Despite substantial investments into new technologies, the adoption of systemic innovations such as construction robotics remains limited. Therefore, this study investigates the discrepancy between the assumed advantages of construction technologies and their actual performance during practical implementation, using construction robotics as the empirical case. Through an abductive thematic analysis of 127 interviews across Europe and North America, we identify six enablers of institutional misalignment: cognitive frame differences, divergent time horizons, conflicting market strategies, product versus revenue focus, varying risk tolerances, and information asymmetry. These misalignments between startup founders’ technological logic and investors’ economic logic constrain adoption, emphasizing the influence of institutional dynamics over technological feasibility. Our findings suggest these challenges are not unique to construction robotics but may extend to other emerging construction technologies. This highlights the critical need for aligning institutional logics to fully harness the potential of innovation in construction.

While most research in human-building-interaction looks at the interaction between humans and building automation, few studies question the agency of the building itself. This paper explores how blockchain technology can be combined with intelligent buildings to achieve self-ownership and self-agency. Using a design science research approach, a blockchain-based smart meditation cabin, the “no1s1” prototype, is iteratively designed, tested and evaluated. no1s1 demonstrates that a building can autonomously manage access, finances, and operation with minimal human oversight. These findings suggest that blockchain can redefine technical system design by embedding ownership and agency into the building itself. The findings encourage further exploration into decentralized coordination mechanisms within intelligent environments, such as combining blockchain with artificial intelligence and advanced sensing environments, to rethink the coordination, ownership and agency of cyber–physical systems in the built environment.

The management of lifecycle data poses significant challenges for the built environment, hindering effective transformation toward important concepts such as a circular economy. Many recent scholars propose blockchain technologies as a solution; however, there is almost no investigation into decentralized data networks, which also offer significant potential for lifecycle data management. This might be due to a lack of clarity in understanding the fundamental characteristics and potential use cases for decentralized data networks. Therefore, this paper combines a comprehensive review with inductive reasoning to classify three functional typologies—immutable, comprehensive, and privacy-centric – of decentralized data networks. Through testing with material passport data, we evaluate the practical implications of these typologies for lifecycle data management in the built environment. The findings highlight that decentralized data networks can improve data sovereignty and interoperability, but their effectiveness depends on use-case-specific trade-offs, such as mutability, access control, and storage location control. To navigate these trade-offs, the paper derives a decision framework that guides practitioners and researchers in selecting the most suitable decentralized data network. These insights contribute to a better understanding of decentralized technologies beyond blockchain and provide actionable recommendations for the future of data management in the built environment.

As the construction industry increasingly adopts digital technologies, recent studies emphasize digital twins as essential tools for managing construction projects and automating workflows. Although research has advanced the technical aspects of digital twins, there is a notable gap in examining human performance factors, particularly situation awareness – a cognitive process crucial for recognizing, comprehending, and anticipating changes in the work environment. With greater reliance on automation, neglecting this critical capability can lead to severe oversights, particularly during disruptions. To address this gap, we conducted a qualitative study grounded in a theoretical framework to explore the situation awareness requirements under different disruption scenarios in two contrasting construction contexts: offsite production and onsite assembly. First, drawing on 16 semi-structured interviews and non-participant field observations, we employ goal-directed task analysis to reveal the distinct information needs in each context. Second, through a comprehensive content analysis of the interview narratives, we identify the dynamics of gaining and maintaining situation awareness and provide digital twin design recommendations. Findings indicate that managers must shift from a macro-level overview to a micro-level detail in offsite production, requiring digital twin displays with adaptable granularity. In contrast, onsite assembly demands an intensely iterative approach to situational awareness, which calls for comprehensive real-time digital twin displays that support quick back-and-forth assessments. This study contributes by formalizing experts’ background knowledge, which can serve as a valuable basis for creating context-sensitive digital twin systems that better support human decision-making in offsite construction contexts and beyond.

