Abstracts – Browse Results
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Ahn, S and Lee, S (2015) Methodology for Creating Empirically Supported Agent-Based Simulation with Survey Data for Studying Group Behavior of Construction Workers. Journal of Construction Engineering and Management, 141(01).
Arroyo, P, Tommelein, I D and Ballard, G (2015) Comparing AHP and CBA as Decision Methods to Resolve the Choosing Problem in Detailed Design. Journal of Construction Engineering and Management, 141(01).
Borg, L and Song, H (2015) Quality Change and Implications for Productivity Development: Housing Construction in Sweden 1990–2010. Journal of Construction Engineering and Management, 141(01).
Caldas, C H, Kim, J, Haas, C T, Goodrum, P M and Zhang, D (2015) Method to Assess the Level of Implementation of Productivity Practices on Industrial Projects. Journal of Construction Engineering and Management, 141(01).
Castillo, G, Alarcón, L F and González, V A (2015) Implementing Lean Production in Copper Mining Development Projects: Case Study. Journal of Construction Engineering and Management, 141(01).
Goh, Y M (2015) Empirical Investigation of the Average Deployment Force of Personal Fall-Arrest Energy Absorbers. Journal of Construction Engineering and Management, 141(01).
Ha, S K, Jang, J G, Park, S H and Lee, H K (2015) Advanced Spray Multiple Layup Process for Quality Control of Sprayed FRP Composites Used to Retrofit Concrete Structures. Journal of Construction Engineering and Management, 141(01).
Hu, H and Zhu, Y (2015) Social Welfare–Based Concession Model for Build/Operate/Transfer Contracts. Journal of Construction Engineering and Management, 141(01).
Inayat, A, Melhem, H and Esmaeily, A (2015) Critical Success Factors in an Agency Construction Management Environment. Journal of Construction Engineering and Management, 141(01).
Matthews, J C and Stowe, R (2015) Critical Data Needs Associated with Asbestos Cement Pipe Renewal Methods. Journal of Construction Engineering and Management, 141(01).
Patel, D A and Jha, K N (2015) Neural Network Model for the Prediction of Safe Work Behavior in Construction Projects. Journal of Construction Engineering and Management, 141(01).
- Type: Journal Article
- Keywords: Behavior; Neural network; Prediction; Safety climate; Labor and personnel issues;
- ISBN/ISSN: 0733-9364
- URL: https://doi.org/10.1061/(ASCE)CO.1943-7862.0000922
- Abstract:
A model has been developed employing an artificial neural network (ANN) to predict the safe work behavior of employees using 10 safety climate constructs determined through literature review. The model utilizes safety climate constructs (determinants) as inputs and safe work behavior as an output. Two hundred twenty-two responses from several construction projects across India were collected through a questionnaire survey. A three-layer feed-forward back-propagation neural network (10-11-1) was appropriate in building this model which has been trained, validated, and tested with sufficient data sets. The model predicts the safe work behavior of employees reasonably well. In addition, a sensitivity analysis was carried out to study the impact of each construct on the safe work behavior of employees. As a result, safety climate constructs like supervisory environment, work pressure, employees’ involvement, personal appreciation of risk, and supportive environment were significantly associated with the safe work behavior of employees. This model has great potential in aiding contractors and clients in promoting safe work behavior and the efficient management of the safety of employees in construction projects.
Roofigari-Esfahan, N, Paez, A and N.Razavi, S (2015) Location-Aware Scheduling and Control of Linear Projects: Introducing Space-Time Float Prisms. Journal of Construction Engineering and Management, 141(01).
Younes, B, Bouferguène, A, Al-Hussein, M and Yu, H (2015) Overdue Invoice Management: Markov Chain Approach. Journal of Construction Engineering and Management, 141(01).