Data Management Practices among South African Construction Professionals: Implications for Industry 4.0 Technologies in Construction Practices

Timothy Oluwafemi Ayodele, Abel Olaleye, Ayodele Adegoke and Chioma Okoro

AfRES from African Real Estate Society (AfRES)

Abstract: Purpose – This study examined the sources of construction data, the methods of data acquisition and storage, and the factors that influence data management practices among construction professionals in South Africa with a view to establishing their preparedness for Industry 4.0 technologies. Design/Methodology/Approach - The study sampled the construction professionals registered with the South African Council for the Project and Construction Management Professions (SACPCMP). A closed-ended questionnaire was administered using an online survey tool. The data collected from a total of 134 responses were analysed using mean scores, standard deviations, one-sample t-test, and principal component analysis. Findings – The results showed that the main sources of construction data are: firms' databases, networking with professional colleagues, and employees’ personal records, with mean values of 4.19, 3.51, and 3.40 respectively. Also, findings revealed that data are stored mainly via electronic databases (mean = 4.33) and paper/manual records (mean = 3.94). The PCA result showed that project characteristics/industry/organizational idiosyncrasies and level of standardization/ICT tools/skills were the major factors influencing data management practices. While these two components have variances of 35.876% and 29.540% respectively, the two cumulatively explained 65.417% of the total variance. The study concluded that data management has become an important part of the construction professional’s role Originality/value – With the increasing integration of Industry 4.0 into construction practices, and the important roles of construction professionals in data sharing and assemblage, the paper highlights the need for conscious efforts toward ensuring good data management practices.

Keywords: Automation; construction professionals; data assemblage; data sources; Industry 4.0 (search for similar items in EconPapers)
JEL-codes: R3 (search for similar items in EconPapers)
Date: 2023-01-01
New Economics Papers: this item is included in nep-ict
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