Off-site construction has been a crucial part of industrializing the industry to realize higher productivity, better quality, and a more sustainable approach for constructing buildings. Off-site construction requires decomposing a floor plan into modules that can be in the form of either panelized walls or volumetric modules. However, the previous modularization models and approaches are limited due to their inability to consider the topological constraints of the modules, the flexible modularization of varying floor plans, and the mixed use of panelized walls and volumetric modules. As such, this paper proposes a graph-based optimization methodology for the hybrid modularization of building floor plans. The methodology was implemented using a multiobjective genetic algorithm that encodes and decodes the floor plan using novel graph modeling and operations. A visual programming script was developed to extract the wall properties, their adjacencies, and junction information from the building information model (BIM) of the floor plan. Time and cost estimation functions were developed to evaluate the hybrid strategies of panelized-volumetric modularization. The deployment of the methodology was demonstrated using an example floor plan design, which resulted in a spectrum of hybrid modularization plans ranging between fully volumetric and fully panelized solutions. For this specific example, the fully volumetric solution was 23% faster than the fully panelized solution but was 22% more expensive. The main contributions of this study are the topological modeling of module types, their floor plan postdesign flexible utilization, and the ability to explore hybrid modularization strategies. The findings of this study can prove useful for modular and off-site building manufacturers to improve their agility and increase their market share.

Effective collaboration is essential in construction. In addition to organizational science, anthropology, and law frameworks (see Chapters 2–4), a robust economic framework is needed for coordinating and incentivizing participants. The prevailing economic collaboration paradigm in construction scholarship is, however, limited, favoring classical market and hierarchical models. Construction economic collaboration often assumes one of these models, and then uses game theory to predict economic interactions. Yet, game theory’s limitations—its static nature, the overemphasis on rationality, neglect of transaction costs, and disregard for institutional contexts—suggest that a broader economic lens is necessary. [...]

The digitization and automation of contracts within the built environment through blockchain has demonstrated potential. Nonetheless, the use of on-chain smart contracts can amount to substantial costs. This study proposes a blockchain-governed approach to individually assess whether and how to use blockchain for different components of contracts. We explain the rationale behind the concept and implement a pilot prototype of a performance-based, blockchain-governed contract. The results promise an alternative and more cost-effective approach to smart or intelligent contracts in the built environment, while still allowing for trusted verification of key contract parts through blockchain.

Modularization aims to decompose a building or system into modules of components with controlled interdependencies to allow for the parallelization of their design tasks and the transfer of the work from the construction site to an efficient offsite manufacturing environment. However, these design and construction benefits of modular building decomposition may result in increased complexities that amplify the impact of design changes. This study proposes a quantitative methodology for assessing the complexity of hybrid building modularization strategies that combine the use of volumetric and panelized modules. The methodology integrates novel graph-based modeling schema, graph algorithms, a hybrid modularization modeling approach, and a structural complexity metric. The proposed methodology was assessed using an illustrative project case. The main contributions of this study is the development of a graph-based modeling approach for hybrid modularization and a quantitative approach for assessing the complexity of modularized buildings.

Digital Fabrication (DFAB) faces challenges in project delivery due to various barriers, such as its complex technical processes and unclear benefits. However, there is no specific research on project delivery methods for DFAB. This study conducts a comparative case study to understand the delivery of projects with varying degrees of DFAB implementation. Modularity theory is used as a lens to explore project delivery methods. This study tentatively proposes strategies for establishing potential project delivery methods for DFAB. The research identifies three key characteristics: 1) the adoption of modular products and processes, 2) the adoption of an integral type of project delivery method, and 3) the significant role of informal relationships in project delivery. The study finds that misalignment relationships at the product, process, and supply chain levels, namely the combination of modular products and processes with integral supply chains, have fostered flexibility and coordination in DFAB project delivery. Theoretically, this study discusses the symbiosis and interrelationship between modularity and integration within the context of project delivery. Practitioners can build on these strategies to establish project delivery methods.

Mobile factories promise an increased project efficiency with on-demand production and Just-in-Time delivery of prefabricated elements. However, traditional scheduling methods predominantly focus on either factory or site and neglect the factory mobility, often leading to suboptimal synchronization. To address this gap, this paper introduces a novel reinforcement learning (RL)-based model for optimizing the operational policy of mobile factories in infrastructure projects. The developed model simultaneously schedules on-site and off-site operations, effectively integrating the performance metrics at the project level. Utilizing RL, the factory's production management system continuously learns and adjusts in response to real-time project developments, ensuring optimal decision-making regarding scheduling and resource allocation.

Poor installation and misaligned supply chain incentives can impact the energy performance and user comfort of External Thermal Insulation Composite System (ETICS) panels. This paper investigates a combined IoT-blockchain solution to create trusted traceability of the process, together with performance-based incentives based on sensor data about the panel state. The system is implemented on the University of Brescia prototype, an experimental test house. The results demonstrate the feasibility of an integrated system of smart contracts, IoT sensors and a digital twin for visualization. The work provides insights into an IoT-blockchain solution applied to a real-world use case for supply chain process improvement.

