Data-Driven Decision-Making Capability and Strategic Decision Quality in Saudi Universities: A Contingency Perspective on Environmental Uncertainty

Abstract

Purpose: Purpose: This study examines the relationship between Data-Driven Decision-Making (DDDM) Capability and Strategic Decision Quality in Saudi higher education institutions and tests the moderating role of Environmental Uncertainty.

Design / Methodology:            A quantitative cross-sectional survey was administered to 150 senior academic and administrative leaders across Saudi public and private universities. Partial Least Squares Structural Equation Modeling (PLS-SEM) with 5,000 bootstrap subsamples was employed for hypothesis testing.

Findings:         DDDM Capability significantly and positively predicts Strategic Decision Quality (β = 0.412, R² = 0.384, f² = 0.187). Environmental Uncertainty significantly attenuates this relationship (β = −0.187, p = .001), with Dynamism and Complexity exerting the strongest constraining effects, indicating that data-driven governance yields its highest decision-quality premium under moderate rather than extreme uncertainty.

Originality / Value: This is the first empirical study to establish a multidimensional DDDM–decision quality nexus in higher education and to document a negative contingency moderation effect, advancing both contingency theory and the evidence base for evidence-based governance reform under Vision 2030.