A model for decision-makers' adoption of big data in the education sector

Baig, Maria Ijaz and Shuib, Liyana and Yadegaridehkordi, Elaheh (2021) A model for decision-makers' adoption of big data in the education sector. Sustainability, 13 (24). ISSN 2071-1050, DOI https://doi.org/10.3390/su132413995.

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Big Data Adoption (BDA) has already gained tremendous attention from executives in various fields. However, it is still not well explored in the education sector, where a large amount of academic data is being produced. Therefore, integrating Technology Organization Environment (TOE) and Diffusion of Innovation (DOI), this study aims to develop a theoretical model to identify the factors that influence BDA in the higher education sector. To do so, significant technology-, organization-, and environment-related factors have been extracted from previous BDA studies. Meanwhile, the moderating effects of the university size and the university age are added into the developed model. A sample of 195 data was collected from the managerial side of virtual university (VU) campuses in Pakistan using an online survey questionnaire. Structural equation modeling (SEM) was used to test the research model and developed hypotheses. The results showed that relative advantage, complexity, compatibility, top management support, financial resources, human expertise and skills, competitive pressure, security and privacy, and government policies are significant determinants of BDA. However, the results did not support the influence of IT infrastructure on BDA. Based on the findings, this study provides guidelines for the successful adoption of big data in higher education sector. This study can serve as a piece of help to the ministry of education, administrators, and big data service providers for the smooth adoption of big data.

Item Type: Article
Uncontrolled Keywords: Big data adoption; Theoretical model; Higher education sector; Structural equation modeling; Technology organization environment; Diffusion of innovation
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Computer Science & Information Technology
Depositing User: Ms Zaharah Ramly
Date Deposited: 25 May 2022 01:47
Last Modified: 25 May 2022 01:47
URI: http://eprints.um.edu.my/id/eprint/27140

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