The construction sector is increasingly recognized as a critical domain in the pursuit of a circular economy (CE) (Adams et al. 2017). In the Netherlands, the landfilling of construction and demolition waste (CDW) is already minimized, underlining the transition outcome to CE, but most of the CDW is currently only processed low level recycling or backfilling (Azcárate- Aguerre 2023). Among the various strategies to circularity, reuse of construction products has shown particular promise, where materials and components are recovered, refurbished if necessary, and reintroduced into new or ongoing building projects(Tsui 2023; Van Uden et al. 2025). Yet, despite its potential, this approach faces a series of practical challenges that impede mainstream adoption: fragmented stakeholder networks, inconsistent or incomplete data about available used materials, and a general lack of robust, integrative logistics mechanisms (Tjahjono 2010). […]

There has been growing interest in the adoption of advanced digital technologies in the Architecture, Engineering and Construction (AEC) sector, as shown by the increasing number of review studies on the adoption of Digital Twin (DT) in the sector. While previous reviews on DT in the AEC sector have emphasised the technical opportunities and challenges, reviews that take a specific organisational and management focus on the use of DT are lacking. In this systematic review, we close this gap by analysing 102 papers from three main scientific databases (Google Scholar, Scopus and Web of Science), which emphasise organisational and management aspects of using DT in the AEC sector across the project and asset lifecycle phases. The findings indicate that, whereas there is still a stronger focus on finding optimisations for various performance concerns (e.g. project efficiency, health and safety and maintenance performance), there is increasing awareness and interest in using DT to encourage collaboration and (end-)user participation. Despite this recognition, our review also identified a number of critical knowledge gaps on the use and user perspectives of DT, which includes how powerful computational tools can be developed into user-friendly interfaces to reduce complexity and increase accessibility to all stakeholders in the decision-making process, and how participatory design frameworks can be combined with structured feedback systems and standardised data access protocols in order to stimulate communication, continuous improvement, and data-driven decision making.

As a tool serving other disciplines of enquiry, artificial intelligence (AI) offers the potential of a potent discovery, a design and analysis paradigm to address (new) questions in urban planning. This thematic issue raises a forum for cross-disciplinary dialogues at the intersection of urban planning and AI. Nine articles discuss both emerging use cases in urban planning practice and the relevant AI techniques being used and developed, as well as articulate the challenges associated. Future development of AI in urban planning shall address the ethical, inclusive, and just implications of AI applications for urban planning while navigating human and AI agents’ interactions and intra-actions to facilitate a better understanding of the intentions of AI development and use, and the impacts on the behaviour of designers and users in complex urban planning practices.

Energy-efficient renovation (EER) is a complex process essential for reducing emissions in the built environment. This research identifies homeowners as the main decision-makers, whereas intermediaries and social interactions between peers are highly influential in home renovations. It investigates information and communication barriers encountered during the initial phases of EERs. The study reviews AI tools developed within the EERs domain to assess their capabilities in overcoming these barriers and identifies areas needing improvement. This research examines stakeholders, barriers, and the AI tools in the literature for EERs. The discussion compares the functionalities of these tools against stakeholder needs and the challenges they face. Findings show that tools often overlook methodologies in human–computer interaction and the potential of textual and visual AI methods. Digital tool development also lacks insights from social science and user feedback, potentially limiting the practical impact of these innovations. This article contributes to the EERs literature by proposing an AI-supported framework and outlining potential research areas for future exploration, particularly improving tool effectiveness and stakeholder engagement to scale up the EER practice.

