Purpose This study addresses the lack of integration between component-, building- and urban-scale life cycle assessments (LCAs) in the built environment, which limits their effectiveness in guiding policymaking for prospective impact reductions. It proposes a multi-level approach for assessing the embodied impacts of residential building stocks to support more comprehensive and informed decisions. Design/methodology/approach A representative stock of sixteen newly constructed residential buildings in New Zealand, spanning four typologies—apartments, townhouses, double-storey detached and single-storey detached (SD) dwellings—is assessed using multi-level LCA (according to ISO 14040:44) across four environmental impact categories: global warming, eutrophication, ozone depletion and acidification. Two functional units, gross floor area (GFA) and number of occupants, were used to analyse and compare results. Findings Timber and steel emerged as the most impact-intensive materials across most categories due to their extensive use, while plastics and paint contributed between 10 and 29% of impacts. Apartments and townhouses showed higher impacts per GFA due to structural requirements—up to 139 and 20% greater than SD houses, respectively. Upfront impacts (modules A1–A5) accounted for 63%–75% of total impacts. Functional unit selection revealed significant variations, with the impact percentage differences for some buildings shifting from +59% to −25%. Originality/value The novel proposed approach enables the identification of impact hotspots often missed by fragmented assessments. By integrating scales and functional units, it offers a necessary understanding of residential embodied impacts—crucial for designing future housing and currently absent from global literature.

Purpose Construction and demolition activities generate substantial waste worldwide, resulting in environmental and health issues. While the circular economy (CE) offers a promising solution, the interrelationships among key factors influencing CE implementation in construction waste management (CWM) remain underexplored. This study addresses this gap using a semi-quantitative multi-criteria decision-making approach to support more effective CE adoption in CWM. Design/methodology/approach This study uses a systematic literature review (SLR) to identify key factors influencing the implementation of CE in CWM. It then applies the fuzzy DEMATEL method to analyse the interrelationships among these factors, drawing on input from experts across various geographical regions. Findings Analysing the results revealed six classes of factor groups and 14 sub-factors influencing CWM. The key factor groups are supervision, regulation, information technology, economy, knowledge and understanding, and infrastructure. Using the Fuzzy DEMATEL technique, it was revealed that the most influential sub-factors within each group, in order, are “selective supervision,” “vague regulations,” “lack of technological standards,” “transportation costs,” “worker knowledge and skills” and “efficient transportation networks.” Originality/value This study is the first attempt to illustrate the complex relationships among the factors affecting CWM in relevant literature using the fuzzy DEMATEL approach. It is the first to quantify the level of influence and establish cause-and-effect relationships among the factors affecting CE utilisation for CWM.

Purpose This paper presents a pilot study of a machine learning (ML) approach to predict occupants' satisfaction with the indoor environment in high-rise mixed-use buildings, aiming to validate a proof of concept for integrating ML models into early-stage design tools to support occupant-centred performance evaluation. Design/methodology/approach Using post-occupancy evaluation data from a case study building, Random Forest and Neural Network models were trained to classify satisfaction levels–Dissatisfied, Neutral or Satisfied–for both residents and workers based on indoor environmental factors. The methodology focuses on addressing class imbalance through data resampling and cost-sensitive learning, with model performance assessed using class-specific metrics. Findings Both models achieved high overall accuracy (cross-validation score >0.80), with notable improved performance in identifying minority classes after balancing methods were employed. While limited to a single case study, future data collection across diverse buildings and occupant profiles has the potential to improve performance and enable generalisability. Originality/value This research demonstrates the feasibility of a scalable framework for predicting indoor environmental satisfaction, enabling the integration of ML models into simulation-based workflows for data-driven, occupant-centric design evaluation. It advances the field by (1) classifying satisfaction into three actionable categories while explicitly addressing class imbalance, (2) operationalising POE data to move beyond retrospective reporting and (3) establishing a proof of concept for embedding ML models into early-stage design tools.

Purpose This paper introduces a new type of biomimicry green façade system that integrates live cyanobacteria into a digitally generated architectural surface. The aim is to improve building envelope performance by combining natural biological processes with computational design. Design/methodology/approach The study follows a three-phase methodology. Phase 1 establishes a generative design process, using Rhino and Grasshopper to create Voronoi-based geometries inspired by natural morphogenesis. A genetic algorithm filters variants based on solar gain, daylight autonomy and fabrication suitability. Phase 2 involves environmental simulation and optimisation using Ladybug and Galapagos, refining the design through solar, daylight and thermal performance metrics. Phase 3 embeds selected cyanobacteria strains into a bio-gel medium tested under controlled lab conditions to assess viability, photosynthetic response and integration feasibility. Findings Simulation results demonstrate that the prototype significantly reduces peak solar gain (SHGC <0.25), improves daylight autonomy (>50% above 300 lux) and enhances passive cooling through porous geometry. The embedded cyanobacteria show stable photosynthetic activity, enabling CO2 absorption and O2 release under appropriate light and hydration. Material testing confirms the feasibility of modular construction using recyclable substrates and hydrophobic coatings, while lab-scale trials show metabolic activity consistent with early-stage air purification potential. Comparative analysis shows the system's superiority in integrating biological and environmental performance in one responsive façade. Originality/value This is the first façade prototype to integrate generative geometry, parametric environmental optimisation and living cyanobacteria within a functional, digitally fabricated system. Unlike existing biomimetic or algae façades, this design supports real-time metabolic interaction, enabling CO2/O2 exchange and adaptive performance. It establishes a new model for biologically active, performance-driven façades that contribute to environmental and urban resilience.

