4 Discussion
4.2 Limitations and Future Research
Although the present study developed a conceptual model based on four well-known established theories, the main limitation is that it did not validate the proposed model in an empirical study. Therefore, it is highly recommended that further research should validate the proposed model in an empirical study in order to understand the factors affecting the adoption of CC in HEIs. In addition, it was unfortunate that the present study did not consider the role of any moderating variables in understanding the adoption of CC in HEIs. Further research could consider this point by extending the proposed conceptual model with some moderating factors.
5 Conclusion
CC offers a number of opportunities in terms of scalability and cost-efficiency. The unique features of CC allow the HEIs to make CEaaS as a reality in the educational community at a rapid speed and low costs. Despite these significant features, under- standing the factors affecting the CC adoption at the organizational level of HEIs is still scarce and requires further research. Therefore, this research developed a conceptual model based on the integration of four well-known established theories, including TOE, FVM, DOI, and INT in order to understand the factors affecting the adoption of CC at the organizational level of HEIs.
The proposed model provides a theoretical basis through which to assess the fac- tors affecting the adoption of CC in HEIs by considering different characteristics, including task, organization, technology, and environment. With regard to the provi- sion of CEaaS initiatives in HEIs, it is considered that this research was able to make an original contribution through its focus on the effect of CC adoption. It is believed that the conclusions derived from this study would add a significant contribution to the existing literature on one hand, and the decision-makers in the HEIs on the other hand.
Acknowledgements The authors would like to thank Universiti Putra Malaysia (UPM)—RMC—
for supporting and funding this research under Grant No. 95223100.
Towards the Development of a Comprehensive Theoretical … 71
References
1. Mell, P., Grance, T.: The NIST definition of cloud computing (2011)
2. Armbrust, M., et al.: A view of cloud computing. Commun. ACM53(4), 50–58 (2010) 3. Abdullah, R., Eri, Z.D., Talib, A.M.: A model of knowledge management system for facili-
tating knowledge as a service (KaaS) in cloud computing environment. In: 2011 International Conference on Research and Innovation in Information Systems (ICRIIS), pp. 1–4. IEEE (2011) 4. AlAjmi, Q., Arshah, R.A., Kamaludin, A., Sadiq, A.S., Al-Sharafi, M.A.: A conceptual model of e-learning based on cloud computing adoption in higher education institutions. In: 2017 Inter- national Conference on Electrical and Computing Technologies and Applications (ICECTA), 21–23 Nov 2017, pp. 1–6 (2017).https://doi.org/10.1109/icecta.2017.8252013
5. Thomas, P.Y.: Cloud computing: a potential paradigm for practising the scholarship of teaching and learning. Electron. Libr. 29(2), 214–224 (2011). https://doi.org/10.1108/
02640471111125177
6. Razak, S.F.A.: Cloud computing in Malaysia universities. In: 2009 Innovative Technologies in Intelligent Systems and Industrial Applications, 25–26 July 2009, pp. 101–106 (2009).https://
doi.org/10.1109/citisia.2009.5224231
7. Abdullah, R., Alsharaei, Y.A.: A mobile knowledge as a service (mKaaS) model of knowledge management system in facilitating knowledge sharing of cloud education community envi- ronment. In: 2016 Third International Conference on Information Retrieval and Knowledge Management (CAMP). IEEE, pp. 143–148 (2016)
8. Sabi, H.M., Uzoka, F.M.E., Langmia, K., Njeh, F.N.: Conceptualizing a model for adoption of cloud computing in education (in English). Int. J. Inf. Manage.36(2), 183–191 (2016).https://
doi.org/10.1016/j.ijinfomgt.2015.11.010
9. Alharthi, A., Alassafi, M.O., Walters, R.J., Wills, G.B.: An exploratory study for investigating the critical success factors for cloud migration in the Saudi Arabian higher education context.
Telematics Inform.34(2), 664–678 (2017).http://doi.org/10.1016/j.tele.2016.10.008 10. Tornatzky, L.G., Fleischer, M., Chakrabarti, A.K.: Processes of Technological Innovation.
