Outputs (101)

Big data innovation and implementation in projects teams: Towards a SEM approach to conflict prevention (2024)
Journal Article
Owolabi, H., Oyedele, A. A., Oyedele, L., Alaka, H., Olawale, O., Aju, O., …Ganiyu, S. (in press). Big data innovation and implementation in projects teams: Towards a SEM approach to conflict prevention. Information Technology and People, https://doi.org/10.1108/ITP-06-2019-0286

Purpose: Despite an enormous body of literature on conflict management, intra-group conflicts vis-à-vis team performance, there is currently no study investigating the conflict prevention approach to handling innovation-induced conflicts that may hin... Read More about Big data innovation and implementation in projects teams: Towards a SEM approach to conflict prevention.

Conversational artificial intelligence in the AEC industry: A review of present status, challenges and opportunities (2023)
Journal Article
Saka, A. B., Oyedele, L. O., Akanbi, L. A., Ganiyu, S. A., Chan, D. W., & Bello, S. A. (2023). Conversational artificial intelligence in the AEC industry: A review of present status, challenges and opportunities. Advanced Engineering Informatics, 55, 101869. https://doi.org/10.1016/j.aei.2022.101869

The idea of developing a system that can converse and understand human languages has been around since the 1200 s. With the advancement in artificial intelligence (AI), Conversational AI came of age in 2010 with the launch of Apple's Siri. Conversati... Read More about Conversational artificial intelligence in the AEC industry: A review of present status, challenges and opportunities.

Performance evaluation of deep learning and boosted trees for cryptocurrency closing price prediction (2022)
Journal Article
Oyedele, A. A., Ajayi, A., Oyedele, A., Bello, S., & Oyedele, L. (2023). Performance evaluation of deep learning and boosted trees for cryptocurrency closing price prediction. Expert Systems with Applications, 213(Part C), Article 119233. https://doi.org/10.1016/j.eswa.2022.119233

The emergence of cryptocurrencies has drawn significant investment capital in recent years with an exponential increase in market capitalization and trade volume. However, the cryptocurrency market is highly volatile and burdened with substantial het... Read More about Performance evaluation of deep learning and boosted trees for cryptocurrency closing price prediction.

Robotics in construction: A critical review of the reinforcement learning and imitation learning paradigms (2022)
Journal Article
Davila Delgado, M., & Oyedele, L. (2022). Robotics in construction: A critical review of the reinforcement learning and imitation learning paradigms. Advanced Engineering Informatics, 54, Article 101787. https://doi.org/10.1016/j.aei.2022.101787

The reinforcement and imitation learning paradigms have the potential to revolutionise robotics. Many successful developments have been reported in literature; however, these approaches have not been explored widely in robotics for construction. The... Read More about Robotics in construction: A critical review of the reinforcement learning and imitation learning paradigms.

Internet of things and machine learning techniques in poultry health and welfare management: A systematic literature review (2022)
Journal Article
Ojo, R. O., Ajayi, A. O., Owolabi, H. A., Oyedele, L. O., & Akanbi, L. A. (2022). Internet of things and machine learning techniques in poultry health and welfare management: A systematic literature review. Computers and Electronics in Agriculture, 200, Article 107266. https://doi.org/10.1016/j.compag.2022.107266

The advent of digital technologies has brought substantial improvements in various domains. This article provides a comprehensive review of research emphasizing AI-enabled IoT applications in poultry health and welfare management. This study focused... Read More about Internet of things and machine learning techniques in poultry health and welfare management: A systematic literature review.

A deep learning approach to concrete water-cement ratio prediction (2022)
Journal Article
Oyedele, L., Bello, S., Olaitan, O. K., Olonade, K. A., Olajumoke, A. M., Ajayi, A., …Bello, A. L. (2022). A deep learning approach to concrete water-cement ratio prediction. Results in Materials, 15(September 2022), Article 100300. https://doi.org/10.1016/j.rinma.2022.100300

Concrete is a versatile construction material, but the water content can greatly influence its quality. However, using the trials and error method to determine the optimum water for the concrete mix results in poor quality concrete structures, which... Read More about A deep learning approach to concrete water-cement ratio prediction.

A scalable deep learning system for monitoring and forecasting pollutant concentration levels on UK highways (2022)
Journal Article
Akinosho, T. D., Oyedele, L. O., Bilal, M., Barrera-Animas, A. Y., Gbadamosi, A. Q., & Olawale, O. A. (2022). A scalable deep learning system for monitoring and forecasting pollutant concentration levels on UK highways. Ecological Informatics, 69, Article 101609. https://doi.org/10.1016/j.ecoinf.2022.101609

The construction of intercity highways by the government has resulted in a progressive increase in vehicle emissions and pollution from noise, dust, and vibrations despite its recognition of the air pollution menace. Efforts that have targeted roadsi... Read More about A scalable deep learning system for monitoring and forecasting pollutant concentration levels on UK highways.

Life cycle optimisation of building retrofitting considering climate change effects (2022)
Journal Article
Luo, X. J., & Oyedele, L. O. (2022). Life cycle optimisation of building retrofitting considering climate change effects. Energy and Buildings, 258, 111830. https://doi.org/10.1016/j.enbuild.2022.111830

Novelty: Climate change has significant impacts on building energy performance. A novel life cycle optimisation strategy is developed for determining optimal retrofitting solutions for office buildings with climate change effects taken into considera... Read More about Life cycle optimisation of building retrofitting considering climate change effects.

A self-adaptive deep learning model for building electricity load prediction with moving horizon (2022)
Journal Article
Luo, X., & Oyedele, L. (2022). A self-adaptive deep learning model for building electricity load prediction with moving horizon. Machine Learning with Applications, 7, Article 100257. https://doi.org/10.1016/j.mlwa.2022.100257

A self-adaptive deep learning model powered by ranking selection-based particle swarm optimisation (RSPSO) is developed to predict electricity load in buildings with moving horizons. The main features of the load prediction model include its self-ada... Read More about A self-adaptive deep learning model for building electricity load prediction with moving horizon.

Construction site layout planning methods: An analytical review (2021)
Conference Proceeding
Otukogbe, G., Oyedele, L., Akanbi, L., Manuel Davila-Delgado, M., Owolabi, H., Ganiyu, S., …Kadiri, K. (2021). Construction site layout planning methods: An analytical review. In Proc. of the IDoBE International Conference on Uncertainty in the Built Environment: How can we build a resilient future in the new normal?

Designing an effective construction site layout planning is essential to the successful implementation of construction projects. Construction site layout planning involves the optimal layout of facilities (i.e., fixed, and temporary facilities). Seve... Read More about Construction site layout planning methods: An analytical review.

Integrated life-cycle optimisation and supply-side management for building retrofitting (2021)
Journal Article
Luo, X., & Oyedele, L. O. (2022). Integrated life-cycle optimisation and supply-side management for building retrofitting. Renewable and Sustainable Energy Reviews, 154, Article 111827. https://doi.org/10.1016/j.rser.2021.111827

Building retrofitting is a powerful approach to enhance building energy performance. The net-zero ambition urges the need to renovate building energy system in view of the life-cycle optimal, to address climate and environmental challenges. Existing... Read More about Integrated life-cycle optimisation and supply-side management for building retrofitting.

Rainfall Prediction: A Comparative Analysis of Modern Machine Learning Algorithms for Time-Series Forecasting (2021)
Journal Article
Barrera Animas, A., Oladayo Oyedele, L., Bilal, M., Dolapo Akinosho, T., Davila Delgado, J. M., & Adewale Akanbi, L. (2022). Rainfall Prediction: A Comparative Analysis of Modern Machine Learning Algorithms for Time-Series Forecasting. Machine Learning with Applications, 7, Article 100204. https://doi.org/10.1016/j.mlwa.2021.100204

Rainfall forecasting has gained utmost research relevance in recent times due to its complexities and persistent applications such as flood forecasting and monitoring of pollutant concentration levels, among others. Existing models use complex statis... Read More about Rainfall Prediction: A Comparative Analysis of Modern Machine Learning Algorithms for Time-Series Forecasting.

Assessment and optimisation of life cycle environment, economy and energy for building retrofitting (2021)
Journal Article
Luo, X. J., & Oyedele, L. O. (2021). Assessment and optimisation of life cycle environment, economy and energy for building retrofitting. Energy for Sustainable Development, 65, 77-100. https://doi.org/10.1016/j.esd.2021.10.002

Building retrofitting plays a vital role in realising net-zero carbon ambition. Conventional retrofitting solutions are generally based upon decreasing operating energy usage or corresponding costs. However, many of these would increase the embodied... Read More about Assessment and optimisation of life cycle environment, economy and energy for building retrofitting.

Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges (2021)
Journal Article
Abioye, S. O., Oyedele, L. O., Akanbi, L., Ajayi, A., Davila Delgado, J. M., Bilal, M., …Ahmed, A. (2021). Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges. Journal of Building Engineering, 44, Article 103299. https://doi.org/10.1016/j.jobe.2021.103299

The growth of the construction industry is severely limited by the myriad complex challenges it faces such as cost and time overruns, health and safety, productivity and labour shortages. Also, construction industry is one the least digitized industr... Read More about Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges.

Deep learning with small datasets: Using autoencoders to address limited datasets in construction management (2021)
Journal Article
Davila Delgado, M., & Oyedele, L. (2021). Deep learning with small datasets: Using autoencoders to address limited datasets in construction management. Applied Soft Computing, 112, Article 107836. https://doi.org/10.1016/j.asoc.2021.107836

Large datasets are necessary for deep learning as the performance of the algorithms used increases as the size of the dataset increases. Poor data management practices and the low level of digitisation of the construction industry represent a big hur... Read More about Deep learning with small datasets: Using autoencoders to address limited datasets in construction management.

Forecasting building energy consumption: Adaptive long-short term memory neural networks driven by genetic algorithm (2021)
Journal Article
Luo, X., & Oyedele, L. O. (2021). Forecasting building energy consumption: Adaptive long-short term memory neural networks driven by genetic algorithm. Advanced Engineering Informatics, 50, Article 101357. https://doi.org/10.1016/j.aei.2021.101357

The real-world building can be regarded as a comprehensive energy engineering system; its actual energy consumption depends on complex affecting factors, including various weather data and time signature. Accurate energy consumption forecasting and e... Read More about Forecasting building energy consumption: Adaptive long-short term memory neural networks driven by genetic algorithm.

A data-driven life-cycle optimisation approach for building retrofitting: A comprehensive assessment on economy, energy and environment (2021)
Journal Article
Luo, X. J., & Oyedele, L. O. (2021). A data-driven life-cycle optimisation approach for building retrofitting: A comprehensive assessment on economy, energy and environment. Journal of Building Engineering, 43, Article 102934. https://doi.org/10.1016/j.jobe.2021.102934

A novel data-driven life-cycle optimisation approach is proposed for building retrofitting. The innovation points include big-data information, integrated retrofitting design, and life-cycle optimisation through a comprehensive assessment of the econ... Read More about A data-driven life-cycle optimisation approach for building retrofitting: A comprehensive assessment on economy, energy and environment.

Digital Twins for the built environment: Learning from conceptual and process models in manufacturing (2021)
Journal Article
Davila Delgado, J. M., & Oyedele, L. (2021). Digital Twins for the built environment: Learning from conceptual and process models in manufacturing. Advanced Engineering Informatics, 49, Article 101332. https://doi.org/10.1016/j.aei.2021.101332

The overall aim of this paper is to contribute to a better understanding of the Digital Twin (DT) paradigm in the built environment by drawing inspiration from existing DT research in manufacturing. The DT is a Product Life Management information con... Read More about Digital Twins for the built environment: Learning from conceptual and process models in manufacturing.

Deep learning and boosted trees for injuries prediction in power infrastructure projects (2021)
Journal Article
Oyedele, A., Ajayi, A., Oyedele, L. O., Delgado, J. M. D., Akanbi, L., Akinade, O., …Bilal, M. (2021). Deep learning and boosted trees for injuries prediction in power infrastructure projects. Applied Soft Computing, 110(107587), 1 - 14. https://doi.org/10.1016/j.asoc.2021.107587

Electrical injury impacts are substantial and massive. Investments in electricity will continue to increase, leading to construction project complexities, which undoubtedly contribute to injuries and associated effects. Machine learning (ML) algorith... Read More about Deep learning and boosted trees for injuries prediction in power infrastructure projects.

IoT technologies for livestock management: A review of present status, opportunities, and future trends (2021)
Journal Article
Akhigbe, B. I., Munir, K., Akinade, O., Akanbi, L., & Oyedele, L. O. (2021). IoT technologies for livestock management: A review of present status, opportunities, and future trends. Big Data and Cognitive Computing, 5(1), Article 10. https://doi.org/10.3390/bdcc5010010

The world population currently stands at about 7 billion amidst an expected increase in 2030 from 9.4 billion to around 10 billion in 2050. This burgeoning population has continued to influence the upward demand for animal food. Moreover, the managem... Read More about IoT technologies for livestock management: A review of present status, opportunities, and future trends.

Cloud computing in construction industry: Use cases, benefits and challenges (2020)
Journal Article
Bello, S. A., Oyedele, L. O., Akinade, O. O., Bilal, M., Davila Delgado, J. M., Akanbi, L. A., …Owolabi, H. A. (2021). Cloud computing in construction industry: Use cases, benefits and challenges. Automation in Construction, 122, Article 103441. https://doi.org/10.1016/j.autcon.2020.103441

Cloud computing technologies have revolutionised several industries (such as aerospace, manufacturing, automobile, retail, etc.) for several years. Although the construction industry is well placed to also leverage these technologies for competitive... Read More about Cloud computing in construction industry: Use cases, benefits and challenges.

IoT for predictive assets monitoring and maintenance: An implementation strategy for the UK rail industry (2020)
Journal Article
Gbadamosi, A., Oyedele, L., Davila Delgado, J. M., Kusimo, H., Akanbi, L., Olawale, O., & Muhammed-Yakubu, N. (2021). IoT for predictive assets monitoring and maintenance: An implementation strategy for the UK rail industry. Automation in Construction, 122, Article 103486

With about 100% increase in rail service usage over the last 20 years, it is pertinent that rail infrastructure continues to function at an optimal level to avoid service disruptions, cancellations or delays due to unforeseen asset breakdown. In an e... Read More about IoT for predictive assets monitoring and maintenance: An implementation strategy for the UK rail industry.

BIM competencies for delivering waste-efficient building projects in a circular economy (2020)
Journal Article
Ganiyu, S. A., Oyedele, L. O., Akinade, O., Owolabi, H., Akanbi, L., & Gbadamosi, A. (2020). BIM competencies for delivering waste-efficient building projects in a circular economy. Developments in the Built Environment, 4, 100036. https://doi.org/10.1016/j.dibe.2020.100036

Competency measures are increasingly becoming effective ways for construction organizations to measure their ability to deliver waste-efficient projects. Despite the ongoing efforts in achieving the goals of the circular economy through BIM adoption,... Read More about BIM competencies for delivering waste-efficient building projects in a circular economy.

Offsite construction for emergencies: A focus on Isolation Space Creation (ISC) measures for the COVID-19 pandemic (2020)
Journal Article
Gbadamosi, A., Oyedele, L., Olawale, O., & Abioye, S. (2020). Offsite construction for emergencies: A focus on Isolation Space Creation (ISC) measures for the COVID-19 pandemic. Progress in Disaster Science, 8, Article 100130. https://doi.org/10.1016/j.pdisas.2020.100130

The outbreak of a pandemic of global concern, the Corona Virus Disease 2019 (COVID-19) has tested the capacity of healthcare facilities to the brim in many developed countries. In a minacious fashion of rapid spread and extreme transmission rate, COV... Read More about Offsite construction for emergencies: A focus on Isolation Space Creation (ISC) measures for the COVID-19 pandemic.

Big data for design options repository: Towards a DFMA approach for offsite construction (2020)
Journal Article
Gbadamosi, A., Oyedele, L., Mahamadu, A., Kusimo, H., Bilal, M., Davila Delgado, J. M., & Muhammed-Yakubu, N. (2020). Big data for design options repository: Towards a DFMA approach for offsite construction. Automation in Construction, 120, Article 103388. https://doi.org/10.1016/j.autcon.2020.103388

A persistent barrier to the adoption of offsite construction is the lack of information for assessing prefabrication alternatives and the choices of suppliers. This study integrates three aspects of offsite construction, including BIM, DFMA and big d... Read More about Big data for design options repository: Towards a DFMA approach for offsite construction.

Deep learning in the construction industry: A review of present status and future innovations (2020)
Journal Article
Akinosho, T. D., Oyedele, L. O., Bilal, M., Ajayi, A. O., Delgado, M. D., Akinade, O. O., & Ahmed, A. A. (2020). Deep learning in the construction industry: A review of present status and future innovations. Journal of Building Engineering, 32, Article 101827. https://doi.org/10.1016/j.jobe.2020.101827

The construction industry is known to be overwhelmed with resource planning, risk management and logistic challenges which often result in design defects, project delivery delays, cost overruns and contractual disputes. These challenges have instigat... Read More about Deep learning in the construction industry: A review of present status and future innovations.

