Understanding the factors influencing the adoption of cloud computing in higher education during coronavirus disease: a case of University of KwaZulu-Natal.

Abstract

Cloud computing (CC) as a model for internet-based service provisioning, enables the delivery and access of services based on dynamically scalable and virtualized resources (infrastructure, platforms, etc.). For higher education institutions (HEIs) cloud computing provides services anywhere and anytime, as a result of its scalability and pay-as-you-use approach. Although scalable processing and storage, data sharing, and anytime, anywhere access are some of the key advantages that CC may offer enterprises, there are also risks and barriers to adoption, and it is still in its infancy in developing nations. The Coronavirus (Covid-19) pandemic, which struck the entire world in 2020, compelled institutions to alter their procedures and methods as a result of the social distancing laws that were put in place to stop the spread of Covid-19. The sudden surge of the Covid-19 pandemic caused a quick acceleration towards the adoption and use of CC in learning and education to ensure the continuation of classes. CC had a significant impact in fighting the epidemic and became a saviour for various fields including the education sector. This study seeks to investigate the factors influencing the adoption of CC in HEIs during the upsurge of the Covid-19 virus. The research model utilised is the unified theory of acceptance and use of a technology (UTAUT). The study used a quantitative technique to identify the factors that influence the adoption of cloud computing through a questionnaire survey that was administered to a convenient sample at the UKZN Pietermaritzburg campus. The study found that effort expectancy (EE), performance expectancy (PE) and social influence (SI) all positively influence the behavioural intention (BI) to use CC for learning purposes, with performance expectancy being the highest predictor of behavioural intention to adopt CC for students. Additionally, facilitating conditions (FC) and behavioural intention (BI) were also found to influence the actual sage of CC for learning purposes. These findings are useful as they give university’s policymakers, designers insights into what factors are crucial when implementing CC to ensure the successful adoption by students.