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Optimisation of resource management in construction projects: A big data approach

Kusimo, Habeeb; Oyedele, Lukumon; Akinade, Olugbenga; Oyedele, Ahmed; Abioye, Sofiat; Agboola, Alirat; Mohammed-Yakub, Naimah


Habeeb Kusimo
Research Associate - Digital Construction with Big Data

Olugbenga Akinade
Associate Professor - AR/VR Development with Artificial Intelligence

Ahmed Oyedele

Sofiat Abioye
TSU Research Associate (NOM Timesheet)

Alirat Agboola

Naimah Mohammed-Yakub


Resource management is one of the key factors for achieving project success, which includes the management of project teams, labour and plant and equipment needed to deliver the project. This study aims to identify challenges facing resource management in the UK construction industry and outline solutions proposed through focus group discussion with industrial experts. Based on a qualitative research methodology, fourteen (14) experts from the UK construction industry were chosen to be participants in the study. The participants were equally divided into two focus groups to discuss resource management using five projects as case studies. Thematic analysis of the discussion reveals seven key factors that affect resource management. The results show that most of the problems identified are due to poor data management processes and the practice of having data in silos. Overcoming this challenge requires the adoption of big data approaches for resource management to allow the integration of huge and different forms of data.


Kusimo, H., Oyedele, L., Akinade, O., Oyedele, A., Abioye, S., Agboola, A., & Mohammed-Yakub, N. (2019). Optimisation of resource management in construction projects: A big data approach. World Journal of Science, Technology and Sustainable Development, 16(2), 82-93.

Journal Article Type Article
Acceptance Date Dec 6, 2018
Online Publication Date Jan 21, 2019
Publication Date 2019
Deposit Date Dec 10, 2018
Journal World Journal of Science, Technology and Sustainable Development
Publisher Emerald
Peer Reviewed Peer Reviewed
Volume 16
Issue 2
Pages 82-93
Public URL
Publisher URL
Additional Information Additional Information : This is the author's accepted manuscript. The final published version is available here:


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