The concept of circular economy (CE) has gained momentum in the construction industry to mitigate the effects of climate change and decouple economic growth from environmental impact. There is a growing body of research related to the circularity of specific construction materials, as well as to the entire building. However, there remains a lack of understanding at the construction product level, and this lack of transparency prevents informed decisions when choosing which products to use in projects and how those products support the CE. A maturity assessment is one methodology that can provide insights for both product decisionmakers and product suppliers. Maturity assessments are a way to evaluate the level of development or progress towards a certain goal, whether at the organization, project, or product level. This paper proposes a conceptual framework to assess construction product system circularity maturity. Through a systematic literature review, the authors analyze existing CE maturity assessments and CE indicators for construction products to develop the framework. The functional unit is defined as a construction product, which is defined as an integrated system with multiple materials (i.e. a prefabricated wall system). This research finds that while there are many CE assessment frameworks for the construction sector, these must be translated into a construction product context, which requires a tailored subset of circularity indicators and maturity levels. The paper proposes construction product maturity levels ranging from "initial" to "optimizing" for key circularity indicators at the construction product level, including, material procurement, manufacturing, product use phase, and end-of-life. This conceptual framework serves as a practical tool for decisionmakers and as an educational tool for suppliers on how to support the CE in construction.

The field of construction informatics is fragmented and lacks clarity in understanding the interconnection of different data management strategies. This makes it challenging to address industry-specific data management issues. Using a critical interpretive synthesis, this study reviews and integrates both present and emerging data management approaches in construction informatics. The review is meant to be comprehensive, encompassing technologies and concepts such as Open Schema, Information Container, Common Data Environments, Linked Data, as well as cutting-edge Web3 technologies such as blockchain and decentralized data protocols. The different approaches are identified and classified into five categories and mapped into a two-dimensional framework that considers data storage and data processing modes. The systematic categorization provides a simple, but comprehensive understanding of data management strategies in construction informatics. Moreover, the framework allows to identify the state of the art and trends of data management approaches, providing guidance for future research perspectives, especially in the intersection with Web3 technologies.

There are differences in implementing a design-build approach across the building construction, highway, and industrial sectors. These differences affect many aspects of a project, including the role of the design-integration manager. A design-integration manager is an employee of the designer-builder who serves as a bridge between design lead and construction manager. The role of a design-integration manager was explored through virtual research charrettes, surveys, and one-on-one interviews. Participants in these activities included academics and subject matter experts (SMEs) from industry with sector-specific knowledge on design-build. From the qualitative data collected, unique characteristics of the industrial and highway sectors were identified that differentiate their projects from projects in the building construction sector. The results show that the complexity of highway and industrial projects differs from building construction due to different factors such as project scope and size, construction phasing, and public involvement for highway projects. For industrial projects, facility design is dependent on process design, uncertainty in design persists longer, and time to market is extremely important. The results of this study show how the practice of design management in design-build will need to change to accommodate the differences between market sectors.

This paper presents a first conceptualization for decentralized project delivery through the combination of blockchain technology and common pool resource governance theory, also known as the ”crypto commons”. While previous literature on project delivery models identifies the use of decentralized governance, there is not yet a holistic conceptualization nor a specific overview of governance applications that can be applied. To develop the concept, we use a literature review to synthesize fourteen blockchain governance mechanisms useful for managing the crypto-commons. Subsequently, we use systematic combining to identify twenty-two specific applications for decentralized project delivery in the construction industry, one of the largest project-based industries. Each application is briefly reviewed, and examples of their relevance to realize decentralized project delivery models are provided. We discuss the potential for novel forms of project delivery, but also the need for future research on the applications, as well as on the system level implications, the system design challenges, and the implementation barriers in the specific context of the construction industry. Overall, the concepts and mechanisms presented provide a theoretical foundation upon which future researchers can use to design novel decentralized project delivery models.

In the rapidly evolving organisational fields of construction robotics and digital fabrication (DFAB), the pace of technological advancement contrasts with the slow rate of adoption within the industry. This discrepancy raises critical questions regarding the factors influencing the integration of these innovations into construction practices. In response, entering its concluding phase, this doctoral study reexamines the seminal frameworks that Kangari and Halpin (1990) and Brown and Katz (2009) established. This project aims to uncover the complex dynamics that govern the adoption of construction robotics and DFAB technologies by embracing multiple research paradigms. This approach acknowledges the multifaceted nature of technological integration, suggesting that barriers to adoption extend beyond technical considerations to encompass a broader range of socioeconomic, organisational, and cultural dynamics. [...]

