Application of the SWARA–TOPSIS method for prioritizing turnover intention factors among nurses: a case study in an Isfahan hospital, Iran

Abstract

Introduction: Nurse turnover intention poses a significant challenge to healthcare systems, particularly in hospitals. So, it disrupts clinical care and reduces patient satisfaction. This study aimed to identify and prioritize factors influencing turnover intention among nurses in a hospital to provide actionable insights for improving nurse retention. Methods: This study employed a hybrid Fuzzy Delphi-SWARA-TOPSIS methodology. First, a systematic literature review and the Fuzzy Delphi Technique were used to identify key factors. These factors were categorized into four groups: individual (e.g., age, education), organizational (e.g., salary, benefits), job-related (e.g., job security), and managerial (e.g., leadership style). The SWARA method was then applied to determine the relative weights of these factors, followed by the TOPSIS technique to rank them based on their impact on turnover intention. Results: The findings revealed that managerial factors, particularly leadership style (closeness coefficient: 0.44), had the strongest effect on nurses’ turnover intention. Organizational factors such as salary and job-related factors such as job security placed in next ranks. These results highlight the need for interventions focusing on effective leadership, competitive compensation, and job security to reduce nurse turnover. Conclusion: This study provides a comprehensive analytical framework for understanding and addressing nurse turnover intention. The findings suggest that hospital administrators should develop effective leadership, reform compensation structures, and improve job security to enhance nurse retention. These strategies can not only reduce turnover rates but also stabilize the workforce and improve healthcare service quality. The results offer valuable insights for policymakers and healthcare managers.