Integrated BIM-based Cost Planning for Construction Projects: Design, Implementation, Evaluation

Thesis Abstract

The construction industry faces persistent cost overruns and fragmented cost management due to disjointed estimating practices, design development delays, and limited interoperability between traditional cost planning tools and Building Information Modeling (BIM) workflows. This study investigates integrated BIM-based cost planning as a design, implementation, and evaluation framework to enhance accuracy, transparency, and collaboration across project lifecycle. The aim is to develop, implement, and assess an integrated BIM-enabled cost planning process that links early design decisions to robust cost estimates and performance outcomes. Specific objectives are (i) to conceptualize an integrated BIM-based cost planning framework that aligns architectural, structural, and MEP models with cost data; (ii) to implement a BIM-enabled cost planning workflow in a real-world project using a standardized data environment; (iii) to evaluate the framework’s impact on cost accuracy, schedule adherence, and change management; (iv) to identify organizational, technical, and regulatory enablers and barriers to adoption; and (v) to formulate a pragmatic set of guidance for practitioners. The methodology adopts a mixed-methods design underpinned by the theoretical lens of total cost of ownership and actor-network theory to illuminate stakeholder interactions and information flows within BIM-enabled cost planning. The population comprises 12 ongoing commercial construction projects in a metropolitan region with mature BIM adoption. Purposive sampling selects three case study projects exhibiting varying procurement routes (design-bid-build, design-build, and collaborative delivery). Data sources include BIM model revisions, cost schedule (4D/5D) datasets, project budgets, and change orders, complemented by semi-structured interviews with 18 key informants (project managers, cost consultants, BIM coordinators, and contractors) and 60 survey responses from field engineers and quantity surveyors. Instruments include a BIM-integrated cost planning protocol, interview guides, and a structured questionnaire. Validity and reliability are ensured through triangulation, pilot testing, and member checking; data analysis employs descriptive statistics, regression analysis to quantify the relationship between BIM-driven cost accuracy and project attributes, and thematic analysis of qualitative data to uncover enablers and barriers. A difference-in-differences approach examines cost performance before and after implementing the integrated framework, while a social network analysis maps information exchange among project participants. The analytical framework integrates a cost accuracy model, incorporating delta cost variance, contingency utilization, and change-order frequency as dependent variables. Expected findings indicate that BIM-driven cost planning reduces cost estimation error by 15–25% and lowers change-order incidence by 10–20% across case study projects, with greater gains observed in projects employing collaborative procurement. Regression results are anticipated to reveal significant negative associations between BIM maturity (model fidelity, data richness, and interoperability) and cost variance (p < 0.05). Thematic analysis is expected to identify critical success factors such as interoperable data standards (IFC/COBie), early supplier involvement, defined data ownership, and integrated governance structures. The study also anticipates qualitative evidence of improved decision-making speed and alignment between design and commercial teams, attributable to enhanced visibility of cost implications during design iterations. The contribution to knowledge includes (1) a validated, scalable integrated BIM-based cost planning framework that explicitly links design evolution to cost outcomes; (2) empirical evidence on the cost and schedule benefits of BIM-enabled, cross-disciplinary cost planning in diverse procurement contexts; and (3) a set of actionable governance, data-standardization, and process recommendations to advance adoption in industry practice. The study advances theory by extending actor-network theory to the domain of cost planning, illustrating how BIM-enabled information flows shape actors’ responsibilities and actions, and by integrating total cost of ownership perspectives into BIM maturity models. The main conclusion posits that integrating BIM with cost planning, when supported by interoperable data standards, engaged stakeholders, and formal governance, produces measurable improvements in cost predictability and project performance. Recommendations emphasize standardizing BIM-to-cost data pipelines, investing in BIM capability development for quantity surveyors, fostering early supplier collaboration, and incorporating BIM-based cost planning metrics into project performance dashboards to drive continuous improvement.