Purpose This study investigates the application of image captioning technology in automated bridge inspection. Given the scarcity of research in this domain, this study aims to evaluate the feasibility, effectiveness and practical implications of using transformer-based models to generate natural language descriptions of bridge damage from visual data. Design/methodology/approach A triangulated research methodology was used, comprising a systematic literature review to assess the current state of image captioning in bridge inspection; a feasibility study using an encoder–decoder architecture (EfficientNet–transformers) trained on a structural damage dataset; and an interview-based transferability study with seven industry professionals to evaluate practical adoption challenges. Findings The systematic review identified only four relevant studies, underscoring the nascent state of research in this field. The feasibility study demonstrated promising results, with EfficientNet–transformers achieving high bilingual evaluation understudy (BLEU) scores (BLEU-1:0.944, BLEU-4:0.904) in structural damage description tasks. Finally, industry feedback highlighted potential benefits in inspection efficiency but emphasized challenges in workflow integration and model reliability. Originality/value To the best of the authors; knowledge, this study represents one of the first comprehensive explorations of image captioning for bridge inspection, contributing both methodological and practical insights. It identifies key research gaps, including the need for domain-specific data sets and standardized evaluation frameworks, while proposing actionable directions for future AI applications in infrastructure maintenance. The findings provide a foundation for advancing automated inspection technologies toward safer and more efficient infrastructure management.

Purpose This study aims to improve the generalization of computer vision models used for automated construction progress monitoring by addressing the domain shift problem between synthetic and real images. The objective is to enable more reliable deployment of synthetic data-driven models in actual construction environments. Design/methodology/approach A hybrid optimization algorithm is proposed to minimize domain discrepancy, measured by maximum mean discrepancy (MMD), between synthetic and real images. The method uses a YOLOv8-based feature extractor to compute class-specific distributions and applies both gradient-based and Bayesian optimization techniques to tune image transformation parameters. These transformations are selectively applied to synthetic images to improve alignment with real-world feature distributions. Findings Experimental results show that the proposed method effectively reduces MMD values for both concrete and insulation classes, enhancing visual and structural similarity to real images. Moreover, the use of class-wise single-transformation optimization demonstrated superior performance and stability compared to full-parameter optimization. The hybrid data set combining raw and transformed synthetic images yielded the highest detection accuracy across all test scenarios. Originality/value This study introduces a domain adaptation framework based on MMD optimization specifically tailored for the construction industry. Unlike conventional approaches, the proposed method provides a class-specific, quantitatively driven adaptation strategy that enhances model reliability without requiring extensive real-image data sets. The framework offers practical applicability for progress inference and forms a foundational module for future integration with BIM-based monitoring systems.

Purpose The construction industry is increasingly adopting offsite construction as a solution to improve efficiency, reduce costs and enhance project sustainability. However, managing offsite projects remotely requires construction professionals to develop specific construction management skills and competencies (CMSC) that align with digital technologies and Industry 5.0 advancements. This study aims to identify the critical CMSC necessary for the effective management of offsite construction projects and explores their impact on project outcomes in a digital era. Design/methodology/approach A thorough literature review initially identified 57 CMSC, which were refined to 48 CMSC through conceptual clustering. This study adopts a mixed-methods research approach, integrating quantitative and qualitative techniques. Survey data were collected from 155 registered and licenced engineering professionals across Nigeria’s private and public construction sectors, complemented by 30 semi-structured interviews. The survey data were analysed using descriptive statistics and hierarchical clustering, while thematic analysis in NVivo was applied to interview transcripts. Findings This study identifies training and learning, team building/work, health/safety and security, design and maintenance updates, communication, quality control and assurance, employee welfare/counselling, recruiting and selecting personnel, use of computer technology and sourcing finance and control as the top ten CMSC required for effective offsite construction management in Industry 5.0. These competencies facilitate digital transformation and remote project execution. Research limitations/implications The findings inform the design of targeted training programmes and policy interventions to equip construction professionals with the necessary CMSC for effective digital and automated project delivery. In practice, the identified competencies promote resource efficiency, ensure higher quality assurance and support workforce well-being − critical outcomes for successful offsite construction management. Originality/value This research stands out by offering a validated and prioritised framework of CMSC specifically tailored to the demands of offsite construction in the Industry 5.0 era. Unlike prior studies that focus broadly on digital transformation or traditional project management, this study integrates digitalisation, human-centric values and remote project realities to define the unique competency set needed in emerging offsite contexts.