Heritage planning is changing, in both theory and practice. There is greater attention to the cultural significance (values and attributes) conveyed to a heritage property, rather than focusing on the property alone. Identifying and revealing this cultural significance has become a critical step in heritage planning. Moreover, international guidelines increasingly encourage public participation in defining the cultural significance of heritage sites. However, effectively involving diverse stakeholders and capturing the cultural significance they attribute to heritage remains a challenge, particularly when dealing with extensive datasets and multiple stakeholders. Although automated methods have shown potential in fields like digital humanities, their application in heritage planning is still limited. This article explores the innovative use of artificial intelligence (AI), particularly text classification analysis, to analyze unstructured textual data (e.g., policy documents, literature, and social media) to uncover the cultural significance of built heritage. Focusing on Yazd, Iran, and specifically on windcatchers—a key cultural attribute recognized for its “outstanding universal value” by UNESCO—this study integrates AI to enhance both urban and socio-cultural planning. This article, as the concluding piece of a broader research project, synthesizes the project’s findings to highlight AI’s potential for inclusive heritage planning, referencing related publications of the same project to provide context while remaining concise. The research is structured in three phases: first, a literature review on AI applications in participatory heritage planning and value-based heritage planning; second, the methodology for data collection and analysis, including coding and comparing values and attributes of windcatchers conveyed by different stakeholders; and third, findings on the values and attributes, and their interrelationships as revealed through the data. The results confirm that while there are both conflicts and alignments in the cultural significance attributed to windcatchers in Yazd among various stakeholders, the theoretical framework presented here offers a valuable tool for heritage planning. By decoding and measuring cultural significance from diverse perspectives, this framework aids in identifying conflicts and alignments and in better aligning stakeholder perspectives. This model can be adapted to other key attributes in Yazd and other case studies, offering broader applications in heritage planning. Additionally, the findings underscore the potential of AI to evaluate the legislative framework’s effectiveness in enhancing public engagement.

The transition to a circular economy necessitates cities to effectively manage their waste flows by capturing and redirecting them within the municipal domain. Traditional approaches to controlling waste flows have primarily relied on quantitative methods, such as material flow analyses. These methods excel in mapping the quantitative aspects of the materials and visualizing their sequential movements. However, recent advancements have highlighted the significant role of human behavior in shaping waste flows. For example, the way that citizens sort their waste determines the components and calorific value of the flows and directly impacts the circular rerouting challenges within the city. This paper argues that enhancing waste management practices in a circular economy requires analytical tools capable of incorporating the social dimension. Based on this premise, a novel approach termed the Waste Journey is developed and tested using a case study on household renovation waste in the Netherlands. Various methodological options to map the case are discussed and an initial framework for the Waste Journey is then proposed. The study emphasizes the influence of social processes on waste handling and offers a comprehensive means in which these processes can be mapped to effectively address challenges toward zero-waste cities.

Automatic design tools are being developed to assist designers handle tedious work at scale. However, knowledge gaps still exist in harnessing deep learning models to learn from human experience for more efficient design generation while keeping the data understandable and interoperable. Moreover, human-in-the-loop approach is largely neglected, which are essential for more user-centered design. This research utilizes graph data to parametrically represent housing designs and graph-representative deep generative models for design generation, which provides an interactive design approach for the users at every step. This method would facilitate the human-centered design process by returning feasible and parametric housing design alternatives.

The recent research focus on circular construction supply chains challenges the integration of supply chain processes. There is a need to build simulation tools for construction, facility management, deconstruction and reuse of building components. This paper introduces a model-based tool to enhance supply chain process integration developed with Business Process Mapping and Notation (BPMN). The model captures the remanufacturing supply chain for façade products that are demounted and reapplied in a different construction project. The paper highlights the tool’s potential for predictive analysis and decision support based on supply chain performances. The demonstration shows an innovative approach to CE-driven supply chains.

Artificial Intelligence (AI) has become one of the most dicussed topics of today and are being used to support solving complex problems. AI has given opportunities for efficiency, control, safety while raising issues around trust, optimism and responsibility. One of the prominent features of AI resides in the digitalization of the built environment. Optimizing the built environment to improve quality of life, adapt to climate change and respond to crises requires strategies to redesign, reproduce and manage the traditional ways the built environment has been shaped. In this chapter, we present demonstate how we can use AI for post-pandemic recovery. To do that, we first start with addressing digital transformation and the role of AI. We then discuss how we can accelerate this transformation in cities. We will reflect on the covid-19 crises and the impact of the crises in the built environment. We argue that the use of AI raises new possibilities, questions and problems around how we can better organize the built environment and more inclusive participation while supporting existing logics of the built environment.

