The impact of diversity, equity, inclusivity, and belongingness on employee retention in private hospitals in Chennai: An empirical study

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Type of the article: Research Article

Abstract
Increasing demographic diversity and shortages in labor necessitate healthcare organizations to establish inclusive workspaces that promote retention. In a dynamic and diverse labor market, this study evaluates how diversity, equity, inclusivity, and belongingness influence employee retention in multispecialty hospitals in Chennai, a major healthcare center in South India. A standardized questionnaire was administered to collect data from 247 physicians, who represent a critical group within the hospital between January and March 2025. The data were analyzed using structural equation modeling to examine direct and indirect relationships. The findings indicate that diversity, equity, inclusivity, and belongingness practices have a substantial and positive impact on employee retention (β = 0.700, 0.784, 0.410; p = 0.000), thereby improving the overall well-being of employees. It is worth noting that the inclusion-specific strategies implemented within this framework did not have any statistically significant effects (β = 0.095; p = 0.459) on retention. Also, well-being played a significant role in mediating the relationship between diversity, equity, inclusivity, and belongingness practices and retention (β = 0.411; p = 0.000). Furthermore, the individual mediation paths revealed statistically significant results (β = 0.228, 0.371, 0.189, 0.167; p = 0.010, 0.001, 0.003, 0.002). Higher organizational commitment has a positive impact since it has been shown to moderate the relationship between retention and well-being (β = 0.076; p < 0.01). In addition to contributing to the expanding corpus of literature on urban healthcare settings, findings may help policymakers enhance workforce stability through more equitable and inclusive organizational practices.

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    • Figure 1. Conceptual research framework
    • Table 1. Measurement scales
    • Table 2. Demographic characteristics
    • Table 3. Factor loadings, AVE, CR, and Cronbach’s alpha
    • Table 4. Reliability
    • Table 5. Discriminant validity (Fornell-Larcker)
    • Table 6. Sampling adequacy
    • Table 7. Model estimation
    • Table 8. Statistical analysis (Direct effects)
    • Table 9. Statistical analysis (Indirect effects)
    • Table 10. Moderator testing
    • Table A1. Questionnaire
    • Conceptualization
      Sindu Bharathi S. K., Sujatha S.
    • Formal Analysis
      Sindu Bharathi S. K.
    • Investigation
      Sindu Bharathi S. K., Sujatha S.
    • Methodology
      Sindu Bharathi S. K.
    • Project administration
      Sindu Bharathi S. K., Sujatha S.
    • Resources
      Sindu Bharathi S. K.
    • Software
      Sindu Bharathi S. K.
    • Visualization
      Sindu Bharathi S. K., Sujatha S.
    • Writing – original draft
      Sindu Bharathi S. K.
    • Writing – review & editing
      Sindu Bharathi S. K., Sujatha S.
    • Data curation
      Sujatha S.
    • Supervision
      Sujatha S.
    • Validation
      Sujatha S.