Big Data Analytics Technology Capability and Data-Driven Decision Making in Malaysian Higher Education Institutions: A Conceptual Framework

Abstract

Abstract In the era of big data, many organizations are aiming to become more data-driven and increase their decision-making efficiency. Nevertheless, there is an insufficient investigation that explores the antecedents of data-driven decision making (DDDM) in the context of Malaysian Higher Education Institutions (HEIs). Therefore, the study examines existing literature and utilises the Big Data Analytics Technology Capability (BDATC) dimensions such as connectivity, compatibility and modularity to conceptualize a DDDM framework. The study utilises Resource-Based Theory (RBT) to highlight the key dimensions for BDATC and how these dimensions are being integrate in order to establish effective DDDM for excellent performance. The antecedents of DDDM is a relatively new approach that is documented in literature, where literature seems to be diversified in terms of offering theoretical and conceptual frameworks, together with a model that Higher Education Institutions (HEIs) can utilize. The study chooses HEIs that undergo Malaysian Research Assessment Instrument (MyRA) as the focus of investigation. The data was collected from the key informants of Malaysian HEIs. In conclusion, the contribution of the study is to highlight the influence of BDATC for DDDM to attain better performance of HEIs in Malaysia.