Analysis demonstrates that workforce diversity enhances employee engagement and retention, suggesting the need for improved organizational climate in IT sectors.
This study has made an attempt to expand on existing research on workforce diversity by analyzing its effects on employee engagement (EE) and employee retention (ER). It also aims to understand the relationship between job satisfaction and employee performance. The study specifically examines the influence of organizational climate (OC) on the specific outcome. Data was collected from 422 experts working in the IT and ITeS industry. A multi-phase analytical methodology was employed. The variables of workforce diversity were initially discovered using exploratory factor analysis (EFA), which generated five important factors: the benefits of a diverse workforce (BDW), recruitment and selection (RS), orientation, training and development (OTD), and conflict management (CM). To validate the generated factors confirmatory factor analysis (CFA) was used, and structural equation modelling (SEM) was used to evaluate the impact of the identified variables with EE and ER. The results show that RS, OTD, CM, and BDW when considering the importance of diversity, significantly affect the EE and ER. Additionally, the pathways connecting OTD and CM with EE and BDW, OTD, and CM with ER were found to be significantly mediated by OC. This study contributes to both theory and practice by signifying that workforce diversity has an impact that goes beyond traditional indicators of job satisfaction. Inclusive hiring, well-structured training programs, resolving disputes positively, and encouraging more diversity policies can all work together to enhance employee engagement and retention and build a long-lasting workplaces in the IT and ITeS industry. The studies may be expanded in the future by looking at the interaction effects of diversity dimensions, by adding more mediators like knowledge management, and using cutting-edge analytical techniques like artificial neural networks (ANNs). It is also recommend to apply random sampling more widely to improve generalizability across organizational contexts and industries.
No takes yet. Share an insight, caveat, or question.
Ramasamy et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: