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PurposeConstruction work involves high-risk activities and requires intense focus and physical exertion. Accordingly, working conditions at construction sites contribute to physical fatigue and mental stress in workers, which is the primary cause of accidents. This study aims to examine the relation between construction accidents and physiological variables, indicative of physical fatigue and mental stress.Design/methodology/approachFour different real-time physiological values of the construction workers were measured including blood sugar level (BSL), electrodermal activity (EDA), heart rate (HR) and skin temperature (ST). The data were collected from 21 different workers during the summer and winter seasons. Both seasonal and hourly correlation analyses were performed between the construction accidents and the four physiological variables gathered.FindingsThe analysis results demonstrate that BSL values of the workers are correlated inversely with construction accidents taking place before lunch break. In addition, except BSL a significant seasonal association between the physiological variables and construction accidents was found.Originality/valueIt is disclosed that variations in physiological risk factors at certain working periods pose a high risk for construction workers. Therefore, efficient work-cycle rests can be arranged to provide frequent but short breaks for workers to overcome such issues. Besides, an early warning system could be introduced to monitor the real-time physiological values of the workers.

As occupational accidents usually occur due to unsafe human behaviours in the construction industry, safety training is inevitably necessary for site personnel. On construction sites, various training methods including traditional and innovative ones, have been adopted to prevent accidents. In recent years, virtual safety training has been more prevalent because of providing highly engaging practice in a risk-free environment. Although these training tools have innumerable advantages in providing safety knowledge and awareness, they can be further improved. This study introduces a virtual safety training tool, V-SAFE.v2, to provide a more reliable and effective safety training for high-risk construction works. V-SAFE.v2 consists of three main modules; i) Training Module, ii) Testing Module 1, and iii) Testing Module 2. These modules are generated firstly to provide safety training for scaffolding and formwork activities and then to evaluate the safety performance of the trainees. An experiment was conducted with fifteen construction workers and ten engineers to measure the effectiveness of the training tool. The findings showed that V-SAFE.v2 is a reliable safety training tool for high-risk construction tasks as it supports collaboration, provides individual feedback, and repeatable practice. Also, the participants stated that V-SAFE.v2 has a great potential to reduce the falling from height accidents in the construction workplaces.

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Quality problems are crucial in construction projects since poor quality might lead to delays, low productivity, and cost overruns. In case preventive actions are absent, a lack of quality results in a chain of problems. As a solution, this study deals with non-conformities proactively by adopting an AI-based predictive model approach. The main objective of this study is to provide an automated solution structured on the data recording system for the adverse impacts of construction quality failures. For this purpose, we collected 2527 non-conformance reports from 59 diverse construction projects to develop a predictive model regarding the cost impact of the quality problems. The first of three stages forming the backbone of the study determines crucial attributes linked to quality problems through a literature survey and the Delphi method. Secondly, the Analytical Hierarchy Process (AHP) and a Genetic Algorithm (GA) were used to determine the attribute weights. In the final stage, we developed models to predict the cost impacts of non-conformities, using Case-based Reasoning (CBR). We made a comparison between the developed models to select the most precise one. The results show that the performance of CBR-GA using an automated weighting model is slightly better than CBR-AHP based on a subjective weighting system, whereas the case is the opposite in standard deviation in forecasting the cost outcome of the quality failures. Using both automated and expert systems, the study forecasts the cost impact of failures and reveals the factors linked to poor record-keeping. Ultimately, we concluded that the outcome of non-conformities can be predicted and prevented using past events via the developed AI-based predictive model.

PurposeCost overruns remain a persistent problem in the construction industry. Although various cost management strategies have been implemented, innovative approaches are still required. Therefore, the authors attempted to introduce and test a new cost management strategy for the construction industry.Design/methodology/approachZero-based budgeting (ZBB) is one such method whose effectiveness has been proven in different industries over many years. Therefore, the authors initially developed two different frameworks related to the integration of ZBB into a multinational construction contractor and the application process of ZBB for a construction project in this study. Then, the effectiveness and feasibility of the proposed frameworks are tested via an actual field study in a mega construction project.FindingsThe results show savings of 0.81% of the total project budget and 4.74% of the focused cost items by following the ZBB framework compared to the traditionally estimated project budget. The feedback received from the employees in the construction company shows that ZBB could be efficiently implemented during ongoing construction projects.Research limitations/implicationsThe authors believe that implementing new cost management strategies such as ZBB will open doors to deal with the complex cost overrun issues and improve construction cost performances.Originality/valueThis manuscript is the first actual application of the ZBB cost management approach in the construction industry.