Examining the influence of authentic leadership on employees’ intention to leave: The mediatıng role of employee wellbeing & psychological capital

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03/10/2024

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İstanbul Bilgi Üniversitesi, Lisansüstü Eğitim Enstitüsü

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info:eu-repo/semantics/openAccess

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Intention to leave is the strongest predictor of employee turnover behavior before it occurs. Consequently, managing this intention effectively can provide organizations with significant control over employees’ tendency to leave their jobs, one of the most critical challenges in the modern corporate world. This study investigates the interrelationships between authentic leadership as an independent variable, employee wellbeing and psychological capital as a mediator, and turnover intention as a dependent variable. A sample of 152 employees participated in the research, with data collected through self-reported measures. The study employs reliability analysis, descriptive analysis, correlation, mediation and hierarchical regression analyses to test three hypotheses. The findings indicate that authentic leadership is a significant predictor of turnover intention, and its effect is mediated by employee wellbeing. Even though psychological capital shows significant association with dependent and independent variables separately, it individually is not mediate the relationship between authentic leadership and intention to leave. The results highlight the importance of developing authentic leadership and enhancing employee wellbeing to reduce turnover intentions. Practical recommendations for organizations include developing leadership practices, organizational structures to develop financial, social, and intellectual wellbeing of employees and embedding psychological capital and wellbeing metrics into performance appraisals and development plans. Limitations of the study include the small sample size, potential biases from self-reported data, and the cross-sectional design, which limits the ability to establish causality. Future research should aim to address these limitations by including larger and more diverse samples and employing longitudinal designs.

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