Analysis of the systems nature of safety incidents in the construction industry from a post-2010 literature review

ABSTRACT

This review aims to develop a comprehensive understanding of multi-system and multi-dimensional characteristics of learning from incidents (LFI) and improve the ability to learn from incidents effectively in construction. LFI is a continuous learning process within the organisational safety management system and an essential means of improving organisational safety and preventing similar incidents in the future. Efforts to understand the LFI behaviours and characteristics that occur in the construction industry require us to develop a multi-system, multi-dimensional perspective to explore the factors that influence effective learning. This study provides a systematic literature review (SLR) of exploring factors influencing effective LFI among various industries and conducts a proper bibliometric analysis with Citespace. Through three stages of literature collection, filtering and analysis, we identified and summarised the papers on factors affecting LFI from different industries, contrasting them through the characteristics and commonalities of each industry. The results show that LFI is influenced by multiple systems and dimensions, ranging from the organisation, individual, work, external environment and knowledge system. Furthermore, based on the post-framework analysis, the most critical dimensions of the system are demonstrated so that they can be given more attention to improving the level of LFI behaviours in the construction industry.

KEYWORDS:

• Learning from incidents
• construction safety
• systematic literature review
• cross-industry research

Acknowledgements

This work was supported by the National Natural Science Foundation of China (grant number 72201188); Postgraduate Research and Practice Innovation Program of Jiangsu Province of China (grant number SJCX23_1742; SJCX21_1412).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Natural Science Foundation of China (grant number 72201188); Postgraduate Research and Practice Innovation Program of Jiangsu Province of China (grant number SJCX23_1742; SJCX21_1412).