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Purpose Small- and medium-sized enterprises (SMEs) within the construction sector are highly vulnerable to disruptions caused by political and economic decisions or even pandemics. This study evaluated the current operations of selected SMEs providing engineering design and consultancy services against Toyota Production System (TPS) lean tool. The purpose is to juxtapose SME operations and processes with TPS to ascertain the level of their operations conformity to the established TPS lean thinking tool. Design/methodology/approach This study used a qualitative data collection and analysis approach to evaluate the current processes of participating SMEs against Liker's 14 management principles of TPS. The data collected were analysed using thematic analysis to identify patterns and themes that emerged from the qualitative data. Findings The analysis revealed that focus on short-term goals, immediate profit and duplication of effort resulting from insufficient collaboration is currently creating waste in participating SMEs' operations. Hence, the implementation of TPS was recommended as a lean tool and a framework based on TPS lean tool was developed for improving the operations of SMEs. Research limitations/implications The study is limited to SMEs operating only as consultants providing project planning design within the construction industry. Data collection is limited to qualitative even though observations would improve the outcome of the study. Originality/value The study advances contemporary issues in promoting lean implementation in construction sector and developed an improved framework based on the TPS to enhance the performance of SME construction businesses.

The construction industry produces enormous volumes of construction waste that have a negative influence on the environment. This study examines the underlying causes of waste generation in the Indonesian construction industry based on professional perspectives. This study used a questionnaire as a research instrument and examined data with reliability and exploratory factor analysis. Based on the analysis, there are eight underlying causes that contribute to the generation of construction waste in the Indonesian construction sector. The five most significant underlying causes of waste generation that obstruct sustainable practices are waste-inducing site and human resources management approach, inadequate collaboration and support among stakeholders, equipment management approach, material logistics management, and poor working environment. As a result, it is crucial for Indonesian experts to pay attention to the factors that contribute to waste generation in order to lessen its negative effects on the environment and promote sustainable practices.

Purpose: Amidst all solutions posited to address sustainable construction practices in Nigeria, the implementation plans are repudiated by sustainable barriers. This study examines and confirms the strategy with the most significant impacts on the identified barrier to Sustainable Construction Practice (SCP). Design/Methodology/Approach: The study deployed a questionnaire survey to evaluate the perspective of 100 construction actors on the barriers and strategies of sustainable construction practice in Nigeria. Factor Analysis was employed to categorize key barriers and strategies into their underlying clusters for further analysis. Partial Least Squares Structural Equation Modelling (PLS-SEM) was used to confirm the constructs significant relationship and magnitude, thereby establishing the strategies with the highest impacts on the barriers to sustainable construction practices. Findings: The findings revealed three clusters of barriers and four groups of strategies to SCP, including techno-politic barrier, perception and awareness barrier, and sociocultural barrier. For the significant strategies, education and training, stakeholder regulation, incentive support and government and legislative support strategies were established. Overall, education and training strategy was identified as the most dominant and effective strategy to mitigate the barriers of SCP in Nigeria. Originality/Value: The paper establishes education and training as the key strategy to achieving sustainable quest in the AEC industry. The practical implication is that policy makers, educators and professional bodies can harness sustainable knowledge transfer through education and training to improve sustainable construction practices in Nigeria.

Purpose – In the past decade, transforming key processes and activities towards a more digital nature has been the focus of most industries due to the associated advantages. Despite that, organisations in the construction sector are lagging the list of early adopters. The slow rate of a fundamental digital transformation is linked to the challenges facing an effective leadership. The purpose of this paper is, therefore, to shed light on the barriers to digital leadership enactment in the construction industry. Limited research has empirically analysed and discussed these barriers to explain the low transformation rate in the existing body of knowledge. Design/methodology/approach – This paper empirically investigates the perspectives of construction industry professionals acquiring various roles in the industry. Overall, the study comprises the views of 38 participants, adopting a qualitative methodological approach to explore relative barriers and explain the slow digital transformation rate. Findings – Findings are grouped into five themes: leadership characteristics, management and organisational issues, resource constraints, technological issues, and risk perceptions. The findings are helpful to business leaders, researchers, trainers, and educators to develop measures to encourage leaders in the industry to be at the forefront of digital transformation in their organisations. Originality/value – Literature, however, is discreet in reflecting the challenges and barriers facing today’s leadership in facilitating digital transformation among construction stakeholders. This paper provides insights into the variables that may be undermining wider digital adoption across the construction sector’s organisations.

