Quantification and Analysis of Bullwhip Effect using Complexity Calculations

Table of Contents

• CHAPTER 1. INTRODUCTION
  • 1.1. Bullwhip Effect
  • 1.2. Complex Systems
  • 1.3. Hurst Exponent
  • 1.4. Importance of The Topic
• CHAPTER 2. LITERATURE REVIEW
• CHAPTER 3. METHODOLGY
  • 3.1 Data collection
  • 3.2 The Present Method
  • 3.3 The Proposed Method
  • 3.4 Hurst Exponent Calculation
  • 3.5 Lyapunov Exponent
  • 3.6 Matlab Software
• CHAPTER 4. COMPUTATIONL RESULTS AND ANALYSIS
  • 4.1 Variance Change as a Function of H
  • 4.2 Variance Change as a Function of Number of Data
  • 4.3. Hurst Exponent Calculation from Data
  • 4.4 Lyapunov Exponent Calculation from Data
• CHAPTER 5. CONCLUSION AND FUTURE WORKS
• REFERENCES

Objectives and Key Themes

This thesis investigates the quantification and analysis of the bullwhip effect in supply chains, leveraging complexity calculations. The primary aim is to develop a more accurate method for quantifying the bullwhip effect by considering the dependency within data sets, which is often overlooked in traditional approaches.

• Quantification of the Bullwhip Effect
• Analysis of Bullwhip Effect Using Complexity Calculations
• The Role of Hurst Exponent and Data Dependency
• Application of Detrended Fluctuation Analysis (DFA)
• Impact of Data Dependency on Supply Chain Dynamics

Chapter Summaries

Chapter 1 introduces the concept of the bullwhip effect, emphasizing its significance in unstable market environments. It also explains the relevance of complex systems and the Hurst exponent in analyzing supply chain dynamics. Chapter 2 provides a comprehensive review of existing literature on the bullwhip effect, outlining previous research and methodologies. Chapter 3 delves into the methodology employed in this thesis, including data collection, the proposed method, and the calculation of the Hurst exponent using techniques like rescaled range analysis and detrended fluctuation analysis. Chapter 4 presents computational results and analysis, exploring the variation of variance based on the Hurst exponent and data size. It also details the calculation of the Hurst and Lyapunov exponents from data related to different product categories, such as computer consumables, automotive components, washing powder, and fresh juice.

Keywords

The key concepts and terms explored in this thesis include the bullwhip effect, complexity calculations, data dependency, Hurst exponent, detrended fluctuation analysis (DFA), rescaled range analysis, Lyapunov exponent, and supply chain dynamics.