Dr Anderson Akponeware

The carbon assessment of infrastructure products are becoming increasingly important drivers for infrastructure acquisition and climate change response. This emphasises the importance of the rail infrastructure industry accurately assessing and reducing its greenhouse gas contribution. However, assessing the greenhouse gas impact of an infrastructure product is a fundamentally complex global issue. Traditional carbon assessment techniques in the UK railway industry face a number of well-known issues that not only impede the adoption of innovative assessment techniques, but may also jeopardise the industry's 2050 net-zero carbon commitment. Few studies have investigated the problem thoroughly. As a result, this study examines the perspectives of UK rail practitioners on the substantive factors impeding the adoption of integrated carbon assessment techniques. In this study, an empirical analysis based on 14 semi-structured interviews and thematic analysis was carried out. The results shed light on the underlying issues surrounding rail carbon assessment. The findings confirm that current carbon assessment regulations in the UK rail infrastructure industry, due to their lack of prescriptiveness, fall short of driving long-term carbon reduction. Our research also reveals widespread support for the development of standardised greenhouse gas assessment methodologies in order to provide reliable baselines for measuring emission reductions. To drive carbon reduction, we conclude that current carbon assessment techniques must be modified. In this paper, we propose a rail carbon knowledge model for organising organisational knowledge based on the policy, process, people, and technology dimensions. Integrating different perceptions of carbon assessment is a valuable starting point for improving current practices and achieving net-zero carbon targets.

Early collaboration is crucial if the final design is to be clash-free, and automation processes through Building Information Modelling (BIM) have the capacity to reduce clashes through 3D design coordination. Yet, current design practices are still dependent on clash detection and contemporary literature presents several reasons for this. This paper investigates the root causes of clashes with respect to achieving “clash avoidance” as proposed in PAS 1192-2 design phase specifications for BIM in the UK. Empirical data from BIM coordinators around the world was collected and analyzed using explanatory sequential mixed-methods. It was found that: (i) isolated working was the prime cause of high occurrences of clashes linked to mechanical, electrical and plumbing (MEP) 3D BIM systems; (ii) there is a link between non-BIM specific training (or the professional qualifications) of design practitioners with the high incidence of clashes; and (iii) the current structure of cloud-based common data environments (CDEs) does not facilitate clash avoidance and in fact, encourages isolated working in the early design stage by creating “digital information silos”. A conceptual framework for an open work in progress (OWIP) has been proposed to address this problem. These findings point to the need for more transparency during collaboration through CDE where designers from multidisciplinary backgrounds can engage in concurrent co-creation. This transparent and inclusive process could have consequences on how future architectural, engineering and construction (AEC) professionals are trained.

Urban growth is supported by “infrastructure,” which has a wide range of applications. Thus, there is an extensive and diverse body of study on infrastructure development. However, as infrastructure expands, user demands and needs expand and change as well. For this reason, it is critical for researchers to be able to include stakeholders while investigating such growth, appropriately interpret their needs, and reflect and receive feedback on these interpretations. Furthermore, the current global push towards net-zero and decarbonisation of infrastructure and energy systems calls for innovative solutions with minimal negative impact on the quality of life of their occupants. However, this will require massive infrastructure developments and improvements in key sectors such as: a) the housing sector; b) the retrofitting and transformation of the energy system towards cleaner and renewable energy; c) the water sector to improve and optimise the technologies and components used to deliver water to its customers; and lastly, d) the transportation sector to enable the transition of public transportation such as railways to move towards automation and digitalisation. This paper investigates and discusses the role and importance of stakeholder engagement in research from the perspectives of four different domains: 1) the housing domain, 2) the energy domain, 3) the water domain, and 4) the railway transportation domain. It then compares the four approaches and draws conclusions, thus adding to the evidence of the importance of stakeholder engagement and its role in increasing research impact. This paper has found that stakeholder engagement is challenging and recommends early stakeholder involvement. Furthermore, this paper recommends tailoring stakeholder engagement approaches to context-specific needs, though there are overarching principles that can be applied across sectors.

