(untitled) (International Journal of Built Environment and Sustainability, 2018)
The volume of data generated by the construction industry has increased exponentially following an intense use of modern technologies. The data explosion thus lead towards the big data phenomenon which is envisioned to revolutionize the construction like never before. Like any other technologies, big data is a disruptive paradigm and inevitably will give impact to the construction industry. As the industry is refocusing towards an improved productivity, the appeal to embrace big data is certain given the value it offers. This certainly will benefit construction akin to the manufacturing and the retail industry alike. Nevertheless, a review of the literature suggested a limited coverage on the potential application of big data in construction as compared to other industries. This limits understanding of its potential, where the industry is seemingly unaware thus could not relate and extract its real value. Hence, this study aims to draw insights on the specific areas of construction big data research. The research objectives include: (1) to analyse the current extent of construction big data research; (2) to map out the orientation of the current construction big data research; and (3) to suggest the current directions of construction big data research. The qualitative method through a desk study approach has been carried out to attain the first two objectives. It involved a structured review process which covered articles from the online databases assisted by the Nvivo software. This resulted in the theoretical orientation which was conceptualized as: (1) project management; (2) safety (3) energy management; (4) decision making design framework and (5) resource management. The theoretical orientation discovered from the review process will form the basis to suggest the prospective directions of research on big data in construction. This exploration is substantial as a precursor to a much deeper study on big data. As big data is set to influence the industry, the finding made would be a catalyst for creating an awareness to support the development of big data for the construction industry.