Abstract
Migrating existing resources to cloud computing is a strategic organisational decision that can be difficult. It requires the consideration and evaluation of a wide range of technical and organisational aspects. Although a significant amount of attention has been paid by many industrialists and academics to aid migration decisions, the procedure remains difficult. This is mainly due to underestimation of the range of factors and characteristics affecting the decision for cloud migration. Further research is needed to investigate the level of effect these factors have on migration decisions and the overall complexity. This paper aims to explore the level of complexity of the decision to migrate the cloud. A research model based on the diffusion of innovation (DOI) theory and the technology-organization-environment (TOE) framework was developed. The model was tested using exploratory and confirmatory factor analysis. The quantitative analysis shows the level of impact of the identified variables on the decision to migrate. Seven determinants that contribute to the complexity of the decisions are identified. They need to be taken into account to ensure successful migration. This result has expanded the collective knowledge about the complexity of the issues that have to be considered when making decisions to migrate to the cloud. It contributes to the literature that addresses the complex and multidimensional nature of migrating to the cloud.
Highlights
Over the last decade, advances in computing have enabled cost-effective realisation of large-scale data centres [1]
Many previous studies explored the business benefits and barriers for adoption. They focused mostly on the cost benefits, scalability, agility and the security issues, for examples see [13,14,15,16,17]. While these studies identified some factors that influence the decisions to migrate to the cloud, they were developed at an early stage of the evolvement of cloud computing
Our results show that Average Variance Extracted (AVE) mean square root of each value variable is significantly greater than its correlation coefficient with other variables, discriminant validity is supported
Summary
Advances in computing have enabled cost-effective realisation of large-scale data centres [1]. The emergence of this phenomenon fundamentally changed the way information systems are developed, deployed, scaled, supported, and paid for [2]. Many previous studies explored the business benefits and barriers for adoption They focused mostly on the cost benefits, scalability, agility and the security issues, for examples see [13,14,15,16,17]. While these studies identified some factors that influence the decisions to migrate to the cloud, they were developed at an early stage of the evolvement of cloud computing. The majority of them explored the factors affecting the adoption of cloud services while little attention was paid to the migration of legacy systems
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