Decarbonising industrial clusters globally is crucial in combating climate change and is integral to the United Kingdom's ambition of achieving a net-zero economy by 2050. The absence of holistic frameworks that provide a nuanced understanding of the broad spectrum of mitigation options for decarbonising industrial clusters, coupled with a deficiency in real-world empirical evaluations, present a substantial barrier in realising set targets for reducing CO2 emissions. The increasing fragmentations in industrial decarbonisation frameworks further exacerbates the challenge of identifying the necessary and sufficient actions for achieving optimal industrial decarbonisation and net-zero transitioning. This paper proposes an assessment framework for industrial cluster decarbonisation and aims to address the existing gaps, particularly in the assessment of social, economic, and environmental impact of any deployed technology. Focusing on a wide range of technologies, sectoral strategies, and regional dynamics, the proposed framework is driven by specific key performance indicators and a comprehensive human and data-driven analytical approach that reflects descriptive, diagnostic, and prescriptive insights on the Teesside industrial cluster in the United Kingdom. Following the validation of the proposed assessment framework, empirical findings from 30 in-depth semi-structured interviews, two workshops, focus group meetings and the literature on industrial decarbonisation reveal that the framework recognises the complex interplay of technology and decision-making in the transition to net-zero of industrial clusters. The article concludes that the proposed assessment framework can assist stakeholders, policymakers, and researchers in assessing the impacts of energy transition, which is critical to policy design and decision-making while also contributing to achieving sustainable decarbonisation goals.

A key 21st century infrastructure challenge is lowering cost and carbon over an infrastructure’s whole lifecycle. But, accounting for the carbon footprint of a railway system is problematic due to the complexity of railway systems. Within the rail sector, there is still a lack of infrastructure frameworks which can accurately capture actions, interactions and associated processes by role actors during lifecycle analysis. Whilst there is increased focus to facilitate information digitisation in railway systems, there is a scarcity of literature which attempt to systematise and formalise the process of conducting lifecycle analysis (LCA) of railway systems. This paper identifies complexities associated with legacy LCA methodologies in the rail sector. It then proposes a methodology which applies design science techniques to facilitate the creation and re-use of information and data in a systematic way within a structured process workflow. The proposed methodology enables lifecycle information for a rail-track to be produced collaboratively in an integrated format. In addition, the proposed LCA technique allows the creation of LCA process workflows which can be deployed to the web, potentially integrating with other optioneering applications and BIM platforms.

The transition to sustainable construction introduces additional legal and contractual risks alongside traditional challenges such as cost overruns, delays, and disputes. While industry risk management frameworks and standards provide structured approaches to identifying and mitigating risks, their broad governance structures often fail to address the complexities of legal compliance, contract enforcement, and sustainability related liabilities in green building projects. Standard construction contracts, incorporate risk allocation mechanisms, however, their approaches to sustainability obligations, liability distribution, and dispute resolution remain inconsistent. This paper critically evaluates the effectiveness of these frameworks and contractual models in managing green building related risks. The review employed a traditional literature review, initially using a traditional approach to identify relevant research. However, the limited data set (n=4) prompted an expanded search strategy, ultimately yielding 60 documents for review. The analysis reveals that existing risk management standards, approaches and frameworks may lack sector specific risk assessment tools, and traditional contractual mechanisms often struggle to enforce sustainability obligations, leading to legal uncertainties and potential disputes. The findings advocate for the development of an integrated risk management model that aligns legal enforceability, liability allocation, and proactive risk mitigation strategies. The research contributes to the ongoing discourse on sustainable construction risk governance and provides a foundation for exploring legal and contractual risk management frameworks for the built environment.

