Building Information Modeling (BIM) is a trending technology in the building industry that can increase efficiency throughout construction. Various practical information can be obtained from BIM models during the project life cycle. However, accessing this information could be tedious and time-consuming for non-technical users, who might have limited or no knowledge of working with BIM software. Automating the information inquiry process can potentially address this need. This research proposes an Artificial Intelligence-based framework to facilitate accessing information in BIM models. First, the framework uses a support vector machine (SVM) algorithm to determine the user's question type. Simultaneously, it employs natural language processing (NLP) for syntactic analysis to find the main keywords of the user's question. Then it utilizes an ontology database such as IfcOWL and an NLP method (latent semantic analysis (LSA)) for a semantic understanding of the question. The keywords are expanded through the semantic relationship in the ontologies, and eventually, a final query is formed based on keywords and their expanded concepts. A Navisworks API is developed that employs the identified question type and its parameters to extract the results from BIM and display them to the users. The proposed platform also includes a speech recognition module for a more user-friendly interface. The results show that the speed of answering the questions on the platform is up to 5 times faster than the manual use by experts while maintaining high accuracy.

‘Global Projects’ and ‘Global Virtual Teams’ are revolutionizing the construction industry. An increasing number of multi-national engineering firms are adopting this business model due to the possible advantages of cost and time optimization. However, literature identifies several challenges that the project teams endure in temporarily organizing while transitioning through time and space, some of which include cross-cultural differences in teams and limited richness of the communication media. Perceiving virtual project execution as a multi-variable construct, organizational theorists and sociologists adopt a socio-technical approach to understand the dynamics of action embedded in the process and recommend implementation of pre-process, during process or post process intervention strategies to enable performance. In this paper, we address this research concern through an experimental study conducted across two global universities, National Institute of Construction Management and Research, Pune, India and Washington State University, USA. Around 24 students from each university in ten teams collaborated virtually for a period of 2.5 weeks to develop a 3-dimensional Revit model and a 4-dimensional BIM model in Autodesk Revit and Navisworks, respectively, for a multi-storey residential building. The study aimed to investigate the role of project teams in organizing and coordinating projects tasks and taking a socio-technical approach, explored the role of a BIM Execution Plan as a pre-process intervention strategy. Data collected through qualitative survey post the experiment was qualitatively analyzed using ethnographic coding techniques. Findings showed that the project and team challenges primarily stemmed from coordination issues and institutional differences. Members significantly mitigated the issues through a proactive approach and a priori planning. The BIM Execution Plan allowed members to instantly get involved with the tasks and plan the process apart from being able to foresee the complexity. Teams emphasized the importance of implementing a detailed BIM Execution Plan during the planning phase for a collaborative and successful project outcome and further observed that pre-process intervention strategy such as a BIM plan was the needed impetus for members to collaborate and coordinate project tasks.