Hybrid fuzzy Monte Carlo agent-based modeling of workforce motivation and performance in construction
ISSN: 1471-4175
Article publication date: 21 May 2021
Issue publication date: 29 July 2021
Abstract
Purpose
This paper aims to cover the development of a methodology for hybrid fuzzy Monte Carlo agent-based simulation (FMCABS) and its implementation on a parametric study of construction crew performance.
Design/methodology/approach
The developed methodology uses fuzzy logic, Monte Carlo simulation and agent-based modeling to simulate the behavior of construction crews and predict their performance. Both random and subjective uncertainties are considered in model variables.
Findings
The developed methodology was implemented on a real case involving the parametric study of construction crew performance to assess its applicability and suitability for this context.
Research limitations/implications
This parametric study demonstrates a practical application for the hybrid FMCABS methodology. Though findings from this study are limited to the context of construction crew motivation and performance, the applicability of the developed methodology extends beyond the construction domain.
Practical implications
This paper will help construction practitioners to predict and improve crew performance by taking into account both random and subjective uncertainties.
Social implications
This paper will advance construction modeling by allowing for the assessment of social interactions among crews and their effects on crew performance.
Originality/value
The developed hybrid FMCABS methodology represents an original contribution, as it allows agent-based models to simultaneously process all types of variables (i.e. deterministic, random and subjective) in the same simulation experiment while accounting for interactions among different agents. In addition, the developed methodology is implemented in a novel and extensive parametric study of construction crew performance.
Keywords
Acknowledgements
This paper forms part of a special section “Hybrid Simulation in Construction”, guest edited by Farnad Nasirzadeh, Susan Howick and SangHyun Lee.
This research is funded by the Natural Sciences and Engineering Research Council of Canada Industrial Research Chair in Strategic Construction Modeling and Delivery (NSERC IRCPJ 428226–15). The authors gratefully acknowledge the support and data provided by industry partners and all personnel who participated in this study.
Citation
Raoufi, M. and Fayek, A.R. (2021), "Hybrid fuzzy Monte Carlo agent-based modeling of workforce motivation and performance in construction", Construction Innovation, Vol. 21 No. 3, pp. 398-416. https://doi.org/10.1108/CI-03-2020-0045
Publisher
:Emerald Publishing Limited
Copyright © 2021, Emerald Publishing Limited