Navigating IT turnover: Impact of supervisor support on role stressors dynamics

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This study aims to investigate the impact of leadership support on the interplay between role stressors and turnover intentions among IT workers in Bengaluru. The study focuses on five constructs: role stressors, job performance, job satisfaction, supervisor support, and turnover intention. Using a questionnaire, data were collected from 196 IT employees, with 187 valid responses for analysis. Structural equation modeling (SEM) through Smart PLS software assessed the relationships between the constructs. The findings reveal that role stressors significantly contribute to IT workers’ intention to leave their organizations. Moreover, the connections between role stressors and both job performance and job satisfaction are influenced by the level of supervisor support. Supervisor support emerges as a crucial moderator in the relationship between role stressors and job satisfaction, highlighting its role in mitigating the negative effects of stress on employees. However, no mediating effect was observed between role stressors and job satisfaction when supervisor assistance was present. Furthermore, the study identifies a negative impact of role stressors on job satisfaction and, subsequently, a negative influence of job satisfaction on turnover intentions. These findings underscore the importance of supportive leadership in enhancing employee performance and job satisfaction, reducing the likelihood of turnover. This paper emphasizes the significance of leadership support as a key factor in shaping the dynamics between role stressors and turnover intentions among IT workers. The results suggest that fostering a supportive supervisory environment can positively influence employee well-being and retention in the IT industry.

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    • Figure 1. Research model
    • Figure 2. Outer loadings and AVE
    • Table 1. Sample description
    • Table 2. Validity and reliability measure of reflective variables
    • Table 3. Discriminant validity
    • Table 4. R square
    • Table 5. Validity measure of a formative construct
    • Table 6. Collinearity statistics (VIF)
    • Table 7. Hypothesis testing
    • Conceptualization
      Velaga Sri Sai
    • Data curation
      Velaga Sri Sai
    • Investigation
      Velaga Sri Sai
    • Resources
      Velaga Sri Sai
    • Software
      Velaga Sri Sai
    • Writing – original draft
      Velaga Sri Sai
    • Formal Analysis
      Anitha Kumari Pinapati
    • Methodology
      Anitha Kumari Pinapati
    • Project administration
      Anitha Kumari Pinapati
    • Supervision
      Anitha Kumari Pinapati
    • Validation
      Anitha Kumari Pinapati
    • Visualization
      Anitha Kumari Pinapati
    • Writing – review & editing
      Anitha Kumari Pinapati