۱- Introduction

۲- Literature review

۳- Classification framework

۴- Methodology for the review

۵- Presentation of findings

۶- Discussion

۷- Conclusion

References

Abstract

This paper presents a meta-analysis of cloud computing research in information systems with the aim of taking stock of literature and their associated research frameworks, research methodology, geographical distribution, level of analysis as well as trends of these studies over the period of 7 years. A total of 285 articles from 67 peer review journals from year 2009 to 2015 were used in the analysis. The findings indicate that extant cloud computing literature tends to skew towards the technological dimension to the detriment of other under researched dimensions such as business, conceptualization and application domain. Whilst there has been a constant increase in cloud computing studies over the last seven years, a significant number of these studies have not been underpinned by theoretical frameworks and models. Also, majority of cloud computing studies utilized experiment and simulation as methods of enquiry as compared to the qualitative, quantitative, and mixed methodologies. This study contributes to cloud computing research by providing holistic insights into trends on themes, methodology, research framework, geographical focus and future research directions.

Introduction

In recent times, the global use of computers and smartphones has increased significantly. This trend has heightened global competition and the need for businesses to expand into different geographical areas in order to be sustainable. To address this need, there is a necessity for efficient use of resources toward operational excellence. Cloud computing, an emerging innovation seeks to address these needs. Even though cloud computing is not totally new, its commercialization started around year 2000. Cloud computing simply involves the provision of information technology (IT) solutions as a service rather than as a product through the Internet (Senyo, Effah, & Addae, 2016). According to Gartner (2016), by year 2020, more than $1 trillion in IT expenditure will be directly or indirectly toward transition to cloud computing systems. As such, there is fierce competition among major cloud service providers such as Amazon, Microsoft, Salesforce, and Google for a share in this projected revenue. In academia, cloud computing has attracted a growing number of studies in recent years. Among these studies are some literature reviews (e.g., Bayramusta & Nasir, 2016; El-Gazzar, 2014; Venters & Whitley, 2012; Yang & Tate, 2012). Although these reviews provide useful insights into cloud computing, some knowledge gaps still exist, thus the need for further reviews. These gaps are (1) limited knowledge on theories, frameworks and models that underpinned cloud computing research; (2) partial understanding of under-researched areas of cloud computing; (3) limited understanding of underpinning methodologies of cloud computing research; and (4) limited knowledge of level of analysis and geographical focus of cloud computing research. We argue that better understanding of these knowledge gaps will not only provide springboard for future studies but also enhance holistic understanding as well as contribute to the practical development of cloud computing. Thus, this paper provides a summative metaanalysis of cloud computing research from 2009 to 2015. With the aim of taking stock and providing insights into theoretical frameworks and models, research methodologies, geographical focus, and trends of cloud computing research over these years. The rest of the paper is organized as follows. Section 2 presents a literature review of cloud computing with discussions on the general notions, delivery and deployment models of cloud computing. Section 3 presents the research framework that guided the literature classification. In Section 4, the methodology for this study is presented whilst Section 5 presents findings from the review. Discussions of the findings are presented in Section 6. Section 7 concludes the paper with contributions and direction for future research.