Journal of Civil Engineering and Management
type: channel
description: The Journal of Civil Engineering and Management publishes original research that seeks to improve civil engineering competency, efficiency and productivity in world markets. More information ...
publisher: Vilnius Gediminas Technical University
language: en
publication name: Journal of Civil Engineering and Management
issn: 1392-3730
copyright: Copyright © 2021 The Author(s). Published by Vilnius Gediminas Technical University. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
items: When capital meets control: governance dilemmas of financial investors in PPP projects
items: Hypothesis-validated construction accident analysis and framework for potential multi-sensor fusion with 360° camera and LiDAR
items: Construction waste governance in China: policy analysis and roadmap for circular economy transition
items: Investigating key factors in the digitalization of value engineering in the Malaysian construction industry
items: Advancing the circular economy: a BIM and lean construction dynamic framework for pre-construction phases
items: Utilization of Public-Private Partnerships (PPP) in the development of smart infrastructure in developing nations: empirical findings from Sri Lanka
items: Ontology development using language model-based Named Entity Recognition for integrated construction information
items: Integrating Monte Carlo simulation and Digital Twin technology for advanced risk management in fast-track infrastructure projects
items: ESG, open innovation, and firm performance in construction firms: exploring the mediating role of digital transformation
items: Automated progress monitoring in pipeline construction: a systematic review
items: Selection of optimal construction service provider: a combined decision framework with hyperbolic fuzzy data
items: Integrating AI-enhanced and conventional market selection approaches for the construction industry: insights from Indian firms
items: Innovation in construction: assessing the role of transformational leadership and knowledge governance
items: Scheduling the production of prefabrication construction supply chains considering variable delivery times
items: Post-pandemic building resilience: Building Information Modeling and green building integration
items: An intelligent construction system based on digital twin and foundation model optimization
items: Transforming railway transportation: the role of emerging technologies in efficiency, safety, and sustainability
items: Physics-informed neural network–integrated point cloud decimation and 3D mesh modeling for thermo-mechanical simulation of rail fasteners in digital twin systems
items: Recyclability and environmental impact of typical solid waste materials (rubber, RAP, SS) in asphalt mixtures: a state-of-the-art review
items: Evaluating the role of unmanned aerial vehicles to enhance construction project productivity
items: Overview and analysis of safety management in prefabricated construction (2012–2022)
items: Exploring the technology-organization-environment configurations to enhance stakeholder collaboration in the off-site construction projects
items: Exploring the causes of contract disputes and their social network relationships in the megaprojects: a case of Jinan Airport Project
items: The impact of environmental turbulence on construction enterprise performance: unveiling the systemic response mechanisms
items: Influence of institutional isomorphism on unethical pro-organizational behavior of construction teams based on the mediating effect of organizational routines
items: Factors influencing sustainable construction in Egypt
items: Dynamic risk assessment of international engineering projects from the life cycle perspective
items: YOLOv11n-CDL: accurate and lightweight pavement defect detection via enhanced multi-scale attention and feature fusion
items: Determining safety-related critical success factors in petrochemical projects through an extensive fuzzy risk assessment approach
items: An integrated vision-based dynamic collision risk assessment framework of workers and mobile machinery on construction site

When capital meets control: governance dilemmas of financial investors in PPP projects
type: item
description: While financial investors typically provide substantial share of capital in Public Private Partnership (PPP) Projects, they frequently lack meaningful operational control, leaving them vulnerable to opportunism from both government entities and contractors (i.e., industrial investors). This study investigates these unique governance challenges through a dual trajectory approach: first, by developing a comprehensive PPP governance theoretical model specifically tailored to financial investors’ needs, and second, by empirically validating this model through an in-depth case analysis of a financial investor’s innovative governance practices. The research makes three significant contributions to the field: First, it reconceptualizes financial investors as distinct stakeholders with specialized governance requirements in PPP ecosystems. Second, it advances a holistic theoretical model comprising 19 critical governance elements across institutional, organizational, contractual, and managerial dimensions. Third, it derives four practical, evidence-based strategies for maintaining control while preserving partnership viability: 1) implementing contractor profit-sharing mechanisms to align incentives, 2) developing integrated risk-transfer structures, 3) establishing joint government-contractor oversight systems, and 4) creating debt service reserve funds from construction margins to mitigate government payment delays. These findings offer both theoretical insights and actionable solutions for improving financial investor protection in PPP arrangements.
subject: Articles
  topic: section
subject: Public-Private Partnership (PPP)
  topic: keywords
subject: project governance
  topic: keywords
subject: financial investor
  topic: keywords
subject: opportunistic behavior
  topic: keywords
subject: stakeholder
  topic: keywords
subject: risk
  topic: keywords
subject: project benefits
  topic: keywords
creator: Chuan Chen
creator: Baoheng Chen
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-06-04
publication date: 2026-06-04
starting page: 670
ending page: 683
doi: 10.3846/jcem.2026.27151

Hypothesis-validated construction accident analysis and framework for potential multi-sensor fusion with 360° camera and LiDAR
type: item
description: Construction sites are among the most hazardous work environments, with frequent accidents such as falls, entrapments, and collisions. Traditional single-sensor detection systems suffer from occlusions, poor lighting, and limited depth perception, reducing reliability in complex conditions. This study addresses these limitations by proposing a realtime multi-sensor fusion framework integrating a 360° camera and LiDAR. A three-year construction accident dataset was analyzed, and Chi-squared tests and ANOVA (p < 0.05) confirmed the statistically significant superiority of the fusion approach over single-sensor systems. Deep learning techniques were applied to enhance real-time detection and prevention capabilities. The results demonstrate that sensor fusion substantially improves detection accuracy, especially in high-risk scenarios such as falls and collisions. This study provides a comprehensive statistical analysis based on national incident records and proposes an AI-driven monitoring framework. The findings offer strong empirical support for multi-sensor fusion as a foundation for next-generation construction site safety systems.
subject: Articles
  topic: section
subject: construction safety
  topic: keywords
subject: multi-sensor fusion
  topic: keywords
subject: 360° camera
  topic: keywords
subject: LiDAR-based detection
  topic: keywords
subject: hypothesis testing
  topic: keywords
subject: chi-squared test
  topic: keywords
creator: Jaemin Jeong
creator: Kangwon Lee
creator: Daeyoung Gil
creator: Sejun Jang
creator: Youngjae Song
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-06-02
publication date: 2026-06-02
starting page: 655
ending page: 669
doi: 10.3846/jcem.2026.27071

