Ababio, B.K., Lu, W., Darko, A. and Agyekum, K. (2025), “A cross-economy examination of circular procurement implementation in construction: key drawbacks and strategies toward a sustainable built environment”, Smart and Sustainable Built Environment, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/SASBE-09-2024-0349
View Publication
Abstract
Purpose
Circular procurement (CP) systems have become essential in the face of resource scarcity, environmental degradation and the need for cost savings. However, its widespread adoption for construction projects has been notably slow. This study sets out to examine the barriers to CP implementation and explore potential solutions to accelerate its uptake within the global construction industry.
Design/methodology/approach
The study employs a quantitative approach to examine perspectives of 132 procurement experts from a split sample of two geo-economic contexts: developed and developing economies. It determines, categorizes and evaluates the barriers and strategies associated with CP implementation using descriptive statistics, principal components and comparative agreement analysis.
Findings
The findings revealed major impediments at different system levels including inadequate leadership and commitment for circular practices, little knowledge of CP opportunities, linear construction business setup and weak policies on circularity. These drawbacks were prevalent among experts from both geo-economic contexts. However, other barriers like cultural and industry behaviors were not commonly considered significant. Some effective strategies recommended by industry professionals were centered around organizational dynamics, industry nudging and financing, skill and cultural adaptation, and innovation and development mechanisms. The cross-economy comparison highlighted varying degrees of consensus in the significance of the strategies, indicative that approaches to dealing with challenges vary across economies.
Originality/value
This study, the first of its kind in the construction sector, offers insights into CP implementation dynamics, i.e. challenges and strategies relevant to different geoeconomic contexts. The comparative approach between developed and developing economies adds a unique dimension to the understanding of the peculiarities of CP adoptions and what strategies may apply.
Keywords
Circular procurement (CP); barriers; strategies; construction sector; geoeconomic context; comparative analyses
Shah, S.H., Haverkamp, J.A., Guzmán, C.B. et al. Beyond unintentionality: considering climate maladaptation as cyclical. Climatic Change 178, 77 (2025). https://doi.org/10.1007/s10584-025-03922-7
View Publication
Abstract
Climate adaptation is imperative; however, instances of maladaptation are increasingly documented in sectors and locations around the world. Despite the prevalence of maladaptation, researchers and intergovernmental actors, including the Intergovernmental Panel on Climate Change, consistently frame it as “unintentional.” Drawing from environmental injustice, critical development studies, critical race theory, and coloniality scholarship, we argue the impossibility of characterizing maladaptation—now a global-scale phenomenon—as an unintended consequence of well-intentioned adaptation planning. This paper reframes the (re)production of climate maladaptation as a foreseeable result of the unequal systems of colonial racial capitalism through which adaptation is implemented and refracted. Systems-level change that confronts uneven relations of power, rather than incremental institutional reform, can address the prevalence of maladaptation. Treated as such, tackling climate maladaptation becomes a “political project”— not merely a “planning project.”
Keywords
Climate maladaptation; climate vulnerability; transformative adaptation; Longue durée; colonialism, injustice
Feng, R., Li, G., Alberti, M., Wang, F., Liu, S., & Yu, G. (2025). Optimizing Urban Greenspace Landscapes to Mitigate Population Exposure to Extreme Heat in 21st Century Chinese Cities. Environmental Science & Technology, 59(11), 5510–5520. doi:10.1021/acs.est.4c11345
View Publication
Abstract
Urban greenspace (UGS) is a crucial nature-based solution for mitigating increasing human exposure to extreme heat, but its long-term potential has been poorly quantified. We used high spatial-temporal resolution data sets of urban land cover and population grid in combination with an urban climate model, machine learning, and land use simulation model to assess the impact of UGS on population exposure to extreme (high-heat exposure, HHE) and its potential spatial optimization strategies. Results showed that the UGS and HHE have a strong spatiotemporal dynamic coupling in 21st century Chinese cities. Moreover, UGS shrinkage increased the HHE by 0.58–1.15 °C, while UGS expansion mitigated it by 0.72–1.26 °C, both stronger in the SSP3–7.0 and SSP5–8.5 scenarios. Different from common impressions, spatial relationships, rather than quantities of UGS, are more influential (1.3–1.8 times) on HHE. Our solutions suggest that simply enhancing the spatial dynamic connectivity between patches can mitigate HHE by 9.1–21.1%, especially for the eastern and central cities. Our results provide an example of how to improve climate adaptation in urban ecological space designs and strongly promote research on optimal spatial patterns for future robust urban heat mitigation.
Keywords
Urban greenspace; extreme heat exposure; mitigation effects; optimization solution; future projection
Linyan Chen, Amos Darko, Fan Zhang, Albert P.C. Chan, Qiang Yang,Can large language models replace human experts? Effectiveness and limitations in building energy retrofit challenges assessment,Building and Environment,Volume 276,2025,112891, ISSN 0360-1323,
https://doi.org/10.1016/j.buildenv.2025.112891.
