Effects of Data Science, Predictive Analytics & Big Data (DPB) on the Supply Chain

Inhaltsverzeichnis (Table of Contents)

• Abstract
• Acknowledgements
• 1. Introduction
• 1.1. Background of the Research
• 1.2. Research Question
• 1.3. Research Objective
• 1.4. Structure of the Dissertation
• 2. Literature Review
• 2.1. Development of Big Data
• 2.2. Impact of Big Data on Supply Chain
• 2.3. Application of Big Data in Supply Chain
• 3. Research Methodology
• 3.1. Qualitative Data Collection
• 3.2. Interviewing Techniques
• 3.3. Data Analysis
• 4. Analysis and Results
• 4.1. Interview Findings
• 4.2. Interpretation of Findings
• 4.3. Supply Chain Framework
• 5. Discussion
• 5.1. Opportunities and Threats
• 5.2. Critical Evaluation
• 6. Conclusion
• 6.1. Summary of Findings
• 6.2. Recommendations for Future Research
• References
• Appendix

Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)

This dissertation investigates the effects of big data on the supply chain and decision-making within the financial services sector. It addresses the lack of research on the application of big data in service provider supply chains.

• The impact of big data on supply chain processes
• Decision-making processes in the context of big data
• Opportunities and challenges of implementing big data in service provider supply chains
• A proposed supply chain framework leveraging big data opportunities
• The role of data privacy and economic viability in the implementation of big data solutions

Zusammenfassung der Kapitel (Chapter Summaries)

• Chapter 1: Introduction

This chapter introduces the research topic, its significance, and outlines the research question and objectives. It also provides a structure for the dissertation.

• Chapter 2: Literature Review

This chapter explores the development of big data, its impact on supply chains, and its various applications within the context of supply chain management. The chapter analyzes existing literature to establish a framework for understanding big data's implications in the service sector, particularly in the supply chain.

• Chapter 3: Research Methodology

This chapter outlines the research methodology employed in the dissertation, focusing on qualitative data collection through interviews with employees of a leading German leasing and asset finance company. The chapter describes the interview techniques and data analysis methods used to gain insights into the company's operations and challenges related to big data implementation.

• Chapter 4: Analysis and Results

This chapter presents the findings of the interviews, analyzing the data to identify opportunities and threats related to big data in supply chain management. It explores the impact of big data on various aspects of the company's operations, including background processes, sales efficiency, and decision-making. The chapter also introduces a proposed supply chain framework based on the collected data and analysis.

• Chapter 5: Discussion

This chapter delves into a discussion of the opportunities and threats identified through the research, providing a critical evaluation of the potential benefits and drawbacks of big data implementation in the service sector. The chapter examines the implications of data privacy, economic viability, and adaptability within the context of big data.

Schlüsselwörter (Keywords)

The main focus of this dissertation lies on the application of big data in supply chain management and its impact on decision-making within the financial services sector. Key themes include: big data, supply chain management, business intelligence, data analytics, service provider supply chains, opportunities and threats, data privacy, economic viability, and decision making.