Lexington Books, Lexington (1990)
11. Tjan, A.K.: Finally, a way to put your internet portfolio in order. Harvard Bus. Rev.79(2), 76–85, 156 (2001)
12. Rogers, E.M.: Diffusion of Innovations, vol. 12. Free Press, New York (1995)
13. Chatterjee, D., Grewal, R., Sambamurthy, V.: Shaping up for e-commerce: institutional enablers of the organizational assimilation of web technologies. MIS Q. 65–89 (2002)
14. Sultan, N.: Cloud computing for education: a new dawn? Int. J. Inf. Manage.30(2), 109–116 (2010).https://doi.org/10.1016/j.ijinfomgt.2009.09.004
15. Thorsteinsson, G., Page, T., Niculescu, A.: Using virtual reality for developing design communication. Stud. Inform. Control19(1), 93–106 (2010)
16. Pocatilu, P., Alecu, F., Vetrici, M.: Using cloud computing for E-learning systems. In: Pro- ceedings of the 8th WSEAS International Conference on Data Networks, Communications, Computers, pp. 54–59. Citeseer (2009)
17. Katz, R., Goldstein, P., Yanosky, R., Rushlo, B.: Cloud computing in higher education. In:
EDUCAUSE [Online], vol. 10. Retrieved October 5, 2010.http://net.educause.edu/section_
params/conf/CCW(2010)
18. Sasikala, S., Prema, S.: Massive centralized cloud computing (MCCC) exploration in higher education (2011)
19. Sabi, H.M., Uzoka, F.-M.E., Langmia, K., Njeh, F.N., Tsuma, C.K.: A cross-country model of contextual factors impacting cloud computing adoption at universities in sub-Saharan Africa.
Inform. Syst. Front. 1–24 (2017).https://doi.org/10.1007/s10796-017-9739-1
20. Alajmi, Q.A., Kamaludin, A., Arshah, R.A., Al-Sharafi, M.A.: The effectiveness of cloud-based e-learning towards quality of academic services: an Omanis. Expert view. Int. J. Adv. Comput.
Sci. Appl. (IJACSA)9(4), 158–164 (2018).https://doi.org/10.14569/ijacsa.2018.090425 21. Ashtari, S., Eydgahi, A.: Student perceptions of cloud applications effectiveness in higher
education. J. Comput. Sci.23, 173–180 (2017)
72 Y. A. M. Qasem et al.
22. Militaru, G., Purc˘area, A.A., Negoi¸t˘a, O.D., Niculescu, A.: Examining cloud computing adop- tion intention in higher education: exploratory study. In: International Conference on Exploring Services Science, pp. 732–741. Springer, Berlin (2016)
23. Bhatiasevi, V., Naglis, M.: Investigating the structural relationship for the determinants of cloud computing adoption in education. Educ. Inf. Technol.21(5), 1197–1223 (2016)
24. Almazroi, A.A., Shen, H., Teoh, K.-K., Babar, M.A.: Cloud for e-learning: determinants of its adoption by university students in a developing country. In: 2016 IEEE 13th International Conference on E-Business Engineering (ICEBE), pp. 71–78. IEEE (2016)
25. Hwang, B.-N., Huang, C.-Y., Yang, C.-L.: Determinants and their causal relationships affecting the adoption of cloud computing in science and technology institutions. Innovation18(2), 164–190 (2016)
26. Tashkandi, A.N., Al-Jabri, I.M.: Cloud computing adoption by higher education institutions in Saudi Arabia: an exploratory study. Cluster Comput.18(4), 1527–1537 (2015)
27. Behrend, T.S., Wiebe, E.N., London, J.E., Johnson, E.C.: Cloud computing adoption and usage in community colleges. Behav. Inf. Technol.30(2), 231–240 (2011)
