Fuzzy Agent-Based Multicriteria Decision-Making Model for Analyzing Construction Crew Performance

Abstract

Selecting economically feasible policies for maximizing crew motivation and performance is a multifaceted problem, and each aspect of the process poses considerable unique challenges for construction practitioners. Fuzzy agent-based modeling (FABM) addresses some of the challenges of predicting crew performance (e.g., it accounts for both subjective uncertainties and crew dynamics), but strategy selection is a decision-making problem that is also compounded by expert disagreements, insufficient information, and differing stakeholder priorities. This paper proposes a methodology for integrating multicriteria decision-making (MCDM) with FABM to develop a decision support model that simulates the complex relationships and social interactions between crews and crew members for use in decision-making. This model also accounts for dynamic construction environments and captures the subjective factors that influence crew motivation and performance. The contributions of this paper are twofold. First, it proposes a methodology that will help improve decision-making processes in construction by expanding the scope of MCDM through integration with FABM. Second, it develops a fuzzy agent-based multicriteria decision-making model that helps construction practitioners adopt economically feasible strategies for improving the motivation and performance of construction crews. Furthermore, the proposed methodology can be adapted to several construction problems to help decision makers prioritize and select from several strategies intended to improve different crew performance measures.