Manuscript Title:

PILOT STUDY OF BIG DATA ENGINEERING IMPACT TOWARDS CLOUD COMPUTING ADOPTION IN UAE

Author:

WALEED SAEED MAHMOUD MAHMOUD ALI, PROF. Dr. ABD SAMAD HASAN BASARI, Dr. ZERATUL IZZAH MOHD YUSOH, Dr. MOHAMED DOHEIR, Dr. NOORRAYISAHBE BINTI MOHD YAACOB

DOI Number:

DOI:10.17605/OSF.IO/VQAXH

Published : 2021-12-10

About the author(s)

1. WALEED SAEED MAHMOUD MAHMOUD ALI - Information & Communication Technology, Universiti Teknikal Malaysia Melaka (UTeM) & UteM University (PhD Candidate Big Data Engineering Impact Towards Cloud Computing Adoption).
2. Dr. ABD SAMAD HASAN BASARI - Information & Communication Technology, Universiti Teknikal Malaysia Melaka (UTeM) & UteM University (main supervisor).
3. Dr. ZERATUL IZZAH MOHD YUSOH - Information & Communication Technology, Universiti Teknikal Malaysia Melaka (UTeM) & UteM University (Co- supervisor).
4. Dr. MOHAMED DOHEIR - Information & Communication Technology, Universiti Teknikal Malaysia Melaka (UTeM) & University Malaysia of Computer Science & Engineering (UNIMY) - Lecturer
5. Dr. NOORRAYISAHBE BINTI MOHD YAACOB - Information & Communication Technology, Universiti Teknikal Malaysia Melaka (UTeM) & Taylor’s University (Lecturer).

Full Text : PDF

Abstract

Big Data Engineering (BDE) requirements within Cloud Computing Adoption (CCA) to be used by large employers in the UAE have been extensively studied in the literature review. Research that is available currently is in constant support of the theoretical power that Technology Organizational Environmental (TOE) framework owns in investigating factors in the firm-level that support the technology acceptance theory with mixed theories from TAM, TOE and BDE variables. There has been a new interest in Cloud Computing Adoption (CCA) founded within large organizations in UAE, and that’s because of all the new technologies that are surfacing which have very strong relations to CCA and BDE. BDE is responsible for the implementation of CCA into large business organizations. It’s a necessity for CCA to develop and transform from basic knowledge to a higher level of corporate results. The motives to construct a forecast model for CCA which involves BDE variables and variables from the other two most involved technology adoption theories which are, TAM, and TOE, the act of inserting BDE related variables helped evolve cloud computing’s mixed theory of the approach they should take when implementation takes place. Six independent variables were involved. They were seen as useful, easy to use, cost-effective, security capability, had the intention of using BDE, and needed it. Information obtained from UAE. were studied using binary logistic regression. The outcome described that a model which includes all six independent variables was more statistically dependable for speculating CCA with an accuracy of 90.6%. Separately, however, only usefulness was the variable that can be used to elevate the use of CCA. These results illustrated that CCA could rise if it's accompanied by BDE movements in order to make it more helpful for its purchaser.


Keywords

Cloud Computing Adoption (CCA),Cloud Computing Model (CCM), Applications of Intelligence (AI), Technology Acceptance Models (TAM), Technology Organization Environment (TOE).