This research reports upon the scale of building information modeling (BIM) implementation maturity, from nonadoption to full-scale deployment, within small-to-medium enterprises (SMEs) operating within the Australian construction industry. The research utilizes a competitive dynamics perspective (CDP) as the theoretical lens and analyses data collected from 135 SMEs using Bayesian belief networks (BBNs) to provide a richer insight into levels of BIM implementation maturity. Findings reveal that there is no meaningful association between BIM implementation maturity within SMEs and their organizational attributes, such as size and level of experience. A paucity of solid evidence to support a reasonable return on investment (ROI) was also identified as a key barrier to using BIM in higher levels of maturity. In practical terms, the study focuses on pertinent issues associated with mandated BIM in Australia from SMEs' perspectives, pointing out potential consequences and challenging the pressure for mandating. The research concludes by outlining industrial implications and providing pragmatic recommendations designed to accelerate the pace that Australian SMEs move across a BIM trajectory from nonadoption to higher levels of maturity.

Purpose: Integrating building information modelling (BIM) into facility management (FM) has generated fervent debate within the extant literature given an increasing realisation amongst practitioners that the majority of BIM benefits reside within the whole lifecycle management. Converting a building’s in-use data and information into tangible business knowledge to augment FM performance is crucial for business growth and prosperity. Yet curiously, scant academic attention has been paid in investigating the data and information hand-over process through BIM required by FM. The purpose of this paper is to address this knowledge gap. Design/methodology/approach: The research approach adopted draws upon pertinent BIM in the FM literature and a qualitative discourse accrued via focus group meetings of Australian FM experts. Findings: The study’s findings are presented as a data and information typology matrix that captures the associations among different forms of data ownership, FM service delivery categories and data and information typologies for using BIM in FM. Practical implications: The analysis results will prove invaluable for policy-makers, researchers and practitioners by providing a relevant data and information typology and capturing the complex associations in the process of integrating BIM into FM. Originality/value: This study contributes to the field by providing a better understanding of different forms of data and information, required by members of a FM team. The original insight shared here is the necessity to consider a distinctive array of interests and the potential for using different forms of data and information when integrating BIM into FM.