The rural infrastructures require inclusiveness in the whole lifecycle (WLC) for the benefits of the society. The theory of inclusive growth has been widely studied since its introduction in the infrastructure system research. However, the majority of the related studies has focused on macro level measurements and no systematic research has been carried out on the microlevel for inclusiveness formation and impact path discovery so that detailed recommendations regarding the process can be formulated. The WLC of infrastructure is a dynamic process, reflected in different stages with various activities and multiple factor groups that connect and influence each other. To address and analyze this dynamic and interdependent process from a micro perspective, this study applies the logical framework method in constructing nine impact paths of rural infrastructure inclusiveness for the WLC, which revealed the influence mechanism of rural infrastructure inclusiveness at the microlevel. According to the results, "project quality"has the most significant influence on the rural infrastructure inclusiveness.

Public participation has been growing in both theory and practice of urban planning, including heritage planning. The reasoning is to facilitate the involvement of a broader group of stakeholders, beyond experts. More specifically, for heritage planning, participation could enable consensus-building on defining the significance of heritage, namely attributes (the resources that should be listed as heritage), and values (the reasons that attributes are important). However, there is not yet a holistic understanding of the influencing factors behind consensus-building in the participatory planning processes for cultural heritage. To evaluate existing research from this angle, a systematic literature review was conducted on peer-reviewed articles using the Scopus database. As most of the studies focuse on urban planning, this research examines the factors influencing consensus-building in the participatory planning process applied to urban and heritage planning and reflects on the applicability of these factors in heritage planning. The main factors were identified inductively and grouped into two categories: 1) public participation: actors, methods, and levels of public participation, and 2) consensus: approaches, and conflicts. The relations between these factors and their frequencies are investigated using statistical analysis methods, namely frequency analysis, independent-samples t-test, and Spearman correlation. The literature confirms that urban planning has applied more diverse methods and tools for public participation compared to studies in the field of heritage planning, and could inspire heritage planning. Conflict is recognized as an intertwined concept with consensus which is considered either as a challenge or as a necessity for an inclusive decision-making. By proposing a framework integrating these factors and sub-factors and illustrating their relationships, this research could also be useful for decision-makers and practitioners to better tailor the public participation process and means to implement it, considering the relevant factors involved.

This paper aims to investigate the theoretical and practical links between digital twin (DT) application in heritage facilities management (HFM) from a life cycle management perspective and to signpost the future development directions of DT in HFM.

This state-of-the-art review was conducted using a systematic literature review method. Inclusive and exclusive criteria were identified and used to retrieve relevant literature from renowned literature databases. Shortlisted publications were analysed using the VOSviewer software and then critically reviewed to reveal the status quo of research in the subject area.

The review results show that DT has been mainly adopted to support decision-making on conservation approach and method selection, performance monitoring and prediction, maintenance strategies design and development, and energy evaluation and management. Although many researchers attempted to develop DT models for part of a heritage building at component or system level and test the models using real-life cases, their works were constrained by availability of empirical data. Furthermore, data capture approaches, data acquisition methods and modelling with multi-source data are found to be the existing challenges of DT application in HFM.

In a broader sense, this study contributes to the field of engineering, construction and architectural management by providing an overview of how DT has been applied to support management activities throughout the building life cycle. For the HFM practice, a DT-cum-heritage building information modelling (HBIM) framework was developed to illustrate how DT can be integrated with HBIM to facilitate future DT application in HFM. The overall implication of this study is that it reveals the potential of heritage DT in facilitating HFM in the urban development context.