View Publication
Abstract
Retrofitting existing buildings is essential to improve energy efficiency and achieve carbon neutrality in the fight against global climate change. Large language models (LLMs) have recently attracted significant attention for their ability to process data efficiently. While LLMs have emerged as useful tools for various tasks, their potential to replace human experts in assessing building energy retrofit challenges remains unexplored. This research explores the potential of replacing human experts with LLMs by evaluating four mainstream LLM chatbots and comparing their performance against a human expert benchmark through semantic similarity and text correlation metrics. It answers the research question: can LLMs replace human experts in assessing the challenges to building energy retrofits? Prompt engineering techniques, including zero-shot and chain-of-thought (CoT) prompting, were employed to guide LLM responses. Results show that LLMs perform well in identifying challenges but are less reliable in ranking them. CoT prompting improves challenge ranking accuracy but does not enhance challenge identification. Incorporating domain-specific knowledge in prompts significantly enhances LLM performance, whereas prompts designed to simulate experts have notable limitations in improving LLM performance. Furthermore, there are no significant performance differences among LLMs, including their advanced versions. While LLMs can streamline the initial identification of building energy retrofit challenges, they cannot fully replace expert judgment in ranking challenges due to their lack of tacit knowledge. This research provides valuable insight into the capabilities and limitations of LLMs in the challenge assessment, offering practical guidance for industry practitioners seeking to integrate LLMs into their building energy efficiency practices.
Keywords
Large language model; Building energy retrofit; Challenges assessment; Prompt engineering; Generative artificial intelligence
Pineo, H., Moore, G., Barrantes Chaves, K., Cooper, E., Dianati, V., & Braithwaite, I. (2025). ‘Best practice’ for healthy urban development: learning from others while maintaining local responsiveness in an emerging planning specialism. Planning, Practice & Research, 1–28. https://doi.org/10.1080/02697459.2025.2475628
View Publication
Abstract
Lack of clarity about what ‘healthy’ urban development means, alongside financial and technical challenges, has slowed progress on health-promoting development. Case studies could support learning, however, scholars have been critical of their risks when they are applied without adequate consideration of required adaptations or alternatives. We explored how health is promoted through new development via a narrative synthesis of published cases and critically evaluated their value. Cases more frequently achieved sustainability goals than equity and inclusion goals. We conclude that case studies have particular value when shared in a manner that encourages critical examination and discussion, such as through storytelling.
Keywords
Health; wellbeing; planning; best practice; urban development
Bourassa, S.C., Hoesli, M., Mayer, M. and Stalder, N. (2025), “Reflections on hedonic price modeling”, Journal of European Real Estate Research, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/JERER-11-2024-0087
View Publication
Abstract
Purpose
This paper provides a critical history of residential hedonic price modeling, highlighting key issues and advances. It is based on the keynote address presented by the first author at the European Real Estate Society Annual Conference in Sopot (Gdańsk), Poland, in June 2024.
Design/methodology/approach
The core of the paper is a high-level review of the methodological literature, focusing on three issues: model specification, multicollinearity and functional form. This review is framed by an early example of hedonic price modeling and a current application. These examples demonstrate key issues and advances in hedonic price modeling.
Findings
Hedonic price research has expanded dramatically with the advent of personal computing. Increased availability of data has enabled better model specification. At the same time, the development of interpretable machine learning techniques has allowed much more flexible modeling of functional form. However, multicollinearity continues to be, by definition, an intractable problem.
Originality/value
This paper presents a review of residential hedonic price modeling intended to provide researchers with a useful high-level perspective on the topic. A case study of Gdańsk illustrates an approach to producing interpretable results from machine learning estimations.
Keywords
Hedonic modeling; house prices; specification issues; multicollinearity; functional form; interpretable machine learning; R31
Akerele, D. D., Aguayo, F., & Wu, L. (2025). Portland Limestone Cement in Concrete Pavement and Bridge Decks: Performance Evaluation and Future Directions. Buildings, 15(5), 660. https://doi.org/10.3390/buildings15050660
View Publication
Abstract
With the rising demand for sustainable infrastructure, addressing the limitations of Ordinary Portland Cement (OPC) is crucial, particularly for exposed structures such as pavements and bridge decks. Portland limestone cement (PLC) is a sustainable alternative that delivers environmental benefits and comparable performance. This study used a systematic review and meta-analysis with a random-effects model to evaluate PLC’s strength development, durability, and sustainability. The findings indicate that PLC generally matches or surpasses OPC in terms of compressive strength, freeze–thaw resistance, and sulfate durability. However, its setting time and early-age cracking require further optimization, especially in cold climates. Additionally, this study highlights the fire performance advantages of PLC and its enhanced chloride resistance. The analysis identified critical research gaps, including long-term field performance and regional adaptation to extreme environmental conditions. These findings contribute to a deeper understanding of PLC’s role in sustainable construction and offer future research directions on hybrid cements and admixture compatibility.