Construction waste governance in China: policy analysis and roadmap for circular economy transition
type: item
description: Despite the proliferation of circular economy (CE) policies targeting construction and demolition waste – the largest urban solid waste stream in China – a critical policy-practice gap persists between regulatory frameworks and on-site recycling practices. Existing literature often lacks a systematic diagnosis of the institutional and behavioral barriers hindering this sector’s transition to circularity. Drawing on policy design theory, this study formulates an integrated analytical framework that synthesizes policy instrument analysis with stakeholder-centered perspectives to address this research gap. By integrating a mixed-methods content analysis of 925 policy documents with qualitative insights from 23 expert interviews, this study identifies six systemic deficiencies in China’s CE transition in the construction sector: institutional fragmentation, policy instrument imbalance, limited upstream stakeholder engagement, regional disparities, insufficient standardization, and inadequate economic incentives. To transcend these barriers, the study then proposes a novel dynamic transformation roadmap. Unlike static solutions, this framework articulates a phased evolution (short-, medium-, and long-term) that guides the transition from rigid administrative control to a market-driven, lifecycle-integrated ecosystem.
subject: Articles
  topic: section
subject: construction and demolition waste
  topic: keywords
subject: policy analysis
  topic: keywords
subject: policy instrument
  topic: keywords
subject: stakeholder
  topic: keywords
subject: circular economy
  topic: keywords
subject: China
  topic: keywords
creator: Kaiyi Li
creator: Kun Wang
creator: Hafez Bin Salleh
creator: Yaying Chen
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-06-02
publication date: 2026-06-02
starting page: 635
ending page: 654
doi: 10.3846/jcem.2026.26550

Investigating key factors in the digitalization of value engineering in the Malaysian construction industry
type: item
description: Value Engineering (VE) is widely recognized for enhancing value and minimizing unnecessary costs in construction projects. As the industry moves toward digital transformation, integrating digital tools into the VE process offers new opportunities to improve efficiency, collaboration, and decision-making. This study aims to identify and evaluate the critical factors influencing the digitalization of VE in the Malaysian construction industry and to propose a validated conceptual framework tailored to its specific context. A quantitative approach was employed, using data from 199 Malaysian construction professionals and analyzed through Structural Equation Modelling (SEM). The confirmatory factor analysis revealed high factor loadings (≥ 0.8) for key enablers such as real-time information access, data validation, digital workflow integration, operational scalability, regulatory compliance, decision-support systems, and long-term implementation support, including training and system maintenance. In contrast, lower loadings (< 0.7) for constructs like alternative evaluation and return on investment suggest a declining emphasis on traditional costcentric perspectives. The findings demonstrate that digitalizing VE can lead to enhanced project value, cost efficiency, and process automation within the Malaysian construction sector. The study introduces a comprehensive, phase-based conceptual framework that integrates digital technologies with conventional VE practices, offering actionable insights for project managers, engineers, and policymakers seeking to adopt and scale digital VE in Malaysia.
subject: Articles
  topic: section
subject: value engineering
  topic: keywords
subject: digitalization
  topic: keywords
subject: residential buildings
  topic: keywords
subject: functional analysis
  topic: keywords
subject: structural equation modelling
  topic: keywords
creator: Abdul Mateen Khan
creator: Wesam Salah Alaloul
creator: Khalid Mhmoud Alzubi
creator: Muhammad Ali Musarat
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-05-29
publication date: 2026-05-29
starting page: 605
ending page: 634
doi: 10.3846/jcem.2026.25855

Advancing the circular economy: a BIM and lean construction dynamic framework for pre-construction phases
type: item
description: The execution of construction technology projects generates substantial construction waste, both site-based and non-site-based, posing significant environmental and economic challenges worldwide. This paper explores a proactive approach to minimizing construction waste by controlling its causes during the pre-construction phase by integrating Building Information Modeling (BIM) and Lean Construction principles. Key pre-construction activities such as cost estimation, scheduling, constructability reviews, value engineering, procurement, and contracting are analyzed for their potential to reduce waste. Two scenarios - Existing Waste Management Strategies and Waste-Effective Site Management Practices are assessed using quantitative metrics and system dynamics modeling. The proposed technique employs eight causal loop diagrams, reflecting expert insights into waste reduction strategies, and is implemented using AnyLogic software with a stock-flow system dynamics model. Validation is achieved through a real-world case study, demonstrating the technique’s applicability and effectiveness in minimizing construction waste during the pre-construction phase. The findings highlight the dynamic buildup of critical variables influencing waste generation and provide a framework for evaluating and implementing optimal waste reduction strategies. This research underscores the potential of BIM and Lean Construction to drive sustainable waste management practices in construction technology projects, contributing to enhanced efficiency and environmental stewardship.
subject: Articles
  topic: section
subject: sustainable pre-construction phase
  topic: keywords
subject: construction waste
  topic: keywords
subject: lean construction and BIM
  topic: keywords
subject: system dynamics
  topic: keywords
subject: sustainability
  topic: keywords
creator: Ahmed Nouh Meshref
creator: ELsayed Abdel Fattah Ahmed Elkasaby
creator: Ahmed Abdel Kader Mohamed Farid
creator: Haytham Elmousalami
creator: Abdulaziz Alotaibi
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-05-21
publication date: 2026-05-21
starting page: 583
ending page: 604
doi: 10.3846/jcem.2026.26828

Utilization of Public-Private Partnerships (PPP) in the development of smart infrastructure in developing nations: empirical findings from Sri Lanka
type: item
description: Managing cities has become more complex recently with rapid urbanization triggering serious concerns in areas including quality of life, environment, safety, health and access to reliable infrastructure and high-quality services. Smart infrastructure (SI) development helps to address such concerns and meet societal aspirations. However, increasing development costs and risks in developing SI, have prompted a wider adoption of public-private partnerships (PPPs). Thus, this research study aims to determine and assess the major barriers to implementing PPPs for SI developments in Sri Lanka (SL), a developing country in South Asia, and to provide effective strategies for mitigating those barriers. Ten expert-interviews and an empirical questionnaire survey followed a systematic and extensive literature review to achieve this aim. Lack of expertise and certain public-related barriers such as citizens’ reluctance to accept private sector participation and unawareness on the perceived advantages from PPP were identified as major barriers in SL. Among the mitigation strategies, creating awareness and capacity-building of stakeholders was discerned as a significant strategy. Quantifying each barrier’s influence, interdependence and providing effective strategies for overcoming the barriers are described herein, leading to the findings that construction industry practitioners and policymakers could adopt to develop SI in SL more smoothly and efficiently.
subject: Articles
  topic: section
subject: Public-Private Partnerships (PPPs)
  topic: keywords
subject: smart infrastructure
  topic: keywords
subject: barriers
  topic: keywords
subject: developing nations
  topic: keywords
subject: Sri Lanka
  topic: keywords
creator: Daniel W. M. Chan
creator: Nimesha Sahani Jayasena
creator: Abdullahi Saka
creator: Mohan M. Kumaraswamy
creator: Sakibu Seidu
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-05-19
publication date: 2026-05-19
starting page: 563
ending page: 582
doi: 10.3846/jcem.2026.24104