The mental health of older adults has become one of the major health challenges facing society today, which has attracted wide concerns from scholars in urban areas, but research in rural areas has been neglected. Therefore, this paper took rural older adult residents of 11 sample villages in Jintang County, Chengdu City, Sichuan Province, as the research object. After controlling the demographic characteristics of older adults in rural areas, this paper attempted to explore the effects of the rural built Environment on the mental health of older adults. Through field investigation in the sample villages, 515 valid questionnaires were obtained. The results from the Binary Logistic Regression Model show that good marital status, physical health, education level, well-constructed roads, and safe neighborhoods had significant positive effects on the mental health of rural older adults. Rural older adults who prefer to walk, cycle, and use public transport have better mental health, and accessibility to the periodic market, health station, bus station, village committee, supermarket, and the main road is positively correlated with the mental health of rural older adults, while the distance from home to the town center and coach terminal has a significant negative impact on the mental health of rural older adults. The research results provide a theoretical reference for further construction of rural aging environments.

To close the loop for the circular economy (CE) transition in the construction industry, forward logistics (FL) and reverse logistics (RL), as enabling operations for CE, are important topics to be addressed. However, current research mainly focuses on either FL or RL, with a lack of synthesis that presents an overview of the bi-directional logistics system integrating FL and RL and related mechanisms to close the loop. This review, therefore, explores the current cases of FL and RL in the construction arena through a systematic literature review (SLR) process. A review framework to synthesize and compare both FL and RL operations in various phases of the construction project life cycle (CPLC) has been established for this purpose. The phases include - in FL: design, manufacturing, construction, and operations; and in RL: deconstruction, product reuse, waste distribution, and material reprocessing. The review concludes that while similar methods and CE strategies are used in FL and RL, RL operations require more integration between supply chain actors to close the loop for CE in construction. The findings also indicate that more lateral integration between FL and RL phases beyond the life cycle and industrial boundaries is necessary for CE-driven construction projects, instead of only direct vertical integration with up- and down-stream partners. This review proposes a new conceptual framework of circular logistics integration (CLI) that consists of channel creation, network integration, and inventory management to guide and inspire future research in tackling the systematic barriers that hinder materials and resource flow from RL to FL in construction life cycles.

This paper focuses on the information and communication challenges in the Dutch energy transition in the built environment, with a specific focus on energy-efficient retrofits (EER) in homeowners’ associations (HOAs). The research surveyed the literature on barriers and drivers related to information and communication in EERs. It systematically investigated the information sources and communication channels provided by governmental and non-governmental institutions on financial subsidies, step-by-step guidelines, home evaluation tools, and participation guidelines. Lastly, the research categorised and evaluated the interfaces designed to deliver the information to the Dutch homeowners’ associations. The research also explored the barriers and drivers related to trust issues in EERs as the correlation between trust and information and communication emerged as one of the most prominent factors affecting EERs' acceptance. The paper analysed the online information sources based on readability, credibility, and interactivity, focusing on accessibility and the ability to generate tailor-made suggestions. The analysis revealed that the online information sources are disorganised and dispersed. The online platforms rarely provide information on prior case studies and more on financial subsidies, guidelines, and EER benefits. Lastly, we discussed the main barriers and potential solutions for these challenges.

To address the need for a shift from a linear to a circular economy in the built environment, this paper develops a semi-automated assistive process for planning building material deconstruction for reuse using sensing and scanning, Scan-to-BIM, and computer vision techniques. These methods are applied and tested in a real-world case study in Geneva, Switzerland, with a focus on reconstruction and recovery analysis for floor beam systems. First, accessible sensing and scanning tools, such as mobile photography and smartphone-based consumer-grade Lidar devices, are used to capture imagery and other data from an active demolition site. Then, photogrammetry and point cloud data analysis are performed to construct a 3D BIM model of relevant areas. The structural relationships between reconstructed BIM elements are evaluated to score the feasibility for recovery of each element. This study illustrates what is feasible and where further development is necessary for automating building material reuse planning at scale to increase the uptake of circular economy practices in the construction sector.

Facing circular transition challenges, building circularity should be evaluated in the early design phase to reduce the risks of circular and environmental performance problems found in later project phases. However, due to the current design workflow, such practice is hindered because there is not enough information to evaluate building circularity in detail in the early design phases. An improved workflow to emphasize circularity more in the early design phase is thus needed. This research explores the current workflow and designs an improved workflow by developing an automated decision support system to assess early design phase building circularity with limited available information, aiming to improve the working efficiency and efficacy. This automated system helps in data-driven decision-making by integrating different data sources and presenting the calculated results interactively with business intelligence interfaces. The interfaces involve different types of evaluations based on the data availability in both schematic design and detail design sub-phases. It also visualizes the data quality and future scenarios. This system has been designed based on interviews and literature studies, and verified and validated with practitioners. This study serves as a starting point to rethink the workflow to improve circularity with currently available technology.