Keywords
Portland limestone cement (PLC); type 1L cement; concrete pavement; bridge deck; sustainability; low-carbon; CO2 reduction
Rashtian, Z., Manesh, M. T., Tahsildoost, M., & Zomorodian, Z. S. (2025). Data-driven real-time visualization of urban heat islands using mean radiant temperature for urban design. Energy and Buildings, 115470-. https://doi.org/10.1016/j.enbuild.2025.115470
View Publication
Abstract
The Mean Radiant Temperature (Tmrt), is a critical indicator for understanding urban thermal comfort and microclimate conditions, particularly in urban areas experiencing higher temperatures compared to rural surroundings. Tmrt is heavily influenced by urban morphology, including building layout, street design, and green spaces which alter airflow, shading, and heat retention. Evaluating geometry alternatives during the early design stages in urban neighborhoods is challenging due to lengthy simulations and the need for extensive expertise in physical models. Recent studies have employed data-driven methods for quick design comparisons and new urban layout evaluations, successfully predicting Thermal indicators of Urban heat Island phenomenon but often limited by the diversity of urban configurations inputs used in training datasets. To address these limitations, this study proposes a novel framework that uses machine learning models to predict Tmrt as the primary indicator. A comprehensive training dataset of 200 cases was generated in Rhino7 using Grasshopper, Ladybug, and Dragonfly plugins. Sensitivity analysis was conducted to assess the impact of input uncertainties on model predictions, and the model’s performance was validated against unseen configurations. Among six machine learning algorithms tested, the CatBoost Regressor achieved the highest accuracy, predicting Tmrt with an R2 = 0.93, RMSE = 4.30 °C, and MAE = 2.34 °C. Validation using 20 additional cases showed an accuracy of R2 = 0.71, RMSE = 3.34 °C, and MAE = 2.27 °C in predicting Tmrt heat maps for new urban configurations. This framework successfully enables real-time Tmrt heat map analysis in simplified cubic neighborhoods within a 3D environment. Additionally, it enhances the temporal and spatial resolution of thermal patterns predictions, offering rapid and detailed insights into various urban design alternatives.
Colburn, Gregg, and Rebecca J. Walter. Affordable Housing in the United States. Routledge, 2025.
View Publication
Abstract
Affordable Housing in the United States addresses the issue of affordability of housing, or the lack thereof, going beyond conventional policy discussions to consider fundamental questions such as: What makes housing affordable and for whom is it affordable? What are the consequences of a lack of affordable housing? How is affordable housing created? And what steps can be taken to ensure all people have access to affordable housing?
With the understanding that different households face different challenges, the book begins by breaking down the variables relevant to the study of affordable housing, including housing costs, household income, geographic location, and market forces, to help readers understand and quantify affordability at the individual and societal level. Part II examines the consequences of unaffordable housing, highlighting racial inequities in housing access and affordability, and multiple forms of housing precarity including eviction and homelessness. Part III explores the entities involved in providing affordable housing such as local and federal governments, regulatory agencies, non-profit organizations, and for-profit developers. In Part IV, case studies from US cities demonstrate the complex web of organizations, policies, and market conditions that influence housing affordability, revealing substantial regional variations in access and policy response. Part V proposes a future roadmap and outlines four potential states with radically different outcomes for the affordable housing system in the United States.
An ideal book for graduate and undergraduate courses in economics, public policy, real estate finance and development, sociology, and urban planning, this title will also be of value to professionals and policymakers seeking to understand and improve housing affordability and access.
Ruoniu (Vince) Wang, Wei Kang, Xinyu Fu, Do inclusionary zoning policies affect local housing markets? An empirical study in the United States, Cities, Volume 158, 2025, 105736, ISSN 0264-2751, https://doi.org/10.1016/j.cities.2025.105736.
View Publication
Abstract
In the face of a housing affordability crisis, many cities have adopted inclusionary zoning (IZ) policies to increase the supply of affordable housing. Yet, IZ remains a controversial local policy due to its varied and inconclusive effects on housing market outcomes. This study investigates this debate by adopting a quasi-experimental design with a national dataset of IZ policies in the United States. We find that, on average, IZ policies did not affect municipality-wide housing permits or rents. However, the implementation of IZ resulted in an average of 2.1 % increase in home prices. Our results also underscore the connection between IZ policy design and market outcomes: more stringent IZ policies (i.e., those that are mandatory and apply to the entire jurisdiction) led to a higher impact on home prices while mitigating the rent effect. Additionally, IZ's market effects varied based on market conditions and the time elapsed since policy adoption. We discuss these findings in terms of implications for policy design and planning practice.
Keywords
Inclusionary zoning; Housing market outcome; Policy effect; United States; Staggered Difference-in-Differences