TQM-10-2015-0133 [Google Scholar]
- Muñoz A, Gonzalez J, and Maña A (2012). A performance-oriented monitoring system for security properties in cloud computing applications. The Computer Journal, 55(8): 979-994. https://doi.org/10.1093/comjnl/bxs042 [Google Scholar]
- O’Driscoll A, Daugelaite J, and Sleator RD (2013). ‘Big data’, Hadoop and cloud computing in genomics. Journal of Biomedical Informatics, 46(5): 774-781. https://doi.org/10.1016/j.jbi.2013.07.001 [Google Scholar] PMid:23872175
- Oliveira T and Martins MF (2010). Understanding e‐business adoption across industries in European countries. Industrial Management and Data Systems, 110(9): 1337-1354. https://doi.org/10.1108/02635571011087428 [Google Scholar]
- Oliveira T, Thomas M, and Espadanal M (2014). Assessing the determinants of cloud computing adoption: An analysis of the manufacturing and services sectors. Information and Management, 51(5): 497-510. https://doi.org/10.1016/j.im.2014.03.006 [Google Scholar]
- Park SC and Ryoo SY (2013). An empirical investigation of end-users’ switching toward cloud computing: A two factor theory perspective. Computers in Human Behavior, 29(1): 160-170. https://doi.org/10.1016/j.chb.2012.07.032 [Google Scholar]
- Parkhill DF (1966). Challenge of the computer utility. Addison-Wesley Publisher, Boston, USA. [Google Scholar]
- Peng H, Wen WS, Tseng ML, and Li LL (2019). Joint optimization method for task scheduling time and energy consumption in mobile cloud computing environment. Applied Soft Computing, 80: 534-545. https://doi.org/10.1016/j.asoc.2019.04.027 [Google Scholar]
- Petter S, DeLone W, and McLean ER (2012). The past, present, and future of “IS success.” Journal of the Association for Information Systems, 13(5): 341-362. https://doi.org/10.17705/1jais.00296 [Google Scholar]
- Podsakoff PM, MacKenzie SB, Lee JY, and Podsakoff NP (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. Journal of Applied Psychology, 88(5): 879-903. https://doi.org/10.1037/0021-9010.88.5.879 [Google Scholar] PMid:14516251
- Ramdani B, Kawalek P, and Lorenzo O (2009). Predicting SMEs' adoption of enterprise systems. Journal of Enterprise Information Management, 22(1-2): 10-24. https://doi.org/10.1108/17410390910922796 [Google Scholar]
- Ringle CM, Wende S, and Becker JM (2015). SmartPLS 3. SmartPLS GmbH, Bönningstedt, Germany. [Google Scholar]
- Rittinghouse JW and Ransome JF (2017). Cloud computing: implementation, management, and security. CRC Press, Boca Raton, USA. https://doi.org/10.1201/9781439806814 [Google Scholar]
- Ryan WM and Loeffler CM (2010). Insights into cloud computing. Intellectual Property and Technology Law Journal, 22(11): 22-28. [Google Scholar]
- Sabi HM, Uzoka FME, Langmia K, Njeh FN, and Tsuma CK (2018). A cross-country model of contextual factors impacting cloud computing adoption at universities in sub-Saharan Africa. Information Systems Frontiers, 20: 1381-1404. https://doi.org/10.1007/s10796-017-9739-1 [Google Scholar]
- Saedi A and Iahad NA (2013). An integrated theoretical framework for cloud computing adoption by small and medium-sized enterprises. In the Pacific Asia Conference on Information Systems, Jeju Island, Korea: 1-12. https://doi.org/10.1109/ICRIIS.2013.6716757 [Google Scholar]
- Saha M, Panda SK, and Panigrahi S (2019). Distributed computing security: Issues and challenges. In: Le DN, Kumar R, Mishra BK, Chatterjee JM, and Khari M (Eds.), Cyber security in parallel and distributed computing: Concepts, techniques, applications and case studies: 129-138. John Wiley and Sons, Hoboken, USA. https://doi.org/10.1002/9781119488330.ch8 [Google Scholar] PMid:30269299
- Sarstedt M, Ringle CM, Smith D, Reams R, and Hair Jr JF (2014). Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers. Journal of Family Business Strategy, 5(1): 105-115. https://doi.org/10.1016/j.jfbs.2014.01.002 [Google Scholar]
