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

Eric Ohene*, Gabriel Nani, Maxwell Fordjour Antwi-Afari, Amos Darko, Lydia Agyapomaa Addai, Edem Horvey

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

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.

Original languageEnglish
Number of pages33
JournalEngineering, Construction and Architectural Management
Early online date24 Sept 2024
DOIs
Publication statusE-pub ahead of print - 24 Sept 2024

Keywords

  • AEC
  • Bibliometric analysis
  • Big data
  • Big data analytics
  • Systematic analysis

Fingerprint

Dive into the research topics of 'Big data analytics in the AEC industry: scientometric review and synthesis of research activities'. Together they form a unique fingerprint.

Cite this