Business intelligence adoption in higher education: the role of data-driven decision-making culture and UTAUT

Purpose While “business intelligence” (BI) has demonstrably improved decision-making across various industries, its application in “Higher Education Institutions” (HEIs) remains under-explored. HEIs collect vast amounts of data on students, faculty and operations. The purpose of this paper is to investigate the significant variables affecting the adoption and utilization of BI in HEIs, aiming to bridge this gap in knowledge. Design/methodology/approach Drawing upon the theoretical foundation provided by the “Unified Theory of Acceptance and Use of Technology” (UTAUT) framework, this research developed a novel conceptual model integrating a context-specific variable: “data-driven decision-making culture” (DDMC). To investigate the effect of these factors within Jordanian HEIs, a cross-sectional Web-based questionnaire was administered to 427 individuals holding various management positions. Findings “Structural equation modelling” (SEM) analysis demonstrated that perceived “performance expectancy” (PE), “social influence” (SI) and “facilitating conditions” (FC) significantly affect behavioural intentions to use BI systems. Furthermore, these results suggest that an organizational culture emphasizing data-driven decision-making acts as a significant antecedent within the UTAUT model for BI technology adoption. Originality/value This investigation holds significant implications for the practical application of BI technology within HEIs. These insights are useful for the HEIs stakeholders in the development, design and provision of services, as well as policymakers in the same sector. These key findings can help inform the development of effective strategies and BI systems for HEIs. These advancements have the potential to broaden user engagement in BI systems within the HEI community.