Methodology for Creating Empirically Supported Agent-Based Simulation with Survey Data for Studying Group Behavior of Construction Workers

Abstract

Construction workers’ attitudes and behaviors are one of the most important factors of a construction project’s performance. As the attention paid to the impact of social influences and norms on worker behavior grows, agent-based modeling and simulation (ABMS) emerges as a research tool for studying workers’ group behavior. With ABMS, researchers can uncover the underlying process of group behavior emerging from individuals’ interactions in an organization. However, validating agent-based simulation with real data is the greatest challenge in using ABMS for organizational behavior research. With this background in mind, the objective of this paper is to propose a methodology for creating an empirically supported agent-based model for studying workers’ behavior influenced by social norms. The proposed methodology suggests that empirical data collected by a questionnaire can be used for ABMS in three steps: (1) testing the agent behavior rules used in an agent-based model (i.e., testing the modeling assumptions), (2) demonstrating the model behavior’s qualitative agreement with real workers’ behavior (i.e., testing the simulation results against real data in a qualitative manner), and (3) creating a specific agent-based model with the model parameters that correspond to a specific empirical case. A specific agent-based model created in this way can then be seen as a scenario generator that corresponds to a specific reality and can be used to answer