Ontology development using language model-based Named Entity Recognition for integrated construction information
type: item
description: Named Entity Recognition (NER) is crucial for building knowledge bases and facilitating semantic search in the construction industry. While conventional NER models can identify general entities such as spatial and organizational information, extracting domain-specific entities, like materials and dimensions from construction-related texts –particularly in Bill of Quantities (BoQ) and Building Information Modeling (BIM) parameters – remains challenging extensive manual annotation. Key entity categories were defined, and datasets from four BoQ and two BIM sources were annotated to establish ground truth labels. A semi-automated labelling process was introduced to streamline annotation and improve training efficiency. Experimental results demonstrate that the proposed framework reduces annotation time by nearly threefold compared to manual processes. This study developed a BERT-based NER model achieving F1 scores ranging from 0.81 to 0.97, with higher performance for well-defined construction parameters (name, material, size, thickness, diameter, length, type: 0.95–0.97) compared to miscellaneous text entities (0.81). Despite extensive research in construction NLP, existing approaches fail to address the integration challenges between heterogeneous BIM-BoQ data formats and lack domain-specific entity recognition capabilities. The extracted entities are aligned with standardized formats using semantic text similarity techniques. This ontology-based integration enhances data consistency, interoperability, and retrieval accuracy, improving semantic alignment while minimizing discrepancies from heterogeneous terminology.
subject: Articles
  topic: section
subject: Large Language Models (LLM)
  topic: keywords
subject: Natural Language Processing (NLP)
  topic: keywords
subject: Named Entity Recognition (NER)
  topic: keywords
subject: deep learning
  topic: keywords
subject: Building Information Modeling (BIM)
  topic: keywords
subject: construction data integration
  topic: keywords
subject: ontology development
  topic: keywords
subject: data standardization
  topic: keywords
creator: Goeun Choi
creator: Soonwook Kwon
creator: Jinwoo Song
creator: Ali Akbar
creator: Jung-taek Hong
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-05-13
publication date: 2026-05-13
starting page: 548
ending page: 562
doi: 10.3846/jcem.2026.26519

Integrating Monte Carlo simulation and Digital Twin technology for advanced risk management in fast-track infrastructure projects
type: item
description: Fast-tracked infrastructure projects are prone to unforeseen factors that can disrupt commissioning schedules, due to quicker timelines, concurrent work, and changing site conditions. Existing risk analysis techniques have very limited flexibility to keep pace with real-time changes and do not sufficiently address the dynamic nature of interdependent activities within the project. The study aims to bridge this gap by formulating an integrated risk management mechanism using Monte Carlo Simulation (MCS) and a Digital Twin (DT), along with a tailored optimization module. The framework describes the risks associated with multiple work package overlaps while calibrating performance forecasts via DT’s feedback loop. MCS is used to simulate uncertainty and monitor cost-time impacts, while the optimization module helps to find the least detrimental overlap arrangement. Continuous field data sync with the simulation model enables proactive, data-driven decisions that improve situational awareness in the DT environment. Real project conditions show this MCS/DT approach improves prediction accuracy, reduces risk, and aids change during execution. The proposed framework serves as a pragmatic, adaptive risk management tool for fast-track projects while enhancing the integrity and resilience of the parent project as a whole.
subject: Articles
  topic: section
subject: Monte Carlo simulation
  topic: keywords
subject: Digital Twin technology
  topic: keywords
subject: overlapping risks
  topic: keywords
subject: infrastructure
  topic: keywords
subject: economics
  topic: keywords
creator: Yazhini Selvaraj
creator: Suresh Kumar Paramasivam
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-05-13
publication date: 2026-05-13
starting page: 534
ending page: 547
doi: 10.3846/jcem.2026.26549

ESG, open innovation, and firm performance in construction firms: exploring the mediating role of digital transformation
type: item
description: The construction industry faces growing pressure to reconcile financial performance with Environmental, Social, and Governance (ESG) commitments and open innovation strategies. Although ESG and open innovation are recognized as drivers of long-term corporate value, their impact mechanisms on firm performance, particularly the mediating role of digital transformation and the moderating role of financing constraints, remain insufficiently understood. This study addresses this gap by empirically analyzing Chinese listed construction firms from 2013 to 2021. Using multiple regression, bootstrap mediation, and moderation analysis, we examine how ESG performance and open innovation affect firm performance, and how digital transformation and financing constraints shape these relationships. The results reveal that both ESG performance and open innovation negatively affect firm performance in the short term, while open innovation improves ESG performance. Digital transformation partially mediates the relationships between ESG performance, open innovation, and firm performance. Financing constraints strengthen the positive effect of ESG on digital transformation and weaken the negative effect of open innovation on firm performance. Notably, all these relationships are significant only in state-owned enterprises, not in nonstate-owned enterprises. These findings illuminate the complex interplay among ESG, open innovation, digital transformation, and financing constraints, providing actionable implications for construction enterprise.
subject: Articles
  topic: section
subject: ESG
  topic: keywords
subject: open innovation
  topic: keywords
subject: digital transformation
  topic: keywords
subject: financing constraints
  topic: keywords
subject: firm performance
  topic: keywords
creator: Yong-Mei Ding
creator: Ying-Tao Zheng
creator: Feng Liu
creator: Yung Po Tsang
creator: Sheng-Hua Xiong
creator: Zhen-Song Chen
creator: Mirosław J. Skibniewski
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-05-13
publication date: 2026-05-13
starting page: 513
ending page: 533
doi: 10.3846/jcem.2026.26552

Automated progress monitoring in pipeline construction: a systematic review
type: item
description: Automated progress monitoring for pipeline construction is an evolving research domain among researchers which can provide effective visualisation and control of related projects. Although automation has been widely reviewed in building construction, a focused review on pipeline construction is lacking despite unique challenges and a growing need for automated monitoring. Hence, a systematic review of available methodologies and technologies was necessary to assess the achievement level of automation attained in progress monitoring practice in pipeline construction. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement, relevant studies in the area were identified by using five databases: Scopus, Web of Science, ScienceDirect, American Society of Civil Engineers, and Emerald. Keyword analysis was performed by developing a keyword network, and descriptive statistics were provided. The review examines a wide range of technologies and methods for automated progress monitoring, with a focus on data acquisition tools, monitoring techniques, and their integration within unnecessary article pipeline construction scenarios. A technological process overview was developed to outline the complete monitoring workflow, while a conceptual visual representation illustrated the potential impact of tools selection and integration strategies on successful project completion, and its broader impact on sustainability and economy.
subject: Articles
  topic: section
subject: pipeline construction
  topic: keywords
subject: MEP
  topic: keywords
subject: automated progress monitoring
  topic: keywords
subject: BIM
  topic: keywords
subject: data acquisition tools
  topic: keywords
subject: integration technologies
  topic: keywords
creator: Muhammad Hassaan Farooq Khan
creator: Wesam Salah Alaloul
creator: Muhammad Ali Musarat
creator: Abdul Hannan Qureshi
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-05-11
publication date: 2026-05-11
starting page: 489
ending page: 512
doi: 10.3846/jcem.2025.24800

