ABSTRACT
The adoption of digital technologies such as big data analytics (BDA) for health, safety, and well-being (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, which is a prerequisite for digital solutions. The implications of the findings include the need for an adequate legal framework and international standards to settle the dispute between countries arising from data issues. Empirical studies to assess the barriers are recommended.
