Thesis Abstract

Abstract
Building Information Modeling (BIM) has emerged as a transformative technology in the construction industry, offering advanced capabilities for visualization, collaboration, and data management. This research investigates the application of BIM in Quantity Surveying for cost estimation and project management, aiming to enhance the efficiency and accuracy of cost-related processes in construction projects. The study explores how BIM can streamline cost estimation, improve project planning, and facilitate better decision-making throughout the project lifecycle. Chapter One provides the introduction to the research, presenting the background of the study, problem statement, objectives, limitations, scope, significance, structure of the thesis, and definitions of key terms. Chapter Two conducts a comprehensive literature review, examining existing research on BIM in Quantity Surveying and its impact on cost estimation and project management. The chapter synthesizes key findings and identifies gaps in the literature that this research aims to address. Chapter Three outlines the research methodology, detailing the research design, data collection methods, sampling techniques, and data analysis procedures. The chapter also discusses ethical considerations and limitations of the research approach. Chapter Four presents a detailed discussion of the research findings, analyzing the application of BIM in Quantity Surveying for cost estimation and project management. The chapter highlights the benefits, challenges, and best practices associated with integrating BIM into Quantity Surveying processes. In conclusion, Chapter Five provides a summary of the research findings, discusses the implications for practice and future research directions, and offers recommendations for industry professionals looking to adopt BIM in Quantity Surveying. This research contributes to the growing body of knowledge on the use of BIM in Quantity Surveying, offering insights into how this technology can enhance cost estimation accuracy, improve project management efficiency, and drive better project outcomes in the construction industry. Keywords Building Information Modeling (BIM), Quantity Surveying, Cost Estimation, Project Management, Construction Industry, Technology Integration.

Thesis Overview