Information System Utilization and Data-Driven Decision-Making in Higher Education: Evidence from University Faculty

Abstract

Higher education institutions increasingly rely on information systems to enable datadriven decision-making (DDDM), yet empirical evidence on how system usage, system quality, and the information quality mutually shape faculty decision behavior remains scarce. Grounded in the Technology Acceptance Model and the DeLone and McLean Information Systems Success Model, this study examines the combined influence of these three dimensions on DDDM among university faculty in Pakistan. Using a quantitative, cross-sectional survey design, data were collected from 220 faculty members across public and private universities and analyzed via Partial Least Squares Structural Equation Modeling (PLS-SEM) in SmartPLS 4. The measurement model showed satisfactory reliability, convergent validity, and discriminant validity. Structural results revealed that system usage (β = .200), system quality (β = .338), and information quality (β = .439) each significantly and positively predicted DDDM, with information quality emerging as the strongest driver; the model explained 80.5% of the variance in DDDM (R² = .805). These findings indicate that information quality, rather than system usage alone, is the primary lever for effective DDDM in higher education. The study extends technology acceptance and information systems success theory to the higher education context and offers practical guidance for strengthening information quality and system design in Pakistani universities.