Data Management Risks: A Bane of Construction Project Performance

Ornella Tanga (), Opeoluwa Akinradewo (), Clinton Aigbavboa, Ayodeji Oke and Samuel Adekunle
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Ornella Tanga: cidb Centre of Excellence, Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg 2006, South Africa
Opeoluwa Akinradewo: cidb Centre of Excellence, Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg 2006, South Africa
Clinton Aigbavboa: cidb Centre of Excellence, Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg 2006, South Africa
Ayodeji Oke: cidb Centre of Excellence, Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg 2006, South Africa
Samuel Adekunle: cidb Centre of Excellence, Faculty of Engineering and the Built Environment, University of Johannesburg, Johannesburg 2006, South Africa

Sustainability, 2022, vol. 14, issue 19, 1-20

Abstract: The construction industry is a sector that creates employment opportunities for everybody from all backgrounds. A good performance achieved through managing data is one factor that enables the construction industry’s success and development. Unfortunately, data management encounters challenges regarding data safety, due to the implementation of the fourth industrial revolution (4IR) (digitalisation). This study sets out to evaluate the effects of risks to data management on the performance of construction projects. This research work used a quantitative methodology and gathered information from different construction professionals in the South African construction industry via a well-structured questionnaire through online platforms. These professionals were quantity surveyors, architects, civil, mechanical, and electrical engineers practising for a firm, company, organization, or institution within Gauteng province, South Africa. A random sampling technique was used in this research to ensure that each part and set of individuals had an equivalent possibility of being incorporated into the sample. Of 215 questionnaires sent out, 181 (84.19%) responses were received and used for data analysis. Mean item score (MIS), standard deviation (SD), a non-parametric test, and exploratory factor analysis were used to analyse the retrieved data. Findings revealed that loss of construction project data, loss of confidential information, company image and reputational harm are among the top three effects that risks to data have on people working in the construction sector. This study concluded that these data management risk effects could be prevented if construction project stakeholders were aware of the different data management risks.

Keywords: construction industry; data; data management; risks (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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