Thesis Abstract

Abstract
This thesis focuses on the optimization of construction cost estimation techniques in the field of Quantity Surveying. Accurate cost estimation is crucial in the construction industry, as it directly impacts project planning, budgeting, and overall project success. Despite advancements in technology and methodologies, there are still challenges and limitations in current cost estimation practices. This research aims to address these challenges by exploring ways to optimize existing cost estimation techniques, ultimately enhancing the accuracy and efficiency of cost estimation processes in Quantity Surveying. The study begins with an introduction to the importance of cost estimation in construction projects, highlighting its significance in project management and decision-making. The background of the study provides an overview of current cost estimation practices and identifies the need for optimization in Quantity Surveying. The problem statement outlines the existing challenges and limitations faced by Quantity Surveyors in cost estimation processes, emphasizing the critical need for improvement. The objectives of the study are to investigate current cost estimation techniques, identify areas for optimization, and propose enhanced methodologies to improve the accuracy and efficiency of cost estimation in Quantity Surveying. The limitations of the study are also acknowledged, including constraints such as time and resources, which may impact the scope of the research. The scope of the study outlines the specific areas of focus, including the evaluation of traditional and modern cost estimation techniques, the exploration of advanced technologies such as Building Information Modeling (BIM) and Artificial Intelligence (AI) in cost estimation, and the assessment of best practices in the industry. The significance of the study lies in its potential to advance the field of Quantity Surveying by introducing optimized cost estimation techniques that can benefit practitioners, project stakeholders, and the construction industry as a whole. By enhancing the accuracy and efficiency of cost estimation processes, this research aims to contribute to improved project outcomes, reduced cost overruns, and enhanced decision-making in construction projects. The structure of the thesis is outlined, detailing the organization of chapters and key components of the research. The definitions of terms provide clarity on key concepts and terminology used throughout the study, ensuring a common understanding of relevant terms and principles. In Chapter Two, the literature review explores existing research and studies related to cost estimation techniques in Quantity Surveying. It analyzes current methodologies, technologies, and best practices in the field, providing a comprehensive overview of the state of the art in cost estimation. Chapter Three outlines the research methodology, including research design, data collection methods, data analysis techniques, and the approach to be used in investigating and optimizing cost estimation techniques in Quantity Surveying. It includes a detailed description of the research process and the rationale behind the chosen methodology. Chapter Four presents the findings of the study, discussing the outcomes of the research, key insights, and proposed optimized cost estimation techniques. It provides a detailed analysis of the data collected, highlighting the effectiveness of the proposed methodologies in enhancing cost estimation accuracy and efficiency. Finally, Chapter Five offers a conclusion and summary of the thesis, summarizing the key findings, implications, and contributions of the research. It also discusses recommendations for future research and practical applications of the optimized cost estimation techniques proposed in this study. In conclusion, the optimization of construction cost estimation techniques in Quantity Surveying is a critical area of research with the potential to significantly improve project outcomes and industry practices. This thesis aims to contribute to the advancement of cost estimation methodologies, ultimately enhancing the effectiveness and efficiency of cost estimation processes in the field of Quantity Surveying.

Thesis Overview