Life cycle assessment approach for renewable multi-energy system: A comprehensive analysis (2020)
Journal Article
Luo, X., Oyedele, L. O., Owolabi, H. A., Bilal, M., Ajayi, A. O., & Akinade, O. O. (2020). Life cycle assessment approach for renewable multi-energy system: A comprehensive analysis. Energy Conversion and Management, 224, Article 113354. https://doi.org/10.1016/j.enconman.2020.113354

In response to the gradual degradation of natural sources, there is a growing interest in adopting renewable resources for various building energy supply. In this study, a comprehensive life cycle assessment approach is proposed for a renewable multi... Read More about Life cycle assessment approach for renewable multi-energy system: A comprehensive analysis.

Deep learning model for demolition waste prediction in a circular economy (2020)
Journal Article
Akanbi, L. A., Oyedele, A. O., Oyedele, L. O., & Salami, R. O. (2020). Deep learning model for demolition waste prediction in a circular economy. Journal of Cleaner Production, 274, Article 122843. https://doi.org/10.1016/j.jclepro.2020.122843

An essential requirement for a successful circular economy is the continuous use of materials. Planning for building materials reuse at the end-of-life of buildings is usually a difficult task because limited time are usually made available for build... Read More about Deep learning model for demolition waste prediction in a circular economy.

Genetic algorithm-determined deep feedforward neural network architecture for predicting electricity consumption in real buildings (2020)
Journal Article
Luo, X. J., Oyedele, L. O., Ajayi, A. O., Akinade, O. O., Delgado, J. M. D., Owolabi, H. A., & Ahmed, A. (2020). Genetic algorithm-determined deep feedforward neural network architecture for predicting electricity consumption in real buildings. Energy and AI, 2, Article 100015. https://doi.org/10.1016/j.egyai.2020.100015

A genetic algorithm-determined deep feedforward neural network architecture (GA-DFNN) is proposed for both day-ahead hourly and week-ahead daily electricity consumption of a real-world campus building in the United Kingdom. Due to the comprehensive r... Read More about Genetic algorithm-determined deep feedforward neural network architecture for predicting electricity consumption in real buildings.

Comparative study of machine learning-based multi-objective prediction framework for multiple building energy loads (2020)
Journal Article
Luo, X. J., Oyedele, L. O., Ajayi, A. O., & Akinade, O. O. (2020). Comparative study of machine learning-based multi-objective prediction framework for multiple building energy loads. Sustainable Cities and Society, 61, Article 102283. https://doi.org/10.1016/j.scs.2020.102283

Buildings are one of the significant sources of energy consumption and greenhouse gas emission in urban areas all over the world. Lighting control and building integrated photovoltaic (BIPV) are two effective measures in reducing overall primary ener... Read More about Comparative study of machine learning-based multi-objective prediction framework for multiple building energy loads.

Feature extraction and genetic algorithm enhanced adaptive deep neural network for energy consumption prediction in buildings (2020)
Journal Article
Luo, X. J., Oyedele, L. O., Ajayi, A. O., Akinade, O. O., Owolabi, H. A., & Ahmed, A. (2020). Feature extraction and genetic algorithm enhanced adaptive deep neural network for energy consumption prediction in buildings. Renewable and Sustainable Energy Reviews, 131, Article 109980. https://doi.org/10.1016/j.rser.2020.109980

Accurate forecast of energy consumption is essential in building energy management. Owing to the variation of outdoor weather condition among different seasons, year-round historical weather profile is needed to investigate its feature thoroughly. Da... Read More about Feature extraction and genetic algorithm enhanced adaptive deep neural network for energy consumption prediction in buildings.

Big data innovation and diffusion in projects teams: Towards a conflict prevention culture (2020)
Journal Article
Oyedele, A., Owolabi, H. A., Oyedele, L. O., & Olawale, O. A. (2020). Big data innovation and diffusion in projects teams: Towards a conflict prevention culture. Developments in the Built Environment, 3, Article 100016. https://doi.org/10.1016/j.dibe.2020.100016

Despite the enormous literature on how team conflicts can be managed and resolved, this study diverges, by examining factors that facilitate conflict prevention culture in project teams, especially when introducing Big Data Technology. Relying on fin... Read More about Big data innovation and diffusion in projects teams: Towards a conflict prevention culture.

Project reputation in construction: A process-based perspective of construction practitioners in the UK (2020)
Journal Article
Olawale, O., Oyedele, L., Owolabi, H., Gbadamosi, A., & Kusimo, H. (2022). Project reputation in construction: A process-based perspective of construction practitioners in the UK. International Journal of Construction Management, 22(12), https://doi.org/10.1080/15623599.2020.1783598

The overall aim of this study is to elicit the perspective of practitioners (e.g., architects, civil engineers, building engineers, structural engineers and quantity surveyors) on the process-related factors influencing the project reputation of cons... Read More about Project reputation in construction: A process-based perspective of construction practitioners in the UK.

A research agenda for augmented and virtual reality in architecture, engineering and construction (2020)
Journal Article
Davila Delgado, J. M., Oyedele, L., Demian, P., & Beach, T. (2020). A research agenda for augmented and virtual reality in architecture, engineering and construction. Advanced Engineering Informatics, 45, Article 101122. https://doi.org/10.1016/j.aei.2020.101122

This paper presents a study on the usage landscape of augmented reality (AR) and virtual reality (VR) in the architecture, engineering and construction sectors, and proposes a research agenda to address the existing gaps in required capabilities. A s... Read More about A research agenda for augmented and virtual reality in architecture, engineering and construction.

Augmented and virtual reality in construction: Drivers and limitations for industry adoption (2020)
Journal Article
Davila Delgado, J. M., Oyedele, L., Beach, T., & Demian, P. (2020). Augmented and virtual reality in construction: Drivers and limitations for industry adoption. Journal of Construction Engineering and Management, 146(7), https://doi.org/10.1061/%28ASCE%29CO.1943-7862.0001844

Augmented and virtual reality have the potential to provide a step-change in productivity in the construction sector; however, the level of adoption is very low. This paper presents a systematic study of the factors that limit and drive adoption in a... Read More about Augmented and virtual reality in construction: Drivers and limitations for industry adoption.

Two-stage capacity optimization approach of multi-energy system considering its optimal operation (2020)
Journal Article
Luo, X. J., Oyedele, L. O., Akinade, O. O., & Ajayi, A. O. (2020). Two-stage capacity optimization approach of multi-energy system considering its optimal operation. Energy and AI, 1, Article 100005. https://doi.org/10.1016/j.egyai.2020.100005

With the depletion of fossil fuel and climate change, multi-energy systems have attracted widespread attention in buildings. Multi-energy systems, fuelled by renewable energy, including solar and biomass energy, are gaining increasing adoption in com... Read More about Two-stage capacity optimization approach of multi-energy system considering its optimal operation.

BIM data model requirements for asset monitoring and the circular economy (2020)
Journal Article
Davila Delgado, J. M., & Oyedele, L. O. (2020). BIM data model requirements for asset monitoring and the circular economy. Journal of Engineering, Design and Technology, 18(5), 1269-1285. https://doi.org/10.1108/JEDT-10-2019-0284

© 2020, Emerald Publishing Limited. Purpose: The purpose of this paper is to review and provide recommendations to extend the current open standard data models for describing monitoring systems and circular economy precepts for built assets. Open sta... Read More about BIM data model requirements for asset monitoring and the circular economy.

3D pattern identification approach for cooling load profiles in different buildings (2020)
Journal Article
Luo, X. J., Oyedele, L. O., Akinade, O., & Ajayi, A. O. (2020). 3D pattern identification approach for cooling load profiles in different buildings. Journal of Building Engineering, 31, Article 101339. https://doi.org/10.1016/j.jobe.2020.101339

© 2020 Elsevier Ltd Building energy conservation has gained increasing concern owing to its large portion of energy consumption and great potential of energy saving. In-depth understanding of representative patterns of daily cooling load profile will... Read More about 3D pattern identification approach for cooling load profiles in different buildings.

Construction practitioners’ perception of key drivers of reputation in mega-construction projects (2020)
Journal Article
Olawale, O. A., Oyedele, L. O., & Owolabi, H. A. (2020). Construction practitioners’ perception of key drivers of reputation in mega-construction projects. Journal of Engineering, Design and Technology, 18(6), 1571-1592. https://doi.org/10.1108/JEDT-10-2019-0255

Purpose: The purpose of this study is to commence the discourse on the non-inclusiveness of the dynamics of reputation within the construction industry by identifying and examining the key product and process drivers of reputation in mega-constructio... Read More about Construction practitioners’ perception of key drivers of reputation in mega-construction projects.

