Thesis Abstract

Abstract
The construction industry is characterized by the complexity of projects and the need for accurate cost estimation to ensure successful project delivery. This thesis explores the optimization of cost estimation methods in construction projects through a case study analysis. The research aims to address the challenges faced in cost estimation and propose strategies to enhance accuracy and efficiency in estimating project costs. The study begins with a comprehensive introduction, providing background information on the importance of cost estimation in construction projects. The problem statement highlights the existing issues in cost estimation methods, such as inaccuracies, delays, and cost overruns. The objectives of the study are to identify the key factors influencing cost estimation accuracy and to develop practical solutions to improve the process. The limitations and scope of the study are also discussed to provide a clear understanding of the research boundaries. A detailed literature review is conducted in Chapter Two, which examines existing studies, theories, and best practices related to cost estimation in construction projects. The review includes ten key items that explore different aspects of cost estimation methods, such as historical data analysis, risk assessment, software tools, and expert judgment. Chapter Three focuses on the research methodology employed in this study, which includes a detailed description of the research design, data collection methods, sampling techniques, and data analysis procedures. The methodology section comprises eight contents that outline the steps taken to conduct the case study analysis and gather relevant data from construction projects. In Chapter Four, the findings of the case study analysis are presented and discussed in detail. The analysis includes a comparison of different cost estimation methods used in the case study projects, an evaluation of their accuracy and efficiency, and an exploration of the factors influencing cost estimation outcomes. The chapter provides valuable insights into the optimization of cost estimation methods in construction projects. Finally, Chapter Five offers a conclusion and summary of the thesis, highlighting the key findings, implications, and recommendations for future research and practice. The study concludes that optimizing cost estimation methods in construction projects is crucial for project success and proposes practical strategies to enhance accuracy and efficiency in cost estimation processes. In conclusion, this thesis contributes to the existing body of knowledge on cost estimation in construction projects by providing a comprehensive analysis of current methods and proposing innovative solutions to optimize cost estimation practices. The research findings offer valuable insights for industry practitioners, researchers, and stakeholders seeking to improve cost estimation accuracy and efficiency in construction projects.

Thesis Overview

The project titled "Optimizing Cost Estimation Methods in Construction Projects: A Case Study Analysis" aims to investigate and improve the cost estimation practices within the construction industry. The construction industry is inherently complex, with numerous variables that can impact project costs. Effective cost estimation is crucial for project success, as inaccurate estimates can lead to budget overruns, delays, and disputes. Therefore, this research project seeks to identify the challenges and opportunities in current cost estimation methods and propose strategies to optimize these processes. The study will begin with a comprehensive literature review to explore existing cost estimation methods, tools, and techniques used in the construction industry. This review will provide insights into the strengths and limitations of current practices and highlight areas for improvement. By analyzing a wide range of literature sources, including academic research, industry publications, and case studies, the project aims to establish a solid theoretical foundation for the research. The research methodology will involve a detailed case study analysis of real construction projects to understand how cost estimation is currently conducted in practice. By examining specific projects, the study will identify common issues, best practices, and lessons learned in cost estimation. The case study approach will provide valuable insights into the factors that influence cost estimation accuracy and reliability in construction projects. Based on the findings from the literature review and case study analysis, the project will develop recommendations for optimizing cost estimation methods in construction projects. These recommendations may include the adoption of advanced technology, improved data collection and analysis processes, enhanced stakeholder collaboration, and the implementation of best practices identified in the research. The goal is to propose practical and actionable strategies that can help construction industry professionals improve the accuracy and reliability of their cost estimates. The significance of this research lies in its potential to enhance cost estimation practices within the construction industry, leading to better project outcomes, increased efficiency, and reduced risks. By optimizing cost estimation methods, construction companies can improve their competitiveness, enhance client satisfaction, and achieve greater project success. The research findings will be valuable for industry practitioners, researchers, educators, and policymakers seeking to advance cost estimation practices in the construction sector. In conclusion, the project "Optimizing Cost Estimation Methods in Construction Projects: A Case Study Analysis" aims to contribute to the body of knowledge in construction cost estimation by identifying opportunities for improvement and proposing practical strategies for optimization. By addressing the challenges associated with cost estimation in construction projects, this research has the potential to drive positive change and improve project outcomes across the industry.