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    A fuzzy-based approach to understanding barriers in implementing VR and AR for construction safety training
    (Emerald Group Publishing Ltd, 2025) Calik, Idil; Koc, Kerim; Mohandes, Saeed Reza; Ali, Ali Hassan; Ekmekcioglu, Omer; Kidd, Callum
    PurposeThis study aims to examine the interactions among the barriers impeding the use of virtual reality (VR) and augmented reality (AR) technologies for construction safety training and to investigate how these barriers affect the general safety management system. The study uses a hybrid fuzzy-based algorithm to offer a thorough and organised knowledge of these dynamics, thereby attaining this goal.Design/methodology/approachThis study employs a systematic literature review (SLR) approach combined with the Fuzzy Decision-Making Trial and Evaluation Laboratory (FDEMATEL) and Fuzzy Technique for Order of Preference by Similarity to Ideal Solution technique (FTOPSIS) to unravel the related relationships among the barriers and rank the components of the safety management system in terms of their importance levels.FindingsUsing the data collected from the experts in Hong Kong construction sector, the following observations were noted: (1) five barriers and seventeen sub-barriers were identified through an SLR, (2) Using the FDEMATEL technique, cost of implementation, adaptability, require-ments, standardization and compatibility were seen to be the most influential barriers within the corresponding clusters and (3) based on the employment of FTOPSIS technique, safety risk management was the most important component of safety management system in enhancing the adoption and effectiveness of VR/AR technologies for safety training in the construction industry.Practical implicationsFrom the findings derived from this research, stakeholders can develop targeted strategies to overcome challenges to the widespread adoption of immersive technologies, which is not only vital for enhancing worker safety but also for fostering innovation, improving efficiency and supporting the industry's digital transformation.Originality/valueThough some studies have focused on the examination of the barriers impeding the adoption of VR and AR technologies for construction safety training, the current body of literature lacks a thorough understanding of the interrelationships existing among these barriers. Moreover, the relationships between the barriers and the safety management system have not yet been touched on in the literature. Thus, this study fills these critical gaps by employing a hybrid fuzzy-based algorithm.
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    Integrating metaheuristic optimization algorithms with random forest to predict waste generation in construction and demolition projects
    (Elsevier, 2026) Awad, Ruba; Budayan, Cenk; Calik, Idil; Gurgun, Asli Pelin; Koc, Kerim
    The construction sector is a significant source of global waste, making accurate and proactive prediction of Construction and Demolition Waste (C&DW) essential for sustainable resource management and circular economy efforts. However, estimating C&DW at the project level remains a major challenge. This paper investigates whether C&DW prediction accuracy can be enhanced by integrating the Random Forest (RF) model with two metaheuristic optimization algorithms: the Archimedes Optimization Algorithm (AOA) and Grey Wolf Optimization (GWO). Based on data from 200 real-world projects in Palestine, the GWO-RF model achieved the highest predictive accuracy using only four input variables: project type, start date, building type, and number of floors. To ensure model transparency, Shapley Additive Explanations (SHAP) analysis confirmed that project type and the number of floors were the most influential parameters. This study thus provides a practical, robust, and highly accurate model to support effective waste management strategies in the construction industry.
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    Life Cycle Risk Management for Improving Labor Productivity in Construction Projects in Türkiye
    (Mdpi, 2025) Calik, Idil; Koc, Kerim; Sahin, Onur
    The construction industry, being labor-intensive, prioritizes productivity to boost project performance, yet struggles to achieve expected levels despite increased focus by scholars and practitioners. This lagging causes significant losses in time, cost, and quality performance of construction projects but also broader implications for resource efficiency and environmental impacts. As a remedy to the multifaceted issue, this study aims to identify and evaluate life cycle risks of productivity management in construction projects in T & uuml;rkiye. A comprehensive literature review identified risk factors affecting labor productivity, followed by a discussion session to finalize the decision framework, including life cycle phases of productivity management and risk factors in each phase. Then, the fuzzy analytical hierarchy (AHP) process revealed the most critical risk factors in each phase, followed by semi-structured interviews to reveal measures for addressing the most significant risks. The findings show that productivity management in construction projects contains nine phases. In addition, the most important factors were chiefly related to collaboration, information sharing, lack of supervision, work interruptions, and changes. Findings from semi-structured interviews emphasize regular employee training and open communication to enhance project outcomes, optimize workflows, and promote sustainability. The study's key contribution is introducing a life cycle approach to construction productivity management, a previously unexplored perspective. This provides an effective framework that can be implemented in construction projects to manage and improve labor productivity as a whole-life cycle approach.