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Al-Bayati, A J (2019) Satisfying the Need for Diversity Training for Hispanic Construction Workers and Their Supervisors at US Construction Workplaces: A Case Study. Journal of Construction Engineering and Management, 145(06).

Guo, S, Ding, L, Zhang, Y, Skibniewski, M J and Liang, K (2019) Hybrid Recommendation Approach for Behavior Modification in the Chinese Construction Industry. Journal of Construction Engineering and Management, 145(06).

Lohne, J, Kjesbu, N E, Engebø, A, Young, B and Lædre, O (2019) Scoping Literature Review of Crime in the AEC Industry. Journal of Construction Engineering and Management, 145(06).

Shahbazi, B, Akbarnezhad, A, Rey, D, Ahmadian Fard Fini, A and Loosemore, M (2019) Optimization of Job Allocation in Construction Organizations to Maximize Workers’ Career Development Opportunities. Journal of Construction Engineering and Management, 145(06).

Zhang, S, Shang, C, Wang, C, Song, R and Wang, X (2019) Real-Time Safety Risk Identification Model during Metro Construction Adjacent to Buildings. Journal of Construction Engineering and Management, 145(06).

  • Type: Journal Article
  • Keywords: Real-time project risk; Risk identification; Metro construction adjacent to buildings/structures; Interval analytic hierarchy process (IAHP); TOPSIS;
  • ISBN/ISSN: 0733-9364
  • URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0001657
  • Abstract:
    Comprehensive and effective safety risk identification in metro construction has a significant impact on risk management. Although previous studies attempted to obtain a final ranking of the risk factors using various risk identification methods, they did not consider real-time risk identification. To address the complex issues involved, a model was established to identify the possible safety risks among the many potential risk factors in real time, considering the uncertain and complex environment in metro construction adjacent to buildings/structures. The study made decisions regarding the weights of the safety risk criteria at various stages of the construction. The safety risk factors and degrees of closeness were ranked at a specific time using real-time construction data. The model was demonstrated by real-time safety risk identification in a typical case study of metro construction adjacent to buildings/structures. The results are consistent with the reality of safety risks at various stages of such a metro project. The method of real-time risk identification is established to be feasible and effective, and experiments are proposed to identify risks in similar metro projects.