Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

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

Optimisation of resource management in construction projects: a big data approach The purpose of this paper is to identify challenges faced in resource management in the UK construction industry and to propose some solutions to these problems.Design/methodology/approachBased on a qualitative research methodology, 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.FindingsThe 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 large and different forms of data.Originality/valueThis study seeks to bring to the fore challenges faced in resource management by the UK construction industry and to outline some solutions to address them. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png World Journal of Science, Technology and Sustainable Development Emerald Publishing

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

Download PDF
12 pages

Loading next page...
 
/lp/emerald-publishing/optimisation-of-resource-management-in-construction-projects-a-big-2D7wG42A0Q
Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
2042-5945
DOI
10.1108/wjstsd-05-2018-0044
Publisher site
See Article on Publisher Site

Abstract

The purpose of this paper is to identify challenges faced in resource management in the UK construction industry and to propose some solutions to these problems.Design/methodology/approachBased on a qualitative research methodology, 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.FindingsThe 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 large and different forms of data.Originality/valueThis study seeks to bring to the fore challenges faced in resource management by the UK construction industry and to outline some solutions to address them.

Journal

World Journal of Science, Technology and Sustainable Development – Emerald Publishing

Published: May 16, 2019

Keywords: Construction projects; Resource management; Big data; Resource allocation; Resource optimization

References

  • Analysis of factors influencing project cost estimating price
    Akintoye, A.
  • Risk management in construction projects
    Banaitien, N.; Banaitis, A.
  • Optimizing resource allocation for HIV/AIDS prevention programmes: an analytical framework
    Bautista-Arredondo, S.; Gadsden, P.; Harris, J.E.; Bertozzi, S.M.
  • A new framework for determining critical success/failure factors in projects
    Belassi, W.; Tukel, O.I.
  • The project benefits of building information modelling (BIM)
    Bryde, D.; Broquetas, M.; Volm, J.M.
  • Resource leveling in construction by optimization
    Easa, S.M.
  • Single market exit: UK construction ‘could lose 175,000 EU workers
    Fletcher, N.
  • Optimization of resource allocation and levelling using genetic algorithms
    Hegazy, T.
  • Ethical issues in qualitative nursing research
    Holloway, I.; Wheeler, S.
  • Optimal allocation of project management resources for achieving success
    Jaselskis, E.J.; Ashley, D.B.
  • Top 4 challenges facing the construction industry
    Leeds, R.
  • Big data maturity model – a preliminary evaluation
    Mohd Drus, S.; Hassan, N.H.
  • Big Data – concepts, applications, challenges and future scope
    Mukherjee, S.; Shaw, R.
  • Resource management in construction projects – a case study
    Nagaraju, S.K.; Reddy, B.S.
  • The effectiveness in managing a group of multiple projects: factors of influence and measurement criteria
    Patanakul, P.; Milosevic, D.
  • Critical success factors in R&D projects
    Pinto, J.K.; Slevin, D.P.
  • Why Big Data is the booster shot the healthcare industry needs
    Ram, S.
  • A hybrid genetic algorithm for the RCPSP
    Valls, F.; Ballestin, F.; Quintanilla, M.S.
  • Project manager leadership role in improving project performance
    Anantatmula, V.S.
  • Big data computing and clouds: challenges, solutions, and future directions
    Assuncao, M.D.; Calheiros, R.N.; Bianchi, S.; Netto, M.A.; Buyya, R.
  • Big Data in the construction industry: a review of present status, opportunities, and future trends
    Bilal, M.; Oyedele, L.O.; Qadir, J.; Munir, K.; Ajayi, S.O.; Akinade, O.O.; Owolabi, H.A.; Alaka, H.A.; Pasha, M.
  • Some efficient multi-heuristic procedures for resource-constrained project scheduling
    Boctor, F.F.
  • Construction resource scheduling with genetic algorithms
    Chan, W.T.; Chua, D.K.H.; Kannan, G.
  • The construction industry as a loosely coupled system: implications for productivity and innovation
    Dubois, A.; Gadde, L.-E.
  • Moving on-beyond lean thinking
    Koskela, L.J.
  • The evolution of lean six sigma international
    Pepper, M.P.; Spedding, T.A.
  • Resource constrained project scheduling problems-a review article
    Rao, P.B.; Chaitanya, K.M.
  • Resource scheduling using neural dynamics model of Adeli and Park
    Senouci, A.B.; Adeli, H.
  • Analysis of the characteristics of projects in diverse industries
    Tukel, O.I.; Rom, W.O.