Factors influencing user intention towards big data technology adoptions in educational organizations

The emergence of new technologies in the field of Educational Technology such as Learning Analytics has led Big Data to play an increasingly essential role. Big Data is making its presence known in almost every industry and has the potential to not only transform the business world but the educational governance too. Given that organizations in the Malaysian Ministry are still in the early stages of using Big Data, studying factors influencing the users’ intentions to adopt Big Data technology in Malaysia is critical and timely. Grounded in the Dissemination of Innovation (DOI) theory, Technology Acceptance Model (TAM), and Technology-Organization-Environment (TOE) framework, an integrative model is developed to examine the factors influencing the adoption of Big Data technology in this study. The model specifies four technological factors (perceived usefulness, perceived ease of use, compatibility and security), three organizational factors (top management support, IT expertise and organizational resources), and environmental factors (competitive pressure, external support and privacy) as determinants of the users’ intentions to adopt big data technology. The moderator tested was the size of the organization. The size of the organization may exert a moderate effect on the direct relationships previously disclosed. Using a cross sectional survey, empirical data were collected. A total of 227 questionnaires were obtained and screened. There are 3 insufficient answers were subsequently discarded leaving 224 valid structured data review questionnaires. Data was analized using the Partial Least Square Modeling of Structural Equations due to one of the best software for verifying structured data on structural equations modeling (SEM) Smart PLS 3.0 as analytical tools. This study finds that the predictor variables (compatibility, security, top management support and organizational resources) are significant and critically direct to the users’ intentions to adopt big data technology. Among the factors identified in the model, three (top management support, organizational resources and security) are found to play a vital role in all levels of users’ intentions to adopt Big Data. The results indicate that the model is suited for studying users’ intentions to adopt Big Data technology in educational organizations. This study can help the Malaysian ministry of education to emphasize the important factors in further developing the use of Big Data technology in organizations. The findings provide important recommendations and implications for BDA technology practitioners and application developers, which could coincide with successful BDA technology deployment. This study provides practitioners with practical recommendations for guidance in incorporating and endorsing BDA activities in their organizations in order to maximise the benefits of revolutionary technology, particularly in government agencies.

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