Optimised Big Data analytics for health and safety hazards prediction in power infrastructure operations (2020)
Journal Article
Ajayi, A., Oyedele, L., Akinade, O., Bilal, M., Owolabi, H., Akanbi, L., & Delgado, J. M. D. (2020). Optimised Big Data analytics for health and safety hazards prediction in power infrastructure operations. Safety Science, 125, Article 104656. https://doi.org/10.1016/j.ssci.2020.104656

© 2020 Elsevier Ltd Forecasting imminent accidents in power infrastructure projects require a robust and accurate prediction model to trigger a proactive strategy for risk mitigation. Unfortunately, getting ready-made machine learning algorithms to e... Read More about Optimised Big Data analytics for health and safety hazards prediction in power infrastructure operations.

Big Data with deep learning for benchmarking profitability performance in project tendering (2020)
Journal Article
Bilal, M., & Oyedele, L. O. (2020). Big Data with deep learning for benchmarking profitability performance in project tendering. Expert Systems with Applications, 147, Article 113194. https://doi.org/10.1016/j.eswa.2020.113194

© 2020 A reliable benchmarking system is crucial for the contractors to evaluate the profitability performance of project tenders. Existing benchmarks are ineffective in the tender evaluation task for three reasons. Firstly, these benchmarks are most... Read More about Big Data with deep learning for benchmarking profitability performance in project tendering.

Drivers and challenges associated with the implementation of big data within UK facilities management sector: An exploratory factor analysis approach (2020)
Journal Article
Konanahalli, A., Marinelli, M., & Oyedele, L. (2022). Drivers and challenges associated with the implementation of big data within UK facilities management sector: An exploratory factor analysis approach. IEEE Transactions on Engineering Management, 69(4), 916-929. https://doi.org/10.1109/TEM.2019.2959914

The recent advances in Internet of Things (IoT), computational analytics, processing power, and assimilation of Big Data (BD) are playing an important role in revolutionizing maintenance and operations regimes within the wider facilities management (... Read More about Drivers and challenges associated with the implementation of big data within UK facilities management sector: An exploratory factor analysis approach.

Guidelines for applied machine learning in construction industry—A case of profit margins estimation (2019)
Journal Article
Bilal, M., & Oyedele, L. (2020). Guidelines for applied machine learning in construction industry—A case of profit margins estimation. Advanced Engineering Informatics, 43, 101013. https://doi.org/10.1016/j.aei.2019.101013

© 2019 Elsevier Ltd The progress in the field of Machine Learning (ML) has enabled the automation of tasks that were considered impossible to program until recently. These advancements today have incited firms to seek intelligent solutions as part of... Read More about Guidelines for applied machine learning in construction industry—A case of profit margins estimation.

Risk mitigation in PFI/PPP project finance: A framework model for financiers’ bankability criteria (2019)
Journal Article
Owolabi, H., Oyedele, L., Alaka, H., Ajayi, S., Bilal, M., & Akinade, O. (2020). Risk mitigation in PFI/PPP project finance: A framework model for financiers’ bankability criteria. Built Environment Project and Asset Management, 10(1), 28-49. https://doi.org/10.1108/BEPAM-09-2018-0120

Purpose: Earlier studies on risk evaluation in private finance initiative and public private partnerships (PFI/PPP) projects have focussed more on quantitative approaches despite increasing call for contextual understanding of the bankability of risk... Read More about Risk mitigation in PFI/PPP project finance: A framework model for financiers’ bankability criteria.

Design for deconstruction using a circular economy approach: Barriers and strategies for improvement (2019)
Journal Article
Akinade, O., Oyedele, L., Oyedele, A., Davila Delgado, J. M., Bilal, M., Akanbi, L., …Owolabi, H. (2020). Design for deconstruction using a circular economy approach: Barriers and strategies for improvement. Production Planning and Control, 31(10), 829-840. https://doi.org/10.1080/09537287.2019.1695006

This study explores the current practices of Design for Deconstruction (DfD) as a strategy for achieving circular economy. Keeping in view the opportunities accruable from DfD, a review of the literature was carried out and six focus group interviews... Read More about Design for deconstruction using a circular economy approach: Barriers and strategies for improvement.

Deep learning models for health and safety risk prediction in power infrastructure projects (2019)
Journal Article
Ajayi, A., Oyedele, L., Owolabi, H., Akinade, O., Bilal, M., Davila Delgado, J. M., & Akanbi, L. (2020). Deep learning models for health and safety risk prediction in power infrastructure projects. Risk Analysis, 40(10), 2019-2039. https://doi.org/10.1111/risa.13425

Inappropriate management of Health and safety (H&S) risk in power infrastructure projects can result in occupational accidents and equipment damage. Accidents at work have detrimental effects on workers, company, and the general public. Despite the a... Read More about Deep learning models for health and safety risk prediction in power infrastructure projects.

Big data analytics system for costing power transmission projects (2019)
Journal Article
Delgado, J. M. D., Oyedele, L., Bilal, M., Ajayi, A., Akanbi, L., & Akinade, O. (2020). Big data analytics system for costing power transmission projects. Journal of Construction Engineering and Management, 146(1), https://doi.org/10.1061/%28ASCE%29CO.1943-7862.0001745

© 2019 American Society of Civil Engineers. Inaccurate cost estimates have significant impacts on the final cost of power transmission projects and erode profits. Methods for cost estimation have been investigated thoroughly, but they are not used wi... Read More about Big data analytics system for costing power transmission projects.

Critical success factors for ensuring bankable completion risk in PFI/PPP megaprojects (2019)
Journal Article
Owolabi, H. A., Oyedele, L. O., Alaka, H. A., Ajayi, S. O., Akinade, O. O., & Bilal, M. (2020). Critical success factors for ensuring bankable completion risk in PFI/PPP megaprojects. Journal of Management in Engineering, 36(1), https://doi.org/10.1061/%28ASCE%29ME.1943-5479.0000717

© 2019 American Society of Civil Engineers. This study investigates project financiers' perspectives on the bankability of completion risk in private finance initiative and public-private partnership (PFI/PPP) megaprojects. Using a mixed methodology... Read More about Critical success factors for ensuring bankable completion risk in PFI/PPP megaprojects.

Complexities of smart city project success: A study of real-life case studies (2019)
Presentation / Conference
Olawale, O., Oyedele, L., Owolabi, H., Kusimo, H., Gbadamosi, A., Akinosho, T., …Olojede, I. (2019, July). Complexities of smart city project success: A study of real-life case studies. Presented at CIB World Building Congress 2019, Hong Kong SAR, China

Over the years, the world has moved towards an unprecedented level of urbanisation as half of the world’s total population live in cities. This trajectory of rapid urbanisation has greatly improved the modern economy as well as the standard of living... Read More about Complexities of smart city project success: A study of real-life case studies.

The role of Internet of Things in delivering smart construction (2019)
Presentation / Conference
Gbadamosi, A., Oyedele, L., Mahamadu, A., Kusimo, H., & Olawale, O. (2019, July). The role of Internet of Things in delivering smart construction. Presented at CIB World Building Congress 2019, Hong Kong SAR, China

The construction industry is the least digitised sector in the world and it contributes significantly less, in terms of productivity, to the global economy than its average potential. Current trends in the construction industry are aimed at leveragin... Read More about The role of Internet of Things in delivering smart construction.

Robotics and automated systems in construction: Understanding industry-specific challenges for adoption (2019)
Journal Article
Davila Delgado, J. M., Oyedele, L., Ajayi, A., Akanbi, L., Akinade, L., Bilal, M., & Owolabi, H. (2019). Robotics and automated systems in construction: Understanding industry-specific challenges for adoption. Journal of Building Engineering, 26, Article 100868. https://doi.org/10.1016/j.jobe.2019.100868

© 2019 The Authors The construction industry is a major economic sector, but it is plagued with inefficiencies and low productivity. Robotics and automated systems have the potential to address these shortcomings; however, the level of adoption in th... Read More about Robotics and automated systems in construction: Understanding industry-specific challenges for adoption.

