The Relationship Between Leadership Decision-Making Styles and Employee Performance in Government Public Sector

Leadership decision-making styles exert a significant influence on employee performance, yet the underlying mechanisms are seldom linear, as heterogeneity, nonlinear responses, and cross-level dependencies often complicate the relationships. To address these complexities, this study proposes a Hybrid Multi-Method Framework (HMMF) that integrates four complementary perspectives: symmetric structural modeling to estimate direct and mediated paths, configurational analysis to capture equifinality and causal asymmetry, necessary-condition testing to identify noncompensatory constraints, and cross-level evaluation to account for organizational context. Applied to diverse organizational settings, HMMF examines how leadership styles, mediators, and moderators jointly shape performance and is benchmarked against widely used single-paradigm approaches such as PLS-SEM, CB-SEM, and fsQCA. The evaluation covers explanatory power, predictive relevance, configurational strength, and robustness, and results show that HMMF consistently outperforms these baselines.