Due to the practical complexity and fragmented nature of the construction industry, digitalisation, like other innovations, is not easily achieved. This study aimed to explore organisational influences on digitalisation within construction firms. Due to the practical complexity and fragmented nature of the construction industry, digitalisation, like other innovations, is not easily achieved. This study aimed to explore organisational influences on digitalisation within construction firms. Construction professionals from twenty-two organisations provided their perspectives on digital transformation and their organisations. Under four constructs- structure, culture, leadership, and internal processes, findings uncovered sixteen determinants critical to digitalisation in construction firms. The study offers a offers a theoretical perspective supported by empirical data to explore the complex dynamics and internal interactions of organisational influence on the uptake of digitalisation in the construction industry. This paper offers arguments from a theoretical lens by applying the organisational influence model and capturing the variables under each construct in an exploratory manner to highlight the reasoning behind the low digital uptake in construction firms. This research aids academia and practice on the pressure points responsible for enhancing, or undermining, digital uptake in construction firms at an organisational level.

The fragmented nature of construction operations makes it challenging to implement carbon-reduction strategies. However, attaining a holistic construction sector decarbonisation hinges upon ensuring all aspects of a construction project’s lifecycle are decarbonised, including the construction process stage. Therefore, to mitigate the implementation challenge of reducing the levels of carbon involved in construction processes, this study attempts to synthesise and categorise carbon-reduction strategies that could be employed to decrease the carbon footprint during a construction projects’ delivery. To achieve the aim of this study, a systematic literature review approach was adopted. Based on this technique, a total of 26 relevant articles within the built environment research area were eligible for the study, and their analysis revealed 56 carbon minimisation measures, which were summarised into nine distinct categories to ease their application and overcome the construction operations’ complexities. The nine categories include material transport, waste transport, materials and equipment, waste, materials, on-site office, on-site lighting, on-site transportation of material and equipment, and construction methods. The findings of this study provide contractors with a suite of measures that can be deployed to reduce the carbon impact of construction project delivery.

Deconstruction is an innovative and sustainable option for building end-of-life. It can turn the negative impacts of demolition, including diverting valuable resources from the congested landfill into beneficial use through reuse and recycling. However, the feasibility of deconstruction has placed a massive limitation on the implementation of deconstruction. This research carried out a systematic literature review of 35 academic and 3 non-academic pieces of literature to develop a construct-based deconstructability framework. This framework – built around technical, economic, legal, operational, schedule and social construct – describes the condition under which deconstruction is likely to work and drivers influencing deconstructability. A total of 44 drivers influencing deconstructability were established and ranked from which design and building technology, cost including expense and revenues from the resale, supply and demand of the recovered component and material, the schedule for the deconstruction were identified as most influential. However, every identified driver should be considered during the deconstructability assessment of a building.

