Subgrade materials refer to the original ground underneath a road pavement, when these materials are made up of expansive soil it is referred to as expansive subgrade. Sometimes, these materials do not have sufficient capacity to support the weight of the road pavement and traffic load, which means they require some form of modification and re-engineering to enhance their load capacity. Chemical modification techniques using traditional stabilisers (such as cement and lime) have proved to be an effective means of subgrade stabilisation. However, high costs and environmental concerns associated with the use and production of these additives have highlighted the need for more sustainable and environmentally friendly substitutes. This study reviews the use of industrial by-products and other waste materials used for subgrade stabilisation, focusing on the sustainability of using processed wastes and how they alter the engineering properties of weak subgrade, compared to the use of cement and also reviews the availability of processed waste materials in quantities sufficient to meet the current demand for subgrade stabilisation. The findings illustrate that, processed waste is less expensive and has better sustainability credentials compared to cement. Moreover, processed wastes are available in sufficient quantities to meet existing demands for subgrade stabilisation. Therefore, it is recommended that the use of processed wastes should be promoted and utilised to improve and enhance the geotechnical properties of weak subgrade materials where possible.

Realisation of the sustainable development goals (SDGs) will provide improvements to people's lives and longevity of the planet. The architectural, engineering and construction (AEC) sectors have a potentially huge role in aiding the delivery of many SDGs; however, there appears to be a lack of research into the engagement within this sector. The leading environmental management system (EMS), ISO 14001, can enable organisations in the AEC sectors to improve their business operations, whilst minimising their impacts on the environment and improving society. Therefore, the study sets out to use institutional theory to determine the usefulness of ISO 14001 as a tool within the AEC sector and to demonstrate how the organisational benefits could facilitate the delivery of the SDGs. A stepwise PRISMA review process facilitated the compiling of academic articles and professional reports (n = 44), which enabled the creation of an inventory of the perceived benefits (n = 85) and the recognised barriers (n = 63) to implementing ISO 14001 across the AEC sectors. These barriers and benefits were confirmed by environmental practitioners as being relevant to the incorporation of an EMS. The most widely reported benefits within the AEC sectors were improving environmental performance and compliance with legislation. Lack of government pressure and lack of expertise were the most widely reported barriers, followed by cost to AEC organisations utilising an EMS. Following on from this inventory of benefits, it was possible to develop of a conceptual roadmap, which illustrates where linkages exist with the SDGs. SDG 4, 8, 12 and 13 are shown as exhibiting the most associations with the benefits. This roadmap was reviewed by AEC sector professionals who confirmed its usefulness. Therefore, it is surmised that the roadmap could aid strategic organisational sustainable planning or for organisations to demonstrate the delivery of their corporate social responsibilities.

Purpose: In spite of emerging research on building information modelling (BIM) capability assessment, there is a general dearth of knowledge about the links between often pre-emptive capability measurement attributes and actual delivery success. More so, current studies have not considered success from the wider construction supply chain (CSC) perspective. So far, the perceived importance of capability metrics is not based on post-project evaluations of their contribution to BIM delivery success. This paper aims to identify relevant BIM capability attributes used for qualifying CSC organisations for projects and further aims to investigate their relative importance and influence on some key aspects of BIM delivery success. Design/methodology/approach: Based on heretofore validated set of BIM capability attributes from semi-structured interviews and a Delphi study, a survey of CSC firms on BIM-enabled projects was used to model the influence of BIM capability attributes on BIM delivery success. Multiple regression modelling was performed to ascertain the nature of the relationship between BIM capability attributes and the key aspects of BIM delivery success as identified from the literature. Findings: BIM staff experience and the suitability of proposed methodology prior to project commencement were identified as the most influential on BIM delivery quality, as well as delivery within schedule and on budget. Conversely, the administrative and strategic-level capacities were found as the most influential in leveraging collaboration, coordination or integration of the CSC on projects through BIM. Originality/value: This study provides a step change in prioritising BIM capability criteria based on evidence of their contribution to delivery success in key performance areas, rather than their perceived importance as capability metrics as widely practised.

Purpose: Predictive digital twin technology, which amalgamates digital twins (DT), the internet of Things (IoT) and artificial intelligence (AI) for data collection, simulation and predictive purposes, has demonstrated its effectiveness across a wide array of industries. Nonetheless, there is a conspicuous lack of comprehensive research in the built environment domain. This study endeavours to fill this void by exploring and analysing the capabilities of individual technologies to better understand and develop successful integration use cases. Design/methodology/approach: This study uses a mixed literature review approach, which involves using bibliometric techniques as well as thematic and critical assessments of 137 relevant academic papers. Three separate lists were created using the Scopus database, covering AI and IoT, as well as DT, since AI and IoT are crucial in creating predictive DT. Clear criteria were applied to create the three lists, including limiting the results to only Q1 journals and English publications from 2019 to 2023, in order to include the most recent and highest quality publications. The collected data for the three technologies was analysed using the bibliometric package in R Studio. Findings: Findings reveal asymmetric attention to various components of the predictive digital twin’s system. There is a relatively greater body of research on IoT and DT, representing 43 and 47%, respectively. In contrast, direct research on the use of AI for net-zero solutions constitutes only 10%. Similarly, the findings underscore the necessity of integrating these three technologies to develop predictive digital twin solutions for carbon emission prediction. Practical implications: The results indicate that there is a clear need for more case studies investigating the use of large-scale IoT networks to collect carbon data from buildings and construction sites. Furthermore, the development of advanced and precise AI models is imperative for predicting the production of renewable energy sources and the demand for housing. Originality/value: This paper makes a significant contribution to the field by providing a strong theoretical foundation. It also serves as a catalyst for future research within this domain. For practitioners and policymakers, this paper offers a reliable point of reference.