Investigating profitability performance of construction projects using big data: A project analytics approach (2019)
Journal Article
Bilal, M., Oyedele, L. O., Kusimo, H. O., Owolabi, H. A., Akanbi, L. A., Ajayi, A. O., …Davila Delgado, J. M. (2019). Investigating profitability performance of construction projects using big data: A project analytics approach. Journal of Building Engineering, 26, Article 100850. https://doi.org/10.1016/j.jobe.2019.100850

© 2019 The Authors The construction industry generates different types of data from the project inception stage to project delivery. This data comes in various forms and formats which surpass the data management, integration and analysis capabilities... Read More about Investigating profitability performance of construction projects using big data: A project analytics approach.

Smart Cities Implementation: Challenges in Nigeria (2019)
Presentation / Conference
kadiri, K., Oyedele, L., Owolabi, H., Akinade,, O., Akanbi,, L., & Gbadamosi, A. (2019, June). Smart Cities Implementation: Challenges in Nigeria. Presented at CIB World Building Congress 2019, Hong Kong SAR, China

A city is a large human settlement that have extensive systems for housing, transportation, sanitation, utilities, land use, and communication. Their density facilitates interaction between people, government organizations and businesses, sometimes b... Read More about Smart Cities Implementation: Challenges in Nigeria.

Stimulating the attractiveness of PFI/PPPs using public sector guarantees (2019)
Journal Article
Owolabi, H., Oyedele, L., Alaka, H., Bilal, M., Ajayi, S., Akinade, O., & Agboola, A. (2019). Stimulating the attractiveness of PFI/PPPs using public sector guarantees. World Journal of Entrepreneurship, Management and Sustainable Development, 15(3), 239-258. https://doi.org/10.1108/WJEMSD-05-2018-0055

Purpose: Although the UK Guarantee Scheme for Infrastructures (UKGSI) was introduced in 2012 to address the huge financing gap for critical infrastructures, PFI sponsors have so far guaranteed only few projects. Many stakeholders in the project finan... Read More about Stimulating the attractiveness of PFI/PPPs using public sector guarantees.

Development of an IoT-based big data platform for day-ahead prediction of building heating and cooling demands (2019)
Journal Article
Luo, X. J., Oyedele, L. O., Ajayi, A. O., Monyei, C. G., Akinade, O. O., & Akanbi, L. A. (2019). Development of an IoT-based big data platform for day-ahead prediction of building heating and cooling demands. Advanced Engineering Informatics, 41, Article 100926. https://doi.org/10.1016/j.aei.2019.100926

© 2019 Elsevier Ltd The emerging technologies of the Internet of Things (IoT) and big data can be utilised to derive knowledge and support applications for energy-efficient buildings. Effective prediction of heating and cooling demands is fundamental... Read More about Development of an IoT-based big data platform for day-ahead prediction of building heating and cooling demands.

Integrating construction supply chains within a circular economy: An ANFIS-based waste analytics system (A-WAS) (2019)
Journal Article
Akinade, O. O., & Oyedele, L. O. (2019). Integrating construction supply chains within a circular economy: An ANFIS-based waste analytics system (A-WAS). Journal of Cleaner Production, 229, 863-873. https://doi.org/10.1016/j.jclepro.2019.04.232

© 2019 The circular economy agenda makes it paramount for construction supply chains to reduce material waste. Although a collaborative platform called Building Information Modelling (BIM) offers a means of supply chains integration, it has not been... Read More about Integrating construction supply chains within a circular economy: An ANFIS-based waste analytics system (A-WAS).

Benchmarks for energy access: Policy vagueness and incoherence as barriers to sustainable electrification of the global south (2019)
Journal Article
Monyei, C. G., Oyedele, L. O., Akinade, O. O., Ajayi, A. O., & Luo, X. J. (2019). Benchmarks for energy access: Policy vagueness and incoherence as barriers to sustainable electrification of the global south. Energy Research and Social Science, 54, 113-116. https://doi.org/10.1016/j.erss.2019.04.005

© 2019 The unavailability of tangible policy benchmarks continues to mitigate against sustainable electrification in the global south. Furthermore, incoherent policy benchmarks as to what should constitute clean energy allow for varying interpretatio... Read More about Benchmarks for energy access: Policy vagueness and incoherence as barriers to sustainable electrification of the global south.

Disassembly and deconstruction analytics system (D-DAS) for construction in a circular economy (2019)
Journal Article
Akanbi, L. A., Oyedele, L. O., Omoteso, K., Bilal, M., Akinade, O. O., Ajayi, A. O., …Owolabi, H. A. (2019). Disassembly and deconstruction analytics system (D-DAS) for construction in a circular economy. Journal of Cleaner Production, 223, 386-396. https://doi.org/10.1016/j.jclepro.2019.03.172

© 2019 Despite the relevance of building information modelling for simulating building performance at various life cycle stages, Its use for assessing the end-of-life impacts is not a common practice. Even though the global sustainability and circula... Read More about Disassembly and deconstruction analytics system (D-DAS) for construction in a circular economy.

Changing significance of embodied energy: A comparative study of material specifications and building energy sources (2019)
Journal Article
Ajayi, S. O., Oyedele, L. O., & Ilori, O. M. (2019). Changing significance of embodied energy: A comparative study of material specifications and building energy sources. Journal of Building Engineering, 23, 324-333. https://doi.org/10.1016/j.jobe.2019.02.008

© 2019 Elsevier Ltd Despite the increasing significance of embodied impacts of buildings, efforts to reduce their environmental footprints have been concentrated on the operational impacts of buildings. This study investigates the changing significan... Read More about Changing significance of embodied energy: A comparative study of material specifications and building energy sources.

Design optimisation using convex programming: Towards waste-efficient building designs (2019)
Journal Article
Bilal, M., Oyedele, L. O., Akinade, O. O., Delgado, J. M. D., Akanbi, L. A., Ajayi, A. O., & Younis, M. S. (2019). Design optimisation using convex programming: Towards waste-efficient building designs. Journal of Building Engineering, 23, 231-240. https://doi.org/10.1016/j.jobe.2019.01.022

© 2019 The Authors A non-modular building layout is amongst the leading sources of offcut waste, resulting from a substantial amount of onsite cutting and fitting of bricks, blocks, plasterboard, and tiles. The field of design for dimensional coordin... Read More about Design optimisation using convex programming: Towards waste-efficient building designs.

Offsite construction: Developing a BIM-Based optimizer for assembly (2019)
Journal Article
Gbadamosi, A. Q., Mahamadu, A. M., Oyedele, L. O., Akinade, O. O., Manu, P., Mahdjoubi, L., & Aigbavboa, C. (2019). Offsite construction: Developing a BIM-Based optimizer for assembly. Journal of Cleaner Production, 215, 1180-1190. https://doi.org/10.1016/j.jclepro.2019.01.113

© 2019 Elsevier Ltd The lack of adequate consideration of the underlying factors affecting the methods of building assembly often results in inefficiencies in the uses of building materials, equipment and manpower. These inefficiencies are further co... Read More about Offsite construction: Developing a BIM-Based optimizer for assembly.

Dynamic relationship between embodied and operational impacts of buildings: An evaluation of sustainable design appraisal tools (2019)
Journal Article
Ajayi, S. O., Oyedele, L. O., & Dauda, J. A. (2019). Dynamic relationship between embodied and operational impacts of buildings: An evaluation of sustainable design appraisal tools. World Journal of Science, Technology and Sustainable Development, 16(2), 70-81. https://doi.org/10.1108/WJSTSD-05-2018-0048

Purpose – Buildings and their construction activities consume a significant proportion of mineral resources excavated from nature and contribute a large percentage of CO2 in the atmosphere. As a way of improving the sustainability of building constru... Read More about Dynamic relationship between embodied and operational impacts of buildings: An evaluation of sustainable design appraisal tools.

Optimisation of resource management in construction projects: A big data approach (2019)
Journal Article
Kusimo, H., Oyedele, L., Akinade, O., Oyedele, A., Abioye, S., Agboola, A., & Mohammed-Yakub, N. (2019). Optimisation of resource management in construction projects: A big data approach. World Journal of Science, Technology and Sustainable Development, 16(2), 82-93. https://doi.org/10.1108/WJSTSD-05-2018-0044

Purpose – The purpose of this paper is to identify challenges faced in resource management in the UK construction industry and to propose some solutions to these problems. Design/methodology/approach – Based on a qualitative research methodology, 14... Read More about Optimisation of resource management in construction projects: A big data approach.

An income-reflective scalable energy level transition system for low/middle income households (2018)
Journal Article
Monyei, C. G., Oyedele, L. O., Akinade, O. O., Ajayi, A. O., Ezugwu, A. E., Akpeji, K. O., …Onunwor, J. C. (2019). An income-reflective scalable energy level transition system for low/middle income households. Sustainable Cities and Society, 45, 172-186. https://doi.org/10.1016/j.scs.2018.10.042

© 2018 Elsevier Ltd In mitigating against energy poverty in Nigeria, research interest has focused mainly on electricity access and reduced electricity bills for low/medium income households. However, energy poverty in the global south is not only a... Read More about An income-reflective scalable energy level transition system for low/middle income households.

