Journal of Construction Engineering, Management & Innovation

Saeed Raeisi Morteza Bagherpour

Effective claims management is essential in construction projects, particularly in the oil and gas sector, where disputes can lead to significant cost and schedule overruns. This study focuses on identifying and preventing claims in oil and gas piping construction projects—a critical yet underexplored area. A systematic methodology was employed, beginning with the identification of potential claims through expert consultation, followed by prioritization using a probability-impact analysis based on survey data collected from 70 industry professionals. The study then proposes practical preventive strategies derived from expert interviews and aligned with PMBOK risk response principles. Results indicate that delays in material delivery, design changes, and contractual ambiguities are among the most critical claims. The proposed strategies, including improved work breakdown structures, timely issuance of drawings, and enhanced communication protocols, can significantly reduce disputes and improve project performance. These findings provide actionable insights for project managers and contribute to the broader discourse on risk and claim management in complex industrial projects.

https://doi.org/10.31462/jcemi.2026.614

Elif Gürbüz Taştekin Umutcan Kılıç Semra Çomu

High rates of fatal and non-fatal occupational accidents worldwide have made construction safety a global concern. Despite the proven effectiveness of construction safety training in reducing these rates, current safety implementations often fail to enhance construction workers’ safety awareness and knowledge. Recently, virtual reality (VR) has been increasingly employed in safety training to enhance its effectiveness and contribute to occupational safety. While construction workers and engineers are usually the intended target audience for safety training, students are frequently used as surrogates during the development of training tools. However, the appropriateness of this practice has not been thoroughly investigated in the literature. This study utilizes the V-SAFE v.2 training tool in the experiments to investigate this phenomenon by comparing the performances of students, construction workers, and engineers. The paper-based test scores of students, construction workers, and engineers before and after receiving safety training in the virtual environment are analyzed using appropriate statistical analysis approaches, including paired T-test, Wilcoxon signed-rank test, and two-factor mixed ANOVA. Results indicate that V-SAFE v.2 has significantly improved the learning outcomes of all groups. Additionally, the study reveals that students can serve as surrogates for construction workers during the development of virtual safety training tools. However, students’ performances significantly differ from those of engineers, indicating they are not suitable surrogates for this subject group.

https://doi.org/10.31462/jcemi.2026.683

Muhammed Yusuf Kahveci Ali Sercan Kesten

The transition to electric mobility requires charging systems that are not only physically available but also perceived as reliable, convenient, and compatible with everyday travel. This exploratory study combines survey evidence from 94 respondents with a province- and NUTS-2-level assessment of electric vehicle (EV) charging infrastructure in Türkiye. Four perception dimensions—charging station availability, home charging availability, charging time, and battery range—were examined using descriptive statistics, reliability analysis, one-way analysis of variance, and ordered logistic regression. Respondents assigned high importance to all four dimensions, with home charging availability receiving the highest mean score. ANOVA results showed that statistically significant differences were concentrated mainly in home charging availability, charging station availability, and charging time, particularly across marital-status, employment-status, and occupational groups. Charging station availability showed the strongest positive association with near-term vehicle purchase readiness and approached the conventional 5% significance threshold (β = 0.588, p = 0.051); however, the overall model was not significant, and the outcome was a general vehicle-purchase measure rather than a direct EV-purchase intention item. The spatial assessment showed that charging provision was concentrated in metropolitan and western regions and was not distributed proportionally to regional population or land area. Taken together, the findings support user-centred, phased, and equity-sensitive infrastructure planning, while the regression evidence is interpreted as exploratory rather than as proof of EV-adoption determinants.

https://doi.org/10.31462/jcemi.2026.724

Ferdinand Senam Hassan Schalk Grobbelaar

The global construction industry is under pressure to reduce its carbon emissions, and mass timber has emerged as a promising alternative to conventional building materials such as concrete and steel. While hundreds of multi-storey timber buildings have been constructed worldwide, there is limited evidence of corresponding growth in Africa. This study investigates the factors influencing design professionals' behavioural intention to adopt mass timber in the South African construction industry. A conceptual model was developed by extending the Unified Theory of Acceptance and Use of Technology (UTAUT) with three context-specific constructs: perceived environmental motivation, personal resistance, and perceived cost. Data were collected from 92 architects and structural engineers through a structured survey and analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM). Iterative measurement model assessment led to the removal of social influence due to indicator reliability and discriminant validity failures, the merger of effort expectancy and facilitating conditions into a single construct termed execution capability, and the reduction of the instrument from 43 to 33 indicators. The final structural model explained 66.2% of the variance in behavioural intention and demonstrated high out-of-sample predictive power. Three predictors were statistically significant: perceived environmental motivation was the strongest predictor, followed by execution capability and performance expectancy. Personal resistance and perceived cost were not significant. The findings suggest that environmental credentials, rather than technical performance or cost, are the primary driver of intention to adopt mass timber among South African design professionals, and that professionals do not distinguish between the ease of using mass timber and the infrastructural conditions enabling its use. The study contributes to the limited empirical literature on mass timber adoption in Africa and demonstrates the need for context-specific modifications when applying UTAUT to construction material adoption.