Design for manufacturing and assembly (DfMA) is an engineering methodology which aims to increase ease of manufacture and efficiency of assembly by considering manufacturing and assembly constraints in the design process. However, current DfMA approaches in the construction sector are not automated enough to identify the design features that may cause project delay in real time. This leads to longer design cycle. Also, current scheduling algorithms rely on human intervention to generate activity network from a design output. Addressing these inefficiencies, we propose an interpretative machining learning model to predict the construction duration given a design output. More importantly, the same model identifies the design features that may cause the most delay in the project. The model is trained on a residential design dataset with various features, such as layout, geometry, and element typology. The output of the model is the project duration and an importance map, indicating the influence each feature of the given design has on the total project duration. The results from this model can considerably reduce the design cycle by supporting architects to create fabrication and assembly aware design even when they have little knowledge of production and assembly processes. This model will contribute to a novel computational approach for DfMA.

Purpose
Cross-laminated timber (CLT) is an innovative construction material that provides a balanced mix of structural stiffness, fabrication flexibility and sustainability. CLT development and innovation diffusion require close collaborations between its supply chain architectural, engineering, construction and manufacturing (AECM) stakeholders. As such, the purpose of this study is to provide a preliminary understanding of the knowledge diffusion and innovation process of CLT construction.

Design/methodology/approach
The study implemented a longitudinal social network analysis of the AECM companies involved in 100 CLT projects in the UK. The project data were acquired from an industry publication and decoded in the form of a multimode project-company network, which was projected into a single-mode company collaborative network. This complete network was filtered into a four-phase network to allow the longitudinal analysis of the CLT collaborations over time. A set of network and node social network analysis metrics was used to characterize the topology patters of the network and the centrality of the companies.

Findings
The study highlighted the scale-free structure of the CLT collaborative network that depends on the influential hubs of timber manufacturers, engineers and contractors to accelerate the innovation diffusion. However, such CLT supply collaborative network structure is more vulnerable to disruptions due to its dependence on these few prominent hubs. Also, the industry collaborative network’s decreased modularity confirms the maturity of the CLT technology and the formation of cohesive clusters of innovation partners. The macro analysis approach of the study highlighted the critical role of supply chain upstream stakeholders due to their higher centralities in the collaborative network. Stronger collaborations were found between the supply chain upstream stakeholders (timber manufacturers) and downstream stakeholders (architects and main contractors).

Originality/value
The study contributes to the field of industrialized and CLT construction by characterizing the collaborative networks between CLT supply chain stakeholders that are critical to propose governmental policies and industry initiatives to advance this sustainable construction material.

The challenge of implementing industrialized construction to achieve sustainable future-proof healthcare facilities is not only about construction methods themselves but also about how to shift design methodologies. COVID-19 has raised the attention of research and practices in using modular design and construction for healthcare facilities. However, the lifespan and functional differences between general and emergency healthcare facilities mean that their sustainable design requirements are not exactly the same. Drawing from 27 interviews and design review sessions with 19 international groups of experts, this research proposes a modular adaptable hospital design (MAHD) approach based on the Open Building Concept (OBC). This includes an evaluation framework composed of five design categories and 23 subcategories complemented with a set of design guidelines and it concludes by identifying a future implementation pathway. This research extends the implementation of OBC through theoretical contributions for modular and adaptable designs and practical guidelines for future design implementation.

Developing economies need to supply housing and ensure resource efficiency in the process. Industrialised construction, which increases productivity in construction, can be one means to deliver the needed housing. However, the resource efficiency of industrialised construction in developing economies is under-researched. This paper studies factors influencing resource efficiency in industrialised housing products from the perspective of value chain and environmental impact in Addis Ababa, Ethiopia; Nairobi, Kenya; and Cape Town, South Africa. Specifically, wall systems with varying degrees of industrialised construction implementation are studied. The study uncovers four main insights-first, the choice of materials influences the resource efficiency of industrialised wall systems; however, the current value chain does not promote the adoption of new materials. Second, products used for industrialised wall systems are imported and incur added transportation-related impacts and more. Third, industrialised construction wall systems often use lightweight materials and have the potential for disassembly; however, end users have reservations about such design strategies. Fourth, controlled production of wall systems reduces construction waste and increases the quality of products. Nevertheless, governments are currently promoting labour-intensive construction methods. Based on these insights, the paper concludes with recommendations, levers and action points for stakeholders to promote resource efficiency in industrialised construction adoption.