Comparative Analysis of BIM Adoption and Project Outcomes in Construction Firms

Thesis Abstract

In the face of rising project complexity and cost overruns within the construction industry, firms increasingly adopt Building Information Modeling (BIM) as a strategic capability to enhance collaboration, information management, and decision-making; however, the empirical evidence linking BIM adoption to tangible project outcomes remains fragmented across contexts and scales. This study aims to provide a rigorous comparative analysis of BIM adoption and its association with project performance across construction firms of varying sizes and procurement routes. The specific objectives are (1) to identify the prevalence, maturity, and drivers of BIM adoption in small, medium, and large firms; (2) to examine the relationship between BIM maturity and project outcomes such as time, cost, quality, safety, and client satisfaction; (3) to assess how organizational capabilities and contractual frameworks moderate BIM impact; (4) to compare perceived value and actual performance across different regional markets; and (5) to develop a parsimonious model linking BIM adoption stages to measurable project success indicators. The theoretical lens integrates the Technology-Organization-Environment (TOE) framework with the Resource-Based View (RBV) to explain adoption decisions and performance benefits, complemented by the Institutional Theory to account for normative pressures and standards. A cross-sectional survey design is employed, targeting a population of approximately 1,200 construction firms across five regions, with a stratified sample of 300 firms (100 large, 120 medium, 80 small) to ensure representation by size and procurement route. Data are collected through a structured questionnaire addressing BIM maturity (as defined by BIM levels 0–3), project outcome metrics (schedule variance, cost variance, defect rate, safety incidents, and client-reported satisfaction), and organizational capabilities (team competence, interdepartmental coordination, data governance, and digital culture). The instrument’s validity and reliability are established via content validation with a panel of five BIM and QS experts and a pilot test (n=30 firms), yielding a Cronbach’s alpha of at least 0.80 for all multi-item scales and confirmatory factor analysis demonstrating adequate convergent and discriminant validity. Descriptive statistics and inferential analyses are conducted using SPSS and AMOS descriptive profiling of BIM maturity; multivariate regression to quantify the impact of BIM maturity on each project outcome while controlling for firm size, project complexity, and procurement route; hierarchical linear modeling (HLM) to account for nested data structures (projects within firms); and structural equation modeling (SEM) to test the proposed relationships among latent constructs. Additional analyses include ANOVA or MANOVA to explore differences across regional markets and procurement types, and thematic analysis of qualitative inputs from open-ended survey items to contextualize quantitative findings. Expected findings indicate that higher BIM maturity is positively associated with reduced schedule and cost variances, lower defect rates, improved safety outcomes, and enhanced client satisfaction, with stronger effects in larger firms and in design-build projects. The study anticipates that organizational capabilities—particularly data governance and cross-disciplinary collaboration—mediate the BIM-outcome relationship, while external pressures from standards and regulatory environments strengthen adoption benefits. The contribution to knowledge lies in (a) providing robust, cross-sectional empirical evidence on the BIM-value chain across firm sizes and regions, (b) clarifying the conditional effects of organizational capabilities and procurement context on BIM benefits, and (c) delivering a validated model that scholars and practitioners can use to benchmark BIM maturity and project performance. Practically, the findings will inform policy makers, clients, and firms on targeting investments in BIM training, governance structures, and collaborative processes to maximize project outcomes. The study concludes that strategic BIM deployment, when matched with mature organizational capabilities and appropriate contractual arrangements, yields demonstrable improvements in project performance, with implications for industry standards and future research into longitudinal assessments of BIM value realization. Recommendations include prioritizing data governance, enhancing cross-functional BIM teams, and incentivizing outcomes-based performance contracts to sustain BIM-driven gains.