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Abbasnejad, B, Nasirian, A, Duan, S, Diro, A, Prasad Nepal, M and Song, Y (2024) Measuring BIM implementation: A mathematical modeling and artificial neural network approach. Journal of Construction Engineering and Management, 150(05).
Asadian, E, Azeez, S, Leicht, R M and Asadi, S (2024) Exploring the barriers to women in construction and the opportunities presented through lean. Journal of Construction Engineering and Management, 150(05).
Henao, Y, Grubert, E, Korey, M, Bank, L C and Gentry, R (2024) Life cycle assessment and life cycle cost analysis of repurposing decommissioned wind turbine blades as high-voltage transmission poles. Journal of Construction Engineering and Management, 150(05).
Huang, Y, Liu, D, Bell, F M, Yu, J and Pena-Mora, F (2024) Influences of intra- and interorganizational IT innovations on knowledge sharing and team creativity: Evidence from construction projects in China. Journal of Construction Engineering and Management, 150(05).
Min, Y and Lee, H W (2024) Adoption inequalities and causal relationship between residential electric vehicle chargers and heat pumps. Journal of Construction Engineering and Management, 150(05).
Nabi, M A, El-Adaway, I H and Assaad, R H (2024) Modeling inflation transmission among different construction materials. Journal of Construction Engineering and Management, 150(05).
Nguyen, P H D and Tran, D (2024) Exploring the use of quality control plans for alternative contracting methods in highway projects. Journal of Construction Engineering and Management, 150(05).
Ning, X, Ye, X, Li, H, Rajendra, D and Skitmore, M (2024) Evolutionary game analysis of optimal strategies for construction stakeholders in promoting the adoption of green building technology innovation. Journal of Construction Engineering and Management, 150(05).
Shi, M, Chen, C, Xiao, B and Seo, J (2024) Vision-based detection method for construction site monitoring by integrating data augmentation and semisupervised learning. Journal of Construction Engineering and Management, 150(05).
Tao, Y, Hu, H, Xu, F and Zhang, Z (2024) Work-rest schedule optimization of precast production considering workers' overexertion. Journal of Construction Engineering and Management, 150(05).
Turkoglu, H, Arditi, D and Polat, G (2024) Augmented time-cost trade-off optimization using particle swarm optimization. Journal of Construction Engineering and Management, 150(05).
Wang, H, Xu, S, Cui, D, Xu, H and Luo, H (2024) Information integration of regulation texts and tables for automated construction safety knowledge mapping. Journal of Construction Engineering and Management, 150(05).
Wang, J, Liang, M and Liao, P C (2024) Toward an intuitive device for construction hazard recognition management: Eye fixation-related potentials in reinvestigation of hazard recognition performance prediction. Journal of Construction Engineering and Management, 150(05).
Wang, L, Lee, J, Nimawat, J, Han, K and Gupta, A (2024) Integrated 4D design change management model for construction projects. Journal of Construction Engineering and Management, 150(05).
Wang, S, Hasan, M and Lu, M (2024) Global sensitivity analysis methodology for construction simulation models: Multiple linear regressions versus multilayer perceptions. Journal of Construction Engineering and Management, 150(05).
Zhang, S, Hua, X and Shi, X (2024) Measurement for risk perception ability. Journal of Construction Engineering and Management, 150(05).
- Type: Journal Article
- Keywords: construction.; measurement; risk perception ability
- ISBN/ISSN: 0733-9364
- URL: http://doi.org/10.1061/JCEMD4.COENG-13783
- Abstract:
Unsafe behaviors may be aroused by inaccurate risk perception. Rather little is known about the measurement of risk perception ability in the construction industry. Based on the conception of risk perception ability, we proposed a measurement of risk perception ability, which conducted a questionnaire and a behavioral experiment. The specific measurement included an indicators system proposed to measure risk perception ability, which contained hazard identification degree, hazard identification accuracy, accuracy of the risk evaluation, deviation degree of the expected damage, deviation degree of the probability, and deviation degree of the risk evaluation. Based on the six indicators, the weighing values for each indicator were calculated, and a formula calculating risk perception ability (RPA) was proposed. Then, we applied the measurement to 327 construction professionals, which showed RPA differed from different construction professionals, and managers RPAwas significantly superior to workers (p = 0.000 < 0.05). The method can measure construction professionals RPA conveniently and easily, which filled the lack of research regarding RPA in construction. Measurement results can help to provide targeted safety training recommendations, which is beneficial to reducing workers unsafe behavior and accident rates.