IMPROVING SUSTAINABILITY IN CONSTRUCTION VIA MATERIALS MANAGEMENT AND BUILDING INFORMATION MODELING INTEGRATION: EXPLORING THE POTENTIAL OF KAZAKHSTAN

Abstract

Materials management represents a critical yet often overlooked component in construction projects, accounting for up to 60% of overall building costs. Effective construction materials management (CMM) is crucial for project success, yet traditional approaches often fall short in addressing modern sustainability and efficiency demands. Despite widespread Building Information Modeling (BIM) adoption across construction phases, its potential for optimizing materials management remains understudied, particularly in developing economies. Global sustainability awareness continues to grow; however, research in the sustainable CMM field remains scarce, with existing literature often prioritizing design and engineering while overlooking critical noncore practices, like material management. Moving beyond conventional BIM research, this study explored technology’s pivotal role in implementing sustainable CMM for improved project delivery. This study synthesizes three complementary theoretical perspectives: cognitive processing principles from Information Integration Theory to conceptualize data consolidation mechanisms; contextual innovation adoption factors from the Technology- Organization-Environment framework to examine implementation dynamics; and problem-solving approaches from Design Science Research that emphasize knowledge creation through purposeful artifact development addressing specific business requirements. The research aims to evaluate the significance of CMM in achieving building sustainability by exploring drivers, barriers, and implementation strategies that can be facilitated by BIM technologies in Kazakhstan. A mixed-methods approach was employed, comprising: (1) comprehensive literature review, (2) case studies to gain insights on existing materials management practices by participating in scrum project, expert interview and observations, (3) and online survey. The analytical framework for survey data analysis involved mean score ranking to identify priority indicators, the Kruskal-Wallis H test to evaluate differences between respondent group and Kendall's Coefficient of Concordance to assess the consensus evaluation. Further investigation included exploratory factor analysis (EFA) to uncover pattern and partial least squares structural equation modeling (PLS-SEM) to examine relationships between latent constructs. Two industry-leading companies were selected for case studies to benchmark BIM adoption and its CMM potential, revealing high levels of supply chain fragmentation and the diversity of disparate software among stakeholders, that generate incompatible data format. These managerial and system inefficiencies led to disruptions and delays in material supply, leading to project leftovers, surplus material, and waste accumulation...