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PurposeThe government plays a critical role in driving building information modeling (BIM) implementation. The purpose of this study is to investigate the government efforts for driving BIM implementation in three benchmark countries, namely, Singapore, the UK and the US, so as to develop appropriate roadmaps for increasing BIM implementations in other countries.Design/methodology/approachThis study performs a review on the government efforts and roles in BIM implementation in three benchmark countries, namely, Singapore, the UK and the US.FindingsThrough cross comparison with existing literature, it is found that Singapore and the UK adopt a government-driven approach and a phase-by-phase development pattern is observed. The first phase focuses on the building sector to rapidly increase the use of BIM and the government generally plays the role of an initiator. In the second phase, BIM is expanded to other implementation areas, e.g. smart city. The importance of the initiator role decreases and more attention is paid to supporting roles such as researcher, educator and regulator. In contrast, an industry-driven approach is adopted in the US. The main role of the government is that of a regulator, with research institutions actively supporting the BIM implementation.Research limitations/implicationsGeneral roadmaps of the two mandating approaches are presented. The results can provide a useful reference for countries and regions that intend to develop roadmaps to increase their BIM maturity level and enhance readiness to accept and implement BIM.Originality/valueThis study is one of the first studies that investigate the step-by-step roadmaps for implementing BIM from the perspective of changing government roles.

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Prefabrication housing production (PHP) processes are fragmented and full of variability. Their schedule reliability is particularly disturbed by the constraints deriving from task executions in the on-site assembly process. Proactive constraints modeling, including identifying constraints and understanding their interrelationships, is crucial to ensure successful task executions and enhance sociability in collaborative working. However, current methods for constraints modeling are often sluggish and heavily rely on human's commitments because there is no real-time and value-added information for decision-making. To address this issue, this study proposes an approach of smart work packaging (SWP)-enabled constraints modeling service, which consists of three dynamic sub-services: social network analysis (SNA) service, hybrid system dynamics (SD)-discrete event simulation (DES) model service, and constraints scenario analysis service. It can equip the workers with the ability to (1) automatically identify the critical constraints, (2) dynamically explore interactional and interdependent relationships of these constraints, and (3) simulate and analyze the impact on schedule performance under different constraints scenarios. Five critical constraints are identified, including adverse weather conditions, lack of collision-free path planning, lack of visible and audible communication mechanism, lack of optimal buffer layout, and lack of optimal installation sequence. Most interrelationships are depicted in the four modules of the hybrid SD-DES model, including the assembly process, resource availability, operation efficiency, and schedule performance. Finally, the most influential constraint "lack of collision-free path planning" to schedule performance is identified in the constraints scenario analysis process.

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.