Understanding laborers' behavioral diversities in multinational construction projects using integrated simulation approach

Purpose: Employing multi-type laborers (MLs) is common in multinational and cross-culture projects (MPCs). Different attributes of MLs can lead to uncertain and dynamic laborer behaviors (i.e. behavioral diversities), which may cause project deviations. Previous studies do not consider the uncertainties or dynamics of behaviors adequately or they only provide general suggestions. The purpose of this paper is to combine system dynamics (SD) and agent-based modeling (ABM) to build an integrated model. The proposed ABM-SD can gain better understanding of MLs' behavioral diversities, reveal the associated impacts and improve project management. Design/methodology/approach: Based on extensively review in construction labor management and computer simulation, architecture is built to depict the relationships between the affecting factors of MLs' behaviors, MLs' behavioral diversities and project performance. Second, conceptual structures of the ABM-SD model are developed. Third, methods to implement the model in practice are introduced, focusing on data collection and model structure adjustment. Finally, the model is tested in a case study. Findings: Different ML groups have distinctive behaviors which constantly change through interactions between MLs, engineers and external environment. Inadequate consideration of the diversities can result in inaccurate estimation of productivity, work quality and absenteeism, causing severe project deviations such as schedule delay, cost overrun and high absenteeism. On the other hand, using the ABM-SD model, the root causes of project deviations are analyzed from the perspective of MLs' behavioral diversities and the optimization of labor management can significantly improve project performance. Research limitations/implications: This paper supplements previous studies because the ABM-SD model takes fully use of the strength of simulation of solving uncertain and dynamic problems and combines both qualitative and quantitative findings in existing studies of labor management. Besides, the ABM-SD model is also a practical management tool to better monitor laborer behaviors and forecast the impacts. The limitation is mainly about the small scale of the case study. However, the ABM-SD model already demonstrates the mechanism about how MLs' different behaviors affect a project, which fulfill the aim of the study. Practical implications: The ABM-SD model can simulate MLs' behavioral diversities and produce reliable estimations of project performance. It also allows to optimize management plans. Furthermore, The ABM-SD model is adjustable based on specific project conditions, which make it applicable for different tasks, different laborer compositions and even different projects. Thus, the ABM-SD model can be a practical tool for engineers in MCPs. Originality/value: SD and ABM are applied to study behaviors with well-known benefits in both separated and integrated manner. However, few studies use the approach to investigate MLs' behaviors in MCPs. Hence, the proposed ABM-SD model is an original attempt to improve the laborer management level in MCPs.