https://doi.org/10.31462/jcemi.2026.728

İlker Baki Alkan Hasan Basri Basaga

Climate change has increased the need for effective educational approaches that can promote climate-related awareness and environmentally responsible behaviors. This study investigates the effects of a passive 360-degree virtual reality educational intervention on climate change awareness and operational water consumption in a real industrial setting. The study was conducted with 17 cafeteria workers at an operating factory in Türkiye. A VR-based educational video consisting of seven scenarios addressing climate change impacts, water scarcity, and water-saving practices was developed using Unity and experienced by the participants using an Oculus Quest 2 headset. Climate change awareness was assessed using a validated 5-point Likert scale administered one month before and one month after the VR intervention. In addition, the cafeteria’s total hot and cold water consumption was monitored for one week before and one week after the intervention. The mean climate change awareness score increased from 39.24 (SD = 4.67) before the intervention to 41.65 (SD = 3.08) after the intervention, with a statistically significant increase confirmed by both a paired-samples t-test and a non-parametric Wilcoxon Signed-Rank test (p = 0.022). Weekly operational water consumption decreased from 104.2 m³ before the intervention to 97.9 m³ after the intervention, corresponding to a reduction of 6.3 m³ (6.05%), which was confirmed to be statistically significant using a pairedsamples t-test (p = 0.042). These findings indicate that passive VR-based climate change education can increase climate change awareness and is associated with reduced operational water consumption in a real industrial cafeteria setting.

https://doi.org/10.31462/jcemi.2026.745

Antonio J. Sánchez-Garrido Lorena Yepes-Bellver Víctor Yepes

The construction sector plays a key role in achieving global sustainability targets, making extending the service life of existing buildings a priority. In this context, micropile underpinning is widely used to restore the structural performance of foundations affected by severe geotechnical conditions. However, current structural and geotechnical standards provide limited and fragmented guidance for the analytical verification of load transfer mechanisms between micropiles and existing foundations. This study proposes a practical analytical framework to evaluate these connection interfaces through a two-interface decomposition of the load-transfer mechanism, by considering two governing mechanisms: (i) bond behavior between the steel casing and grout, and (ii) shear transfer between the grout and the existing concrete footing. The methodology is analytically verified through a full-scale underpinning project involving 158 micropiles, combining normative formulations, empirical approaches, and standardized pull-out test data. Results from the analyzed case study indicate that relying solely on the natural bond between smooth steel casings and conventional concrete joints results in a significant reduction in load transfer capacity, limiting it to approximately 15–20% of the theoretical structural capacity. In contrast, the use of welded corrugated connectors and high-performance expansive mortars significantly enhances interface capacity, allowing safe load transfer within practical geometric constraints. The study also provides a mechanical interpretation of how these solutions modify the internal strut-and-tie mechanism, improving stress distribution and reducing the risk of premature failure. These findings also highlight the potential of integrating the proposed analytical framework into digital design environments (e.g., BIM-based workflows), where interface-level verification could be incorporated as parametric checks to support decision-making in foundation retrofitting projects. The proposed framework offers a rational and practical basis for the design of micropile underpinning connections, contributing to more efficient and sustainable foundation retrofit solutions.

https://doi.org/10.31462/jcemi.2026.725

Bayram Ali TEMEL

Rockfall mitigation projects involve high occupational health and safety (OHS) risks due to steep topography, hardto-access work zones, rope-access operations, and environmental uncertainties. In such projects, conventional supervision and communication practices may be limited by blind spots, restricted visibility, and difficult terrain conditions. This study develops and field-evaluates an unmanned aerial vehicle (UAV)-based supervision framework to support OHS planning and operational coordination in rope-access operations carried out within rockfall mitigation projects. A descriptive and exploratory field-based research design was adopted. Questionnaire data were collected from 128 Rope Access Technicians (RATs) working in 16 active rockfall mitigation projects in different regions of Türkiye. The survey examined participants’ professional profiles, accident experiences, safety checks, communication and supervision practices, UAV awareness, UAV-related training status, and perceptions regarding UAV-supported monitoring. Field observations were also used to document the physical and operational characteristics of rope-access worksites. Based on the survey findings and field observations, a UAV-based supervision framework was structured around real-time visual monitoring, blind-spot reduction, communication support, hazard observation, and operational coordination. The proposed framework was then examined through a single-site pilot implementation in an active rockfall mitigation project. The findings indicate that RATs generally perceive UAV-supported monitoring and communication as potentially useful for improving situational awareness and supporting field coordination. The pilot implementation provided observational evidence that UAVs can assist supervisors by extending visual access to hardto-observe work areas. However, the study does not claim to demonstrate quantitative reductions in accident rates, work duration, or costs. The proposed UAV-based framework should therefore be considered a complementary decision-support and supervision tool rather than a replacement for trained rope-access supervision.

https://doi.org/10.31462/jcemi.2026.715

Gozde Basak OZTURK Fatih Soygazi Gamze Gulsun Gazi

Traditional scientometric analysis methods primarily rely on binary keyword associations, which limits the ability to capture complex research structures. This study proposes a multi-association rule-based method (MAR) that enables the extraction of higher-order (n-ary) associations among keywords to address the stated limitation. The method integrates the Apriori algorithm with knowledge graph visualization to quantitatively analyse multi-keyword associations. The proposed method is applied to the Building Information Modelling (BIM) research domain. The bibliometric data, comprising 12,185 publications, is retrieved from the Scopus database following a systematic refinement of the initial search results to the architecture, engineering, construction, and operation (AECO)-relevant literature. The results demonstrate that the MAR method effectively identifies complex research patterns. The framework advances traditional scientometric tools by enabling the identification of multi-keyword semantic associations with quantified strength metrics (support, confidence, lift). Emerging trends revealed by the regression analysis include the convergence of BIM with generative artificial intelligence, real-time data integration, explainable AI, and human-centric approaches. The findings provide a scalable and analytical approach for identifying interdisciplinary research trends and gaps. The proposed method enables a deeper understanding of complex knowledge structures while supporting strategic decision-making and technology adoption

https://doi.org/10.31462/jcemi.2026.710