Decoding Employee Exit: A Systematic Review of Turnover Intention and Its Determinants
Keywords:
Employee turnover, Job satisfaction, Leadership style, Supervisor support, Job insecurity, Job embeddedness, Employee retention.Abstract
Employee turnover continues to be a major issue for businesses, as it affects financial performance, workplace stability, and productivity. It is necessary to comprehend turnover intention and its factors in order to design effective retention tactics. In this systematic literature review (SLR), the findings of peer-reviewed studies published in esteemed journals that are included in major academic databases like Scopus, Web of Science, Science Direct, Springer Link, and others are compiled. The goal of the review is to compile the body of knowledge and offer a thorough grasp of the variables affecting turnover intention. The findings show that a number of individual factors, including job engagement, emotional exhaustion, burnout, and job insecurity, influence the intention to leave a job. Other important drivers include organizational elements like commitment, supervisor support, leadership style, and job satisfaction. Employee departure decisions are also influenced by outside factors like labor market dynamics, economic conditions, and the availability of alternative employment opportunities. These associations were found to be moderated by demographic factors such as tenure, age, gender, and generational differences, indicating that retention tactics need to be customized to fit a range of employee profiles. Understanding turnover behaviors is supported by a number of theoretical frameworks, most notably the Push-Pull-Mooring (PPM) Model, Job Embeddedness Theory, and Social Exchange Theory. These models place a strong emphasis on elements like workplace attachment, perceived organizational support, and striking a balance between opportunities from outside sources and internal discontent. For academics and professionals looking to comprehend and reduce turnover risks, this review provides insightful information. It also emphasizes how future studies must concentrate on longitudinal designs in order to capture how turnover intention changes over time.
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