The COVID-19 pandemic has forced many organizations around the world to make full use of a variety of emerging online communication platform technologies. Universities are among the organizations that have asked students, tutors, and lecturers to use a number of different online communication platforms to ensure the education process remains uninterrupted. However, the COVID-19 pandemic has generated considerable challenges for the global higher education community while using such emerging technologies. This research has two main goals. First, this paper will begin by investigating whether the online learning platforms used by university students during the COVID-19 period have presented any challenges to their learning. Second, the paper will then go on to address proposed solutions by developing a conceptual model to reduce the impact of such challenges. This research uses an exploratory qualitative research approach, supported by literature content analysis techniques. The data set for this study was collected during the first peak of the pandemic period in Malaysia, between the 16th of May 2020 and the 5th of June 2020. We used SPSS to conduct a descriptive analysis and NVivo12 to analyse data collected from 486 students from different universities in Malaysia. These students disclosed various obstacles they encountered when they used IT platform applications for online learning. These obstacles include (a) work and information overload received from instructors, (b) inadaptability and unfamiliarity of the new online learning environment, and (c) personal health challenges related to stress and anxiety. Based on previous relevant research, this study introduced a set of motivational factors and developed a conceptual motivational model for sustainable and healthy online learning.

Purpose This paper aims to develop a model and measurement to investigate the factors influencing cloud computing adoption as a part of developing countries’ alternatives to implement e-government services. Design/methodology/approach This study proposes a theoretical model based on the literature of technology adoption models. It constructs scale measurements for the proposed model constructs by extracting and adapting the items from the literature. The authors verify the scales’ content validity and reliability by applying face validity, pre-testing and pilot study. For the pilot study, the authors collect the data from 26 information technology staff in five public organizations in Yemen. The authors test the reliability of the scales using Cronbach’s alpha criterion, and then conduct exploratory factor analysis to evaluate the validity of the scales. Findings The results show that the scale measurements meet the conventional criteria of reliability and validity. Originality/value Theoretically, this paper provides an integrated model for examining cloud computing adoption for e-government implementation in developing countries. In addition, it develops an instrument to empirically investigate the influencing factors of cloud computing adoption in the context of developing countries’ e-government initiatives.

Cloud computing essentially is a scalable, flexible and pay-per-use model for the way IT services are delivered. It can significantly improve the way a government functions, the services it provides to its citizens and institutions. This paper aims to explore the factors that influence adopting cloud computing as a part of public sector organizations' alternatives to implement e-government services. Based on two dominant theories in the field of adoption of new technology, the Fit-Viability Model and Diffusion of Innovation Theory, a model is proposed. Data were gathered using a structured questionnaire with a sample of 296 IT staff employed in public organizations in Yemen. The results clarify the need to consider factors affecting two dimensions, fit and viability, to make a decision to adopt cloud computing in an e-government context. The fitness of cloud computing to e-government tasks is affected by factors such as relative advantage, compatibility, trialability and security, but is not affected by the complexity of the technology. On the other hand, the viability is influenced by economic factors (return on investment and asset specificity) and technological readiness (IT infrastructure and IT policy and regulations), while the results do not support the relation between the organizational factors such as top management support and cloud knowledge and viability.

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