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Experience-based systematic construction hazard warning

Mohan Wang (Department of Construction Management, Tsinghua University, Beijing, China)
Pin-Chao Liao (Department of Construction Management, Tsinghua University, Beijing, China)

Engineering, Construction and Architectural Management

ISSN: 0969-9988

Article publication date: 15 September 2022

Issue publication date: 2 January 2024

121

Abstract

Purpose

Hazard warning schemes provide efficient hazard recognition and promote project safety. Nevertheless, these schemes perform poorly because the warning information is calibrated for individual characters and is not prioritized for the entire system. This study proposes a hazard warning scheme that prioritizes hazard characters from the inspection process based on the inspectors' experience.

Design/methodology/approach

First, hazard descriptions were decomposed into their characters, forming a double-layer network. Second, warning schemes based on cascading effects were proposed. Third, character-based warning schemes were simulated for various experiences.

Findings

The results show that when a specific hazard is detected, the degree centrality is the most effective parameter for prioritization, and hazard characters should be prioritized based on betweenness centrality for experienced inspectors, whereas degree centrality is preferred for novice inspectors.

Originality/value

The warning scheme theoretically supplements the information-processing theory in construction hazard warnings and provides a practical warning scheme with priority for the development of automated hazard navigation systems.

Keywords

Acknowledgements

This work was supported by the National Natural Science Foundation of China [grant number 51878382].

Citation

Wang, M. and Liao, P.-C. (2024), "Experience-based systematic construction hazard warning", Engineering, Construction and Architectural Management, Vol. 31 No. 1, pp. 469-486. https://doi.org/10.1108/ECAM-02-2022-0151

Publisher

:

Emerald Publishing Limited

Copyright © 2022, Emerald Publishing Limited

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