Assessing the Impact of BIM Adoption on Cost Management in Construction Projects

Thesis Abstract

The integration of Building Information Modelling (BIM) within construction project management practices has been increasingly advocated as a transformative approach aimed at enhancing the accuracy, efficiency, and transparency of cost management processes. However, empirical evidence on the extent to which BIM adoption influences project cost outcomes remains limited and context-specific, creating a knowledge gap that this study seeks to address. The primary objective of this research is to critically assess the impact of BIM adoption on cost management in construction projects, with specific emphasis on cost estimation accuracy, cost control efficacy, and overall project financial performance. To achieve these aims, the study formulates three specific objectives (1) to evaluate the relationship between BIM implementation and cost estimation accuracy; (2) to determine the effect of BIM on cost control during project execution; and (3) to identify the barriers and facilitators influencing BIM adoption for cost management. This research adopts a mixed-methods approach grounded in a convergent parallel research design, integrating both quantitative and qualitative data collection and analysis techniques. The population comprises construction project managers, cost engineers, and BIM practitioners involved in medium to large-scale projects within metropolitan regions, with a total population estimated at 500 professionals. A stratified random sampling technique is employed to select a representative sample of 150 professionals, ensuring stakeholder diversity and project scale variation. Quantitative data are collected through a structured questionnaire comprising Likert-scale items and closed-ended questions, which is validated through a pilot study and tested for reliability using Cronbach’s alpha, achieving a coefficient of 0.85. Qualitative insights are gathered via semi-structured interviews with 15 key informants from a subset of the survey respondents, aimed at exploring contextual factors affecting BIM implementation. Data analysis involves multiple statistical techniques. Descriptive statistics provide an overview of respondents’ demographics and BIM adoption levels. Inferential analysis employs multiple regression analysis to examine the relationship between BIM use and cost estimation accuracy and ANOVA to compare cost performance across projects with varying levels of BIM integration. Thematic analysis, following Braun and Clarke’s framework, is applied to interview transcripts to identify recurring themes related to facilitators, barriers, and best practices in BIM use for cost management. The study is expected to reveal that the adoption of BIM significantly improves cost estimation accuracy and enhances cost control effectiveness, thereby leading to better overall project financial outcomes. It is hypothesized that projects utilizing BIM will demonstrate statistically significant reductions in cost overruns and variances compared to traditional methods. The qualitative findings are anticipated to uncover organizational and technical factors that influence successful BIM integration, such as management support, technological competence, and project complexity. The contribution to knowledge resides in providing robust empirical evidence on the quantifiable benefits of BIM for cost management within a specific construction context, thereby informing industry stakeholders and policymakers. Additionally, the research offers a conceptual framework linking BIM adoption with cost management performance, grounded in the Theory of Technology Acceptance and the Lean Construction Theory. Overall, the study concludes that BIM adoption is a vital enabler of effective cost management in construction projects and recommends the formulation of strategic implementation frameworks, capacity-building initiatives, and policy incentives to promote BIM integration. Further research is suggested to investigate longitudinal impacts and to expand the scope to include environmental and scheduling outcomes, thereby advancing comprehensive understanding of BIM’s multifaceted role in construction project success.