An association rule mining model for evaluating the potential correlation of construction cross operation risk
Engineering, Construction and Architectural Management
ISSN: 0969-9988
Article publication date: 12 August 2022
Issue publication date: 28 November 2023
Abstract
Purpose
Cross operation is a common operation method in the building construction process nowadays. Due to the crossover, each other's operations are disturbed, and risks also interact. This superimposed relationship of risks is worthy of attention. The study aims to develop a model for analyzing cross-working risks. This model can quantify the correlation of various risk factors.
Design/methodology/approach
The concept of cross operation and the cross types involved are clarified. The risk factors were extracted from cross-operation accidents. The association rule mining (ARM) was used to analyze the results of various cross-types accidents. With the help of visualization tools, the intensity distribution and correlation path of the relationship between each factor were obtained. A complete cross-operation risk analysis model was established.
Findings
The application of ARM method proves that there are obvious risk correlation deviations in different types of cross operations. A high-frequency risk common to all cross operations is on-site safety inspection and process supervision, but the subsequent problems are different. Cutting off the high-lift risk chain timely according to the results obtained by ARM can reduce or eliminate the danger of high-frequency risk factors.
Originality/value
This is the first systematic analysis of cross-work risk in the construction. The study determined the priority of risk management. The results contribute to targeted cross-work control to reduce accidents caused by cross-work.
Keywords
Acknowledgements
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
Citation
Chen, Q., Tian, Z., Lei, T. and Huang, S. (2023), "An association rule mining model for evaluating the potential correlation of construction cross operation risk", Engineering, Construction and Architectural Management, Vol. 30 No. 10, pp. 5109-5132. https://doi.org/10.1108/ECAM-09-2021-0792
Publisher
:Emerald Publishing Limited
Copyright © 2022, Emerald Publishing Limited