Exploring the influence of settlement patterns on the landscape fragmentation in woodlands and biological reserves is key to achieving ecologically sustainable development. In this research, we chose the Nanshan National Park in Hunan Province, China, as a case study, to explore the influence mechanisms. First, we identified the biological reserves through the landscape security patterns of biological conservation. Second, we constructed a coupling coordination model to analyze the coupling relationship between the settlement patterns and landscape fragmentation in the woodlands and biological reserves. The analysis showed that, overall, the effect of the settlement area on the landscape fragmentation in the biological reserves was more pronounced, while the effect of the settlement spread and shape on the landscape fragmentation in the woodlands was more obvious. From a type-specific perspective, we analyzed the coupling relationship between the settlement patterns and (1) the landscape fragmentation in different woodlands and (2) the landscape fragmentation in the biological reserves, namely concerning Leiothrix lutea and Emberiza aureola. We found that the effect of the settlement patterns on the landscape fragmentation of the Leiothrix lutea biological reserve was more significant than that of the landscape fragmentation of its main habitat, the evergreen broad-leaved forest. The effect of settlement patterns on the landscape fragmentation of the Emberiza aureola biological reserve was more significant than that of the landscape fragmentation of its other habitats. In addition, the results demonstrated that the habitat protection of the woodlands was not a substitute for the systematic protection of biosecurity patterns. This research could assist in developing more efficient conservation measures for ecologically protected sites with rural settlements.

The COVID-19 pandemic period brings huge uncertainty, especially for the real estate sector. On the one hand, restrictions on the mobility of a population, decline in travel demands, popularization of remote work and education models caused doubts among investors questioning the future of the sector and the functions of real estate. On the other hand, the large supply of cash after the first waves of the pandemic and the upcoming increase in inflation resulted in many investors boldly investing cash in real estate, considering them as assets of stable value. This research aims to analyze the processes of value migration among real estate companies listed on the Warsaw Stock Exchange during this turbulent process. We analyzed the changes in the main drivers of value and the migration rates of the real estate sector based on data for 2018, 2019, 2020 and Q3 2021. The first period of the pandemic is the time of the collapse of the main profitability factors, sales and profitability of sales decline in the entire sector. However, the financial pillars of the analyzed companies are stable and we are not seeing signs of liquidity problems or a significant increase in debt. The second year of the pandemic is a significant reflection of most of the drivers of value, often to levels higher than those observed before the pandemic. Investors seem to remain insensitive to turbulent changes in accounting measures of effectiveness. We observe the relative stability of market measures. The processes of the migration of values from and to the sector do not show significant changes when comparing the periods before and during the pandemic. We observe various intensities of the studied phenomena in various groups of the real estate segment.

Sustainable development on a local scale requires well-functioning instruments in the spatial planning system. Any weakness in the planning system may result in forms of spatial development that are socially, environmentally or economically disadvantageous. Therefore, the aim of this study was to examine whether master plans and land development monitoring in the Polish system are effective instruments in shaping sustainable spatial development. The factor analyzed was the share of a biologically active area and four villages located near a regional city were analyzed. Data from master plans, cadaster and orthophoto maps were used in this study. Verification of land use made it possible to evaluate whether the properties meet the provisions of spatial planning documents. In each of the analyzed villages, properties that do not meet the provisions of master plans were identified. In one of the villages, more than half of the properties had a smaller share of biologically active areas than per-mitted by the local law. The research also analyzed alternative scenarios of the potential impact of the application of permanent vegetation on sealed surfaces. These results showed that using green roofs, for example, can significantly re-duce the problem of local laws being broken. The results quantitatively confirm that the provision of master plans in the Polish system are not effective tools in regulating land development.