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Akin, F D, Damci, A and Arditi, D (2024) Optimum finance-based scheduling. Journal of Construction Engineering and Management, 150(09).
Assaad, R H, Omran, A, Soliman, N and Assaf, G (2024) Prediction of the lateral pressure of self-consolidating concrete on construction formwork systems using machine-learning algorithms. Journal of Construction Engineering and Management, 150(09).
Assaf, G and Assaad, R H (2024) Analyzing the critical success factors affecting project bundling performance of infrastructure projects. Journal of Construction Engineering and Management, 150(09).
Chammout, B, El-Adaway, I H, Abdul Nabi, M and Assaad, R H (2024) Price escalation in construction projects: Examining national and international contracts. Journal of Construction Engineering and Management, 150(09).
Dorignon, L, Oswald, D, Kempton, L, Boehme, T, Iyer-Raniga, U, Moore, T and Dalton, T (2024) Investigating residential building materials in a circular economy: An Australian perspective. Journal of Construction Engineering and Management, 150(09).
Görsch, C, Seppänen, O, Peltokorpi, A and Lavikka, R (2024) Unlocking productivity: Revealing waste and hidden disturbances impacting mep workers. Journal of Construction Engineering and Management, 150(09).
Gao, M Y, Han, J, Yang, Y, Tiong, R L K, Zhao, C and Han, C (2024) BIM-based and IoT-driven smart tracking for precast construction dynamic scheduling. Journal of Construction Engineering and Management, 150(09).
Jiang, Y, Yang, G, Li, H, Zhang, T and Khudhair, A (2024) Physics-informed knowledge-driven decision-making framework for holistic bridge maintenance. Journal of Construction Engineering and Management, 150(09).
Koo, H J, Kelly, D and Deman, D (2024) Risk assessment of the challenges in the adaptive reuse of historic buildings. Journal of Construction Engineering and Management, 150(09).
Namian, M, Nabil, F R, Al-Mhdawi, M K S, Kermanshachi, S S and Nnaji, C (2024) Postpandemic era: Investigating the impact of COVID-19 on construction workers' situational awareness. Journal of Construction Engineering and Management, 150(09).
Ning, X, Yang, Y, Liu, C and Han, Y (2024) Construction workers' unsafe behavior contagion under government-contractor dual influence. Journal of Construction Engineering and Management, 150(09).
- Type: Journal Article
- Keywords: construction worker; dual influence; epidemic model; evolutionary game theory; unsafe behavior contagion
- ISBN/ISSN: 0733-9364
- URL: http://doi.org/10.1061/JCEMD4.COENG-14282
- Abstract:
Despite efforts to prevent and correct unsafe behavior on construction sites, such behavior persists among construction workers. Much of what makes unsafe behavior so difficult to eradicate is its contagious nature. The contagion pattern of unsafe behavior is not only based on the group characteristics of construction workers but also influenced by government regulatory agencies (GRA) and general contractors (GC). In this study, we established a contagion model of construction workers' unsafe behavior based on group-level factors and the dual influence of GRA and GC and employed evolutionary game theory and epidemic models to explore the contagion patterns and interventions of unsafe behavior. We find that, although the strong and weak regulation strategies by GRA suppress the contagion of unsafe behavior, the strong regulation strategy exhibits a better preventive effect; further, the active management strategies by GC have a dampening effect on the contagion of unsafe behavior and vice versa, enhanced perceived social benefits of GRA prevent unsafe behavior more than enhanced perceived image loss, and a high degree of group identity perception effectively inhibits the contagion of unsafe behavior when construction workers have relatively high levels of safety awareness. By portraying the contagion state of construction workers' unsafe behavior in actual situations, this study provides a theoretical basis for the decision-making of GRA and GC and helps to improve the work efficiency of GRA as well as the safety management level of GC.
Olugboyega, O (2024) Diverse forms of greed and self-interest that contribute to corruption among construction stakeholders. Journal of Construction Engineering and Management, 150(09).
Ouyang, Y and Luo, X (2024) Effects of physical fatigue on construction workers' visual search patterns during hazard identification. Journal of Construction Engineering and Management, 150(09).
Paneru, S, Suh, S, Seo, W and Rausch, C (2024) Evaluating the decarbonization potential of industrialized construction: A review of the current state, opportunities, and challenges. Journal of Construction Engineering and Management, 150(09).
Sadoughi, A, Kouhirostami, M, Kouhirostamkolaei, M, Qi, B and Costin, A (2024) Autonomous building design for manufacturing and assembly: A systematic review of design application, challenges, and opportunities. Journal of Construction Engineering and Management, 150(09).
Shahedi, F, Etemadfard, H, Omrani, F and Ghalehnovi, M (2024) Cost performance modeling for steel fabrication shops with machine learning algorithms. Journal of Construction Engineering and Management, 150(09).
Shuang, Q, Liu, X, Wang, Z and Xu, X (2024) Automatically categorizing construction accident narratives using the deep-learning model with a class-imbalance treatment technique. Journal of Construction Engineering and Management, 150(09).
Wang, R D, Zayed, T, Eltoukhy, A E E and Wu, H (2024) Integrated planning approach for optimizing tower crane and truck locations in modular integrated construction. Journal of Construction Engineering and Management, 150(09).
Wu, H, Chang, Y and Chen, Y (2024) Transitioning work arrangements in the construction industry: Changes in time-use patterns and individual greenhouse gas emissions. Journal of Construction Engineering and Management, 150(09).
Yang, J, Wu, Y and Li, D (2024) Block planning based on grid's topology for the dismantling of long-span spatial lattice structures. Journal of Construction Engineering and Management, 150(09).
Zhang, Y, Chang, R, Mao, W, Zuo, J, Liu, L and Han, Y (2024) Challenges of automating interior construction progress monitoring. Journal of Construction Engineering and Management, 150(09).
Zhang, Y, Liu, L, Song, Z, Zhao, Y and He, S (2024) Enhancing tunnel boring machine penetration rate predictions through particle swarm optimization and elman neural networks. Journal of Construction Engineering and Management, 150(09).