Journal of Construction Engineering, Management & Innovation

Kerim Koc

Employees working on construction projects have a higher risk of experiencing occupational accidents compared to workers in other sectors. Newly employed workers, in particular, might face an occupational accident shortly after they start working due to not being able to notice risky environmental conditions. Despite existing studies in construction safety literature focusing on several output variables such as fatality, accident type or accident severity predictions, no studies have examined the short-term susceptibility of construction workers to occupational injuries. This study aims to develop a model to predict construction workers’ susceptibility to short-term occupational accidents using interpretable machine learning (ML) methods. Hence, the primary research objective is to identify construction workers who have high probability of experiencing an occupational accident shortly after their employment. In this respect, a national dataset of occupational accidents encountered in the construction industry in Turkey was collected and subjected to various pre-processing elements (data cleaning, data scaling, and data resampling) to prepare the data for prediction. At the processing step, Stochastic Gradient Boosting (SGB) algorithm was applied for the classification purpose. In the next step, Shapley Additive Explanations (SHAP) was used as an interpretable artificial intelligence algorithm to explain how, to what extent, and in which direction the input variables affect the prediction scheme, which is another distinguishing feature of the present study compared to past studies in the subject matter. Results show that the proposed SGB model is a powerful detector for the classification problem and salary of workers, past accident in the company, and number of workers in the company were the most influencing factors. Overall, this study contributes to practice by improving the safety conditions of the newly employed workers as well as minimizing their accident probability through intensified safety training. Given that contemporary safety management applications demand a new set of data-driven inputs, proposed model is expected to help industry professionals and safety managers apply more robust safety risk mitigation and/or prevention measures.

https://doi.org/10.31462/jcemi.2023.01001015

Hakan TIRATACI Hakan YAMAN

Time planning for the accurate estimation of construction duration is important to prevent construction delays and successfully complete projects on time. Although the main reasons for construction delays differ among developing countries, several factors related to project characteristics and clients contribute. In this study, interviews and observations were conducted with TOKI (Housing Development Administration of the Republic of Turkey), a major housing construction authority in Turkey, to explore construction delays. It was revealed that TOKI uses three factors to estimate total construction duration, which are the number of flats, type of drawings utilized during the tender stage, and nonworking days. Data analysis of the TOKI Projects Status Table, which lists detailed project information for 2800 completed TOKI projects, showed that most delays occurred in housing projects. Therefore, the construction delays for TOKI housing projects were investigated in this case study. The findings revealed that there is a wide construction duration gap between calculated construction durations using TOKI’s calculation method and durations indicated in official construction contracts between TOKI as a client and the awarded contractors. Therefore, it was emphasized that TOKI significantly shortened the construction duration, which ultimately resulted in delays for a considerable number of housing projects. These findings can be helpful for clients and project managers worldwide to mitigate construction delays. To effectively overcome construction delays in developing countries, suggestions are made for the need to develop accurate construction duration estimation models.

https://doi.org/10.31462/jcemi.2023.01016029

Birsu ECE KAYA İkbal ERBAŞ

Urban transformation projects are being implemented to make spatial arrangements and improvements in line with the changing needs of cities and citizens in the world and Turkey. In urban transformation projects, sustainability goals are essential in order to protect the integrity of cities and to meet the spatial, social and economic needs of the citizens in an environmentally sensitive, balanced and equitable manner. This study aims to analyze the effects of urban transformation practices on citizens, urban space and the environment by using sustainability indicators. For this purpose, the Sur Yapı Antalya Project in Santral District Urban Transformation Area of Antalya was analyzed through the items of the sustainability indicator set. The project was evaluated under eight main criteria, namely “community participation”, “economy and work”, “transport”, “pollution”, “energy”, “waste and resources”, “buildings and land use” and “wildlife and open spaces”. As a result of the study, it was concluded that the effects of the decisions taken and the practices implemented during the planning phase of the project and the ongoing construction process on physical, economic, social and environmental sustainability vary and affect its utilization. This study is expected to contribute to the research and practice by evaluating how the urban transformation project aims to improve the region’s physical conditions and offer a new urban space to the citizens.

https://doi.org/10.31462/jcemi.2023.01030047

Sabah Khodabocus Senem Seyis

The emerging modular construction sector has attained ample interest given the plethora of benefits compared to conventional construction. However, with incorrect execution and lack of early planning, exorbitant costs are witnessed. There is a lack of guidance to aid key decision-makers in integrating BIM and lean methods in the phases of modular construction. These tools and practices enable a team to work in full clarity involving all organizational levels. Hence, this study has as aim to portray the integrated usage of Building Information Modelling (BIM) and lean construction methods throughout the lifecycle of modular construction projects. The intended roadmap to be derived in the study shall allow decision-makers to acknowledge the corresponding BIM and Lean tools to be used at the correct stage of a modular project. As a generalized concept, the study aims shall aid early planning which will promise to achieve quality. In this scope, a systematic literature review was executed and validated with experts’ interactions for developing a roadmap. The studies found were analyzed in terms of case studies performed. This enabled grasping information on how different countries and project types integrated BIM and lean methods at every step of a modular project. Previous studies depicted projects integrating these concepts at the design stage, supply chain, or during module construction. However, this research considers the whole lifecycle, and the methodology integrates hands-on experiences from qualified industry experts. Therefore, the contributions of this research are as follows: (1) Directing team members towards early planning and all-inclusive collaboration, (2) informing key decision makers of lean and BIM tools to integrate at specific stages of modular projects, (3) showcasing awaited benefits upon integration of the proposed tools, and (4) mitigating cost overruns and witnessing value-adding activities throughout the project upon consulting the roadmap.

https://doi.org/10.31462/jcemi.2023.01048056

Aynur Kazaz gökçen arslan

Technological developments, the increase in the world population and rapid changes in customer needs have increased the competitive environment in the construction sector. The highly competitive environment has brought risk management to a much more critical position for construction companies. Construction projects are exposed to many risks due to their unique nature. Successful risk management requires a realistic assessment of these many and varied risks and the identification and implementation of appropriate strategies. Within the scope of the study, first of all, construction project risks were determined and grouped based on expert opinion and literature review. AHP method, which is one of the multi-criteria decision-making techniques, was used to prioritize risks. Strategies that can be taken against the identified risks were determined in line with expert opinions and Fuzzy TOPSIS technique was used to choose among the strategies that could be applied. It is thought that the obtained model can help decision makers in risk management in construction projects.

https://doi.org/10.31462/jcemi.2023.01057069