Enhancing Cost Estimation with Building Information Modeling (BIM) in Construction Industry: A Case Study in Kuala Lumpur

Abstract

Cost estimation is a critical component of construction project management, directly influencing project success by ensuring economic feasibility and effective resource allocation. However, traditional cost estimation methods in Kuala Lumpur, Malaysia, struggle to meet the increasing demands of urbanization and complex project dynamics, often leading to inaccuracies and cost overruns. The purpose of this study is to assess the accuracy of traditional cost estimation methods, to investigate the relationship between Building Information Modeling (BIM) and cost estimation, and to recommend strategies to enhance the adoption of BIM in the construction industry. Data were collected through a quantitative survey of 234 respondents and analyzed using SPSS and Microsoft Excel with descriptive statistics, reliability analysis and Pearson correlation techniques. The results of the study indicate that traditional methods have significant limitations and are not adaptable to dynamic market conditions and project complexity. BIM has the potential to improve the accuracy of cost estimates, reduce errors, and enhance collaboration among stakeholders. However, barriers such as high implementation costs and lack of expertise hinder its widespread adoption. The discussion highlighted the need for government incentives, affordable training programs, and clearer guidelines to encourage BIM implementation. Future research should explore the integration of machine learning models and statistical methods to further improve prediction accuracy, as well as expanding research to other regions. These efforts will support the development of more accurate and efficient cost estimating practices, ultimately advancing the construction industry.