Purpose This paper aims to raise awareness in the construction industry on how and to what extent laser scanning technology can play a key role in dimensional quality assessment (DQA). It demonstrated the effectiveness of laser scanning technology in resolving disputes arising from dimensional deviations compared to conventional methods. Design/methodology/approach This paper adopts the design science research methodology. It conducted a case study on an industrial facility facing a DQA-driven dispute to evaluate laser scanning technology as a solution in the context of reliability and applicability. Findings This paper validates that laser scanning offers the fastest and most precise solution to resolve disputes arising from dimensional deviations, even in a structure with complex responsibility exchanges between contractors, restrictive tolerances and complex manufacturing processes. It suggests that the broader adoption of laser scanning will enhance the efficiency and accuracy of resolving dimensional quality disputes in the industry. Research limitations/implications This paper is one of the rare and pioneering studies that introduces laser scanning as a novel dispute resolution tool in the construction industry, beyond its established role in quality assessment. Practical implications By offering a data-driven and transparent approach to resolving dimensional quality disputes, the paper guides practitioners in adopting laser scanning technology. It contributes to the evolution of a more efficient and technologically advanced dispute resolution paradigm in the industry. Originality/value This paper adds value by linking laser scanning with dispute resolution, offering a unique perspective on how digital developments can support more transparent and effective dispute management in construction.

Purpose This study aims to investigate the impact of network embeddedness, BIM adoption and project definition on project performance. Specifically, it examines the mediating role of project uncertainty and DME, along with the moderating influence of technology recombination and safety measures. Design/methodology/approach A quantitative research approach was used, with data collected through a self-administered questionnaire distributed to 380 employees working in the construction sector. Structural equation modeling (SEM) with SmartPLS was used to analyze the data and test the proposed hypotheses. Findings The results show that all hypotheses were accepted, demonstrating that network embeddedness, BIM adoption and project definition significantly positive impact project performance. Furthermore, project uncertainty was found to mediate the relationships between these factors and project performance, while DME played a crucial role in this process. Technology recombination and safety measures moderated the relationships between project uncertainty and project performance, as well as DME. Originality/value This study contributes to the construction management literature by offering a comprehensive model that integrates network embeddedness, BIM adoption, project definition and decision-making efficiency. Technological recombination is analyzed as a moderator variable since it increases the adaptability and potential for project innovation, especially in complex and dynamic construction settings. In contrast to the fixed adoption of single technologies, technological recombination is an active capability representing a firm’s ability to strategically reconfigure and combine established and emergent technologies to better cope with changing project requirements. This ability assists in faster decision-making and allows construction teams to manage uncertainty better through innovation and responsiveness. Placing technological recombination as a moderator, the study seeks to identify how adaptive and flexible technology strategies affect the interaction between project uncertainty and decision-making effectiveness. The method provides more profound findings regarding the impact of technological flexibility in influencing project performance under different circumstances, bridging a significant gap in current project management research. The findings have significant implications for both theory and practice, providing actionable insights for improving project performance.

Purpose The purpose of this study is to adopt a quantitative approach to critically examine the effectiveness of measures to promote the adoption and implementation of blockchain-enabled smart contracts (BSCs) in long-term infrastructure public–private partnerships (PPPs) projects within the theoretical lens of the hybrid technology, organisation and environment (TOE) framework and institutional theory. Design/methodology/approach A literature review was undertaken to identify 34 measures for mitigating various barriers to the adoption of blockchain-smart contracts. It was used to design a survey questionnaire guided by the six constructs of the hybrid model. A total of 123 questionnaire data were gathered via purposive and snowball sampling techniques from experts across countries. The data was analysed using mean analysis, coefficient of variation, relative effectiveness index, Spearman correlation analysis and fuzzy set theory. Findings It was found that the measures (strategies) assessed were “very effective” in promoting the broader adoption of BSC in infrastructure PPP projects. Mimetic measures, organisational measures, normative pressure and technological measures were the leading and most critical measures for improving the adoption of smart contracts in PPP. A strong, positive and significant impact was observed between the six constructs of the hybrid model and the adoption of BSC in PPP. Originality/value Studies integrating blockchain in PPP are scanty, and a quantitative study on measures to improve BSC adoption and implementation in infrastructure PPP projects is absent. Furthermore, the combination of TOE framework and institutional theory has yet to be used to explore the adoption of BSC in infrastructure PPP projects. This study pioneers the promotion of strategies for the digitalisation of PPP projects using smart contracts for sustainable infrastructure development.