Predicting completion risk in PPP projects using big data analytics (2018)
Journal Article
Owolabi, H., Bilal, M., Oyedele, L., Alaka, H. A., Ajayi, S. O., & Akinade, O. (2020). Predicting completion risk in PPP projects using big data analytics. IEEE Transactions on Engineering Management, 67(2), 430-453. https://doi.org/10.1109/TEM.2018.2876321

Accurate prediction of potential delays in public private partnerships (PPP) projects could provide valuable information relevant for planning and mitigating completion risk in future PPP projects. However, existing techniques for evaluating completi... Read More about Predicting completion risk in PPP projects using big data analytics.

Big data platform for health and safety accident prediction (2018)
Journal Article
Ajayi, A., Oyedele, L., Davila Delgado, J. M., Akanbi, L., Bilal, M., Akinade, O., & Olawale, O. (2019). Big data platform for health and safety accident prediction. World Journal of Science, Technology and Sustainable Development, 16(1), 2-21. https://doi.org/10.1108/WJSTSD-05-2018-0042

Purpose – The purpose of this paper is to highlight the use of the big data technologies for health and safety risks analytics in the power infrastructure domain with large data sets of health and safety risks, which are usually sparse and noisy. Des... Read More about Big data platform for health and safety accident prediction.

Reusability analytics tool for end-of-life assessment of building materials in a circular economy (2018)
Journal Article
Akanbi, L., Oyedele, L., Davila Delgado, J. M., Bilal, M., Akinade, O., Ajayi, A., & Mohammed-Yakub, N. (2019). Reusability analytics tool for end-of-life assessment of building materials in a circular economy. World Journal of Science, Technology and Sustainable Development, 16(1), 40-55. https://doi.org/10.1108/WJSTSD-05-2018-0041

Purpose – In a circular economy, the goal is to keep materials values in the economy for as long as possible. For the construction industry to support the goal of the circular economy, there is the need for materials reuse. However, there is little o... Read More about Reusability analytics tool for end-of-life assessment of building materials in a circular economy.

Public private partnerships (PPP) in the developing world: Mitigating financiers’ risks (2018)
Journal Article
Owolabi, H. A., Oyedele, L., Alaka, H., Ebohon, O. J., Ajayi, S., Akinade, O., …Olawale, O. (2019). Public private partnerships (PPP) in the developing world: Mitigating financiers’ risks. World Journal of Science, Technology and Sustainable Development, 16(3), 121-141. https://doi.org/10.1108/WJSTSD-05-2018-0043

Purpose – A major challenge for foreign lenders in financing public private partnerships (PPP) infrastructure projects in an emerging market (EM) is the bankability of country-related risks. Despite existing studies on country risks in international... Read More about Public private partnerships (PPP) in the developing world: Mitigating financiers’ risks.

A Big Data analytics approach for construction firms failure prediction models (2018)
Journal Article
Alaka, H., Oyedele, L., Owolabi, H., Akinade, O., Bilal, M., & Ajayi, S. (2019). A Big Data analytics approach for construction firms failure prediction models. IEEE Transactions on Engineering Management, 66(4), 689-698. https://doi.org/10.1109/TEM.2018.2856376

Using 693,000 datacells from 33,000 sample construction firms that operated or failed between 2008 and 2017, failure prediction models were developed using artificial neural network (ANN), support vector machine (SVM), multiple discriminant analysis... Read More about A Big Data analytics approach for construction firms failure prediction models.

Critical design factors for minimising waste in construction projects: A structural equation modelling approach (2018)
Journal Article
Ajayi, S. O., & Oyedele, L. O. (2018). Critical design factors for minimising waste in construction projects: A structural equation modelling approach. Resources, Conservation and Recycling, 137, 302-313. https://doi.org/10.1016/j.resconrec.2018.06.005

© 2018 Notwithstanding that efforts made at the design stage of building construction projects have significant impacts on project outcome, most waste management efforts are usually focused on construction stage. This is albeit the understanding that... Read More about Critical design factors for minimising waste in construction projects: A structural equation modelling approach.

Designing out construction waste using BIM technology: Stakeholders’ expectations for industry deployment (2018)
Journal Article
Akinade, O., Oyedele, L., Ajayi, S., Bilal, M., Alaka, H. A., Owolabi, H., & Arawomo, O. (2018). Designing out construction waste using BIM technology: Stakeholders’ expectations for industry deployment. Journal of Cleaner Production, 180, 375-385. https://doi.org/10.1016/j.jclepro.2018.01.022

© 2018 The Authors The need to use Building Information Modelling (BIM) for Construction and Demolition Waste (CDW) minimisation is well documented but most of the existing CDW management tools still lack BIM functionality. This study therefore asses... Read More about Designing out construction waste using BIM technology: Stakeholders’ expectations for industry deployment.

A framework for big data analytics approach to failure prediction of construction firms (2018)
Journal Article
Alaka, H. A., Oyedele, L. O., Owolabi, H. A., Bilal, M., Ajayi, S. O., & Akinade, O. O. (2020). A framework for big data analytics approach to failure prediction of construction firms. Applied Computing and Informatics, 16(1/2), 207-222. https://doi.org/10.1016/j.aci.2018.04.003

This study explored use of big data analytics (BDA) to analyse data of a large number of construction firms to develop a construction business failure prediction model (CB-FPM). Careful analysis of literature revealed financial ratios as the best for... Read More about A framework for big data analytics approach to failure prediction of construction firms.

Waste-efficient materials procurement for construction projects: A structural equation modelling of critical success factors (2018)
Journal Article
Ajayi, S., & Oyedele, L. (2018). Waste-efficient materials procurement for construction projects: A structural equation modelling of critical success factors. Waste Management, 75, 60-69. https://doi.org/10.1016/j.wasman.2018.01.025

© 2018 Albeit the understanding that construction waste is caused by activities ranging from all stages of project delivery process, research efforts have been concentrated on design and construction stages, while the possibility of reducing waste th... Read More about Waste-efficient materials procurement for construction projects: A structural equation modelling of critical success factors.

Salvaging building materials in a circular economy: A BIM-based whole-life performance estimator (2017)
Journal Article
Akanbi, L. A., Oyedele, L., Akinade, O., Ajayi, A. O., Davila Delgado, M., Bilal, M., & Bello, S. A. (2018). Salvaging building materials in a circular economy: A BIM-based whole-life performance estimator. Resources, Conservation and Recycling, 129, 175-186. https://doi.org/10.1016/j.resconrec.2017.10.026

© 2017 The Author(s) The aim of this study is to develop a BIM-based Whole-life Performance Estimator (BWPE) for appraising the salvage performance of structural components of buildings right from the design stage. A review of the extant literature w... Read More about Salvaging building materials in a circular economy: A BIM-based whole-life performance estimator.

Systematic review of bankruptcy prediction models: Towards a framework for tool selection (2017)
Journal Article
Alaka, H. A., Oyedele, L., Owolabi, H. A., Kumar, V., Ajayi, S. O., Akinade, O., & Bilal, M. (2018). Systematic review of bankruptcy prediction models: Towards a framework for tool selection. Expert Systems with Applications, 94, 164-184. https://doi.org/10.1016/j.eswa.2017.10.040

© 2017 Elsevier Ltd The bankruptcy prediction research domain continues to evolve with many new different predictive models developed using various tools. Yet many of the tools are used with the wrong data conditions or for the wrong situation. Using... Read More about Systematic review of bankruptcy prediction models: Towards a framework for tool selection.

Energy security and responses to climate change in Nigeria (2017)
Presentation / Conference
Olawale, O. A., Owolabi, H. A., Oyedele, L., Owolabi, A., & Akinade, O. (2017, May). Energy security and responses to climate change in Nigeria. Paper presented at Environmental Design and Management International Conference, Obafemi Awolowo University, Ile-Ife, Osun state, Nigeria

This study examined energy security and the impact of climate change in Nigeria including the diverse policy and institutional strategies so far adopted by Nigerian government to mitigate its impact on the populace and environs. Using a content-drive... Read More about Energy security and responses to climate change in Nigeria.

