Neural Network Model for the Prediction of Safe Work Behavior in Construction Projects

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.