- Schneiderman R (2010). For cloud computing, the sky is the limit [special reports]. IEEE Signal Processing Magazine, 28(1): 15-144. https://doi.org/10.1109/MSP.2010.938751 [Google Scholar]
- Senyo PK, Effah J, and Addae E (2016). Preliminary insight into cloud computing adoption in a developing country. Journal of Enterprise Information Management, 29(4): 505-524. https://doi.org/10.1108/JEIM-09-2014-0094 [Google Scholar]
- Sharma SK, Al-Badi AH, Govindaluri SM, and Al-Kharusi MH (2016). Predicting motivators of cloud computing adoption: A developing country perspective. Computers in Human Behavior, 62: 61-69. https://doi.org/10.1016/j.chb.2016.03.073 [Google Scholar]
- Shen Z and Tong Q (2010). The security of cloud computing system enabled by trusted computing technology. In the 2nd International Conference on Signal Processing Systems, IEEE, Dalian, China, 2: V2-11-V2-15. https://doi.org/10.1109/ICSPS.2010.5555234 [Google Scholar]
- Singh J and Mansotra V (2019). Factors affecting cloud computing adoption in the Indian school education system. Education and Information Technologies, 24(4): 2453-2475. https://doi.org/10.1007/s10639-019-09878-3 [Google Scholar]
- Son I, Lee D, Lee JN, and Chang YB (2014). Market perception on cloud computing initiatives in organizations: An extended resource-based view. Information and Management, 51(6): 653-669. https://doi.org/10.1016/j.im.2014.05.006 [Google Scholar]
- Sonehara N, Echizen I, and Wohlgemuth S (2011). Isolation in cloud computing and privacy-enhancing technologies: Suitability of privacy-enhancing technologies for separating data usage in business processes. Business and Information Systems Engineering, 3: 155-162. https://doi.org/10.1007/s12599-011-0160-x [Google Scholar]
- Sultan N (2014). Making use of cloud computing for healthcare provision: Opportunities and challenges. International Journal of Information Management, 34(2): 177-184. https://doi.org/10.1016/j.ijinfomgt.2013.12.011 [Google Scholar]
- Sultan NA (2011). Reaching for the “cloud”: How SMEs can manage. International Journal of Information Management, 31(3): 272-278. https://doi.org/10.1016/j.ijinfomgt.2010.08.001 [Google Scholar]
- Tehrani SR and Shirazi F (2014). Factors influencing the adoption of cloud computing by small and medium size enterprises (SMEs). In: Yamamoto S (Ed.), Human interface and the management of information: Information and knowledge in applications and services: 631-642. Volume 8522, Springer, Cham, Switzerland. https://doi.org/10.1007/978-3-319-07863-2_60 [Google Scholar]
- Thiesse F, Staake T, Schmitt P, and Fleisch E (2011). The rise of the “next‐generation bar code”: An international RFID adoption study. Supply Chain Management: An International Journal, 16(5): 328-345. https://doi.org/10.1108/13598541111155848 [Google Scholar]
- Tornatzky LG, Fleischer M, and Chakrabarti AK (1990). Processes of technological innovation. Lexington Books, Lanham, USA. [Google Scholar]
- Truong D (2010). How cloud computing enhances competitive advantages: A research model for small businesses. The Business Review, Cambridge, 15(1): 59-65. [Google Scholar]
- Vasiljeva T, Shaikhulina S, and Kreslins K (2017). Cloud computing: Business perspectives, benefits and challenges for small and medium enterprises (case of Latvia). Procedia Engineering, 178: 443-451. https://doi.org/10.1016/j.proeng.2017.01.087 [Google Scholar]
- Vemula R and Zsifkovits H (2016). Cloud computing for supply chain management. BHM Berg-und Hüttenmännische Monatshefte, 161: 229-232. https://doi.org/10.1007/s00501-016-0485-3 [Google Scholar]
- Vidhyalakshmi R and Kumar V (2016). Determinants of cloud computing adoption by SMEs. International Journal of Business Information Systems, 22(3): 375-395. [Google Scholar]
