Understanding What Drives the Adoption of Data Analytics Among Academic Leaders and Supervisors in a Jewish Higher Education Institution

Abstract

This study explores the determinants influencing the adoption of Big Data Analytics (BDA) within the Jewish higher education system centered in the Northwestern United States of America, emphasizing the impact of six key factors: Absorptive Capacity, Technological Resource Competency, Competition Intensity, Complexity, Compatibility, and Relative Advantage, alongside participants' age. Utilizing a quantitative methodology, the research surveyed 64 managerial role employees across the academic institution. Results from multiple regression analysis indicate a statistically significant relationship between these factors and the behavioral intention toward BDA adoption, with Compatibility emerging as the predominant predictor. This finding underscores the critical role of perceived consistency with existing needs and practices in influencing BDA adoption intentions. Moreover, Marketing Department Leadership exhibited significantly lower ratings in both Absorptive Capacity and behavioral intention toward BDA adoption based on a MANOVA analysis compared to other types of academic institutional leaders, suggesting a discrepancy in recognizing and leveraging new external information for competitive advantage within this group. The study concludes with recommendations for higher education institutions aiming to transition towards data-driven decision-making, highlighting the importance of fostering an organizational culture that values data literacy and aligns BDA initiatives with institutional goals. Limitations and directions for future research are also discussed, advocating for a broader investigation into behavioral intentions and the potential benefits of applying the Decomposed Theory of Planned Behavior in understanding BDA adoption.