In today’s dynamic work environment, employee attrition is a crucial challenge for organizations that are impacted by demographic and job-related factors. This study examines the role of gender in attrition across different job roles and encompasses a multi-method approach taking into consideration 1,470 employees. The analysis found that there is no significant influence of gender in the attrition rates. Job satisfaction and tenure of an employee within an organization emanated as stronger predictors of attrition than gender, aligning with the established theories that highlighted the preference of job-related factors over demographic characteristics that helps in the retention of an employee. The logistic regression model showed a statistically significant result but was not very effective at predicting who leaves, highlighting the complexity of attrition and the role of factors not included in the study. Overall, the findings suggest that gender alone is insufficient to explain attrition patterns, highlighting the importance of contextual factors such as job role and employee satisfaction. This research contributes to the ongoing dialogue on diversity and retention by demonstrating that effective talent management should consider the nuanced interactions between job characteristics and individual experiences rather than relying on broad demographic generalizations.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

Role-Specific Gender Differences in Employee Attrition: Evidence from a Multi-Method Workforce Study

  • Usha Sadhani,
  • Melita Simoes,
  • A. M. Kadakol

摘要

In today’s dynamic work environment, employee attrition is a crucial challenge for organizations that are impacted by demographic and job-related factors. This study examines the role of gender in attrition across different job roles and encompasses a multi-method approach taking into consideration 1,470 employees. The analysis found that there is no significant influence of gender in the attrition rates. Job satisfaction and tenure of an employee within an organization emanated as stronger predictors of attrition than gender, aligning with the established theories that highlighted the preference of job-related factors over demographic characteristics that helps in the retention of an employee. The logistic regression model showed a statistically significant result but was not very effective at predicting who leaves, highlighting the complexity of attrition and the role of factors not included in the study. Overall, the findings suggest that gender alone is insufficient to explain attrition patterns, highlighting the importance of contextual factors such as job role and employee satisfaction. This research contributes to the ongoing dialogue on diversity and retention by demonstrating that effective talent management should consider the nuanced interactions between job characteristics and individual experiences rather than relying on broad demographic generalizations.