Assessing the Impact of Building Information Modeling on Cost Management Efficiency

Thesis Abstract

The increasing adoption of Building Information Modeling (BIM) in construction projects has prompted investigations into its potential to enhance project delivery, particularly in the domain of cost management efficiency. Despite widespread industry interest, empirical evidence assessing the tangible impact of BIM on cost control processes remains limited, with existing studies often constrained by qualitative assessments or case-specific analyses. This study aims to systematically evaluate the influence of BIM implementation on cost management efficiency within mid-sized commercial construction projects, with a focus on quantifiable cost outcomes and process improvements. The specific objectives are to determine the extent to which BIM contributes to cost accuracy, identify the key BIM features that influence cost management, and develop a model correlating BIM utilization levels with cost performance metrics. The research adopts a mixed-methods approach, integrating quantitative and qualitative data collection and analysis. The primary quantitative component involves a cross-sectional survey of 150 project managers, cost engineers, and BIM coordinators involved in recent projects across the construction industry, selected through stratified random sampling. Additionally, detailed case studies of five projects from different firms between 2018 and 2022 provide contextual insights. Data collection instruments include structured questionnaires focusing on BIM usage levels, cost management practices, and project outcomes, complemented by semi-structured interviews to explore practitioners’ perceptions. The validity and reliability of the survey instruments are ensured through pilot testing and Cronbach’s alpha analysis, with a threshold of 0.8 indicating high internal consistency. Data analysis employs multiple regression analysis to quantify the relationship between BIM adoption and cost management efficiency, with control variables such as project size, duration, and complexity. Hierarchical regression models are used to identify the contribution of specific BIM features (e.g., clash detection, quantity takeoff, scheduling integration) to cost outcomes. Thematic analysis of interview transcripts complements the quantitative data, providing nuanced contextual understanding of BIM’s operational benefits and challenges. The study is underpinned by the Theory of Project Integration and the Technology Acceptance Model, which guide the examination of how technological integration influences project cost performance and user acceptance. Expected findings suggest a statistically significant positive correlation between BIM utilization and cost management efficiency, with projects employing more comprehensive BIM features demonstrating reduced cost overruns, enhanced cost estimation accuracy, and improved change management capabilities. The qualitative insights are anticipated to reveal organizational factors that facilitate or hinder BIM’s effective application in cost control processes. This research offers a notable contribution to knowledge by providing empirical evidence on the measurable impacts of BIM on cost management, thus bridging a critical gap in construction management literature. It also provides a practical framework for industry practitioners and policymakers to optimize BIM deployment for cost efficiency. The study concludes that integrating BIM as a standard project management practice can substantially improve cost control mechanisms, provided there is adequate training, organizational commitment, and technological infrastructure. Based on the findings, the study recommends the development of standardized BIM protocols emphasizing cost management functions, investment in training to enhance user acceptance, and further research into long-term project performance outcomes. Future studies could explore longitudinal impacts of BIM adoption across different project types and regions, and investigate the integration of emerging technologies such as artificial intelligence and blockchain within BIM systems to further enhance cost management efficiency.