An adoption model of cloud enterprise resources planning for Malaysian small and medium enterprises - Salum, Khamis (2019)
The Cloud Enterprise Resource Planning (ERP) system offers promising benefits for the development of Small and Medium Enterprises (SMEs). It helps to address many of the challenges faced by SMEs and significantly promotes them in terms of business operations and use of resource. Despite its benefits, the research on cloud ERP adoption among SMEs in developing countries has not been fully explored, leading to a low rate of cloud ERP adoption among SMEs. Furthermore, the factors which influence SMEs to adopt the cloud ERP system are still unclear. In an attempt to tackle the aforementioned situation, this research investigated the influencing factors that have determined and enhanced cloud ERP adoption rates. To identify factors and develop the model used in this research, the researcher conducted a Systematic Literature Review (SLR). The model was proposed based on three integrated Information System (IS) predominant theories, namely, Technology- Organization-Environment (TOE) framework and Fit-Viability Model (FVM) with extension of Diffusion of Innovation (DOI) theory to scrutinize the influential factors leading towards Cloud ERP Adoption. Thirteen hypotheses were developed to test and validate the model based on the decision to adopt cloud ERP. A positivism paradigm with quantitative approach was applied to conduct this research. Purposive sampling technique and a survey method were applied and data were collected from SMEs who have already adopted cloud ERP that provided 174 usable responses. The analysis was conducted by using Structural Equation Modeling (SEM) technique through Partial Least Squares (SmartPLS 3.2.7) software to determine the significant relationships of the independent factors to Cloud ERP Adoption. The results showed that Task- Technology Fit, Task Interdependence, Relative Advantage, Compatibility, System Trust, Security, Top Management Support, Employee Cloud ERP Knowledge, Cost Saving, and Competitive Pressure were significantly related to Cloud ERP Adoption. On the other hand, Security was found to have no relationship (p > 0.05) with Task- Technology Fit. Similarly, Government Support and Vendor Support were found to have no relationship (p > 0.05) with Cloud ERP Adoption. In line with this, the research model can be explained as 65.2% of variance from all the independent variables. This implies that the model has substantial predictive power to explain cloud ERP adoption. Finally, this model can be used to guide cloud ERP ecosystems to enhance their knowledge so as to successfully evaluate and adopt the cloud ERP system.