Don Amila Sajeevan Samarasinghe

Purpose: This study aims to address the growing concerns surrounding the use of artificial intelligence (AI) in property valuation, particularly issues of transparency, trust and accuracy. This study focuses on aligning AI models with expectations to foster responsible adoption in real estate decision-making. Design/methodology/approach: A systematic literature review (SLR) of 44 peer-reviewed studies published between 2018 and 2025 was conducted. NVivo software was used for qualitative coding, and the political, economic, social, technological, legal and environmental framework guided the analysis of external factors influencing AI adoption. The study examined both technical model performance and stakeholder concerns. Findings: Random forest and support vector machines were most frequently applied in structured valuation tasks, while artificial neural networks were reported in contexts involving non-linear modelling and complex data patterns. Despite demonstrated predictive capabilities, policymakers and professional stakeholders placed greater emphasis on transparency, explainability and legal accountability. Identified trust-related challenges included algorithmic bias, limited model interpretability, regulatory ambiguity and insufficient integration of contextual factors. These findings informed the development of a hybrid AI valuation framework that integrates technological performance with governance mechanisms, contextual calibration and professional judgement to strengthen property valuation quality. Research limitations/implications: This study is limited by the absence of primary data from stakeholder interviews. The findings are based solely on published literature, which may not fully capture real-time industry perspectives or emerging on-the-ground challenges. Practical implications: The proposed framework offers a transparent, data-driven solution for valuers, investors and regulators, supporting better-informed decisions and encouraging ethical AI adoption in real estate. Originality/value: This study synthesises technical and stakeholder dimensions of AI in property valuation using a structured qualitative approach via SLR. It proposes a novel hybrid framework that integrates stakeholder trust factors with model precision to enhance both reliability and acceptance of AI tools.

Purpose: The purpose of this study is to identify the key barriers and opportunities shaping the age-friendly retrofitting of older residential buildings. Design/methodology/approach: A systematic literature review was conducted in accordance with Preferred Reporting Items for Systematic reviews and Meta-Analyses guidelines using Scopus and China National Knowledge Infrastructure databases. This review is primarily grounded in literature on urban older residential buildings in China, supplemented by relevant studies from New Zealand, Australia and other international contexts. Relevant keywords identified 114 records. The titles, abstracts, keywords and full texts of the publications were reduced to 75 eligible sources that were related to age-friendly retrofitting of older residential buildings. The contents of the 75 relevant publications were analysed to ascertain the key barriers and opportunities. A content analysis approach was adopted to understand the interaction among the barriers and opportunities. Findings: The study identified five key barriers, including “spatial and infrastructural limitations”, “financial challenges”, “policy fragmentation”, “insufficient assessment and standards” and “mismatch between needs and engagement”. In contrast, five opportunities emerged: “policy advancement”, “collaborative innovation”, “technological integration”, “innovation in care models” and “growing market”. Moreover, the findings indicate that these barriers and opportunities do not exist in isolation but interact in highly interconnected ways. Practical implications: A systemic analysis of the barriers and opportunities associated with age-friendly retrofitting can support more targeted resource allocation, enhance cross-departmental coordination and facilitate the more sustainable implementation of age-friendly retrofitting initiatives in practice. Originality/value: This review provides an interaction-oriented synthesis of how barriers and opportunities relate to one another throughout the age-friendly retrofitting process and, on this basis, synthesises two key research gaps: the lack of a pre-retrofit feasibility assessment framework and the lack of a standardised retrofit pathway guideline.

Natural and human-made hazards are increasing due to global warming and human activities. Occupant evacuation in complex buildings remains challenging due to unfamiliar building layouts, communication failures, and unpredictable occupant behavior. Therefore, this study aims to explore how integrating digital technologies enhances emergency preparedness, supports occupant decision-making during evacuation, and improves occupants’ situational awareness. We conducted a PRISMA-guided systematic literature review across Scopus, IEEE Xplore, and ProQuest Discover, analyzing 31 high-quality journal articles relevant to the research. The focus was on integrating digital technologies to support occupant situational awareness and evacuation outcomes. This review explores the integration of Internet of Things (IoT), Building Information Modeling (BIM), Virtual Reality (VR) /Augmented Reality (AR), Artificial Intelligence (AI), and Digital Twins (DTs) for emergency preparedness, supporting real-world applications. This review highlights three research questions: (1) Evaluate how current digital technologies affect occupant emergency preparedness in buildings; (2) Identify the challenges that limit the effectiveness of digital technologies across key emergency preparedness stages; (3) Understand how digital technologies can support occupant emergency preparedness. The review compiles evidence and presents a conceptual framework to support the integration of digital technologies into occupant-focused emergency preparedness, providing practical guidance for the future direction of risk management research.

3D printing has gained increasing interest as a revolutionary digital technology in the construction industry. This technology has been supported as an effective tool for improving construction efficiency. Through a previous systematic review study, we comprehensively analysed the benefits and challenges of 3D printing technology implementation in the construction industry. This paper will follow the findings of the review study, investigating supply chain management strategies and challenges in 3D concrete printing projects in conjunction with a questionnaire pilot study. This paper is part of an ongoing research programme focusing on the decision-making mechanism of construction supply chain management in 3D printing. The purpose of this study is to identify key challenges in 3D concrete printing and supply chain. This paper adopted data from a literature review and a questionnaire survey pilot study to investigate the challenges of 3D concrete printing implementation and its supply chain management in practical construction projects. A questionnaire survey was conducted with participants who have significant experience in the construction sector. The result of the Five-Point Likert scale questionnaire was statistically analysed and interpreted. As a result, the critical challenges of 3D concrete printing projects have been defined. The findings show that high initial investment, technology awareness, regulation support as well as workforce training significantly affect 3D printing implementation in the construction sector. The study result provides the research programme with practical data in 3D concrete printing practice. The findings of this paper support a follow-up study in discussing the decision-making of the 3D concrete printing supply chain.