Purpose This study proposes measures to overcome barriers hindering the adoption of innovative sustainable construction materials (ISCMs) in Nigeria, to strengthen local sustainable practices and support global goals, particularly SDG 9 (industry, innovation and infrastructure) and SDG 12 (responsible consumption and production). Design/methodology/approach A quantitative cross-sectional survey was conducted with 113 construction professionals in Lagos. Data were analysed using exploratory factor analysis (principal component analysis with varimax rotation) to identify barrier components, while analysis of variance and post hoc Tukey tests assessed differences across micro, small and medium-sized enterprises (MSMEs). Findings Three barrier components were identified: institutional and knowledge-based, capacity and regulatory and economic and resource. Lack of government support, limited training and poor awareness of ISCM benefits were most critical, particularly among small and medium-sized enterprises. Economic barriers were less influential yet evident. Perceptions differed significantly across organisational categories, indicating that MSMEs experience and prioritise barriers differently. Practical implications The results provide practical guidance for policymakers, industry associations, firms and suppliers. Revising building codes, strengthening enforcement, expanding capacity-building, fostering collaboration and promoting long-term value perspectives are essential to accelerate ISCM adoption in Nigeria. Originality/value This study moves beyond cost-centred perspectives by demonstrating the pivotal role of regulatory, cultural and technical barriers in emerging markets. It offers a contextualised understanding of ISCM adoption in Nigeria, with insights applicable to similar developing economies, thereby advancing a more resilient and sustainable construction industry.

Purpose This study aims to automate the visual inspection of piling sheets in water channel construction using artificial intelligence (AI). By employing image classification and object detection techniques, the research focuses on extracting and analysing geometric features to enhance the accuracy and efficiency of the inspection process. It also addresses key challenges associated with the unique characteristics of construction materials and the limited variability of available inspection datasets. Design/methodology/approach Convolutional neural networks (CNNs) with varying complexities are employed for image classification, across four and six classes, and for object detection of piling sheets in water channel environments. A dataset provided by Witteveen + Bos is preprocessed to generate training sets, and the CNN architectures are optimized for enhanced performance. The accuracy and efficiency of the proposed models are evaluated and compared against traditional manual inspection methods. Findings The AI-driven approach significantly reduces processing time, evaluating 40,000 images in just 11.9 h, compared to approximately one month using manual assessment. The 4-class classification model achieves an accuracy of 96%, while the 6-class model attains 72%. The object detection model produces a mean average precision (mAP) of 79%. These results meet the performance standards set by the Dutch company Witteveen + Bos, which demonstrate the effectiveness of AI in automating the inspection of piling sheets. Originality/value This study introduces a novel AI-based approach for assessing piling sheets, demonstrating substantial improvements over traditional inspection methods. It introduces a systematic evaluation of various CNN architectures and hyperparameters to optimize the models specifically for piling sheet inspection rather than relying on off-the-shelf solutions. The use of CNNs for both image classification and object detection adheres to relevant Dutch engineering standards. Notably, the reduction in processing time, from one month to around 12 h, represents a major advancement in the efficiency of civil engineering inspections.

Purpose This paper examines how platform economies extract value from the exclusionary dimensions of migration regimes to drive accumulation. Through the lens of racial capitalism, we analyze how informality functions as a key mechanism in shaping novel forms of racialization, labor stratification and devaluation. Design/methodology/approach This study draws on cross-sectoral qualitative research based on in-depth interviews with migrant workers in cleaning, care, delivery and multitask platforms in Madrid. We use a racial capitalism framework to explore the intersections between informality, exclusionary border regimes, platform labor and migrant agency. Findings Informality appears as a structural logic of platformization. We identify three critical ways in which platforms intersect with informality and precarious migration statuses: through account subletting practices, the amplification of racialized profiles assigned to specific types of work and the emergence of new forms of violence shaped by intersections of gender, race and migratory status. Nevertheless, we underscore the dual role of informality, not only as a driver for exploitation but also as a terrain where solidarities take shape. Originality/value The key contributions of this paper lie in its cross-sectoral analysis of platform labor, shifting the focus from specific working conditions to the structural dynamics inherent to platform economies and integrating an intersectional perspective into the study of labor experiences on digital platforms. We move beyond the conventional dichotomy between migrant vulnerability and traditional unionism, exploring alternative agencies and solidarity networks emerging within these contexts.

