A Model for Decision-Makers’ Adoption of Big Data in the Education Sector

Maria Ijaz Baig, Liyana Shuib and Elaheh Yadegaridehkordi
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Maria Ijaz Baig: Department of Information Systems, Faculty of Computer Science & Information Technology, University of Malaya, Kuala Lumpur 50603, Selangor, Malaysia
Liyana Shuib: Department of Information Systems, Faculty of Computer Science & Information Technology, University of Malaya, Kuala Lumpur 50603, Selangor, Malaysia
Elaheh Yadegaridehkordi: Center for Software Technology and Management, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia

Sustainability, 2021, vol. 13, issue 24, 1-29

Abstract: 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.

Keywords: big data adoption; theoretical model; higher education sector; structural equation modeling; technology organization environment; diffusion of innovation (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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