Enhancing Employee Job Satisfaction in Public Sector Railways: A Data-Driven Analysis using Simulation and Artificial Intelligence
Year: 2024
Type: article
Study design: Observational Study
Abstract: Introduction & Reviews: This study explores employee job satisfaction within the South Central Railway (SCR), a key zone in Indian Railways, emphasizing the role of simulation and artificial intelligence (AI) in enhancing workplace satisfaction. In complex, high-stress environments like railroads, employee well-being directly influences operational efficiency, safety, and service quality. By using simulation to model workplace conditions and AI for real-time feedback and predictive analysis job satisfaction, including stress management, career development, and recognition. The findings provide data-driven insights for SCR, offering actionable strategies to improve employee satisfaction, retention, and overall organizational performance. Methodology: sample 211 SCR employees. Suitable sample style selected. Results & Discussion: The independent sample t-test indicates similar perceptions of organizational factors among employees. KMO and Bartlett’s tests confirm the data's suitability, revealing significant relationships among variables affecting job satisfaction. Conclusion: The study provides actionable insights for SCR management to help & improve employee satisfaction and engagement, ultimately reducing turnover and enhancing organizational performance.
Authors: Ashok Kumar Katta, Shailashri V.T.
Institutions: Vels University, Srinivas University
Language: English
Subfield: Human Factors and Ergonomics
Field: Social Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4406253650