Selection of optimal construction service provider: a combined decision framework with hyperbolic fuzzy data
type: item
description: This study introduces an integrated decision-making framework for Construction Service Provider (CSP) selection, addressing limitations in traditional methods that prioritize cost over quality and holistic evaluation. The framework integrates “Hyperbolic Fuzzy Sets (HYFS)” to capture uncertainties in expert opinions, a variance method to weigh expert reliability, the “Logarithmic Percentage Change-driven Objective Weighting (LOPCOW)” method to determine criterion weights, and the “Weighted Aggregated Sum Product Assessment (WASPAS)” algorithm to rank CSPs. A case study involving five construction companies and fifteen criteria was conducted to validate the proposed framework. The framework proposed in the study is able to effectively rank the CSPs, demonstrating practical utility in selecting an optimal CSP considering both qualitative and quantitative factors. Sensitivity analysis showed the framework is robust to changes in criterion weights. It is to be noted that, “Experience”, “Quality of work”, and “Technology and Innovation” emerged as the top three categories of criterions influencing the selection process. The study contributes to the literature by introducing usage of HYFS to CSP selection problem, explicit computation of expert weights based on variance, LOPCOW for criterion weights, and an integrated HYFS-Variance-LOPCOW-WASPAS framework. The study offers a practical tool for stakeholders to move beyond cost-centric bidding, promoting fairness, efficiency, and accountability in project selection and various other decision-making contexts.
subject: Articles
  topic: section
subject: construction service provider
  topic: keywords
subject: hyperbolic fuzzy sets
  topic: keywords
subject: LOPCOW
  topic: keywords
subject: WASPAS
  topic: keywords
subject: sustainability
  topic: keywords
creator: Abhishek Yadav
creator: Raghunathan Krishankumar
creator: Kattur Soundarapandian Ravichandran
creator: Jurgita Antuchevičienė
creator: Edmundas Kazimieras Zavadskas
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-05-11
publication date: 2026-05-11
starting page: 475
ending page: 488
doi: 10.3846/jcem.2026.26849

Integrating AI-enhanced and conventional market selection approaches for the construction industry: insights from Indian firms
type: item
description: International market selection (IMS) plays a pivotal role in shaping construction companies’ global strategies. However, conventional IMS models generally fail to capture the distinctive challenges in the construction sector, such as the regulatory volatility, supply chain vulnerabilities, and site-specific operational constraints. To address these deficiencies, this study introduces a data-driven IMS framework specifically designed for the construction industry that incorporates financial, institutional, and industry-specific variables. The research adopts a two-phase analytical process: First, key IMS factors are identified and assessed through four methodological approaches, namely, logistic regression, partial least squares structural equation modeling, adaptive neuro-fuzzy inference systems (ANFIS), and the fuzzy ordinal priority approach. Second, the model is validated using 5,656 international market entry records for Indian construction firms from 2016 to 2023. The results demonstrate that the proposed artificial intelligence-enhanced framework significantly outperforms conventional models. Specifically, the ANFIS model achieved a prediction accuracy of 94.523% with an AUC-ROC of 0.874. This quantitative enhancement confirms that the integrated approach effectively captures nonlinear interactions and complex market constraints that conventional models generally neglect. Internal variables such as international experience and engineering productivity contribute positively to predictive accuracy. Meanwhile, external variables, particularly geographic distance and national risk, are demonstrated to be more difficult to model. Overall, the proposed framework provides a reliable foundation for strategic decision-making in global construction. It provides actionable insights for firms aiming to expand sustainably in uncertain international environments.
subject: Articles
  topic: section
subject: international market selection model
  topic: keywords
subject: international construction project
  topic: keywords
subject: artificial intelligence
  topic: keywords
subject: data-driven decision making
  topic: keywords
subject: adaptive neurofuzzy inference system
  topic: keywords
creator: Kyung-Tae Lee
creator: Seung-Hye Shin
creator: Jin-Bin Im
creator: Hyoungmin Choi
creator: Ju-Hyung Kim
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-05-07
publication date: 2026-05-07
starting page: 456
ending page: 474
doi: 10.3846/jcem.2026.26811

Innovation in construction: assessing the role of transformational leadership and knowledge governance
type: item
description: The dynamic nature of today’s world presents numerous challenges, and construction companies are not exempt from these difficulties. This research aimed to investigate the effects of transformational leadership (TL) on both product innovation (PDI) and process innovation (PCI), as well as to determine the mediating role of knowledge governance (KG) and knowledge sharing (KS), along with the moderating impact of innovation climate (IC). A cross-sectional design and structural equation modeling (SEM-AMOS) were employed to analyze data collected from 185 participants from various construction companies in Spain. The findings demonstrate that knowledge sharing and knowledge governance play a significant role in connecting TL with innovation capabilities. Additionally, it was found that the effects of TL and KS on different aspects of innovation capabilities vary and depend on the company’s innovation climate. This study provides valuable insights into the relationship between TL, KG, and innovation capability, highlighting the importance of fostering knowledge sharing, enhancing knowledge governance, and promoting a positive innovation climate to drive organizational innovation.
subject: Articles
  topic: section
subject: knowledge sharing
  topic: keywords
subject: knowledge governance
  topic: keywords
subject: transformational leadership
  topic: keywords
subject: structural equation modeling
  topic: keywords
subject: product innovation
  topic: keywords
subject: process innovation
  topic: keywords
subject: innovation climate
  topic: keywords
subject: knowledge management
  topic: keywords
creator: Salvador López
creator: Víctor Yepes
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-05-07
publication date: 2026-05-07
starting page: 433
ending page: 455
doi: 10.3846/jcem.2026.24919

Scheduling the production of prefabrication construction supply chains considering variable delivery times
type: item
description: The application of prefabrication and modularization in the construction industry has grown significantly recently. The efficiency of prefabrication supply chains yields substantial advantages for construction projects. A challenge is the variability in delivery times, which negatively impacts the economy and reliability of prefabrication supply chains. Most construction prefabrication suppliers have difficulty adjusting their schedules in response to delivery time changes in a timely manner. Despite this critical challenge, limited research has addressed proactive and robust production scheduling to mitigate these uncertainties. This study investigates a method for proactive and robust production scheduling for construction prefabrication suppliers, particularly those with multiple fabrication shops, responding to changes in delivery times. This paper introduces a multi-objective, two-stage stochastic programming model that facilitates the production planning with multiple fabrication shops, considering variable delivery times. Computational results from an experimental study demonstrate that the proposed optimization model achieves a 14.6% cost reduction compared to the traditional EDD method. Computational results also show that the expected cost of the stochastic programming model achieves a cost reduction of 0.23% compared to a deterministic model. These findings suggest the model’s capability to generate robust and flexible schedules that effectively balance cost minimization with time reduction.
subject: Articles
  topic: section
subject: supply chain
  topic: keywords
subject: scheduling
  topic: keywords
subject: prefabrication
  topic: keywords
subject: modularization
  topic: keywords
subject: construction
  topic: keywords
subject: optimization
  topic: keywords
subject: uncertainty
  topic: keywords
subject: stochastic programming
  topic: keywords
creator: Chung Ho
creator: Zelda B. Zabinsky
creator: Yong-Woo Kim
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-04-28
publication date: 2026-04-28
starting page: 415
ending page: 432
doi: 10.3846/jcem.2026.26156