Structural retrofit of existing buildings for reuse remained one of the key steps toward decarbonisation of the existing housing stocks in the UK. This implies that any structural retrofitting procedure should aim at sustainability by ensuring net reduction in energy use with minimum cost, environmental and social impact. However, several factors impede the attainment of sustainable structural retrofit programs. In this study, quantitative data collection and exploratory factor analysis were used to investigate the factors that impede achieving sustainability in structural retrofitting of existing buildings. The study conducted a review of pertinent literature to draw up a list of potential impediments to sustainable structural retrofit. The lists were used to form Likert scale questionnaire that was administered to 126 professionals within the built environment sector in the UK. The data collected were subjected to reliability analysis and exploratory factor analysis using the SPSS IBM Statistics v24. The analysis revealed that there are four groups of barriers that impede sustainability in structural retrofitting of existing buildings. These are (i) cultural barriers involving factors that are characterised by human behaviour and interest; (ii) economic barriers involving cost functions; (iii) technical knowledge barriers involving education & skills factors and (iv) regulatory barriers involving legislation and policies around retrofitting old buildings. The findings of this study contribute to the broader discussion of sustainability within the built environment by increasing awareness of the key barriers to overcome to promote sustainable structural retrofit of existing buildings

Purpose The problem of long delay and waiting time in Disabled Facilities Grants (DFG) housing adaptation has been ongoing for years. This study aimed at constructing an innovative smart solution to streamline the housing adaptation process to prevent lengthy delays for disabled and elderly people. Design/methodology/approach The Adapt-ABLE approach is suggested based on a constructive research approach, where extensive theoretical development of the Adapt-ABLE concept is developed. It consists of four integrated platforms that undergo theoretical and analogical development and validations through applicable theories, a workshop, four brainstorming sessions and a focus group. Findings The proposed Adapt-ABLE approach utilises process optimisation techniques through an IT system for streamlining the process. The merits of the semi-automated system include the development of a preventive measure that allows measurement of suitability index of homes for the occupants, indicative assessment that shorten the application duration, procurement and contracting platform that utilises principles based on framework agreement and call-off contract, and a platform that standardised performance management for continuous improvement. Originality/value The Adapt-ABLE solution will cut the application journey of non-qualified applicants and suggest where help can be sought. The qualified applicants' application journey will also be shortened through an online indicative assessment regime and early online resources (means) testing. Overall, the proposed system reduces the waiting time, and timely delivery improves the applicant's quality of life by living independently. It will potentially save the NHS billions of pounds used to replace hips and residential care costs due to lengthy delays in the housing adaptations process.

Road traffic emissions are generally believed to contribute immensely to air pollution, but the effect of road traffic datasets on air quality predictions has not been clearly investigated. This research investigates the effects traffic dataset have on the performance of Machine Learning (ML) predictive models in air quality prediction. To achieve this, we have set up an experiment with the control dataset having only the Air Quality (AQ) dataset and Meteorological (Met) dataset. While the experimental dataset is made up of the AQ dataset, Met dataset and Traffic dataset. Several ML models (such as Extra Trees Regressor, eXtreme Gradient Boosting Regressor, Random Forest Regressor, K-Neighbors Regressor, and five others) were trained, tested, and compared on these individual combinations of datasets to predict the volume of PM2.5, PM10, NO2, and O3 in the atmosphere at various time of the day. The result obtained showed that various ML algorithms react differently to the traffic dataset despite generally contributing to the performance improvement of all the ML algorithms considered in this study by at least 20% and an error reduction of at least 18.97%. This research is limited in terms of the study area and the result cannot be generalized outside of the UK as many conditions may not be similar elsewhere. Additionally, only the ML algorithms commonly used in literature are considered in this research. Therefore, leaving out a few other ML algorithms. This study reinforces the belief that the traffic dataset has a significant effect on improving the performance of air pollution ML prediction models. Hence, there is an indication that ML algorithms behave differently when trained with a form traffic dataset in the development of an air quality prediction model. This implies that developers and researchers in air quality prediction need to identify the ML algorithms that behave in their best interest before implementation. This will enable researchers to focus more o

