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Assessing Cloud Computing Adoption b...

Ibrahim, Hamza M.

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Assessing Cloud Computing Adoption by IT Professionals in Small Business Using the Technology Acceptance Model.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Assessing Cloud Computing Adoption by IT Professionals in Small Business Using the Technology Acceptance Model./
Author:	Ibrahim, Hamza M.
Description:	235 p.
Notes:	Source: Dissertation Abstracts International, Volume: 75-06(E), Section: B.
Contained By:	Dissertation Abstracts International75-06B(E).
Subject:	Information Technology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3579718
ISBN:	9781303804946

Assessing Cloud Computing Adoption by IT Professionals in Small Business Using the Technology Acceptance Model.
Ibrahim, Hamza M.

Assessing Cloud Computing Adoption by IT Professionals in Small Business Using the Technology Acceptance Model. - 235 p.

Source: Dissertation Abstracts International, Volume: 75-06(E), Section: B.

Thesis (Ph.D.)--Northcentral University, 2014.

Cloud computing provides business applications and data accessed online using web browsers and dedicated clients. It enables usage of shared computing resources distributed around the world. The benefits of cloud computing include a lower total cost of ownership, flexible billing model, real time on-demand provisioning, resource pooling, and access to a broad network. The problem that was addressed by this research was cloud-computing adoption has been relatively slow among many organizations because of concerns about performance, security, compatibility, and adaptability, as the main technology factors. This study investigated the determinants of cloud-computing adoption, using the Technology Acceptance Model (TAM) by measuring the influence of perceived usefulness, perceived ease of use, and the effect of the technology factors of security, performance, compatibility, and adaptability on the behavioral intention to use cloud computing. The research model extended the TAM by adding those factors as external variables. This non-experimental quantitative predictive study was based on sample data collected from 153 respondents from an online survey. Link to the survey was sent to 1050 participants from randomly selected IT organizations in the small and medium-size business sector in the USA. Multiple linear regression as well as analysis of variance was used to assess the influence of performance, security, compatibility, and adaptability on the behavioral intention to use cloud computing moderated by perceived usefulness and perceived ease of use, It was found that performance influences intention to use cloud computing through both perceived usefulness (Regression coefficient --- .481, p = .000) and perceived ease of use (Regression coefficient = .836, p = .000). It was also found that security influences the intention to use cloud computing through its influence on both perceived usefulness (Regression coefficient = .170, p --- .002) and perceived ease of use (Regression coefficient = .148, p --- .013). Compatibility and adaptability were found to have a combined influence on perceived usefulness, with a regression coefficient = .110, p < .05. No statistical evidence was found to suggest that compatibility or adaptability has any influence on perceived ease of use. Recommendations for future studies include assessing additional determinants of cloud computing, especially from individual and social factors and attributes, such as perceived behavioral control and self-efficacy of IT experience.

ISBN: 9781303804946Subjects--Topical Terms:

1030799
Information Technology.

Assessing Cloud Computing Adoption by IT Professionals in Small Business Using the Technology Acceptance Model.
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520 $a Cloud computing provides business applications and data accessed online using web browsers and dedicated clients. It enables usage of shared computing resources distributed around the world. The benefits of cloud computing include a lower total cost of ownership, flexible billing model, real time on-demand provisioning, resource pooling, and access to a broad network. The problem that was addressed by this research was cloud-computing adoption has been relatively slow among many organizations because of concerns about performance, security, compatibility, and adaptability, as the main technology factors. This study investigated the determinants of cloud-computing adoption, using the Technology Acceptance Model (TAM) by measuring the influence of perceived usefulness, perceived ease of use, and the effect of the technology factors of security, performance, compatibility, and adaptability on the behavioral intention to use cloud computing. The research model extended the TAM by adding those factors as external variables. This non-experimental quantitative predictive study was based on sample data collected from 153 respondents from an online survey. Link to the survey was sent to 1050 participants from randomly selected IT organizations in the small and medium-size business sector in the USA. Multiple linear regression as well as analysis of variance was used to assess the influence of performance, security, compatibility, and adaptability on the behavioral intention to use cloud computing moderated by perceived usefulness and perceived ease of use, It was found that performance influences intention to use cloud computing through both perceived usefulness (Regression coefficient --- .481, p = .000) and perceived ease of use (Regression coefficient = .836, p = .000). It was also found that security influences the intention to use cloud computing through its influence on both perceived usefulness (Regression coefficient = .170, p --- .002) and perceived ease of use (Regression coefficient = .148, p --- .013). Compatibility and adaptability were found to have a combined influence on perceived usefulness, with a regression coefficient = .110, p < .05. No statistical evidence was found to suggest that compatibility or adaptability has any influence on perceived ease of use. Recommendations for future studies include assessing additional determinants of cloud computing, especially from individual and social factors and attributes, such as perceived behavioral control and self-efficacy of IT experience.
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