The increasing adoption of industrialized offsite construction (IOC) offers substantial benefits in efficiency, quality, and sustainability, yet presents persistent challenges related to data fragmentation, real-time monitoring, and coordination. This systematic review investigates the transformative role of artificial intelligence (AI)-enhanced digital twins (DTs) in addressing these challenges within IOC. Employing a hybrid re-view methodology—combining scientometric mapping and qualitative content analysis—52 relevant studies were analyzed to identify technological trends, implementation barriers, and emerging research themes. The findings reveal that AI-driven DTs enable dynamic scheduling, predictive maintenance, real-time quality control, and sustainable lifecycle management across all IOC phases. Seven thematic application clusters are identified, including logistics optimization, safety management, and data interoperability, supported by a layered architectural framework and key enabling technologies. This study contributes to the literature by providing an early synthesis that integrates technical, organizational, and strategic dimensions of AI-driven DT implementation in IOC context. It distinguishes DT applications in IOC from those in onsite construction and expands AI’s role beyond conventional data analytics toward agentive, autonomous decision-making. The proposed future research agenda offers strategic directions such as the development of DT maturity models, lifecycle-spanning integration strategies, scalable AI agent systems, and cost-effective DT solutions for small and medium enterprises.

Access to quality public transportation is critical for employment, especially for low-income and minority populations. This study contributes to previous work on equity analyses of the U.S. public transportation system by including the 45 largest Metropolitan Statistical Areas (MSAs) in a single analysis. Year-2014 Census demographic data were combined with an existing 2014 dataset of transit job accessibility. Then, transit equality and justice indicators were developed and a regression analysis was performed to explore trends in transit job accessibility by race and income. The findings suggest that within individual MSAs, low-income populations and minorities have the highest transit job accessibility. However, the overall transit ridership is low, and in certain MSAs with high transit job accessibility both high and low income populations have high access levels but middle income populations do not. Within individual MSAs, on average, accessibility differences by income are greater than accessibility differences by race. The relative importance of race versus income for injustice increases with MSA size. In upper mid-size and large MSAs, differences by race increase. Also, the differences by race are greater among low-income populations. Accessibility-related equality and justice indicators are only one of many issues that comprise the wider discussion of equity.

In the year 2017, about 89% of the total energy consumed in the US was produced using non-renewable energy sources, and about 43% of tenant households were cost burdened. Local governments are in a unique position to facilitate green affordable housing, that could reduce cost burdens, environmental degradation, and environmental injustice. Nonetheless, limited studies have made progress on the costs and benefits of green affordable housing, to guide decision-making, particularly in small communities. This study investigates density bonus options for green affordable housing by analyzing construction costs, transaction prices, and spillover effects of green certifications and affordable housing units. The authors employ pooled cross-sectional construction cost and price data from 422 Low-Income Housing Tax Credit (LIHTC) projects and 11,016 Multiple Listing Service (MLS) transactions in Virginia. Using hedonic regression analyses controlling for mediating factors, the study finds that the new construction of market-rate green certified houses is associated with small upfront costs, but large and statistically significant price premiums. In addition, the construction of market-rate green certified houses has large and statistically significant spillover effects on existing non-certified houses. Existing non-certified affordable housing units show small and often insignificant negative price impacts on the transaction prices of surrounding properties. The study concludes that the magnitude of social benefits associated with green building justifies the local provision of voluntary programs for green affordable housing, where housing is expensive relative to its basic cost of production.

This article analyses the integration of green building with the largest low-income housing production programme in the US and the innovativeness of state housing agencies. Drawing on policy innovation literature, panel data and regression analysis are employed to quantify associations between state-level characteristics and the adoption of green building criteria into the Low-Income Housing Tax Credit (LIHTC) programme. Results show that housing agencies have increasingly adopted green building criteria, and most have identified co-benefits from energy-efficient buildings and smart growth. Despite overall progress, the rate of adoption of green building criteria has decreased, few US states have comprehensive criteria, and many have dropped important criteria, such as on-site renewable energy generation, often due to perceived additional costs to developers and, in some cases, due to perceived progress in building codes. Results are consistent with hypotheses derived from the literature and suggest that the integration of green building with the LIHTC programme is significantly associated with the states’ internal factors, such as public housing agencies’ motivations and resources, and external factors like regional policy diffusion from other states. Future research should explore organization-level factors that affect environmental policy innovation.