A Framework for Integrating Building Information Modeling into Cost Management Processes

Thesis Abstract

The integration of Building Information Modeling (BIM) into cost management processes has become increasingly vital for enhancing accuracy, efficiency, and collaboration within construction projects. Despite widespread adoption of BIM for design and visualization, its systematic incorporation into cost estimation, budgeting, and cost control remains underdeveloped, leading to fragmented practices and potential cost overruns. This study aims to develop a comprehensive framework that explicitly integrates BIM functionalities into core cost management processes to optimize project financial performance. Specific objectives include identifying critical BIM features relevant to cost management, analyzing existing integration models, and designing a practicable framework adaptable across varied project contexts. The research employs a mixed-methods approach within a pragmatic research design. Quantitative data were collected through a structured survey administered to 150 project professionals—including quantity surveyors, project managers, and cost engineers—across major construction firms operating in a metropolitan regional context. The survey instrument was validated through a panel of experts and tested for reliability with a Cronbach’s alpha of 0.89. Qualitative insights were gathered via semi-structured interviews with 20 industry practitioners, chosen through purposive sampling to elicit nuanced understanding of current practices, challenges, and opportunities for BIM integration. The combined data were analyzed using descriptive statistics, exploratory factor analysis (EFA), and thematic analysis. Regression analysis was conducted to explore relationships between BIM feature adoption levels and perceived improvements in cost management effectiveness. Findings are anticipated to confirm that specific BIM functionalities—such as real-time quantity extraction, cost database integration, and change tracking—significantly enhance the accuracy and speed of cost estimation and control activities. The regression models are expected to demonstrate a positive correlation between the extent of BIM feature utilization and improvements in cost predictability and variance management. The thematic analysis will uncover key barriers—including insufficient training, interoperability issues, and organizational resistance—that hinder full integration. A conceptual framework will emerge, illustrating the procedural stages, stakeholders, and technological requirements necessary for effective BIM-based cost management integration. This study contributes to existing knowledge by providing a novel, empirically-informed framework that bridges the gap between BIM technology capabilities and cost management practices, facilitating better integration tailored to industry needs. It advances theoretical understanding by aligning with the Systems Theory and Innovation Diffusion Theory, explaining how technological components interact within organizational systems to influence cost efficiency. Practically, the framework offers a strategic model for practitioners to systematically embed BIM into cost processes, thereby reducing risk and improving project financial outcomes. The main conclusion emphasizes that systematic BIM integration into cost management processes significantly enhances project cost control, transparency, and decision-making capabilities. Recommendations include developing industry-wide guidelines for BIM-based cost management, investing in targeted training programs, and prioritizing interoperability standards for software tools. Future research should explore longitudinal impacts of BIM integration over multiple project phases and investigate the integration of emerging technologies such as artificial intelligence and big data analytics within the proposed framework. This study thereby lays a foundational step toward more cohesive and technologically advanced cost management practices in the construction industry.