Post-pandemic building resilience: Building Information Modeling and green building integration
type: item
description: This research explores how Building Information Modeling (BIM), green building design, and post-pandemic resilience contribute to sustainable, healthy buildings. Although studies have explored BIM’s impact on green buildings, its role after COVID-19 remains largely unexplored. This study fills this gap through a “Green BIM post-pandemic square” taxonomy, integrating findings from a 1999–2024 literature review and BIM software evaluation. The taxonomy delves into project phases, green attributes, BIM features, and post-pandemic considerations to uncover links between BIM, green buildings, and post-pandemic cycles. It reveals how BIM enhances green design, construction, operation, and retrofitting. Additionally, BIM scrutinizes green building parameters such as energy efficiency and supply chain management. The study underscores BIM’s potential in sustainability, occupant health, and supply chain resilience through Green Building Evaluations (GBE). Ultimately, it synthesizes data to guide building researchers and practitioners, identifying gaps and suggesting future initiatives. Relevant journals and software are incorporated to provide comprehensive insights into the subject.
subject: Articles
  topic: section
subject: Building Information Modeling (BIM)
  topic: keywords
subject: green building
  topic: keywords
subject: pandemic
  topic: keywords
subject: Supply chain
  topic: keywords
subject: sustainability
  topic: keywords
creator: Masood Karamoozian
creator: Hong Zhang
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-04-27
publication date: 2026-04-27
starting page: 394
ending page: 414
doi: 10.3846/jcem.2026.25851

An intelligent construction system based on digital twin and foundation model optimization
type: item
description: Construction sites routinely face multi-trade concurrency, spatiotemporal coupling, and high safety risk; relying solely on manual inspection and heuristic scheduling often leads to lagging detection and inconsistent execution. In response, recent practice has introduced digital twins (DT) to fuse video, sensors, and BIM and thus improve site visibility; however, most implementations remain at monitoring/visualization, lacking a mechanism to convert cognition into executable, verifiable decisions. Meanwhile, Transformer foundation models show strong capabilities in multimodal perception and representation learning, yet they are rarely closed-looped with engineering constraints and on-site execution. Against this backdrop, taking high-rise self-climbing platform (SCP) operations as a representative scenario, we build a DT×Transformer closed-loop system. We align video/sensor/BIM/text at the component level via “Component-ID + Timestamp”, train a multimodal Transformer for operation-state recognition and short-horizon risk prediction, and then explicitly encode safety, resource, and spatial precedence constraints in a policy module to generate feasible task sequences, which are delivered to crews via AR with acknowledgments to close the loop. The system integrates multisource perception, digital twin, foundation-model reasoning, and AR-assisted execution, and was validated on a highrise self-climbing platform project for its overall improvement of construction performance. The evaluation covered four key aspects – safety management, operational efficiency, communication and execution, and information transparency. Results show that the system significantly extends the lead time of risk warnings, reduces violation rates, stabilizes construction rhythm, shortens decision latency, and markedly improves the consistency between instruction delivery and on-site feedback.
subject: Articles
  topic: section
subject: intelligent construction
  topic: keywords
subject: digital twin
  topic: keywords
subject: foundation model
  topic: keywords
subject: high-rise self-climbing platform
  topic: keywords
subject: AR interaction
  topic: keywords
creator: Fengyi Guo
creator: Cynthia Changxin Wang
creator: Jun Sun
creator: Kaixin Huang
creator: Xin Wang
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-04-20
publication date: 2026-04-20
starting page: 374
ending page: 393
doi: 10.3846/jcem.2026.26154

Transforming railway transportation: the role of emerging technologies in efficiency, safety, and sustainability
type: item
description: This review explores the transformative role of emerging technologies in railway transportation, emphasizing their contributions to efficiency, safety, and sustainability. With the integration of Artificial Intelligence (AI), the Internet of Things (IoT), Digital Twin technology, and autonomous systems, the railway industry is transitioning towards intelligent and interconnected networks. These advancements address critical challenges such as predictive maintenance, energy optimization, and real-time decision-making, ensuring operational resilience and enhanced passenger experiences. The review methodically evaluates 199 studies, offering insights into regional and temporal trends, and highlighting innovations in automation, safety systems, and sustainability. Additionally, it examines the interplay between advanced technologies and environmental goals, underscoring the importance of green practices and resource efficiency. Despite significant progress, challenges in cybersecurity, regulatory compliance, and legacy infrastructure integration persist. By categorizing literature into thematic domains and identifying critical research gaps, this study provides a comprehensive roadmap for future advancements in intelligent railway systems. Ultimately, it positions emerging technologies as pivotal to addressing contemporary demands and fostering a sustainable and adaptive global railway network.
subject: Articles
  topic: section
subject: railway transportation
  topic: keywords
subject: transportation research
  topic: keywords
subject: emerging technologies
  topic: keywords
subject: temporal trends
  topic: keywords
subject: future of railway transportation
  topic: keywords
creator: Qasim Zaheer
creator: Shi Qiu
creator: Zunaira Atta
creator: S Muhammad Ahmed Hassan Shah
creator: Haleema Ehsan
creator: Syed Faizan Hussain Shah
creator: Weidong Wang
creator: Chengbo Ai
creator: Jin Wang
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-04-17
publication date: 2026-04-17
starting page: 336
ending page: 373
doi: 10.3846/jcem.2026.25811

Physics-informed neural network–integrated point cloud decimation and 3D mesh modeling for thermo-mechanical simulation of rail fasteners in digital twin systems
type: item
description: High-density point cloud data of infrastructure components, such as railway fasteners, often contain excessive noise and redundant points, making them challenging to process for simulation and analysis. This study introduces an integrated framework that transforms raw point clouds into simulation-ready 3D meshes and couples them with PhysicsInformed Neural Networks (PINNs) for thermo-mechanical analysis, enabling applications within digital twin environments. The pipeline begins with a RANSAC-based iterative segmentation and outlier removal, achieving an 82.35% reduction in point count while preserving essential geometry. Poisson surface reconstruction and targeted post-processing then produce a high-fidelity, watertight mesh normalized for consistent simulation input. Leveraging this mesh, PINNs solve the steady-state heat equation to model thermal conduction and linear elasticity equations to estimate stress and displacement fields under defined Dirichlet boundary conditions. The resulting temperature and stress distributions are visualized directly on the mesh, providing interpretable, physics-consistent insights into fastener performance. By unifying geometric simplification with data-driven, physics-aware simulation, this approach supports accurate and computationally efficient digital twin development for railway asset monitoring and maintenance.
subject: Articles
  topic: section
subject: digital twin
  topic: keywords
subject: physics-informed neural networks
  topic: keywords
subject: point cloud decimation
  topic: keywords
subject: 3D mesh generation
  topic: keywords
subject: rail fasteners
  topic: keywords
subject: thermo-mechanical simulation
  topic: keywords
creator: Jin Wang
creator: S Muhammad Ahmed Hassan Shah
creator: Shi Qiu
creator: Weidong Wang
creator: Haleema Ehsan
creator: Chengbo Ai
creator: Yangming Lou
creator: Qasim Zaheer
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 309
ending page: 335
doi: 10.3846/jcem.2026.26522

