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

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

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 o...

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Main Authors:	Baig, Maria Ijaz, Shuib, Liyana, Yadegaridehkordi, Elaheh
Format:	Article
Published:	MDPI 2021
Subjects:	QA75 Electronic computers. Computer science QA76 Computer software
Online Access:	http://eprints.um.edu.my/26078/ https://doi.org/10.3390/su132413995
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id	my.um.eprints.26078
record_format	eprints
spelling	my.um.eprints.260782021-12-29T03:01:57Z http://eprints.um.edu.my/26078/ A Model for Decision-Makers’ Adoption of Big Data in the Education Sector Baig, Maria Ijaz Shuib, Liyana Yadegaridehkordi, Elaheh QA75 Electronic computers. Computer science QA76 Computer software 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. © 2021 by the authors. Licensee MDPI, Basel, Switzerland. MDPI 2021 Article PeerReviewed 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). p. 13995. ISSN 2071-1050 https://doi.org/10.3390/su132413995 doi:10.3390/su132413995
institution	Universiti Malaya
building	UM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaya
content_source	UM Research Repository
url_provider	http://eprints.um.edu.my/
topic	QA75 Electronic computers. Computer science QA76 Computer software
spellingShingle	QA75 Electronic computers. Computer science QA76 Computer software Baig, Maria Ijaz Shuib, Liyana Yadegaridehkordi, Elaheh A Model for Decision-Makers’ Adoption of Big Data in the Education Sector
description	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. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
format	Article
author	Baig, Maria Ijaz Shuib, Liyana Yadegaridehkordi, Elaheh
author_facet	Baig, Maria Ijaz Shuib, Liyana Yadegaridehkordi, Elaheh
author_sort	Baig, Maria Ijaz
title	A Model for Decision-Makers’ Adoption of Big Data in the Education Sector
title_short	A Model for Decision-Makers’ Adoption of Big Data in the Education Sector
title_full	A Model for Decision-Makers’ Adoption of Big Data in the Education Sector
title_fullStr	A Model for Decision-Makers’ Adoption of Big Data in the Education Sector
title_full_unstemmed	A Model for Decision-Makers’ Adoption of Big Data in the Education Sector
title_sort	model for decision-makers’ adoption of big data in the education sector
publisher	MDPI
publishDate	2021
url	http://eprints.um.edu.my/26078/ https://doi.org/10.3390/su132413995
_version_	1720980439526539264
score	13.211869

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

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