# Continuance Use of Cloud Computing in Higher Education Institutions: A Conceptual Model
## 1 Introduction  
Cloud computing (CC) is increasingly becoming a springboard for digital innovation and organizational agility. Higher education institutions (HEIs) are facing the problems with the increasing of participants, growing need of IT and infrastructure, education quality of provision, and affordable education services [1, 2]. With the high rate at which IT technology changes, resource management optimization is a key concern for HEIs [3], not least because on-premise systems can only operate effectively when they receive adequate initial funding and resources, as well as dedicated and systematic maintenance regimes [4, 5]. Institutions looking to compete in the new world need a flexible yet comprehensive digital transformation blueprint that integrates various technologies across the institution with CC being at its foundation. CC, as the current generation in computing technology of the fourth industrial revolution (IR 4.0), has emerged as the main standard of service and resource delivery [6], in which it has become an excellent alternative for HLIs to support cost reduction, quality improvement and, through this, educational sustainability [7] by providing the required infrastructure, software, and storage as a service [3]. Thus, CC has been adopted rapidly in both private and public organizations, including HEIs [3, 8, 9]. As the fifth most frequently used utility after gas, electricity,water, and telephone lines [10], the CC tracking poll from the International Data Corporation indicates that USD 370 bn in CC will be used by 2022, corresponding to an increase in 22.5% in terms of 5-year compound annual growth [11]. However, while the subscription model of cloud services contributes to the growth of the overall market and makes it accessible for HEIs, a new set of challenges have arisen. This research addresses one such challenge that the cloud service providers face. The possibility of making such a decision to discontinue a cloud service provider is exacerbated by the low cost of switching between applications [12] and in general the competitive markets [4]. Therefore, the conceptualization of CC service in HEIs changes to a decision on 'continuance', rather than 'adoption'. Moreover, in subscription models offered via cloud-based education systems, it is possible for HEIs to switch vendors if they perceive greater benefits elsewhere. Thus, it is essential to understand the conceptual differences between adoption and continuance [13]. Hence, research on CC continuance have practical and artifact-specific motivations. Furthermore, theoretical research on organizational-level continuance is also scarce [14], particularly in HEIs [9; 15]. Typically, continuance research has been undertaken at the individual user level; however, organizational continuance decisions are often made by senior IS executives or others in the organization who may not be intense users of the service in question [14]. For many of these executive decision makers, a strong influence may be attributed to factors that are insignificant for individual users (e.g., lowering organizational costs or shifting a strategic goal) [16]. Thus, to contribute to the body of knowledge on the organizational-level continuance, this study draws on the prior literature in organizational-level continuance to establish a conceptual model that extends and contextualizes the IS continuance model to improve our understanding of the determinants of CC continuance use in HEIs through the lens of the TOE framework (i.e., environmental, organizational, and technological influences). Following the establishment of the conceptual model [15], the model was validated by conducting a pilot study with senior decision makers, all of whom were asked about aspects of their organizations relating to CC services. Therefore, this study sought to address was the following: \"What constructs influence the organizational-level continuance of CC in HEIs?\" To address this question, our research relies on a positivist quantitative-empirical research design.