Recyclability and environmental impact of typical solid waste materials (rubber, RAP, SS) in asphalt mixtures: a state-of-the-art review
type: item
description: The utilization of solid waste material (SWM) in sustainable asphalt pavement is one of the key paths to achieving carbon peaking and neutrality. It is imperative to seek a balance between service performance and environmental impacts of sustainable asphalt pavement. This paper makes a state-of-the-art review on recyclability and life cycle assessment of SWM in sustainable asphalt pavements based on recent five-year literatures. According to scientometric analysis results, three typical SWM, crumb rubber (CR), reclaimed asphalt pavement (RAP) and steel slag (SS), are selected to be mainly discussed over the service performance and environmental impacts via life cycle assessment. Especially, influences of material properties or production design of SWM are critically highlighted, including the CR particle size and treatment methods, strategies of RAP to mitigate performance deterioration, and enhancement mechanisms of SS in asphalt mixtures. Further, the current major research gaps and application limitations associated with SWM utilization are concluded, including the trade-offs between the environmental impacts of CR production and the service performances, the uncertainties in binder blending and rejuvenation efficiency of RAP, and the volume expansion and heavy metal leaching of SS asphalt mixtures.
subject: Articles
  topic: section
subject: solid waste material
  topic: keywords
subject: rubber
  topic: keywords
subject: RAP
  topic: keywords
subject: steel slag
  topic: keywords
subject: asphalt pavement
  topic: keywords
subject: life cycle assessment
  topic: keywords
creator: Zijun Xu
creator: Yilin Wang
creator: Zekang Sun
creator: Thomas Ng
creator: Wisal Ahmed
creator: Guoyang Lu
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-04-15
publication date: 2026-04-15
starting page: 276
ending page: 308
doi: 10.3846/jcem.2026.26431

Evaluating the role of unmanned aerial vehicles to enhance construction project productivity
type: item
description: The construction industry, generating significant goods and services annually, remains one of the least digitalized sectors globally, with Malaysia’s construction industry particularly dependent on manual labor. This study investigates the implementation opportunities and challenges of Unmanned Aerial Vehicles (UAVs) in Malaysia’s construction industry to enhance productivity and efficiency. Through a mixed-method approach, the research combines qualitative data from 20 semi-structured interviews with quantitative analysis of 200 survey responses from construction professionals. Structural Equation Modeling identified four key opportunity categories: Site Surveying, Site Inspection, Constructing and Repairing, and Enhancing Manpower, Materials, and Machinery (3M) Coordination. The analysis revealed that Constructing and Repairing (0.62) showed the strongest influence on UAVs implementation, followed by Enhancing 3M Coordination (0.61). Five primary challenges were identified: Safety Concerns (0.74), Cost Challenges (0.69), Technical Difficulties (0.61), Regulation Factors (0.53), and Environmental Factors (0.47). The study developed a comprehensive framework for UAVs implementation in construction, highlighting critical success factors and barriers. Future research opportunities include investigating long-term economic impacts through longitudinal case studies and examining UAVs integration with Building Information Modeling systems and Radio-Frequency Identification to optimize technological coordination between aerial data collection and digital modeling.
subject: Articles
  topic: section
subject: Unmanned Aerial Vehicles
  topic: keywords
subject: construction productivity
  topic: keywords
subject: UAVs challenges
  topic: keywords
subject: Malaysia’s construction industry
  topic: keywords
subject: technology adoption
  topic: keywords
creator: Ian Xin You Tang
creator: Wesam Salah Alaloul
creator: Abdul Mateen Khan
creator: Muhammad Ali Musarat
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-04-09
publication date: 2026-04-09
starting page: 251
ending page: 275
doi: 10.3846/jcem.2026.26099

Overview and analysis of safety management in prefabricated construction (2012–2022)
type: item
description: The stable development of the construction industry plays a significant role in national economic growth. With the continuous reform and progress of the construction industry, construction safety has become a vital issue of concern and emphasis. As an essential means for the sustainable development of the construction industry and industrialization of construction, prefabrication has the advantages of reducing waste of resources and improving construction safety and efficiency and is strongly promoted by the construction industry around the world. Although the safety management of traditional construction has been fully researched, the traditional safety management mode cannot be directly applied to assembled construction because of differences in their construction characteristics and management scopes. Thus, investigating the safety issues of prefabrication is necessary. Although numerous scholars analyzed safety in the different construction stages of assembled buildings, many connections and contents in the literature must be summarized, and systematic literature research must be conducted. Therefore, this study uses a systematic and comprehensive review approach to fill the research gaps. In the first stage, 107 papers related to prefabrication safety management published, meeting the requirements are selected through a literature search. In the second stage, scientometric analysis is conducted to identify the journal sources, scholars, regions, and keywords. In the final stage, content analysis is performed to achieve three main objectives: 1) to identify the differences between prefabricated and conventional buildings and summarize the characteristics of prefabricated buildings (PBs) to obtain the characteristics of prefabrication safety management, 2) to summarize the research topics, and 3) to discuss and provide signposts for potential research directions. This study provides a comprehensive knowledge framework that links current research areas with future…
subject: Articles
  topic: section
subject: prefabrication
  topic: keywords
subject: safety management
  topic: keywords
subject: scientometric analysis
  topic: keywords
subject: science mapping
  topic: keywords
subject: literature review
  topic: keywords
creator: Clyde Zhengdao Li
creator: Qingyi Yu
creator: Vivian W. Y. Tam
creator: Hengqin Wu
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-03-31
publication date: 2026-03-31
starting page: 231
ending page: 250
doi: 10.3846/jcem.2026.23497

