Acceptance and readiness model of cloud computing services for the Malaysian public sectors personnel

Abstract

Cloud computing enables data and applications to be accessed and shared online. Many organisations, including those in the public sector, have taken the initiative to create an innovative technological environment by using the benefits offered by cloud computing. The Malaysian government has accentuated cloud-based services and cloud computing to provide excellent service delivery for the masses. However, reports on the effectiveness of government cloud services, MyGovUC, show that it is unsatisfactory despite the government's encouragement and investment. Many agencies and employees are slow to accept and use cloud computing on a wider scale. Besides, most past studies solely focused on one perspective: acceptance theory, rather than technology readiness which is equally important in measuring user's technology acceptance. Therefore, this study investigates both the acceptance and readiness factors influencing cloud computing acceptance and readiness among Malaysian public sector personnel. The research was initiated to identify the problem and knowledge gaps by reviewing the existing literature and conducting a preliminary study among IT officers of several agencies. Subsequently, the matrix analysis was conducted during the modelling process. This study employed the Unified Theory of Acceptance and Use of Technology (UTAUT) to extend the Technology Readiness Index (TRI 2.0) model and other factors in developing a comprehensive acceptance model that relates readiness factors with acceptance factors. The model is named Cloud Computing Acceptance and Readiness Model (CCAR). The main study involved 351 respondents using a survey instrument that consisted of 15 constructs and 70 items. The research used SPSS and SmartPLS applications to perform descriptive and inferential analysis. Several tests were also conducted to understand the differences between groups. PLS-SEM analysis findings showed that performance expectancy, compatibility, security, mobility, IT knowledge, and social influence had significant effects. However, effort expectancy, top management support, and awareness had non-significant effects. On the other hand, optimism and innovativeness had a significant relationship with performance expectancy and effort expectancy. Discomfort displayed a non-significant relationship between performance expectancy and effort expectancy. Whereas insecurity indicated a significant relationship with performance expectancy but a non-significant relationship with effort expectancy. The CCAR model produced a moderate predictive power (R2) in the variance explained in behavioural intention (63%) and actual use (35%). Hence, the model has predictive relevance and is reliable with the Q2 = 0.291. Moreover, the TRI 2.0 score is 3.38, which means that it is moderate ready to embrace cloud computing. The theoretical contribution of this study is that both factors of UTAUT and TRI 2.0 will ensure extensive assessment of acceptance and readiness of cloud computing users. Practically, the CCAR model can be used by IT administrators in the public sector to measure the level of readiness and acceptance regularly to improve the cloud computing usage among public services personnel.