The global construction industry faces mounting pressure to innovate for sustainability and efficiency, with 3D concrete printing emerging as a transformative technology. Despite its potential, significant challenges such as technological immaturity and insufficient policy support hider widespread 3DCP adoption. Drawing on lessons from the adoption of Building Information Modeling in the United States and Hong Kong, this paper addresses these policy gaps by developing a conceptual framework that facilitates 3D concrete printing adoption. Through a systematic review of 30 publications and a qualitative content analysis, this study identifies and synthesizes 17 key policy factors across six policy dimensions into a comprehensive framework. The findings underscore the critical role of sustainability, transformative technical development policies, and research and development initiatives in accelerating 3D concrete printing adoption. Additionally, the study highlights a policy shift from profit-driven strategies to eco-innovative and socio-environmental entity as the technology matures, particularly in its early development stages. The proposed conceptual policy framework provides actionable strategies for policymakers and industry stakeholders to address existing barriers and accelerate the widespread adoption of 3D concrete printing. A critical insight suggests that governments leadership, along with a shift to business models based on usage rights rather than ownership, could reduce financial burden on end users. This coordinated approach combining government leadership, targeted R&D support, eco-innovative policies, and new business models can establish 3DCP as a sustainable and scalable solution for future construction needs.

Property valuation is a critical component of real estate management, influencing decisions on investments, sales, and financing. Traditional methods, such as Linear Regression and Multiple Regression Analysis, often struggle to address the complexities of modern property markets. In response, Artificial Intelligence (AI) offers innovative solutions by utilising advanced models for more accurate predictions of property value. This paper presents a Systematic Literature Review (SLR) using Scopus database, focusing on 37 selected papers. It evaluates the effectiveness of key AI models in property valuation, assessing their predictive power, interpretability, robustness, and flexibility, and examines how well these models generate reliable valuations and their accuracy. The key models were referred to as the “Valuation Four”: Support Vector Machines (SVM), Random Forest (RF), Decision Trees (DT), and Regression Models (RM). The review highlights each model’s ability to handle complex real estate data, with SVM and RF demonstrating superior accuracy. At the same time, DT excels in interpretability, making it more user-friendly for decision-making. Regression-based models continue to serve as useful benchmarks but are less effective for intricate datasets. The findings of this study provide valuable insights for real estate professionals and policymakers by identifying the AI models that support precise and reliable property valuation on basis of dataset and factors considerations. This contributes to the ongoing evolution of automated valuation methods and helps advance data-driven decision-making in real estate.

3D concrete printing (3DCP) is increasingly used in construction due to its high speed, low waste, and geometric freedom capabilities. Researchers have signaled that 3DCP can help achieve long desired sustainability in the construction industry. Understanding the thermal behaviour of 3DCP based building elements could play a crucial role in attaining an energy efficient envelope, yet research on assessing the thermal behaviour of printed elements remains limited. This systematic literature review of records published between 2013 to 2023, provides a comprehensive overview of the thermal behaviour of several 3DCP-based materials and the important factors affecting heat transfer properties. The most common 3DCP materials with optimal thermal, mechanical and structural properties are geopolymers, phase change materials, fiber reinforced composites, polymer lattices, lightweight and foam concrete. Experimental analysis of heat transfer characteristics shows that 3DCP elements exhibit anisotropic tendencies due to a layered design and a specific fiber orientation. Thermal behaviour is expressed in terms of thermal conductivity (K value, W/mK) and overall heat transfer co-efficient (U value, W/m). Infill rate and pattern, relative density, printing speed, additive infusion, cavity fillers, geometric configurations, mix composition, surface irregularities, material fillers, and structural inhomogeneities are the main factors affecting the thermal behaviour of building elements. Effective control of the printing parameters, geometric optimization, and the correct balance of additives and fillers in the mix have the potential to lower thermal conductivity, providing an effective insulation blanket. Moreover, future research efforts could use standard techniques to interpret the thermal behaviour and the underlying factors.

This paper presents a systematic literature review of the opportunities and challenges of implementing 3D concrete printing (3DCP) in the construction industry. While 3DCP holds significant potential to improve construction processes by enhancing efficiency, sustainability, and design flexibility, its widespread adoption is hindered by several challenges. A structured review methodology was employed, analysing 58 peer-reviewed articles sourced from SCOPUS and Discovery databases, using the PRISMA guidelines for comprehensive screening and analysis. The findings are categorised using the PESTEL framework (Political, Economic, Social, Technological, Environmental, and Legal), offering a detailed perspective on the factors influencing 3DCP implementation. Key opportunities include improved time efficiency, cost-effectiveness, reduced material waste, and greater design flexibility. Conversely, significant challenges include the absence of standardised technical and legal frameworks, a shortage of skilled labour, high initial investment costs for machinery and materials, and limited available resources. These barriers present significant obstacles to adopting technology within the construction sector. This research highlights gaps in cost considerations, governmental support, and technological advancements. Addressing these gaps through industry collaboration, case studies, improved regulatory frameworks, and continued technological innovation could accelerate the adoption of 3DCP, enabling its integration into construction industry practices and fostering more efficient, sustainable, and innovative building processes. The findings contribute valuable insights for researchers, practitioners, and policymakers seeking new insights to overcome current challenges and maximise the potential of 3DCP technology in the construction sector.