Nnedinma Umeokafor
Barriers to big data techniques application in construction safety, health and wellbeing
Umeokafor, Nnedinma; Umar, Tariq
Authors
Dr. Tariq Umar Tariq.Umar@uwe.ac.uk
Senior Lecturer in Construction Project Management
Contributors
Patrick Manu Patrick.Manu@uwe.ac.uk
Editor
Gao Shang
Editor
Paulo Jorge Silva Bartolo
Editor
Valerie Francis
Editor
Anil Sawhney
Editor
Abstract
The adoption of digital technologies such as big data analytics (BDA) for health, safety, and wellbeing (HSW) improvement in construction has increased but continues to experience challenges. Reviewing extant literature, this chapter identifies and discusses the barriers to HSW improvement using BDA. The barriers include technical issues such as the inability of existing machine learning techniques such as the fuzzy-neural method to predict HSW risks by analysing incident data, and the large size, heterogeneous and dynamic nature of construction accident data. While the socio-technical barriers include BDA skills shortage, the financial ones cover the high cost associated with BDA. Data dispute among companies, organisational culture, and ignorance of the potential of BDA in improving HSW which results in its limited acceptance and implementation in HSW are identified. There are also operational barriers in terms of digital poverty in construction, and supply chain issues where the fragmented supply chain of the industry and the uniqueness of projects do not facilitate a collaborative environment, a prerequisite for digital solutions. The implications of the findings include the need for an adequate legal framework international standard to settle the dispute between countries arising from data issues. Empirical studies to assess the barriers are recommended.
Online Publication Date | May 12, 2023 |
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Publication Date | May 12, 2023 |
Deposit Date | May 5, 2023 |
Publicly Available Date | Nov 13, 2024 |
Publisher | Taylor & Francis |
Pages | 169-179 |
Edition | 1st |
Book Title | Handbook of Construction Safety, Health and Well- being in the Industry 4.0 Era |
Chapter Number | 15 |
ISBN | 9781032079929 |
Keywords | Big data, big data techniques, construction, construction safety, health and wellbeing, wellbeing |
Public URL | https://uwe-repository.worktribe.com/output/10741692 |
Publisher URL | https://www.routledge.com/Handbook-of-Construction-Safety-Health-and-Well-being-in-the-Industry/Manu-Shang-Bartolo-Francis-Sawhney/p/book/9781032079929 |
Contract Date | Oct 13, 2022 |
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Copyright Statement
This is the author’s accepted manuscript of an original book chapter published by Taylor & Francis ‘Umeokafor, N., & Umar, T. 2023. Barriers to big data techniques application in construction safety, health and wellbeing. In Handbook of Construction Safety, Health and Well- being in the Industry 4.0 Era (169-179). London: Taylor & Francis’.
The published version is available at: https://www.routledge.com/Handbook-of-Construction-Safety-Health-and-Well-being-in-the-Industry/Manu-Shang-Bartolo-Francis-Sawhney/p/book/9781032079929
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