2022
DOI: 10.1007/s11227-022-04346-1
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The influence of dependability in cloud computing adoption

Abstract: Cloud computing (CC) has many benefits, so its use has spread rapidly, particularly in the business sector. An important consideration in the acceptance of CC is whether the CC system is dependable, and it can differ among industry and service type. However, little research has considered the effect of dependability (composed of availability, reliability, security, maintainability) on CC acceptance. Especially, group comparisons between high IT-intensive (Hi-ITi) and low IT-intensive (Lo-ITi) industries have n… Show more

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Cited by 10 publications
(3 citation statements)
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References 85 publications
(163 reference statements)
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“…The factors of Functional Stability, Reliability, Usability, and Security are defined based on the guidelines provided in the ISO/IEC 25010 standard by referring to the study from Estdale and Georgiadu [25]. Maintainability is another independent factor derived from the findings of Song and Sohn [26], indicating its significant impact on the adoption of cloud computing across various groups, except for software as a service. On top of that, the Portability factor is derived from the research conducted by Sidik and Syafar [27], which highlighted the significant influence of quality of service on students' intention to use mobile learning.…”
Section: Methodsmentioning
confidence: 99%
“…The factors of Functional Stability, Reliability, Usability, and Security are defined based on the guidelines provided in the ISO/IEC 25010 standard by referring to the study from Estdale and Georgiadu [25]. Maintainability is another independent factor derived from the findings of Song and Sohn [26], indicating its significant impact on the adoption of cloud computing across various groups, except for software as a service. On top of that, the Portability factor is derived from the research conducted by Sidik and Syafar [27], which highlighted the significant influence of quality of service on students' intention to use mobile learning.…”
Section: Methodsmentioning
confidence: 99%
“…For finer-grained data such as user day granularity and weekly granularity, the multi-party data participating in the joint modeling is spliced, and time series analysis and matrix analysis algorithms are introduced to extract key user behavior characteristics and mine the cross-features of the data of both parties [11].…”
Section: Federal Feature Engineeringmentioning
confidence: 99%
“…The original model was introduced more than 30 years ago and has been redesigned since then. The final version of the model was presented by Song & Sohn (2022), according to whom perceived ease of use and perceived usefulness have the strongest influence on this model. Both determinants have a direct influence on the behavioural intention to use the new technology.…”
Section: Theoretical Background On Cloud Computing Adoptionmentioning
confidence: 99%