28. Hsu, P.-F., Kraemer, K.L., Dunkle, D.: Determinants of e-business use in US firms. Int. J.
Electron. Commer.10(4), 9–45 (2006)
29. Martins, R., Oliveira, T., Thomas, M.A.: An empirical analysis to assess the determinants of SaaS diffusion in firms. Comput. Hum. Behav.62, 19–33 (2016)
30. Oliveira, T., Martins, M.F.: Literature review of information technology adoption models at firm level. Electron. J. Inf. Syst. Eval.14(1), 110–121 (2011)
31. Mohammed, F., Ibrahim, O., Nilashi, M., Alzurqa, E.: Cloud computing adoption model for e-government implementation. Inf. Dev.33(3), 303–323 (2017)
32. Goodhue, D.L., Thompson, R.L.: Task-technology fit and individual performance. MIS Q.
213–236 (1995)
33. Lee, C.-C., Cheng, H.K., Cheng, H.-H.: An empirical study of mobile commerce in insurance industry: task–technology fit and individual differences. Decis. Support Syst.43(1), 95–110 (2007)
34. Dishaw, M.T., Strong, D.M.: Extending the technology acceptance model with task–technology fit constructs. Inf. Manage.36(1), 9–21 (1999)
35. Teo, T.S., Men, B.: Knowledge portals in Chinese consulting firms: a task–technology fit perspective. Eur. J. Inf. Syst.17(6), 557–574 (2008)
36. Nance, W.D., Straub, D.W.: An investigation of task/technology fit and information technology choices in knowledge work. J. Inf. Technol. Manage.7, 1–14 (1996)
37. Lam, T., Cho, V., Qu, H.: A study of hotel employee behavioral intentions towards adoption of information technology. Int. J. Hospitality Manage.26(1), 49–65 (2007)
38. Yadegaridehkordi, E., Iahad, N.A., Ahmad, N.: Task-technology fit assessment of cloud-based collaborative learning technologies. In: Remote Work and Collaboration: Breakthroughs in Research and Practice, p. 371. IGI Global, USA (2017)
39. Chan, F.T., Chong, A.Y.-L.: Determinants of mobile supply chain management system diffu- sion: a structural equation analysis of manufacturing firms. Int. J. Prod. Res.51(4), 1196–1213 (2013)
40. Chong, A.Y.-L., Lin, B., Ooi, K.-B., Raman, M.: Factors affecting the adoption level of c- commerce: an empirical study. J. Comput. Inf. Syst.50(2), 13–22 (2009)
41. Ciganek, A.P., Haseman, W., Ramamurthy, K.: Time to decision: the drivers of innovation adoption decisions. Enterp. Inf. Syst.8(2), 279–308 (2014)
42. Oliveira, T., Thomas, M., Espadanal, M.: Assessing the determinants of cloud computing adoption: an analysis of the manufacturing and services sectors. Inf. Manag.51(5), 497–510 (2014)
43. Wang, Y.-M., Wang, Y.-S., Yang, Y.-F.: Understanding the determinants of RFID adoption in the manufacturing industry. Technol. Forecast. Soc. Change77(5), 803–815 (2010)
44. Yoon, T.E., George, J.F.: Why aren’t organizations adopting virtual worlds? Comput. Hum.
Behav.29(3), 772–790 (2013)
Towards the Development of a Comprehensive Theoretical … 73 45. Wymer, S.A., Regan, E.A.: Factors influencing e-commerce adoption and use by small and
medium businesses. Electron. Markets15(4), 438–453 (2005)
