International Journal of Human Research and Social Science Studies

Workplace injuries remain a significant concern for organizations, impacting employee well-being, productivity, and organizational performance. This study investigates the effectiveness of various strategies for reducing workplace injuries, focusing on safety training programs, safe work procedures (SWPs), and behavior-based safety (BBS) interventions. Using a mixed-methods approach, the study collected quantitative data from 200 employees across multiple sectors and qualitative insights from in-depth interviews with 30 safety officers and staff. Descriptive statistics, regression, and hierarchical regression analyses were employed to assess the predictive power of the strategies, while thematic analysis explored participants’ experiences and perceptions. The findings reveal that all three strategies significantly reduce workplace injuries, with safety training emerging as the most influential factor, followed by SWPs and BBS interventions. Hierarchical regression confirmed that organizational interventions explained a substantial portion of injury reduction beyond demographic factors. Thematic analysis further highlighted the importance of organizational commitment, resource allocation, and employee engagement in the successful implementation of safety strategies. The study concludes that a holistic, integrated approach combining training, procedural adherence, and behavior-based reinforcement is essential for sustainable occupational safety. These findings provide practical insights for managers, safety officers, and policymakers seeking to enhance workplace safety and protect employee well-being.

Workplace Injuries, Safety Training, Safe Work Procedures, Behavior-Based Safety, Occupational Health

1. Chen, X., Li, Y., & Zhang, H. (2020). Ethical considerations in implementing AI for workplace safety. Journal of Occupational Health and Safety, 32(4), 215–230.
2. Fernandez, R., Kumar, P., & Smith, L. (2019). The impact of AI-based training and simulation on workplace safety compliance. International Journal of Workplace Learning, 11(2), 87–101.
3. Huang, M., & Rust, R. T. (2021). Artificial intelligence in service: A research agenda. Journal of Service Research, 24(1), 3–21.
4. Kumar, P., & Rao, S. (2020). Computer vision and AI applications in industrial safety: Emerging trends. Safety Science, 128, 104742.
5. Lee, J., Park, S., & Choi, K. (2021). Wearable monitoring devices and employee health outcomes: Evidence from manufacturing industries. Applied Ergonomics, 92, 103350.
6. Li, W., Zhang, Q., & Wang, Y. (2022). Predictive analytics for proactive occupational safety management: A systematic review. Safety Science, 150, 105728.
7. Park, H., & Choi, J. (2021). Robotic exoskeletons in industrial workplaces: Potential and limitations. Journal of Occupational Safety, 45(3), 145–158.
8. Smith, L., Johnson, R., & Lee, M. (2020). AI and automation in occupational safety: Evidence from multinational firms. International Journal of Industrial Ergonomics, 80, 103020.
9. Wang, Y., & Li, X. (2019). Challenges and opportunities in AI implementation for workplace safety. Journal of Safety Research, 70, 95–105.
10. Zhang, H., & Wang, Q. (2021). Data-driven approaches in AI-enhanced occupational health and safety management. Journal of Safety Science and Technology, 16(2), 112–124.
11. Chen, Y., & Liu, F. (2021). AI-driven predictive systems for reducing workplace incidents. Journal of Applied Safety Research, 15(1), 45–59.
12. Gupta, R., & Kumar, S. (2020). Machine learning applications for employee well-being and hazard prevention. Occupational Health Journal, 28(3), 211–225.
13. Hernandez, P., & Torres, M. (2019). AI in workplace health monitoring: Benefits and limitations. International Journal of Occupational Safety and Ergonomics, 25(4), 567–578.
14. Kim, J., & Park, Y. (2022). AI-based safety interventions and organizational performance. Safety and Health at Work, 13(2), 140–152.
15. Li, J., & Chen, Z. (2020). Integrating AI and IoT for workplace hazard management. Journal of Industrial Technology and Safety, 12(1), 65–79.