Liu Tong, Li Wenjun
Party Committee Organization Department, Hanjiang Normal University, Shiyan, 442200, China.
Department of Comprehensive Education, Shinhan University, Uijeongbu, Gyeonggi Province, 100032, South Korea.
Sci Rep. 2025 Apr 30;15(1):15247. doi: 10.1038/s41598-025-00161-9.
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.
教师招聘和留用仍然是全球教育系统面临的关键挑战，对教育质量和机构可持续性具有深远影响。传统方法往往无法应对这些问题的复杂性，忽视了多个相互冲突标准之间的相互作用以及决策中固有的不确定性。这一差距需要先进的决策框架，能够有效评估并优先考虑改善教师招聘和留用的策略。为了弥补这一差距，本研究引入了一种新颖的决策框架，整合直觉模糊集（IFS）以更有效地处理不确定性。采用熵方法计算客观权重，而排序比较（RANCOM）方法确定主观权重，确保定性和定量因素得到平衡考虑。然后应用加权聚合和积评估（WASPAS）方法。通过敏感性分析验证该框架以评估其稳健性，并通过比较分析确定其相对于传统方法的优越性。结果确定金票薪资计划[公式：见原文]为最优策略，排名最高（0.3654），其次是[公式：见原文]（0.3487）、[公式：见原文]（0.3485）、[公式：见原文]（0.3400）、[公式：见原文]（0.2976）和[公式：见原文]（0.2707）。这些策略的排名顺序如下：[公式：见原文]。这些发现凸显了结构化决策在优化教师队伍管理中的重要性。本研究为政策制定者和管理人员提供了宝贵的见解，确保教师队伍管理的可持续进步。