- Voas J and Zhang J (2009). Cloud computing: New wine or just a new bottle? IT Professional, 11(2): 15-17. https://doi.org/10.1109/MITP.2009.23 [Google Scholar]
- Wang H (2010). Privacy-preserving data sharing in cloud computing. Journal of Computer Science and Technology, 25: 401-414. https://doi.org/10.1007/978-3-031-01834-3 [Google Scholar]
- Wang N, Liang H, Jia Y, Ge S, Xue Y, and Wang Z (2016). Cloud computing research in the IS discipline: A citation/co-citation analysis. Decision Support Systems, 86: 35-47. https://doi.org/10.1016/j.dss.2016.03.006 [Google Scholar]
- Wang YM, Wang YS, and Yang YF (2010). Understanding the determinants of RFID adoption in the manufacturing industry. Technological Forecasting and Social Change, 77(5): 803-815. https://doi.org/10.1016/j.techfore.2010.03.006 [Google Scholar]
- Willcocks LP and Lacity M (2018). Cloud computing as innovation: Cases and practices. In: Willcocks L, Oshri I, and Kotlarsky J (Eds.), Dynamic innovation in outsourcing: Technology, work and globalization: 197-237. Palgrave Macmillan, Cham, Switzerland. https://doi.org/10.1007/978-3-319-75352-2_7 [Google Scholar]
- Wu D, Greer MJ, Rosen DW, and Schaefer D (2013). Cloud manufacturing: Strategic vision and state-of-the-art. Journal of Manufacturing Systems, 32(4): 564-579. https://doi.org/10.1016/j.jmsy.2013.04.008 [Google Scholar]
- Wu WW, Lan LW, and Lee YT (2011). Exploring decisive factors affecting an organization's SaaS adoption: A case study. International Journal of Information Management, 31(6): 556-563. https://doi.org/10.1016/j.ijinfomgt.2011.02.007 [Google Scholar]
- Xu J and Quaddus M (2012). Examining a model of knowledge management systems adoption and diffusion: A partial least square approach. Knowledge-Based Systems, 27: 18-28. https://doi.org/10.1016/j.knosys.2011.10.003 [Google Scholar]
- Yadav R and Sharma A (2018). A critical review of data security in cloud computing infrastructure. International Journal of Advanced Studies of Scientific Research, 3(9): 112-117. [Google Scholar]
- Yeboah-Boateng EO and Essandoh KA (2014). Factors influencing the adoption of cloud computing by small and medium enterprises in developing economies. International Journal of Emerging Science and Engineering, 2(4): 13-20. [Google Scholar]
- Zhang Q, Cheng L, and Boutaba R (2010). Cloud computing: State-of-the-art and research challenges. Journal of Internet Services and Applications, 1: 7-18. https://doi.org/10.1007/s13174-010-0007-6 [Google Scholar]
- Zhou Z, Abawajy JH, and Li F (2019). Analysis of energy consumption model in cloud computing environments. In: Herawan T, Chiroma H, and Abawajy J (Eds.), Advances on computational intelligence in energy: The applications of nature-inspired metaheuristic algorithms in energy: 195-215. Springer, Cham, Switzerland. https://doi.org/10.1007/978-3-319-69889-2_10 [Google Scholar]
- Zhu K and Kraemer KL (2005). Post-adoption variations in usage and value of e-business by organizations: Cross-country evidence from the retail industry. Information Systems Research, 16(1): 61-84. https://doi.org/10.1287/isre.1050.0045 [Google Scholar]
- Zhu K, Kraemer K, and Xu S (2003). Electronic business adoption by European firms: A cross-country assessment of the facilitators and inhibitors. European Journal of Information Systems, 12: 251-268. https://doi.org/10.1057/palgrave.ejis.3000475 [Google Scholar]
- Zhu K, Kraemer KL, and Xu S (2006). The process of innovation assimilation by firms in different countries: A technology diffusion perspective on e-business. Management Science, 52(10): 1557-1576. https://doi.org/10.1287/mnsc.1050.0487 [Google Scholar]
- Zissis D and Lekkas D (2012). Addressing cloud computing security issues. Future Generation Computer Systems, 28(3): 583-592. https://doi.org/10.1016/j.future.2010.12.006 [Google Scholar]
|