Exploring the technology-organization-environment configurations to enhance stakeholder collaboration in the off-site construction projects
type: item
description: Stakeholder collaboration is critical in empowering off-site construction (OSC) projects to reduce the cost overrun, conflicts and quality problems. Prior studies have explored the factors affecting stakeholder collaboration but focused on the net effects, ignoring their interaction relations. Our study aims to explore the configuration conditions to enhance stakeholder collaboration in OSC projects using fuzzy-set qualitative comparative analysis (fsQCA). 103 valid questionnaires are collected to conduct fsQCA to explore the configurational conditions to achieve the high stakeholder collaboration. The findings reveal that there are no necessary conditions as a bottleneck factor constraining stakeholder collaboration emergence in the OSC projects. Three equivalent configurational conditions are identified to achieve high stakeholder collaboration, referring to environment-driven organizational configuration, technology-organizational configuration, and organizational-driven environment configuration. Our study enriches the literature on the antecedent identification of stakeholder collaboration in the OSC project. It also expands the underlying mechanisms between antecedents and stakeholder collaboration from the configurational perspective. Meanwhile, our study provides practical guidance for policymakers and project managers to make decisions by emphasizing the interaction effects of different project governance mechanisms.
subject: Articles
  topic: section
subject: off-site construction
  topic: keywords
subject: stakeholder collaboration
  topic: keywords
subject: TOE
  topic: keywords
subject: configuration condition
  topic: keywords
creator: Zezhou Wu
creator: Ao Li
creator: Shuhui Zhang
creator: Hao Lang
creator: Qiaohui Chen
creator: Hong Xue
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-03-23
publication date: 2026-03-23
starting page: 213
ending page: 230
doi: 10.3846/jcem.2026.25986

Exploring the causes of contract disputes and their social network relationships in the megaprojects: a case of Jinan Airport Project
type: item
description: Contract disputes hinder the successful delivery of megaprojects. This study aims to identify crucial contract disputes and causes for dealing with contract disputes problems and improving megaproject performance. 107 contract dispute-related documents were collected and analyzed using a mixed method of text mining and social network analysis. Text mining was used to sort out emerging contract disputes and causes. Social network analysis was used to identify crucial contract disputes and causes by analyzing their network relationships. Our study obtained 12 contract disputes and 10 corresponding causes in the megaproject context. The results show that payment dispute is the most prevalent contract dispute in megaprojects. Our study also found that payment dispute and settlement dispute have high degree of centrality; incomplete survey and design content and unclear contract terms are critical causes as the bridging roles in the relationship network of causes in megaprojects. This study expands the literature on the identification of contract disputes and corresponding causes in megaprojects. Meanwhile, it provides practical guidance for project managers on designing contract items and dealing with contract disputes in megaprojects.
subject: Articles
  topic: section
subject: megaproject
  topic: keywords
subject: contract dispute
  topic: keywords
subject: contract cause
  topic: keywords
subject: social network analysis
  topic: keywords
subject: text mining
  topic: keywords
creator: Hong Xue
creator: Chao Ye
creator: Cheng Zhang
creator: Zezhou Wu
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-03-18
publication date: 2026-03-18
starting page: 195
ending page: 212
doi: 10.3846/jcem.2026.26157

The impact of environmental turbulence on construction enterprise performance: unveiling the systemic response mechanisms
type: item
description: This study addresses the overlooked dynamic interaction between strategic agility and absorptive capacity in turbulent environments, particularly within project-based enterprises where knowledge flows are fragmented. By constructing an integrative framework, it examines how strategic agility influences enterprise performance via absorptive capacity under varying environmental turbulence levels. Using data from 198 Chinese construction industry practitioners and PLS-SEM analysis, results reveal that strategic agility dominates enterprise responses, with absorptive capacity mediating this effect. Notably, in high turbulence, the mediation path buffers the negative impact. The study advances organizational adaptability theory and offers guidance for capability development in turbulent contexts.
subject: Articles
  topic: section
subject: mechanism
  topic: keywords
subject: new theoretical framework
  topic: keywords
subject: environmental turbulence
  topic: keywords
subject: potential absorptive capacity
  topic: keywords
subject: strategic agility
  topic: keywords
subject: firm performance
  topic: keywords
creator: Jiangwei Luo
creator: Mohd Wira Mohd Shafiei
creator: Radzi Ismail
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-03-16
publication date: 2026-03-16
starting page: 174
ending page: 194
doi: 10.3846/jcem.2026.26158

Influence of institutional isomorphism on unethical pro-organizational behavior of construction teams based on the mediating effect of organizational routines
type: item
description: Unethical behavior that favors the organization at the expense of unethical conduct is considered an example of unconventional motivation. Unethical pro-organizational behavior (UPB) reduces the project quality and safety in the construction industry and may also lead to increased construction costs and investment losses. By conducting a crosslayer analysis and administering a questionnaire survey with 352 construction team employees, this study examines the influence of institutional isomorphism on UPB and the path between them. Moreover, the study explores the mediating effect of organizational routines. Results indicate that institutional isomorphism has different effects on implicit and explicit routines. Organizational routines play a crucial role in institutional isomorphism and UPB. Several mediating paths exist between institutional isomorphism and UPB. Furthermore, UPB is mainly implemented by strengthening the mediating effect of implicit routines and weakening that of explicit routines.
subject: Articles
  topic: section
subject: construction team
  topic: keywords
subject: unethical pro-organizational behavior
  topic: keywords
subject: institutional isomorphism
  topic: keywords
subject: organizational routine
  topic: keywords
subject: mediating effect
  topic: keywords
creator: Bing Zhang
creator: Ting Fang
creator: Bo Xia
creator: Xueying Liu
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-03-16
publication date: 2026-03-16
starting page: 162
ending page: 173
doi: 10.3846/jcem.2026.25854

Factors influencing sustainable construction in Egypt
type: item
description: The concern about sustainable development has become a global goal, and as such, the United Nations has adopted the seventeen sustainable development goals that are targeted to be achieved by 2030. Furthermore, to address the energy and Greenhouse gases (GHG) crisis, the world has moved towards developing policies concerned with rationalizing energy consumption and reducing GHG emissions. The main idea of sustainable construction is to avoid the depletion of natural resources for both the present and future generations. Therefore, this study aims to investigate the factors that prevent and delay the adoption of sustainable construction practices in Egypt. Using the survey method, a questionnaire was filled out by professionals and practitioners in Egyptian construction projects. The findings of this study indicate that the most critical factors affecting sustainable construction in Egypt are the “poor market demand for green and recyclable construction materials”, and “fear of higher investment costs”. The study recommends raising awareness to overcome these factors.
subject: Articles
  topic: section
subject: sustainable development
  topic: keywords
subject: sustainable construction
  topic: keywords
subject: factors
  topic: keywords
subject: construction industry
  topic: keywords
creator: Jehan Elsamni
creator: Hosam Hegazy
creator: Ibrahim Abdulrasheed
creator: Mohamed Kohail
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-03-16
publication date: 2026-03-16
starting page: 148
ending page: 161
doi: 10.3846/jcem.2026.20955