The application of web of data technologies in building materials information modelling for construction waste analytics (2017)
Journal Article
Bilal, M., Oyedele, L. O., Munir, K., Ajayi, S. O., Akinade, O. O., Owolabi, H. A., & Alaka, H. A. (2017). The application of web of data technologies in building materials information modelling for construction waste analytics. Sustainable Materials and Technologies, 11, 28-37. https://doi.org/10.1016/j.susmat.2016.12.004

© 2017 Elsevier B.V. Predicting and designing out construction waste in real time is complex during building waste analysis (BWA) since it involves a large number of analyses for investigating multiple waste-efficient design strategies. These analyse... Read More about The application of web of data technologies in building materials information modelling for construction waste analytics.

Policy imperatives for diverting construction waste from landfill: Experts’ recommendations for UK policy expansion (2017)
Journal Article
Oyedele, L. O., & Ajayi, S. O. (2017). Policy imperatives for diverting construction waste from landfill: Experts’ recommendations for UK policy expansion. Journal of Cleaner Production, 147, 57-65. https://doi.org/10.1016/j.jclepro.2017.01.075

© 2017 Elsevier Ltd Legislation and fiscal policies have remained the key drivers of construction waste minimization. It has often been suggested that reducing waste to the landfill does not only require improvement on existing waste management polic... Read More about Policy imperatives for diverting construction waste from landfill: Experts’ recommendations for UK policy expansion.

Attributes of design for construction waste minimization: A case study of waste-to-energy project (2017)
Journal Article
Ajayi, S. O., Oyedele, L. O., Akinade, O. O., Bilal, M., Alaka, H. A., Owolabi, H. A., & Kadiri, K. O. (2017). Attributes of design for construction waste minimization: A case study of waste-to-energy project. Renewable and Sustainable Energy Reviews, 73, 1333-1341. https://doi.org/10.1016/j.rser.2017.01.084

© 2017 Elsevier Ltd Despite the consensus that waste efficient design is important for reducing waste generated by construction and demolition activities, design strategies for actual waste mitigation remain unclear. In addition, decisive roles requi... Read More about Attributes of design for construction waste minimization: A case study of waste-to-energy project.

BIM-based deconstruction tool: Towards essential functionalities (2017)
Journal Article
Akinade, O. O., Oyedele, L. O., Omoteso, K., Ajayi, S. O., Bilal, M., Owolabi, H. A., …Looney, J. H. (2017). BIM-based deconstruction tool: Towards essential functionalities. International Journal for Sustainable Built Environment, 6(1), 260-271. https://doi.org/10.1016/j.ijsbe.2017.01.002

© 2017 The Gulf Organisation for Research and Development This study discusses the future directions of effective Design for Deconstruction (DfD) using BIM-based approach to design coordination. After a review of extant literatures on existing DfD pr... Read More about BIM-based deconstruction tool: Towards essential functionalities.

Optimising material procurement for construction waste minimization: An exploration of success factors (2017)
Journal Article
Ajayi, S. O., Oyedele, L. O., Akinade, O. O., Bilal, M., Alaka, H. A., & Owolabi, H. A. (2017). Optimising material procurement for construction waste minimization: An exploration of success factors. Sustainable Materials and Technologies, 11, 38-46. https://doi.org/10.1016/j.susmat.2017.01.001

© 2017 Elsevier B.V. Although construction waste occurs during the actual construction activities, there is an understanding that it is caused by activities and actions at design, materials procurement and construction stages of project delivery proc... Read More about Optimising material procurement for construction waste minimization: An exploration of success factors.

Effective material logistics in urban construction sites: A structural equation model (2017)
Journal Article
Spillane, J. P., & Oyedele, L. (2017). Effective material logistics in urban construction sites: A structural equation model. Construction Innovation: Information, Process, Management, 17(4), 406-428. https://doi.org/10.1108/CI-11-2015-0063

© 2017 Emerald Publishing Limited. Purpose - The purpose of this paper is to identify best practice relating to the effective management of materials in an urban, confined construction site, using structural equation modelling. Design/methodology/app... Read More about Effective material logistics in urban construction sites: A structural equation model.

Insolvency of small civil engineering firms: Critical strategic factors (2016)
Journal Article
Alaka, H. A., Oyedele, L. O., Owolabi, H. A., Bilal, M., Ajayi, S. O., & Akinade, O. O. (2017). Insolvency of small civil engineering firms: Critical strategic factors. Journal of Professional Issues in Engineering Education and Practice, 143(3), 04016026. https://doi.org/10.1061/%28ASCE%29EI.1943-5541.0000321

© 2016 American Society of Civil Engineers. Construction industry insolvency studies have failed to stem the industry's high insolvency tide because many focus on big civil engineering firms (CEF) when over 90% of firms in the industry are small or m... Read More about Insolvency of small civil engineering firms: Critical strategic factors.

Critical management practices influencing on-site waste minimization in construction projects (2016)
Journal Article
Ajayi, S. O., Oyedele, L. O., Bilal, M., Akinade, O. O., Alaka, H. A., & Owolabi, H. A. (2017). Critical management practices influencing on-site waste minimization in construction projects. Waste Management, 59, 330-339. https://doi.org/10.1016/j.wasman.2016.10.040

© 2016 Elsevier Ltd As a result of increasing recognition of effective site management as the strategic approach for achieving the required performance in construction projects, this study seeks to identify the key site management practices that are... Read More about Critical management practices influencing on-site waste minimization in construction projects.

Design for Deconstruction (DfD): Critical success factors for diverting end-of-life waste from landfills (2016)
Journal Article
Akinade, O. O., Oyedele, L. O., Ajayi, S. O., Bilal, M., Alaka, H. A., Owolabi, H. A., …Kadiri, K. O. (2017). Design for Deconstruction (DfD): Critical success factors for diverting end-of-life waste from landfills. Waste Management, 60, 3-13. https://doi.org/10.1016/j.wasman.2016.08.017

© 2016 Elsevier Ltd The aim of this paper is to identify Critical Success Factors (CSF) needed for effective material recovery through Design for Deconstruction (DfD). The research approach employed in this paper is based on a sequential exploratory... Read More about Design for Deconstruction (DfD): Critical success factors for diverting end-of-life waste from landfills.

Emotional intelligence and British expatriates’ cross-cultural adjustment in international construction projects (2016)
Journal Article
Konanahalli, A., & Oyedele, L. (2016). Emotional intelligence and British expatriates’ cross-cultural adjustment in international construction projects. Construction Management and Economics, 34(11), 751-768. https://doi.org/10.1080/01446193.2016.1213399

© 2016 Informa UK Limited, trading as Taylor & Francis Group. Today’s internationalized business demands global mindset, intercultural sensitivity and the ability to skilfully negotiate through cross-cultural interactions. Therefore, the overall ai... Read More about Emotional intelligence and British expatriates’ cross-cultural adjustment in international construction projects.

Methodological approach of construction business failure prediction studies: a review (2016)
Journal Article
Alaka, H. A., Oyedele, L. O., Owolabi, H. A., Ajayi, S. O., Bilal, M., & Akinade, O. O. (2016). Methodological approach of construction business failure prediction studies: a review. Construction Management and Economics, 34(11), 808-842. https://doi.org/10.1080/01446193.2016.1219037

© 2016 Informa UK Limited, trading as Taylor & Francis Group. Performance of bankruptcy prediction models (BPM), which partly depends on the methodological approach used to develop it, has virtually stagnated over the years. The methodological posi... Read More about Methodological approach of construction business failure prediction studies: a review.

Big Data in the construction industry: A review of present status, opportunities, and future trends (2016)
Journal Article
Bilal, M., Oyedele, L. O., Qadir, J., Munir, K., Ajayi, S. O., Akinade, O. O., …Pasha, M. (2016). Big Data in the construction industry: A review of present status, opportunities, and future trends. Advanced Engineering Informatics, 30(3), 500-521. https://doi.org/10.1016/j.aei.2016.07.001

© 2016 Elsevier Ltd The ability to process large amounts of data and to extract useful insights from data has revolutionised society. This phenomenon—dubbed as Big Data—has applications for a wide assortment of industries, including the construction... Read More about Big Data in the construction industry: A review of present status, opportunities, and future trends.

Competency-based measures for designing out construction waste: Task and contextual attributes (2016)
Journal Article
Ajayi, S. O., Oyedele, L. O., Kadiri, K. O., Akinade, O. O., Bilal, M., Owolabi, H. A., & Alaka, H. A. (2016). Competency-based measures for designing out construction waste: Task and contextual attributes. Engineering, Construction and Architectural Management, 23(4), 464-490. https://doi.org/10.1108/ECAM-06-2015-0095

© Emerald Group Publishing Limited. Purpose - Competency-based measure is increasingly evident as an effective approach to tailoring training and development for organisational change and development. With design stage widely reckoned as being decisi... Read More about Competency-based measures for designing out construction waste: Task and contextual attributes.