Cost overrun is a global issue plaguing transportation infrastructure projects, and the rail industry in the United Kingdom is not exempted. This industry plays a significant role in stimulating the country’s economic development and growth in the United Kingdom (UK). Understanding the factors contributing to cost overruns in rail projects is viable to sustain its contribution, especially in the COVID-19 epidemic era. This study analyzed and predicted the impact of cost overruns on rail projects in the UK in a COVID-19 pandemic era through a sparse network and system dynamics approach. It leverages a review of existing literature and perceptions of 80 construction professionals purposively to establish the factors affecting cost overruns affecting the UK rail construction sector. Findings reveal a web of causations that highlights labor productivity, delay in the supply of construction materials and equipment, and access to the site as fundamental predictors of cost overruns during a COVID-19 pandemic era. The resulting findings are beneficial to assist project managers with the needed awareness to strategically plan and mitigate the potential rise in cost overruns of rail projects in the UK during the pandemic.

Health and safety is an important issue in workplaces, and despite safety procedures becoming more strict, serious accidents are still happening within the UK construction sector. This demonstrates poor performance in the implementation of safety procedures on construction sites. One of the key challenges is the unwillingness of the site workforce, especially the subcontracted operatives, to adhere to safety provisions on construction sites. As such, this study investigates the strategies for enhancing safe behaviour among subcontracted operatives in the UK construction industry. The study used exploratory sequential mixed method research, involving interviews and questionnaires as means of data collection, and thematic analysis, reliability analysis and exploratory factor analysis as methods of data analysis. The study suggests that various carrot and stick measures are expected to be put in place as part of the strategies for enhancing safe behaviour among subcontracted operatives. These include adequate enforcement of safety practices by the management, operative engagement and motivation, commendation and rewards, site safety targets, leadership style and motivation. Application of the suggested measures could enhance safety on construction sites, as it provides practical measures and solutions for inculcating safety behaviours among the site operatives who are most likely to be the victims of site accidents.

Building energy efficiency is vital, due to the substantial amount of energy consumed in buildings and the associated adverse effects. A high-accuracy energy prediction model is considered as one of the most effective ways to understand building energy efficiency. In several studies, various machine learning models have been proposed for the prediction of building energy efficiency. However, the existing models are based on classical machine learning approaches and small datasets. Using a small dataset and inefficient models may lead to poor generalization. In addition, it is not common to see studies examining the suitability of machine learning methods for forecasting the energy consumption of buildings during the early design phase so that more energy-efficient buildings can be constructed. Hence, for these purposes, we propose a multilayer extreme learning machine (MLELM) for the prediction of annual building energy consumption. Our MLELM fuses stacks of autoencoders (AEs) with an extreme learning machine (ELM). We designed the autoencoder based on the ELM concept, and it is used for feature extraction. Moreover, the autoencoders were trained in a layer-wise manner, employed to extract efficient features from the input data, and the extreme learning machine model was trained using the least squares technique for a fast learning speed. In addition, the ELM was used for decision making. In this research, we used a large dataset of residential buildings to capture various building sizes. We compared the proposed MLELM with other machine learning models commonly used for predicting building energy consumption. From the results, we validated that the proposed MLELM outperformed other comparison methods commonly used in building energy consumption prediction. From several experiments in this study, the proposed MLELM was identified as the most efficient predictive model for energy use before construction, which can be used to make informed decisions about, manage, and

Due to the practical complexity and fragmented nature of the construction industry, digitalisation, like other innovations, is not easily achieved. This study aimed to explore organisational influences on digitalisation within construction firms. Due to the practical complexity and fragmented nature of the construction industry, digitalisation, like other innovations, is not easily achieved. This study aimed to explore organisational influences on digitalisation within construction firms. Construction professionals from twenty-two organisations provided their perspectives on digital transformation and their organisations. Under four constructs- structure, culture, leadership, and internal processes, findings uncovered sixteen determinants critical to digitalisation in construction firms. The study offers a offers a theoretical perspective supported by empirical data to explore the complex dynamics and internal interactions of organisational influence on the uptake of digitalisation in the construction industry. This paper offers arguments from a theoretical lens by applying the organisational influence model and capturing the variables under each construct in an exploratory manner to highlight the reasoning behind the low digital uptake in construction firms. This research aids academia and practice on the pressure points responsible for enhancing, or undermining, digital uptake in construction firms at an organisational level.

