Understanding the complexity of project team member selection through agent-based modeling

Shu-Chien Hsu, Kai Wei Weng, Qingbin Cui, William Rand

Research output: Journal article publicationJournal articleAcademic researchpeer-review

22 Citations (Scopus)

Abstract

Previous research has recognized the significance of a team's work capacity and suggested the selection of team members based on individual skills and performance in alignment with task characteristics. However, work teams are complex systems with interdependence between workers and the social environment, and exhibit surprising, nonlinear behavior. This study utilizes Agent-Based Modeling (ABM) to understand the complexity of project team member selection and to examine how the functional diversity of teams and worker interdependence affect team performance in different economic conditions. Data for model validation was collected from 116 construction projects for the period from 2009 to 2011. The results show that teams with higher functional diversity can enhance the overall firm performance when the economy is in a downturn. This study suggests managers using knowledge of worker interdependence to protect higher-performing workers by minimizing disruption of interdependence in team member selection for improving firm performance.
Original languageEnglish
Pages (from-to)82-93
Number of pages12
JournalInternational Journal of Project Management
Volume34
Issue number1
DOIs
Publication statusPublished - 1 Jan 2016

Keywords

  • Agent-based modeling
  • Complexity
  • Diversity
  • Interdependence
  • Team member selection

ASJC Scopus subject areas

  • Business and International Management
  • Management of Technology and Innovation

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