46. Chau, P.Y., Tam, K.Y.: Factors affecting the adoption of open systems: an exploratory study.
MIS Q. 1–24 (1997)
47. Kuan, K.K., Chau, P.Y.: A perception-based model for EDI adoption in small businesses using a technology–organization–environment framework. Inf. Manage.38(8), 507–521 (2001) 48. Zhu, K., Kraemer, K.L.: Post-adoption variations in usage and value of e-business by orga-
nizations: cross-country evidence from the retail industry. Inf. Syst. Res. 16(1), 61–84 (2005)
49. Zhu, K., Dong, S., Xu, S.X., Kraemer, K.L.: Innovation diffusion in global contexts: determi- nants of post-adoption digital transformation of European companies. Eur. J. Inf. Syst.15(6), 601–616 (2006)
50. Zhu, K., Kraemer, K.L., Xu, S.: The process of innovation assimilation by firms in different countries: a technology diffusion perspective on e-business. Manage. Sci.52(10), 1557–1576 (2006)
51. Liang, H., Saraf, N., Hu, Q., Xue, Y.: Assimilation of enterprise systems: the effect of institutional pressures and the mediating role of top management. MIS Q. 59–87 (2007) 52. Lin, H.-F., Lin, S.-M.: Determinants of e-business diffusion: a test of the technology diffusion
perspective. Technovation28(3), 135–145 (2008)
53. Ramdani, B., Kawalek, P., Lorenzo, O.: Predicting SMEs’ adoption of enterprise systems. J.
Enterp. Inf. Manage.22(1/2), 10–24 (2009)
54. Shah Alam, S.: Adoption of internet in Malaysian SMEs. J. Small Bus. Enterp. Dev.16(2), 240–255 (2009)
55. Azadegan, A., Teich, J.: Effective benchmarking of innovation adoptions: a theoretical framework for e-procurement technologies. Benchmarking Int. J.17(4), 472–490 (2010) 56. Tsai, M.-C., Lee, W., Wu, H.-C.: Determinants of RFID adoption intention: evidence from
Taiwanese retail chains. Inf. Manage.47(5), 255–261 (2010)
57. Oliveira, T., Martins, M.F.: Understanding e-business adoption across industries in European countries. Ind. Manage. Data Syst.110(9), 1337–1354 (2010)
58. Ghobakhloo, M., Arias-Aranda, D., Benitez-Amado, J.: Adoption of e-commerce applications in SMEs. Ind. Manage. Data Syst.111(8), 1238–1269 (2011)
59. Ifinedo, P.: An empirical analysis of factors influencing Internet/e-business technologies adoption by SMEs in Canada. Int. J. Inf. Technol. Decis. Making10(04), 731–766 (2011) 60. Thiesse, F., Staake, T., Schmitt, P., Fleisch, E.: The rise of the “next-generation bar code”: an
international RFID adoption study. Supply Chain Manage. Int. J.16(5), 328–345 (2011) 61. Low, C., Chen, Y., Wu, M.: Understanding the determinants of cloud computing adoption. Ind.
Manage. Data Syst.111(7), 1006–1023 (2011).https://doi.org/10.1108/02635571111161262 62. Butler, T.: Compliance with institutional imperatives on environmental sustainability: building
theory on the role of Green IS. J. Strateg. Inf. Syst.20(1), 6–26 (2011)
63. Klein, R.: Assimilation of internet-based purchasing applications within medical practices. Inf.
Manage.49(3), 135–141 (2012)
64. Lin, A., Chen, N.-C.: Cloud computing as an innovation: perception, attitude, and adoption.
Int. J. Inf. Manage.32(6), 533–540 (2012).http://dx.doi.org/10.1016/j.ijinfomgt.2012.04.001 65. Nkhoma, M.Z., Dang, D.P., De Souza-Daw, A.: Contributing factors of cloud computing adoption: a technology-organisation-environment framework approach. In: Proceedings of the European Conference on Information Management & Evaluation, pp. 180–189 (2013) 66. Abdollahzadegan, A., Hussin, C., Razak, A., Moshfegh Gohary, M., Amini, M.: The
organizational critical success factors for adopting cloud computing in SMEs (2013) 67. Wu, Y., Cegielski, C.G., Hazen, B.T., Hall, D.J.: Cloud computing in support of supply chain
information system infrastructure: understanding when to go to the cloud. J. Supply Chain Manage.49(3), 25–41 (2013)
74 Y. A. M. Qasem et al.
68. Heikkilä, J.-P.: An institutional theory perspective on e-HRM’s strategic potential in MNC subsidiaries. J. Strateg. Inf. Syst.22(3), 238–251 (2013)
69. Salum, K.H., Rozan, M.Z.A.: Conceptual model for cloud ERP adoption for SMEs. J. Theor.
Appl. Inf. Technol.95(4), 743 (2017)