Assessing the Impact of Building Information Modeling on Cost Control in Construction Projects

Thesis Abstract

Building Information Modeling (BIM) has emerged as a transformative technology in the construction industry, promising enhanced coordination, visualization, and efficiency in project delivery. Despite its growing adoption worldwide, limited empirical evidence exists regarding its specific impact on cost control within construction projects. This study aims to quantitatively and qualitatively assess the effect of BIM implementation on cost management and control, with particular focus on identifying the mechanisms through which BIM influences cost outcomes. The research objectives include evaluating the extent of BIM adoption in construction projects, analyzing its impact on project costs, identifying key factors mediating this relationship, and suggesting strategies to optimize cost control through BIM integration. The study adopts a mixed-methods research design comprising a cross-sectional survey and multiple case studies. The quantitative component involves a survey administered to 150 project managers and quantity surveyors engaged in recent construction projects across the region, selected via stratified random sampling to ensure representation across project types and sizes. The qualitative component includes semi-structured interviews with 20 key stakeholders to gain in-depth insights into BIM’s practical implementation and cost management practices. Data collection instruments include structured questionnaires and interview guides, both pre-tested to ensure validity and reliability, with Cronbach’s alpha values exceeding 0.8 for the quantitative instruments. Data analysis employs a combination of descriptive statistics, multiple regression analysis, and structural equation modeling to examine the relationships between BIM adoption, cost control measures, and project outcomes. The regression models will test the hypotheses that higher levels of BIM utilization positively influence cost accuracy, variance reduction, and overall project expenditure efficiency. Thematic analysis, supported by NVivo software, will be used to analyze qualitative data to identify recurring themes related to facilitators and barriers to effective BIM integration for cost management. The study also integrates relevant theories, including the Technology Acceptance Model (TAM) to interpret adoption behaviors and Yin’s Case Study Theory to understand contextual factors influencing BIM’s effectiveness in cost control. Expected findings indicate that the adoption of BIM significantly improves cost control by enhancing accuracy in cost estimates, facilitating real-time cost monitoring, and reducing rework and change orders. The research anticipates uncovering critical mediators, such as team collaboration, stakeholder engagement, and technological competence, which influence BIM’s effectiveness in cost management. The findings are expected to demonstrate statistically significant relationships (p<0.05) between BIM utilization levels and reduction in project cost overruns, validated through regression coefficients and model fit indices. This research will contribute novel empirical evidence to academic literature by quantifying the impact of BIM on cost control metrics and providing a nuanced understanding of the contextual factors affecting its effectiveness. It extends existing knowledge by integrating technical, organizational, and behavioral dimensions of BIM adoption within the framework of project cost management. Practically, the study offers actionable insights for industry practitioners and policymakers on best practices for integrating BIM to achieve cost efficiencies, including recommended strategies for fostering organizational readiness, training, and stakeholder collaboration. The main conclusion asserts that BIM has a substantial and measurable positive influence on construction project cost control when effectively implemented and supported by appropriate organizational and technological conditions. Recommendations include the development of standardized BIM implementation protocols focused on cost management, investment in capacity building, and fostering a collaborative project environment. The study also suggests avenues for further research, such as longitudinal studies to explore BIM’s long-term impacts on project cost performance and investigations into industry-specific applications of BIM for cost efficiencies.