Fuzzy Agent-Based Modeling of Construction Crew Motivation and Performance

• Author / Creator

  Raoufi, Mohammad

• Crew performance is influenced not only by the environment where construction activities occur, but also by crew motivation, which has largely been overlooked in construction research. For many years, construction engineering researchers have observed that motivational differences within construction crews explain meaningful variance in the performance of those crews. However, construction researchers have long had difficulties identifying the motivational factors that affect crew motivation and performance. These difficulties are due to the uniqueness and dynamism of the construction environment and the fact that motivation occurs at both individual and crew levels. Furthermore, previous construction research has not comprehensively investigated situational/contextual factors and their impact on the relationship between crew motivation and performance. To overcome these difficulties, two methodological approaches, agent-based modeling and fuzzy logic, are applied and integrated to develop a model of construction crew motivation and performance. Agent-based modeling is a good solution for handling complex systems of interacting agents and is therefore suitable for modeling construction crew behaviour. Agent-based modeling can handle system complexities that arise from the interactions of system components; however, many systems—especially those comprising human behaviour and social relationships—also include subjective uncertainties, which are not accounted for in agent-based modeling. Fuzzy logic, on the other hand, is able to deal with subjective uncertainty. Therefore, integrating these two techniques is advantageous for modeling behavioural and social systems, such as those that arise through the interaction of construction crew motivation and performance. This research presents a review of the literature on motivation in both the construction and non-construction domains, and it uses recent advancements in motivation research from non-construction disciplines to bridge the gaps in construction literature. This research identifies the factors affecting construction crew motivation and performance, defines a comprehensive set of crew performance metrics, analyzes the relationship between motivational factors and crew performance metrics, and identifies the key situational/contextual factors that affect the relationship between crew motivation and performance. Given that motivation is subjective in nature, the research provides a fuzzy agent-based model of construction crew motivation and performance, which is validated based on collected field data. This research makes seven major contributions. First, it presents a novel methodology for identifying and measuring motivational factors at both the individual and crew levels. Second, it defines a methodology to evaluate and rank critical factors and factors with a high potential for improvement in construction crew motivation and performance and to evaluate the differences between the perspectives of supervisors and craftspeople on the identified critical factors. Third, it develops a comprehensive set of factors affecting crew motivation and performance; and developing a comprehensive set of construction crew performance metrics that relate not only to task performance, but also to contextual performance and counterproductive behaviour. Fourth, it reveals how motivational factors affect crew performance; and provides a comprehensive list of the key moderators of the relationship between construction crew motivation and performance. Fifth, it expands the scope of applicability of ABM by integrating fuzzy logic with ABM to create fuzzy agent-based models, which can handle both probabilistic and subjective uncertainty. Sixth, it provides a novel methodology for developing fuzzy agent-based models, which can be used to develop new models to assess construction processes and practices. Seventh, it develops a fuzzy agent-based model of construction crew motivation and performance, which improves the assessments of crew performance by considering not only the interactions of crews in the project but also the subjective uncertainties in the model variables such as crew motivation. The findings of this research also directly contribute to the construction industry by helping managers and decision makers improve their workforce practices.

• Subjects / Keywords

  • Constructions
  • Fuzzy
  • Motivations
  • Performance
  • Agent-based

• Graduation date

  Spring 2018

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/R3377695S

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.