## 1 Introduction
CC is a favorable solution for HEIs that supports cost reduction and improves education quality [22]. Besides, the sustainability of HEIs can be achieved by providing the required infrastructure, software, and storage through CC adoption [21; 23; 24]. Thus, the emergence of CC and the advantages it provides can help bridge this technological gap. Generally, CC in HEIs is increasing in popularity, but it is still lagging behind the commercial, government, and other sectors [25]. Past literature has shown that productivity at the organizational-level increases significantly for organizations that have invested in ICTs for their operations [26]. Besides, the Coronavirus 2019 (COVID-19) pandemic affected HEIs not just in Wuhan, China where the virus originated but all other HEIs in 188 countries as of 6 April 2020. CC as a technology of the fourth industrial revolution (IR 4.0) could enable educational countermeasures to continue the education process despite the COVID-19 predicaments [27; 28]. Therefore, CC in this case is not only an alternative option for HEIs but also an essential solution. In the current study, the unit of analysis is the organization level because the primary focus is on decision-makers, who are responsible for CC adoption. Individuals are considered to be the observers for the phenomenon at the organizational level [29]. Besides, most of the prior studies have primarily focused on CC technology, costs, applications, security, and benefits in small and medium organizations [30]. However, a limited number of studies have focused on CC adoption and its usage in HEIs [3]. Furthermore, several studies have looked at CC from different perspectives in various developing countries such as sub-Saharan Africa [30; 31; 32], Malaysia [33; 34], and Saudi Arabia [18; 35; 36]. Other studies discussed CC implementation in academic libraries [37; 38] and the enhancement of overall awareness regarding CC migration issues [18]. Moreover, organization-based studies have evaluated the readiness of HEIs to implement CC's [39; 40; 32], and other studies have examined the impacts of technology on HEIs [41; 14]. Even though a substantial amount of consideration is given to the CC, few studies have been carried out to identify the influential factors in adopting CC in HEIs from the perspective of decision-makers [30; 3]. Meanwhile, in spite of the efficiency and usefulness of advanced artificial neural networks (ANN) as a soft computing technique in identifying and ranking determinants in technology adoption [42], application of this technique in the context of CC remains mainly unexplored, especially in education atmosphere. Taking into consideration these points, the current study aimed to develop and test a proposed adoption model and to examine the key factors, influencing decision-makers' intention of CC adoption in Malaysian higher education institutions. Therefore, the key objectives of the current study are as follow:  
To analyze the factors that influence the adoption of CC in HEIs. To propose an appropriate model for evaluating the adoption of CC in HEIs, validated by using two analytical approaches (i.e., PLS-SEM and ANN). To contribute to the body of knowledge on the organizational-level adoption, this research will first merge two well-established theories which are the Technology-Organizational-Environmental (TOE) framework [43] and the diffusion of innovations (DOI) [44], to fill the gap in previous literature. Drawing on the organizational level adoption theories, our research model is built on the TOE framework and DOI model which is in line with the objectives of this study. Furthermore, the research model constructs are grounded by the literature taking into account the context of the study. The study also implemented variance-based structural equation modeling (PLS-SEM) for assessing the factors impacting CC adoption, and a neural network is used for predicting how CC is adopted in HEIs.