Purpose The sharing economy (SE) presents a promising avenue for achieving circular economy (CE) objectives by facilitating the identification of underused resources and supporting resource optimisation. The SE practices are well established in sectors such as transportation and accommodation; however, scholarly literature reveals a notable gap in research related to the construction industry (CI). Therefore, this paper aims to explore construction-related shareable resources while promoting the SE practices in the industry. Design/methodology/approach A multimethod qualitative approach was used, including a literature review, qualitative website analysis of construction-related digital platforms and semi-structured interviews. The collected data were subjected to thematic analysis, using MS Excel and NVivo 14 software. Findings Out of ten types of shareable resources identified in the literature, the website analysis recognised only seven types of resources (human resources, space/storage, mobility, equipment/ tools/material/machinery/ devices, data and information, energy and goods) that are currently being shared in the industry. Further, expert interviews recognised three additional resources (robots, financial capital and Wi-Fi) as potential shareable resources in the CI. Research limitations/implications The study introduced a novel perspective on the current SE research domain by investigating SE practices in the CI. The study’s findings contributed to reframing traditional perspectives within the resource-based view theory. Practical implications The findings provide actionable insights related to the identification and optimisation of underused resources in the CI. Furthermore, the study established a pathway for integrating SE practices into construction, contributing to the realisation of sustainability and CE goals. Originality/value This research presents one of the first attempts to investigate the SE concept in the CI.

Purpose The competitive dynamics in the construction sectors demand value maximization in projects, whereby the clients expect contractors to deliver value through efficiency and effectiveness, along with flexibility in project execution and use. Thus, the client benchmarks the contractor’s performance on value-driving factors, which act as critical success factors (CSFs) for a project’s value proposition. This paper aims to explore, model and rank CSFs of contractor selection within the construction sector to create a synergy between client objectives and contractor capabilities. Design/methodology/approach The CSFs were identified using a fuzzy Delphi study. Additionally, interpretive structural modeling and Matrice d’Impacts Croisés Multiplication Appliquée à un Classement analysis were carried out to explore and model the interrelationships among the CSFs. An interpretive ranking process was also applied to rank these CSFs. Findings The study has identified eight CSFs that help understand customer/clients’ requirements and translate them to maximize the overall value of their projects. The findings suggest that management capability is the most influential factor, while project duration, value engineering and financial soundness act as critical linkages among all the eight CFSs identified. Social implications The study can help boost the contribution of the construction sector in economic growth stories of many developing countries. The improved value from the project can help in building higher quality infrastructure that benefits the community by improving the quality of life. This also encourages inclusive relationships among stakeholders and provides a fair chance to all in contributing the growth. Originality/value The results would help clients and regulators plan and control deviations in the contracting process more effectively by clearly understanding the inter-relationship between the value-creating CSFs.

Purpose This study aims to investigate the moderating effects of the internet of things (IoT) and wearable technologies (WT) on the relationship between traditional safety practices (TSP) and safety management (SM) outcomes in Shanghai’s construction sector. It examines how these technologies enhance safety performance by addressing limitations in conventional approaches. Design/methodology/approach A survey of 300 construction professionals, including project managers, site managers and safety officers, was conducted in Shanghai. Data analysis using partial least squares structural equation modelling (PLS-SEM) assessed the moderating effects of IoT and WT on SM outcomes. Findings The results indicate that WT has a stronger moderating effect (ß = 0.21, p < 0.01) than IoT (ß = 0.11, p = 0.07). WT offers immediate safety benefits through real-time worker monitoring, whereas IoT enhances long-term safety by enabling predictive analytics and hazard detection. The study highlights the synergy between WT and TSP in improving SM outcomes. Practical implications While both IoT and WT enhance SM practices, their impacts differ. WT significantly improves real-time worker safety, making it essential for high-risk zones, whereas IoT contributes to long-term risk mitigation through data-driven insights. Construction managers should prioritise WT adoption for immediate safety improvements while integrating IoT-driven predictive models for sustained hazard prevention. Originality/value This study provides empirical evidence on the complementary roles of IoT and WT in enhancing SM in construction. It offers valuable insights into digital transformation’s role in improving safety performance.

Purpose This study aims to investigate the state-of-the-art in economic sustainability (EcS) and social sustainability (ScS) of prefabricated construction (PFC), addressing gaps in holistic life cycle perspectives. Design/methodology/approach A bibliometric analysis and a content-based critical review were used to synthesise literature on EcS and ScS of PFC. Findings Results reveal that life cycle sustainability assessment (LCSA), social life cycle assessment and additive manufacturing are emerging themes. EcS is more extensively researched than ScS, with developed regions dominating case studies. While PFC marginally outperforms conventional methods in most EcS and ScS evaluations, critical gaps persist in indicator diversity, stakeholder representation and data availability. Challenges related to methodological immaturity and data availability are discussed in depth, leading to an improvement strategy framework proposal. The discussion emphasises how holistic sustainability assessments, circular economy (CE) principles and alignment with sustainable development goals (SDGs) can position PFC as a driver for sustainable urban development. A future research agenda should prioritise methodological advancements, case-specific studies (e.g. CE), LCSA and SDG-aligned policies and decision support systems to enhance sustainability decision-making in PFC. Originality/value Although environmental sustainability in PFC is well-examined, economic and social dimensions remain underexplored. A holistic life cycle approach that integrates CE principles and SDGs can better reveal performance, assessment methods, system boundaries and gaps, ultimately driving global sustainable development, construction innovation and technological progress.