Critical factors for insolvency prediction: Towards a theoretical model for the construction industry (2016)
Journal Article
Alaka, H. A., Oyedele, L. O., Owolabi, H. A., Oyedele, A. A., Akinade, O. O., Bilal, M., & Ajayi, S. O. (2017). Critical factors for insolvency prediction: Towards a theoretical model for the construction industry. International Journal of Construction Management, 17(1), 25-49. https://doi.org/10.1080/15623599.2016.1166546

© 2016 Informa UK Limited, trading as Taylor & Francis Group. Many construction industry insolvency prediction model (CI-IPM) studies have arbitrarily employed or simply adopted from previous studies different insolvency factors, without justificat... Read More about Critical factors for insolvency prediction: Towards a theoretical model for the construction industry.

Big data architecture for construction waste analytics (CWA): A conceptual framework (2016)
Journal Article
Bilal, M., Oyedele, L. O., Akinade, O. O., Ajayi, S. O., Alaka, H. A., Owolabi, H. A., …Bello, S. A. (2016). Big data architecture for construction waste analytics (CWA): A conceptual framework. Journal of Building Engineering, 6, 144-156. https://doi.org/10.1016/j.jobe.2016.03.002

© 2016 Elsevier Ltd. All rights reserved. In recent times, construction industry is enduring pressure to take drastic steps to minimise waste. Waste intelligence advocates retrospective measures to manage waste after it is produced. Existing waste in... Read More about Big data architecture for construction waste analytics (CWA): A conceptual framework.

Reducing waste to landfill: A need for cultural change in the UK construction industry (2016)
Journal Article
Kadiri, K. O., Alaka, H. A., Ajayi, S. O., Oyedele, L., Akinade, O., Bilal, M., & Owolabi, H. (2016). Reducing waste to landfill: A need for cultural change in the UK construction industry. Journal of Building Engineering, 5, 185-193. https://doi.org/10.1016/j.jobe.2015.12.007

© 2015 Elsevier Ltd. All rights reserved. Owing to its contribution of largest portion of landfill wastes and consumption of about half of mineral resources excavated from nature, construction industry has been pressed to improve its sustainability.... Read More about Reducing waste to landfill: A need for cultural change in the UK construction industry.

Evaluation criteria for construction waste management tools: Towards a holistic BIM framework (2016)
Journal Article
Ajayi, S. O., Akinade, O., Oyedele, L., Munir, K., Bilal, M., Owolabi, H. A., …Bello, S. A. (2016). Evaluation criteria for construction waste management tools: Towards a holistic BIM framework. International Journal of Sustainable Building Technology and Urban Development, 7(1), 3-21. https://doi.org/10.1080/2093761X.2016.1152203

© 2016 Informa UK Limited, trading as Taylor & Francis Group. This study identifies evaluation criteria with the goal of appraising the performance of existing construction waste management tools and employing the results in the development of a ho... Read More about Evaluation criteria for construction waste management tools: Towards a holistic BIM framework.

Waste minimisation through deconstruction: A BIM based Deconstructability Assessment Score (BIM-DAS) (2015)
Journal Article
Akinade, O. O., Oyedele, L. O., Bilal, M., Ajayi, S. O., Owolabi, H. A., Alaka, H. A., & Bello, S. A. (2015). Waste minimisation through deconstruction: A BIM based Deconstructability Assessment Score (BIM-DAS). Resources, Conservation and Recycling, 105(Part A), 167-176. https://doi.org/10.1016/j.resconrec.2015.10.018

© 2015 Elsevier B.V. The overall aim of this study is to develop a Building Information Modelling based Deconstructability Assessment Score (BIM-DAS) for determining the extent to which a building could be deconstructed right from the design stage. T... Read More about Waste minimisation through deconstruction: A BIM based Deconstructability Assessment Score (BIM-DAS).

Analysis of critical features and evaluation of BIM software: towards a plug-in for construction waste minimization using big data (2015)
Journal Article
Bilal, M., Oyedele, L. O., Qadir, J., Munir, K., Akinade, O. O., Ajayi, S. O., …Owolabi, H. A. (2015). Analysis of critical features and evaluation of BIM software: towards a plug-in for construction waste minimization using big data. International Journal of Sustainable Building Technology and Urban Development, 6(4), 211-228. https://doi.org/10.1080/2093761X.2015.1116415

© 2016 Taylor & Francis. The overall aim of this study is to investigate the potential of Building Information Modelling (BIM) for construction waste minimization. We evaluated the leading BIM design software products and concluded that none of the... Read More about Analysis of critical features and evaluation of BIM software: towards a plug-in for construction waste minimization using big data.

Waste effectiveness of the construction industry: Understanding the impediments and requisites for improvements (2015)
Journal Article
Ajayi, S. O., Oyedele, L. O., Bilal, M., Akinade, O. O., Alaka, H. A., Owolabi, H., & Kadiri, K. O. (2015). Waste effectiveness of the construction industry: Understanding the impediments and requisites for improvements. Resources, Conservation and Recycling, 102, 101-112. https://doi.org/10.1016/j.resconrec.2015.06.001

© 2015 Elsevier B.V. All rights reserved. Construction industry contributes a large portion of waste to landfill, which in turns results in environmental pollution and CO2 emission. Despite the adoption of several waste management strategies, waste r... Read More about Waste effectiveness of the construction industry: Understanding the impediments and requisites for improvements.

Use of recycled products in UK construction industry: An empirical investigation into critical impediments and strategies for improvement (2014)
Journal Article
Oyedele, L., Ajayi, S. O., & Kadiri, K. O. (2014). Use of recycled products in UK construction industry: An empirical investigation into critical impediments and strategies for improvement. Resources, Conservation and Recycling, 93, 23-31. https://doi.org/10.1016/j.resconrec.2014.09.011

© 2014 Elsevier B.V. All rights reserved. Construction industry consumes about half of all material resources taken from nature, and generates a large portion of waste to landfill. A way of tackling negative environmental impacts impending from conti... Read More about Use of recycled products in UK construction industry: An empirical investigation into critical impediments and strategies for improvement.

Avoiding performance failure payment deductions in PFI/PPP projects: Model of critical success factors (2013)
Journal Article
Oyedele, L. O., & Oyedele, L. (2013). Avoiding performance failure payment deductions in PFI/PPP projects: Model of critical success factors. Journal of Performance of Constructed Facilities, 27(3), 283-294. https://doi.org/10.1061/%28ASCE%29CF.1943-5509.0000367

The overall aim of this paper is to identify critical success factors that would help Private Finance Initiative/facility management (PFI/FM) contractors to avoid performance failure payment deductions in Public Private Partnership/PFI (PPP/PFI) proj... Read More about Avoiding performance failure payment deductions in PFI/PPP projects: Model of critical success factors.

Analysis of architects' demotivating factors in design firms (2013)
Journal Article
Oyedele, L. O., & Oyedele, L. (2013). Analysis of architects' demotivating factors in design firms. International Journal of Project Management, 31(3), 342-354. https://doi.org/10.1016/j.ijproman.2012.11.009

The overall aim of this study is to identify factors that influence architects' demotivation in design firms. After a review of extant literatures in design management, project management, and organisational behaviour, a list of 43 demotivating crite... Read More about Analysis of architects' demotivating factors in design firms.

Confined site construction: An empirical analysis of factors impacting health and safety management (2012)
Journal Article
Spillane, J. P., Oyedele, L., & von Meding, J. (2012). Confined site construction: An empirical analysis of factors impacting health and safety management. Journal of Engineering, Design and Technology, 10(3), 397-420. https://doi.org/10.1108/17260531211274747

Purpose: The purpose of this paper is to identify, clarify and tabulate the various managerial issues encountered, to aid in the management of the complex health and safety concerns which occur within a confined construction site environment. Design/... Read More about Confined site construction: An empirical analysis of factors impacting health and safety management.

Sustaining architects' and engineers' motivation in design firms: An investigation of critical success factors (2010)
Journal Article
Oyedele, L. (2010). Sustaining architects' and engineers' motivation in design firms: An investigation of critical success factors. Engineering, Construction and Architectural Management, 17(2), 180-196. https://doi.org/10.1108/09699981011024687

Purpose - The overall intent of this research is to identify critical factors influencing architects' and design engineers' (AE) motivational level in design firms. Design/methodology/approach - Motivational theories from the literature on organizati... Read More about Sustaining architects' and engineers' motivation in design firms: An investigation of critical success factors.