Journal of Electrical and Computer Engineering Innovations (Jan 2022)
Determining Effective Factors in Cloud Computing Acceptance Using Rogers’ Diffusion of Innovation Model and Davis’ Technology Adoption Model (A Case of Financial Institution)
Abstract
Background and Objectives: Determining effective factors in cloud computing adoption on employees of Noor credit institution in South Khorasan province, Iran, is the purpose of the present study. A practical oriented method is applied regarding the research objective and a descriptive-survey method is used for collecting field data. Employees of Noor credit institution of South Khorasan province (50 people) are selected as the research sample.Methods: Accurate questionnaires are analyzed. Two researcher-made questionnaires are conducted as research tools. These questionnaires consist of effective factors in cloud computing adoption (12 factors including 47 items) and cloud computing adoption intention (3 items). The reliability of the research is evaluated using Cronbach's alpha coefficient which is obtained α=0.54% for the questionnaire of effective factors in cloud computing adoption and has various values for the questionnaire of the cloud computing adoption intention. Also, the descriptive statistics approach is used to define variables, and confirmatory factor analysis and path analysis are applied in the inferential section. Structural equation modeling using Smart-PLS software is used to determine the effective factors in cloud computing adoptionResults: All 12 determined factors in cloud computing adoption are considered as dependent variables and cloud computing adoption intention is considered as an independent variable. 12 effective factors in cloud computing adoption on Noor credit institution of South Khorasan in Iran are determined and examined.Conclusion: It can be concluded that all factors (except the support of the top manager) have a positive and significant effect on cloud computing adoption intention, nonetheless, the value of statistic t for path analysis of the support of the top manager on cloud computing adoption intention is less than 1.96. This shows that the support of the top manager does not have a significant effect on cloud computing adoption intention.
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