Public building abandonment has a detrimental impact on the advancement of a nation such as Nigeria. Rebuilding such infrastructure sustainably poses several challenges, as identified in the literature. A flexible and dynamic approach is required by decision makers that draws on a range of attributes, alternatives and criteria. This study aims to assess a sustainable, accessible and flexible tool that decision makers can use in place of engaging with complex mathematical calculations and formulas. To test the validity of the tool, two sets of participants (first Demonstration/pilot study – 7 participants and second Demonstration/Expert Validation − 11 participants) were identified for the testing and the validation of the tool. A quantitative data collection approach, making use of a survey and a case study, was considered the most appropriate approach for this study following the demonstration of the model to the participants. From the four alternatives: Refurbishment, Conversion, Demolition and Outright selling, supported with embedded mathematical formulas and calculations, the validated tool presented refurbishment as the most flexible and optimal solution. This study argues that the integration of this tool into the redevelopment process enhances the recognition of a range of solutions for abandoned public buildings in Nigeria. In addition, it concludes that incorporating suitable model configurations into an appropriate tool can foster appropriate decision-making procedures.

The promotion of uptake of building information modelling (BIM) and circular economy (CE) in the UK and Turkiye construction sectors can be enhanced with the addition of AI. Thus, AI-enabled BIM and CE must be addressed from the viewpoint of current practices and capabilities. This study conducted a comparative study of capability maturity modelling (CMM) backed by a state-of-the-art (SOTA) review of 24 peer-reviewed publications via a validatory approach using a focus group webinar of eight experts in the UK and Turkiye. The findings, as extracted through a validated CMM framework of seven dimensions, were used to identify the position of the UK and Turkiye in terms of AI in BIM and CE. It was discovered that the UK is in a position regarding adoption, government policies and incentives at a defined level. AI growth is required in terms of technological advancement, education and training, industry readiness, cultural attitudes and resistance because they are in a managed phase. It was confirmed that Turkiye is at the initial stage of AI adoption, education, training, incentives, policies, technology and cultural attitudes. The originality of this study lies in the recommendations for a 10-year CMM adoption timeframe towards an optimised level. The conclusions of this manuscript will influence government, education, research and technological policies in the UK and Turkiye.

The UK construction sector has increasingly encountered cost management inefficiencies in overruns, errors, rework and variations. This study demonstrated how Generative AI (GAI), an emerging trend in digital construction, can foster large language models (LLMs) from the industry's historical data to predict costs. The process of developing the GAI system architecture applied the V-model and agile methodological approach and BIM templates. As used in the UK construction sector, the BIM templates considered data from building cost information service (BCIS) and task information delivery plan (TIDP) to develop the architecture. The system architecture designed in this study aligned with the RICS New Rules of Measurement 1 (NRM1) for early cost advice and text-to-task models. The implication of the GAI system architecture for digital cost management presented in this study elicited the integration of GAI with the BIM processes, offering substantial benefits to the construction industry. This includes streamlined workflows, reduced errors, and improved decision-making. The implications of the system architecture offer opportunities for increased BIM uptake in the UK and the sector globally.

Persistent gender disparities in science, technology, engineering, and mathematics (STEM) remain a global concern, but their occurrences vary markedly across socio-cultural and geographic contexts. This paper presents a systematic review of literature on gendered participation in STEM higher education in the United Kingdom and Ghana, with a focus on barriers, facilitators, and opportunities for reform. Using structured searches across peer-reviewed and grey literature (2015-2025), 33 studies were identified and synthesised through reflexive thematic analysis. Findings reveal persistent challenges: early subject segregation, entrenched stereotypes, micro-level bias, opaque leadership pathways, and uneven access to digital skills, employability support, and mobility opportunities. Geography shapes how these barriers are experienced-UK research emphasises implicit bias, prestige economies, and work-life constraints, while Ghanaian evidence highlights patriarchal norms, rural-urban inequalities, and resource limitations. Despite contextual variation, a shared set of facilitators emerges, including gender-responsive curricula, mentorship, gender-mainstreamed quality assurance, equitable AI/digital skilling, and targeted mobility schemes. The review also identifies critical research gaps, underscoring the importance of context-sensitive yet transferable strategies to advance gender-transformative policy, pedagogy, and institutional reform. We argue for a transversal learning approach-adapting effective practices bi-directionally-to inform gender-transformative policy and programme design that is locally responsive with transnational ties.