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Big data analytics in the AEC industry: scientometric review and synthesis of research activities

Eric Ohene (Department of Building and Real Estate, The Hong Kong Polytechnic University, Kowloon, Hong Kong) (Department of Construction Technology and Management, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana)
Gabriel Nani (Department of Construction Technology and Management, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana)
Maxwell Fordjour Antwi-Afari (Department of Civil Engineering, Aston University, Birmingham, UK)
Amos Darko (Department of Construction Management, University of Washington, Seattle, Washington, USA)
Lydia Agyapomaa Addai (Office of the Administrator of Stool Lands, Lands Commission, Accra, Ghana)
Edem Horvey (University of Ghana, Legon, Ghana)

Engineering, Construction and Architectural Management

ISSN: 0969-9988

Article publication date: 24 September 2024

244

Abstract

Purpose

Unlocking the potential of Big Data Analytics (BDA) has proven to be a transformative factor for the Architecture, Engineering and Construction (AEC) industry. This has prompted researchers to focus attention on BDA in the AEC industry (BDA-in-AECI) in recent years, leading to a proliferation of relevant research. However, an in-depth exploration of the literature on BDA-in-AECI remains scarce. As a result, this study seeks to systematically explore the state-of-the-art review on BDA-in-AECI and identify research trends and gaps in knowledge to guide future research.

Design/methodology/approach

This state-of-the-art review was conducted using a mixed-method systematic review. Relevant publications were retrieved from Scopus and then subjected to inclusion and exclusion criteria. A quantitative bibliometric analysis was conducted using VOSviewer software and Gephi to reveal the status quo of research in the domain. A further qualitative analysis was performed on carefully screened articles. Based on this mixed-method systematic review, knowledge gaps were identified and future research agendas of BDA-in-AECI were proposed.

Findings

The results show that BDA has been adopted to support AEC decision-making, safety and risk assessment, structural health monitoring, damage detection, waste management, project management and facilities management. BDA also plays a major role in achieving construction 4.0 and Industry 4.0. The study further revealed that data mining, cloud computing, predictive analytics, machine learning and artificial intelligence methods, such as deep learning, natural language processing and computer vision, are the key methods used for BDA-in-AECI. Moreover, several data acquisition platforms and technologies were identified, including building information modeling, Internet of Things (IoT), social networking and blockchain. Further studies are needed to examine the synergies between BDA and AI, BDA and Digital twin and BDA and blockchain in the AEC industry.

Originality/value

The study contributes to the BDA-in-AECI body of knowledge by providing a comprehensive scope of understanding and revealing areas for future research directions beneficial to the stakeholders in the AEC industry.

Keywords

Acknowledgements

Conflicts of interest: The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analysis, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.This paper is part of a larger MSc. research project focused on the adoption and application of big data in the AEC industry. The authors gratefully acknowledge the Ghana Education Trust Fund (GETFund) for funding this study. We also extend our sincere thanks to the Department of Construction Technology and Management at KNUST for their support. Special appreciation goes to the Editors and anonymous reviewers, whose constructive and invaluable comments and suggestions significantly enhanced the quality of this work.

Citation

Ohene, E., Nani, G., Antwi-Afari, M.F., Darko, A., Addai, L.A. and Horvey, E. (2024), "Big data analytics in the AEC industry: scientometric review and synthesis of research activities", Engineering, Construction and Architectural Management, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/ECAM-01-2024-0144

Publisher

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Emerald Publishing Limited

Copyright © 2024, Emerald Publishing Limited

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