An in-depth learn from incidents (LFI) approach based on HFACS-RAs

Recent study has observed that the high-speed railway industry has failed to prevent the recurrences of accident in the workplaces. Therefore, the Learn from Incidents (LFI) theory is applied to detect the factors that have negative influences on LFI in our study from the perspectives of breadth and depth of learning. Based on the identified negative factors, the HFACS-RAs framework is proposed to establish an in-depth learning approach. This approach is conducive to prompt the Double-Loop learning process and strengthen the organization's incident response capabilities. For obtaining more close-fitting intervention plans of accidents, the relationship analysis is conducted to the casual factors identified by the HFACS-RAs framework and how the internal procedures and policies influence the behavior of employees can be revealed. Finally, some recommendation on how to effectively perform the intervention plan is given and with the comprehensive learning process we can build a formal learning mechanism to improve the safety climate in the high-speed railway industry.