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Mandatory Remote Work and Multidimensional Employee Well-Being: Evidence from the Indian IT Sector

Author

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  • Purti Nagesh
  • Smita Premanand

Abstract

The COVID-19 pandemic transformed remote working from a discretionary practice into a mandatory reality for millions of employees worldwide. This study investigates the multidimensional impact of enforced remote work on employee well-being within the Indian IT sector, focusing on physical, psychological, emotional, social, intellectual, and spiritual dimensions. Drawing upon the Job Demands–Resources (JD-R) model and the PERMA well-being framework, a structured survey was administered to 322 employees from leading IT firms such as TCS and Infosys. The findings reveal that while remote work enhanced flexibility, reduced commuting stress, and created opportunities for personal growth, it simultaneously intensified digital fatigue, blurred work–life boundaries, and weakened social connectedness. Gender and household dynamics emerged as critical mediators, with women reporting higher stress due to disproportionate caregiving responsibilities. Regression and structural equation modelling further demonstrated that job resources, including managerial support and ergonomic home setups, moderated the negative effects of remote working demands. The study highlights the complex and context-dependent nature of remote work outcomes in emerging economies, where infrastructural limitations and cultural norms shape employee experiences differently than in Western contexts. These insights contribute to theory by extending the JD-R framework to enforced remote work conditions, and to practice by informing organizations and policymakers about strategies to foster sustainable employee well-being in hybrid and digital-first work environments.

Suggested Citation

  • Purti Nagesh & Smita Premanand, 2024. "Mandatory Remote Work and Multidimensional Employee Well-Being: Evidence from the Indian IT Sector," International Journal of Scientific Research in Science, Engineering and Technology, Technoscience Academy, vol. 11(6), pages 450-466, December.
  • Handle: RePEc:ijs:ijsrse:v11:y2024:i6:id:708
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