Enhancing teacher recruitment and retention through decision-making models in education systems

Teacher recruitment and retention remain critical challenges for education systems worldwide, with far-reaching implications for educational quality and institutional sustainability. Traditional approaches often fail to address the complexity of these issues, neglecting the interplay of multiple conflicting criteria and the inherent uncertainty in decision-making. This gap necessitates advanced decision-making frameworks that can effectively evaluate and prioritize strategies for improving teacher recruitment and retention. To bridge this gap, this study introduces a novel decision-making framework integrating intuitionistic fuzzy sets (IFSs) to handle uncertainty more effectively. The Entropy method is employed to compute objective weights, while the ranking comparison (RANCOM) method determines subjective weights, ensuring a balanced consideration of qualitative and quantitative factors. The weighted aggregated sum product assessment (WASPAS) method is then applied. The framework is validated through sensitivity analysis to assess its robustness and comparative analysis to establish its superiority over traditional methods. The results identify the Golden Ticket Salary Plan [Formula: see text] as the optimal strategy, achieving the highest ranking (0.3654), followed by [Formula: see text] (0.3487), [Formula: see text] (0.3485), [Formula: see text] (0.3400), [Formula: see text] (0.2976) and [Formula: see text] (0.2707). The ranking order for the strategies is as follows: [Formula: see text]. These findings highlight the significance of structured decision-making in optimizing teacher workforce management. This study provides valuable insights for policymakers and administrators, ensuring sustainable advancements in teacher workforce management.