A theoretical model for big data adoption in the higher education institution of Pakistan / Maria Ijaz Baig

Maria Ijaz , Baig (2022) A theoretical model for big data adoption in the higher education institution of Pakistan / Maria Ijaz Baig. PhD thesis, Universiti Malaya.

	PDF (The Candidate's Agreement) Restricted to Repository staff only Download (187Kb)
	PDF (Thesis PhD) Download (1576Kb)

Abstract

Big data adoption 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. The higher education institutions of Pakistan are facing difficulties in upgrading the educational managerial competency that is needed to fulfil future demands. Thus, there is a need of big data adoption in higher education institutions of Pakistan to improve the managerial aptitude. However, there is a limited literature on theoretical model and factors that affect big data adoption in the higher education institutions. This study aims to develop a theoretical model and identify the factors that influence big data adoption in a higher education institution. Ten factors were identified from the literature, and a theoretical model was developed. Technology-Organization-Environment and Diffusion of Innovation theories were adopted as a theoretical base in this study. Meanwhile, the moderating effects of the university size and university age on big data adoption were added to the developed model. A virtual university in Pakistan is recognized by the Higher Education Commission of Pakistan as a higher education institution is chosen. Data was collected from a sample of 195 respondents from the managerial side of a virtual university in Pakistan using an online survey. Structural Equation Modelling was used to predict the relationships between identified factors and big data adoption. According to the results, relative advantage, complexity, compatibility, top management support, financial resources, human expertise and skills, competitive pressure, security and privacy, and government policies were significant determinants of big data adoption. However, results revealed an insignificant relationship between the information technology infrastructure and big data adoption. The findings further revealed the significant moderating effects of university age on government policies, security and privacy concerns with big data adoption. Similarly, substantial moderating effects of the university size between information technology infrastructure and big data adoption were found. The findings from this study can assist the ministry of education, higher education institutions administrators, and big data service providers in the adoption of big data for the education sector. Future studies could be longitudinal, conducted at the post-adoption stage and at other educational levels.

Actions (For repository staff only : Login required)