The recent surge in light emitting diode (LED) lighting retrofitted into schools in the UK is as a result of the UK Government’s 2050 zero carbon pledge. However, the benefits and consequences of LED retrofit projects for staff and enablers and stakeholder knowledge gaps about LED lighting retrofitting have not been fully explored. The aim of this research is to determine the amount of savings in cost, carbon reduction and kilowatt usage and to confirm if repayment from energy and cost savings derived from LED retrofit school projects funded through the SALIX funding option in the UK would be enough to service the loan. Thus, it examines monetary and non-monetary benefits, internal project stakeholder knowledge gaps and the consequences of LED retrofit for the staff and enablers of a large community college in the UK which is funded through the SALIX funding option. Design/methodology/approach: The methodology relied on a hybrid research approach of a case secondary school through the review of literature, analysis of secondary data, focus group and questionnaire survey. The focus group consists of six key project stakeholders. The secondary data was sourced from the Project IGP [Individual Grade Proposal] and the Positive Energy Report from Zenergi, and the closed online questionnaire survey was used to sample 150 teaching staff and school enablers. Findings: The findings show that stakeholders lack project knowledge, trust and expertise/project comprehension. This is in terms of baseline information, LED technology/management, payback modalities, management of risks and ethical issues around environmental impact. The forecasted SALIX savings were not achieved in real-time, partly because it does not take into consideration the increase in energy costs over the payback period. However, the LED retrofit creates efficiencies; drives down energy costs and energy usage; and drives carbon reduction, helping pupils’ learning, improving productivity and performance, and f

The contribution of smart campuses to smart cities’ development and vice versa has been elucidated in extant literature. The micro-transfer of smart technologies and probable procurement and contracting models remain critical for such contributions to take place. This study used a systems thinking approach to establish the interrelationships existing between smart campus technologies which can be scaled towards the development of smart cities and assess the critical failure factors negating the micro-transfer of these technologies to smart city development initiatives in developing countries. To achieve its objective, the study adopted a phenomenological research design wherein qualitative data was elicited from a purposively selected sample of seven interviewees in South African Universities. The next phase of the analysis involved a thematic approach for the production of a causal loop diagram (CLD) reflecting the interrelationships between the abovementioned facets and the associated impact on the transference of knowledge and technologies from smart campuses to smart cities. This CLD was subsequently validated by a cohort of five experts. Findings from the validation phase were incorporated in an improved CLD which provided different archetypes for engendering successful transference. This study holds salient implications for universities, cities and other stakeholders seeking to engage in a quadruple helix innovative arrangement for smart campus/city development. This study concluded that smart campuses could act as living labs for future smartness of cities globally. Government funding and willingness to produce smart cities from campuses is a fundamental feature of creating smart infrastructure in cities.

Sustainable development can be attained at a microlevel and having smart campuses around the world presents an opportunity to achieve city-wide smartness. In the process of attaining smartness on campuses, the elements requiring attention must be investigated. There are many publications on smart campuses, and this investigation used the bibliometric analysis method to identify such publications produced over the last decade. A matrix of 578 nodes and 3217 edges was developed from 285 publications on smart campus construction and procurement. Fifteen cluster themes were produced from the bibliometric analysis. The findings revealed that China contributed 48.4% of all published articles on the smart campus. The findings presented a framework from the cluster themes under the four broad infrastructure areas of building construction or repurposing, technology and IT network, continuous improvement, and smart learning and teaching management. The implications of the findings identified that IT project management, traditional procurement strategy, and standard forms of contracts such as the New Engineering Contract (NEC) and the Joint Contract Tribunal (JCT) are applicable in the procurement of smart cities.