Integrated BIM-Driven Cost Management for Construction Phases

Thesis Abstract

The rapid advancement of building information modeling (BIM) technologies has substantially reshaped cost management practices across construction projects, yet its full integration across design, procurement, and construction phases remains uneven, leading to budget overruns, change orders, and delayed value realization. This study investigates how an integrated BIM-driven approach can enhance cost management accuracy, transparency, and control throughout construction phases in medium-to-large scale projects. The aim is to develop, implement, and evaluate a cohesive BIM-enabled cost management framework that unifies quantity surveying, cost planning, scheduling, and change management processes from concept to handover. Specific objectives are to (1) identify critical BIM-enabled cost management activities across project phases, (2) design a process model linking BIM objects, cost data, and workflow responsibilities, (3) implement the model within a pilot project using a multidisciplinary BIM platform, (4) evaluate cost performance against traditional practices in terms of accuracy, timeliness, and stakeholder satisfaction, and (5) formulate guidelines for scaling the framework to industry practice. The study adopts a mixed-methods design anchored in realist evaluation and action research principles, enabling iterative refinement of the framework within real project conditions. The population comprises 24 ongoing medium-to-large construction projects within a metropolitan region, with a purposive sample of 6 projects selected to implement the pilot BIM-driven cost management framework. Data collection involves (i) archival project data including baseline and final cost reports, change orders, and cash-flow records; (ii) semi-structured interviews with 18 stakeholders across roles in project management, cost consultancy, design, and procurement; (iii) BIM model exports and metadata capturing quantity, unit rates, and cost flags; and (iv) field observations and workshop outputs from monthly review meetings. Instrument reliability and validity are ensured through triangulation, pilot testing of interview guides, and member checks. Descriptive statistics will summarize quantitative cost metrics, while confirmatory factor analysis (CFA) will test the alignment of BIM-derived cost drivers with observed performance. Regression analysis will examine the relationship between BIM-enabled data quality and cost variance, and time-series analyses will assess changes in cash-flow predictability. Thematic analysis will interpret interview data to elucidate enablers and barriers to adoption. A conceptual model integrating the Standards of BIM Execution and the Theory of Integrated Project Delivery (IPD) will guide analysis, complemented by the Resource-Based View (RBV) to explain how BIM data capabilities translate into competitive advantages in project performance. Expected findings include (i) demonstrable reductions in cost variance and change order frequency when BIM-driven cost management processes are properly integrated with project controls, (ii) enhanced early warning indicators for budget overruns driven by real-time quantity and rate updates, (iii) improved stakeholder collaboration and decision-making speed due to centralized, auditable BIM-linked cost data, and (iv) identification of critical data governance requirements, including data standards, model interoperability, and access controls. The study anticipates achieving statistically significant improvements (p < 0.05) in cost predictability and schedule adherence in pilot projects relative to comparable non-integrated projects, with qualitative insights revealing organizational and technological prerequisites for scaling. The contribution to knowledge lies in (a) a validated, scalable BIM-enabled cost management framework that explicitly coordinates design, procurement, and construction cost processes; (b) empirical evidence on how integrated BIM data structures influence cost performance and project outcomes; and (c) practical governance and implementation guidelines for firms seeking to institutionalize BIM-driven cost management practices. The study concludes that integrated BIM-driven cost management substantially improves cost control and decision-making transparency when accompanied by robust data governance, cross-disciplinary collaboration, and executive sponsorship. Recommendations include adopting standardized BIM cost data schemas, integrating BIM with ERP and scheduling tools, establishing cross-functional cost management teams, and prioritizing training on BIM-enabled cost analytics to support broader industry adoption.