Driving sustainable education with big data analytics: empirical evidence from Malaysian higher learning institutions

Purpose In recent years, big data analytics (BDA) has received significant attention in various industries, including education. However, research on the implementation of BDA to promote sustainability in the education sector is scarce. Thus, this study investigates the impact of success factors on BDA toward sustainable education in higher learning institutions (HLIs) in Malaysia. Design/methodology/approach Based on a quantitative approach, this study integrates technology, organization and environment theory and the diffusion of innovation model with sustainability to develop a theoretical framework. Data were collected from 214 HLIs and analyzed using partial least squares–structural equation modeling. Findings Most success factors, including relative advantage, compatibility, institutional readiness, employee competency and competitive pressure, significantly influence BDA and sustainable education, except for complexity. BDA substantially impacts sustainable education and mediates the relationship between success factors and sustainable education. Practical implications The findings provide valuable insights for educators and policymakers on how to leverage BDA for sustainability in the education sector, thus achieving sustainable development goals for the nation. Originality/value The novelty of this study lies in its alignment with the National Fourth Industrial Revolution Policy and the Public Sector Big Data Analytics Policy as well as its integration of BDA and sustainable education in the context of a developing country such as Malaysia. Additionally, an examination of the mediating role of BDA in the connection between success factors and sustainable education sets it apart, as it addresses a unique geographical and sectoral context that has not been sufficiently investigated.