Purpose Embracing circular economy (CE) practices presents a promising pathway to promoting sustainability and improving the efficient use of limited resources and waste management in the construction industry. The purpose of this study is to explore the regulatory barriers that impede the adoption of CE practices in Türkiye’s construction industry and propose actionable strategies to overcome these challenges. Design/methodology/approach Drawing on a comprehensive literature review and a practitioner-focused survey, this study employs Importance-Adoption Quadrant Analysis (IAQA), together with descriptive and inferential statistics, to evaluate participants’ perceptions regarding the significance and current implementation levels of 14 identified regulatory strategies. Findings The research identifies key regulatory challenges in Türkiye, including a lack of supportive legislation, weak enforcement mechanisms and limited institutional support. Findings reveal a misalignment between the perceived importance of CE policies and their actual adoption, highlighting the need for robust financial incentives, clearly defined national targets and strategic infrastructure investments. Furthermore, statistically significant differences in perceptions of regulatory barriers across experience levels, professional backgrounds and company sectors highlight that challenges to CE adoption are highly context specific. Research limitations/implications The limitations of this study stem from the selected barriers and strategies used to analyze the adoption of CE in the construction industry, as well as its focus on a single country context, Türkiye. Originality/value This study advances understanding of regulatory barriers to circular economy adoption in Türkiye’s construction industry, offering new insights from a developing country context with evolving policy initiatives. By applying the Importance–Adoption Quadrant Analysis (IAQA) to regulatory strategies, the study introduces a novel methodological approach that prioritizes actionable solutions for overcoming regulatory challenges. The study contributes to theory and practice by providing a benchmark for comparative studies and delivering evidence-based recommendations for policymakers and industry practitioners to accelerate CE adoption.

Purpose This study explores how a public client as a focal firm enables value co-creation through orchestration that includes navigating and bridging knowledge, business and innovation ecosystems. Design/methodology/approach The research is based on qualitative methods, with 25 semi-structured interviews being conducted with client representatives and project partners from four completed construction projects. Findings This study shows how the orchestration of ecosystems for value co-creation in construction includes activities within and across projects. While business ecosystem activities in projects tend to be exploitative, knowledge ecosystem activities are typically exploratory, and innovation ecosystem activities make up for the transition from exploitation to exploration. Yet, the activities are not exclusive in this sense but entail varying degrees of exploration and exploitation. We show how a small public client firm that commissions new projects and owns its building stock can successfully orchestrate such activities. Guided by an internal strategy and long-term commitment, the firm assumes the role of a focal bridging actor and engages with multiple actors in all three types of systems. We identify key factors contributing to client success in achieving high innovation ambitions: finding suitable partners, fostering strong relationships throughout and among projects, continuously testing and capturing learning from innovation, and engaging with the industry. Originality/value This study shows how varying degrees of exploration and exploitation activities in business, knowledge, and innovation ecosystems within and across projects contribute to value co-creation in construction. We show how a small public client firm that commissions new projects and owns its building stock can successfully orchestrate such activities by taking an active role as a focal firm, bridging different types of ecosystems for value creation from innovation.

Purpose The potential of virtual reality (VR) to replicate real-life scenarios remains an emerging field of research. Despite the promise of VR, there are still limited studies validating immersive virtual environments (IVEs) against real environments (REs), particularly in terms of comfort and behavioral responses across varying activity intensities. The study aims to contribute by examining thermal comfort and adaptive behaviors in both REs and VEs during sedentary and high-intensity activities. Design/methodology/approach Observations were conducted for two activity types: reading/watching and fabrication/machine work, in both the RE involving 50 participants and in IVEs with 24 participants. Between- and within-subject designs were adopted for real/Unreg. and virtual/Reg. environments, respectively. Findings The findings revealed significant differences in thermal comfort and preferences between real and virtual environments, except for thermal sensation during sedentary activities. For high-intensity activity, significant differences were found in thermal sensation and preferences between the two environments, except for thermal comfort. Ecological validity was rated high, particularly regarding the lighting and general appearance of IVEs compared to RE. Originality/value The study gave an insight that thermal perception partially supports criterion validity for activity intensities, i.e., fair agreement between RE and IVEs, adaptive behaviors were supported in both environments and activity intensities. Further research can be used to explore a wider range of activity intensity. Additionally, a more comprehensive validation framework can be incorporated, which encompasses thermal, visual comfort, and behavioral responses in both real and virtual environments.