## 3 Research Design and Conceptual Model  
Scholars adopted different and multiple theories to address different factors and behavioural intentions to adopt a technology [70; 71; 72; 73]. This study adapts the UTAUT as a model that allows the identification of new construct variables to address the challenges of cloud service adoption within the government context; this study develops and validates the measurement scales for the model's constructs. The UTAUT model was developed considering other theoretical models such as the Technology Acceptance Model (TAM), Theory of Planned Behaviour (TPB), Theory of Reasoned Action (TRA), Innovation Diffusion Theory (IDT), Motivation Model (MM), and Social Cognitive Theory (SCT) [18; 74], amongst others. However, while contextualised, the UTAUT is not necessarily the major component of a new theory; it serves as a stepping stone to identifying a new approach to address identified challenges. This paradigm shift is the most promising direction for future research, which can make a significant contribution to the UTAUT literature and advance continuous research on technology acceptance and use in developing economies. The UTAUT research model comprises four constructs (performance expectancy, effort expectancy, social influence, and facilitating conditions) and moderators that significantly direct user acceptance and behaviour usage determinants. The key moderators are gender, age, voluntariness of use, and experience, while the behavioural intention and use behaviour are consistent with the theory in determining the influence of technology usage, such as cloud computing. * Performance Expectancy According to [PERSON], [PERSON] [18], one of the root constructs in the UTAUT is performance expectancy, which determines perceived usefulness. Performance expectancy is the degree to which individuals believe using a system will enhance job performance. [PERSON], [PERSON] [75] captured it as the level at which users believe using government cloud services will help them achieve performance, which is considered in the research. * Effort Expectancy Effort expectancy is the level of ease of use associated with using the system [18]. The construct is significant in contexts where ease of use is important and will be a vital determinant of an individual's intention to adopt the system. The ease-of-use root construct that contributed to the formation of effort expectancy indicates that the measurement scale should measure how easy it is to learn how to operate the system. According to [PERSON], [PERSON] [75], individuals with adequate effort expectancy have significant intentions to accept technology. * Social Influence The social factors (as outlined in the measurement scale, the organisation has supported the use of the system) were identified as one of the root constructs in determining social influence. Social influence, as described by [PERSON], [PERSON] [18], is the degree to which individuals perceive the importance that others ascribe to using the system. It is the direct determinants of behavioural intention influenced by how others perceive the use of the technology [74]. This study will not consider social influence, as it does not significantly relate to what the research intends to examine. * Facilitating Conditions According to [PERSON], [PERSON] [18], facilitating conditions are the level at which an individual believes that an organisation and technical infrastructure exist to support the use of the system. The construct captures operational concepts that include technological and organisational environments designed to remove barriers to using the system. Considering the facilitating conditions, the study assumes that individuals believe that government institutions have a mechanism to mitigate the barrier to adopting cloud services.