AIRCC's International Journal of Computer Science and Information Technology

Open Access Open Access  Restricted Access Subscription Access

Big Data And Cloud Readiness


Affiliations
1 Kulliyyah of Information and Communication Technology (KICT), International Islamic University Malaysia, Kuala Lumpur, Malaysia
 

Integrating big data with an agile cloud platform can significantly affect how businesses achieve their objectives. Many companies are moving to the cloud, but the trust issue seemed to make a move to the cloud slower. This paper investigated the factors that affect Service Satisfaction that led to Trust. Since the sample was not normally distributed, the researchers used the PLS-SEM tool to analyse the relationship of the variables. The variables are Data Security, Data Privacy, Cloud Benefits, Reputation, Service Level Agreement (SLA), Risk Management, Service Satisfaction and Trust. The variables were linked together based on the analysis from qualitative research supported by theories, and the linkages were being validated through quantitative data analysis. The quantitative data analysis found that Data Security, Cloud Benefits, Reputation and SLA influence Service Satisfaction and Service Satisfaction influences trust.


Keywords

Trust, Big Data, Cloud.
User
Notifications
Font Size

  • B. M. Balachandran and S. Prasad, "Challenges and Benefits of Deploying Big Data Analytics in the Cloud for Business Intelligence," Procedia Comput. Sci., vol. 112, pp. 1112–1122, 2017.

  • A. Sether, "Cloud Computing Benefits," SSRN Electron. J., no. January, 2016.

  • K. Tatic, "The benefits of using cloud technology in Bosnia and Herzegovina," no. April, 2020.

  • S. M. Din, R. Ramli, and A. A. Bakar, "A Review on Trust Factors affecting Purchase Intention on Instagram," 2018 IEEE Conf. Appl. Inf. Netw. Secur., no. November, pp. 49–53, 2018.

  • F. Selnes, "Consequences of Trust and Relationships," Eur. J. Mark., vol. 32, no. 3/4, pp. 305–322, 1998.

  • J. K. Adjei, "Explaining the role of trust in cloud computing services," Info, vol. 17, no. 1, pp. 54–67, 2015.

  • Z. Tbatou, A. Asimi, and C. El Balmany, Trust in Cloud Computing Challenges: A Recent Survey, vol. 81, no. January. Springer International Publishing, 2020.

  • R. R. Greene, General systems theory, no. January 2013. 2017.

  • F. Zohra Filali and B. Yagoubi, "Global Trust: A Trust Model for Cloud Service Selection," Int. J. Comput. Netw. Inf. Secur., vol. 7, no. 5, pp. 41–50, 2015.

  • M. Felici and S. Pearson, "Accountability, Risk, and Trust in Cloud Services: Towards an Accountability-Based Approach to Risk and Trust Governance," 2014 IEEE World Congr. Serv., pp. 105–112, 2014.

  • I. Encalada, "General systems theory . Practical approach in education," no. October, 2019.

  • A. Šijan, D. Karabašević, and D. Rajčević, “The importance of the general system theory for the modern world,” Trendovi u Posl., vol. 7, no. 2, pp. 87–94, 2019.

  • A. Steblyanskaya, Y. Jun, and M. Vasiev, "General systems theory for sustainable green development," no. September, pp. 138–141, 2021.

  • J. F. Hair, C. M. Ringle, and M. Sarstedt, “PLS-SEM : Indeed a Silver Bullet,” vol. 19, no. 2, pp. 139–151, 2011.

  • J. F. Hair, J. J. Risher, M. Sarstedt, and C. M. Ringle, "When to use and how to report the results of PLS-SEM," Eur. Bus. Rev., vol. 31, no. 1, pp. 2–24, 2019.

  • J. Risher, "When to use and how to report the results of PLS-SEM," no. December, 2018.

  • J. F. Hair, M. C. Howard, and C. Nitzl, "Assessing measurement model quality in PLS-SEM using

  • M. Sarstedt, C. M. Ringle, and J. F. Hair, Handbook of Market Research, no. September. 2020.

  • P. N. Sharma, M. Sarstedt, G. Shmueli, K. H. Kim, and K. O. Thiele, "PLS-Based Model Selection: The Role of Alternative Explanations in Information Systems Research," J. Assoc. Inf. Syst., no. April, pp. 346–397, 2019.

  • F. Ali, S. M. Rasoolimanesh, and C. Cobanoglu, "Applying Partial Least Squares in Tourism and Hospitality Research," Appl. Partial Least Squares Tour. Hosp. Res., no. September, pp. 1–264, 2018.


Abstract Views: 264

PDF Views: 114




  • Big Data And Cloud Readiness

Abstract Views: 264  |  PDF Views: 114

Authors

Hazirah Bee Yusof Ali
Kulliyyah of Information and Communication Technology (KICT), International Islamic University Malaysia, Kuala Lumpur, Malaysia
Lili Marziana Abdullah
Kulliyyah of Information and Communication Technology (KICT), International Islamic University Malaysia, Kuala Lumpur, Malaysia

Abstract


Integrating big data with an agile cloud platform can significantly affect how businesses achieve their objectives. Many companies are moving to the cloud, but the trust issue seemed to make a move to the cloud slower. This paper investigated the factors that affect Service Satisfaction that led to Trust. Since the sample was not normally distributed, the researchers used the PLS-SEM tool to analyse the relationship of the variables. The variables are Data Security, Data Privacy, Cloud Benefits, Reputation, Service Level Agreement (SLA), Risk Management, Service Satisfaction and Trust. The variables were linked together based on the analysis from qualitative research supported by theories, and the linkages were being validated through quantitative data analysis. The quantitative data analysis found that Data Security, Cloud Benefits, Reputation and SLA influence Service Satisfaction and Service Satisfaction influences trust.


Keywords


Trust, Big Data, Cloud.

References