Thesis Abstract

Abstract
Supply chain management plays a crucial role in the success of businesses by ensuring the efficient flow of goods and services from suppliers to customers. In recent years, the integration of artificial intelligence (AI) and predictive analytics has emerged as a powerful tool for optimizing supply chain operations. This thesis explores the application of AI in predictive analytics for supply chain management optimization. The primary objective is to investigate how AI techniques can be leveraged to enhance decision-making processes, improve forecasting accuracy, and streamline supply chain operations. Chapter One provides an introduction to the research topic, presenting the background of the study, defining the problem statement, outlining the objectives, discussing the limitations and scope of the study, highlighting its significance, and presenting the structure of the thesis. Chapter Two presents a comprehensive literature review, analyzing existing studies on AI, predictive analytics, and supply chain management optimization. The review covers key concepts, methodologies, and findings in the field, providing insights into the current state of research and identifying gaps for further exploration. Chapter Three details the research methodology, including research design, data collection methods, sampling techniques, data analysis procedures, and ethical considerations. The chapter describes how the research aims to collect and analyze data to address the research questions and achieve the research objectives effectively. Chapter Four presents a thorough discussion of the research findings, showcasing the application of AI in predictive analytics for supply chain management optimization. The chapter analyzes the results, discusses their implications, and offers recommendations for future research and practical implementation. In conclusion, Chapter Five summarizes the key findings of the study, reiterates the research objectives and contributions, and provides insights into the potential impact of utilizing AI in predictive analytics for supply chain management optimization. The thesis highlights the significance of AI technologies in transforming supply chain operations, enhancing efficiency, and driving competitive advantage in a rapidly evolving business landscape. Overall, this research contributes to the growing body of knowledge on AI-enabled supply chain management optimization and underscores the importance of embracing technological advancements for sustainable business growth and success.

Thesis Overview