Dynamic risk assessment of international engineering projects from the life cycle perspective
type: item
description: Compared to other types of engineering projects, the development of international engineering projects (IEPs) is particularly challenging due to the uncertainties and risks posed by external environments. The risks of IEPs arise from both external threats and inherent vulnerabilities. As projects progress, these risks evolve dynamically, posing significant challenges for risk management. Existing studies on IEPs have focused mainly on the static assessment of risks at a certain stage or types of risk, but few have considered the dynamic and interconnected nature of risks. This study employs a comprehensive risk assessment framework for IEPs using dynamic Bayesian network. Specifically, the fuzzy set method and Monte Carlo simulation create the prior probabilities of root nodes and conditional probabilities of intermediate and leaf nodes. Then, propagation analysis is conducted to uncover the dynamic evolution of risks throughout the project life cycle. The proposed framework can capture the evolution of critical risks in life cycle. Internal and external risks in the three phases of construction, operation, and maintenance have been identified. Based on the findings from a case study, targeted management strategies are proposed to address critical risks, providing practical guidance for project managers to optimize risk management practices.
subject: Articles
  topic: section
subject: international engineering projects
  topic: keywords
subject: risk assessment
  topic: keywords
subject: dynamic Bayesian network
  topic: keywords
subject: Monte Carlo simulation
  topic: keywords
creator: Xu Duan
creator: Pengcheng Xiang
creator: Shuai Feng
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-03-13
publication date: 2026-03-13
starting page: 133
ending page: 147
doi: 10.3846/jcem.2026.25212

YOLOv11n-CDL: accurate and lightweight pavement defect detection via enhanced multi-scale attention and feature fusion
type: item
description: Pavement defect detection requires both high accuracy and real-time performance in complex road environments, yet existing lightweight models often struggle with blurred textures, background interference, and small cracks. To address these limitations, this study proposes YOLOv11n-CDL, an enhanced lightweight detector integrating three targeted improvements. First, the ConvSmart module expands the receptive field and strengthens multi-scale feature extraction, improving the representation of defects of varying sizes. Second, a Double-Stage Attention (DSA) mechanism, embedded at the deepest backbone stage, iteratively highlights discriminative crack patterns while suppressing shadows, markings, and texture noise. Third, a P2-level small-object detection path provides high-resolution features that significantly improve sensitivity to fine cracks and micro-potholes. Experiments on IRRDD show that YOLOv11n-CDL achieves 75.3% mAP@0.5 and 44.6% mAP@0.5:0.95, outperforming the baseline by 3.0 and 1.1 percentage points, and exceeding YOLOv8n and YOLOv7-tiny in both precision and recall. Additional results on RDD2022 and low-power devices confirm strong generalization and real-time deployability. These improvements demonstrate that YOLOv11n-CDL offers an effective balance between accuracy, robustness, and efficiency for practical pavement inspection applications.
subject: Articles
  topic: section
subject: pavement maintenance
  topic: keywords
subject: repair
  topic: keywords
subject: YOLOv11n
  topic: keywords
subject: attention mechanism
  topic: keywords
subject: pavement defect detection
  topic: keywords
subject: multi-scale perception
  topic: keywords
subject: lightweight convolution module
  topic: keywords
subject: small object detection
  topic: keywords
creator: Jun Dai
creator: Yanyang Gao
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-02-26
publication date: 2026-02-26
starting page: 119
ending page: 132
doi: 10.3846/jcem.2026.26166

Determining safety-related critical success factors in petrochemical projects through an extensive fuzzy risk assessment approach
type: item
description: The construction phase of petrochemical units encounters many risks, a large number of which leads to death and disabling injuries. The purpose of this study is to provide a framework to determine safety-related critical success factors (CSFs) in petrochemical construction projects through risk assessment. The proposed approach involved two phases. At first, 15 potential risks were identified through a review of previous studies and interviews with experts. Then a combination of failure mode and effect analysis (FMEA), criteria importance through inter-criteria correlation (CRITIC) and technique for order preference by similarity to the ideal solution (TOPSIS) in a fuzzy environment was used for risk assessment, and the risks were classified based on their score. In Phase 2, safety-related CSFs were identified and ranked using the solutions provided for each risk and by consulting with experts. Results showed that falling from height and structural collapse due to excavation operations were the most and least important risks, respectively. Top management support was identified as the most important factor amongst the safety-related CSFs. The findings of this paper assist petrochemical construction project managers to adopt a structured approach for the risk assessment and determination of safety-related CSFs in their projects.
subject: Articles
  topic: section
subject: safety-related critical success factors
  topic: keywords
subject: petrochemical construction projects
  topic: keywords
subject: risk assessment
  topic: keywords
subject: fuzzy FMEA
  topic: keywords
subject: fuzzy CRITIC-TOPSIS
  topic: keywords
subject: experts
  topic: keywords
creator: Alireza Azodi
creator: Hamidreza Abbasianjahromi
creator: Emadaldin Mohammadi Golafshani
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-02-19
publication date: 2026-02-19
starting page: 102
ending page: 118
doi: 10.3846/jcem.2026.25992

An integrated vision-based dynamic collision risk assessment framework of workers and mobile machinery on construction site
type: item
description: The concepts of environmental impact index and spatial conflict degree have gained prominence in enhancing the controllability of collision accidents and mitigating the likelihood of collisions during construction processes. Nevertheless, prior studies predominantly focused on exploring collisions in terms of proximity and congestion between pairs of entities, thereby overlooking a comprehensive consideration of workers, construction machinery, environmental factors, and the spatial interaction of specific activities.To this end, this study aims to propose an integrated vision-based dynamic collision risk assessment framework by setting workers and mobile machinery as targeted research objectives and embedding a comprehensive risk assessment model in the proposed framework, thereby comprehensively assessing four types of risk factors (i.e., proximity, congestion, environmental impact index, and spatial conflict), and visualize the hierarchy of risk warnings. Firstly, a comprehensive risk assessment model was developed by using the fuzzy comprehensive evaluation method. This is followed by developing a dynamic risk assessment framework to extract the spatial information of the monitored objects by using computer vision as the underlying data of the risk factors. Finally, the proposed integrated framework was validated by an experimental study. This experiment’s safety risk assessment results are consistent with expectations, which largely illustrates the effectiveness of the evaluation model constructed in this paper. For the vision module, the accuracy of classification and monitoring is more than 95%, and the speed of the object detection algorithm to process the video is about 10 frames per second, which shows the feasibility of this study.
subject: Articles
  topic: section
subject: dynamic collision risk assessment
  topic: keywords
subject: fuzzy comprehensive evaluation
  topic: keywords
subject: environmental impact factor
  topic: keywords
subject: space conflict
  topic: keywords
subject: computer vision
  topic: keywords
creator: Xingrong Gao
creator: Wenjing Kang
creator: Yunting Liu
creator: Qian Zhang
creator: Ting-Kwei Wang
rights: Copyright (c) 2026 The Author(s). Published by Vilnius Gediminas Technical University. https://creativecommons.org/licenses/by/4.0
date: 2026-02-11
publication date: 2026-02-11
starting page: 84
ending page: 101
doi: 10.3846/jcem.2026.24922