Manufacturer’s Optimal Auditing Policy of Supplier's Capacity

Inhaltsverzeichnis (Table of Contents)

• ABSTRACT
• TABLE OF CONTENTS
• 1 INTRODUCTION
• 1.1 Intention and Context of the Research
• 1.2 Motivation and Academic Purpose
• 2 LITERATURE REVIEW
• 2.1 Newsvendor Model: Optimal Inventory and Production Capacity Policy
• 2.2 Competition in the Supply Chain
• 2.3 Principal-Agent Models and Asymmetric Information
• 2.4 Optimal Equilibrium Procurement Strategies
• 2.5 Supplier Auditing
• 3 ORGANIZATION OF THE ARTICLE
• 4 MATHEMATICAL MODEL DEVELOPMENT
• 4.1 Pre-Assumptions and External Contracting Conditions in the Manufacturing Context
• 4.2 Application-Implicit Transformation of Action into Reasonable Variables for the Mathematical Model
• 4.3 Mathematical Model Formulation
• 4.4 Mathematical Model Specification
• 4.4.1 Assumption of Two Types of Suppliers and Two Different Production Schedules
• 4.4.2 Simplification Approach: Reduction of Decision Variables
• 4.4.3 Individual and Overall Welfare Considerations
• 4.5 Optimality Analysis
• 4.5.1 Conversion of Min/Max Functions
• 4.5.2 Optimal Capacity Auditing Probability of the Inefficient Supplier Type
• 4.5.3 Optimal Order Quantities for the Efficient and Inefficient Supplier Type
• 5 NUMERICAL STUDY AND SENSITIVITY ANALYSIS
• 5.1 Transfer of the General Model into MATLAB
• 5.2 MATLAB Solver for Optimal Selection of Decision Variables
• 5.3 Sensitivity Analysis
• 5.3.1 Impact of Efficient Supplier Occurrence Probability on Manufacturer's Profit
• 5.3.2 Impact of Marginal Retailing Price Level on Manufacturer's Profit
• 5.3.3 Impact of Efficient Supplier Occurrence Probability on Inefficient Supplier Capacity Audit Probability
• 5.3.4 Impact of Inefficient Supplier's Untrustworthiness Penalty on Inefficient Supplier Capacity Audit Probability
• 5.3.5 Impact of Market Demand Variation on Optimal Order Quantity
• 5.3.6 Impact of Efficient Supplier Occurrence Probability on Optimal Order Quantity
• 6 SUMMARY AND FUTURE OUTLOOK
• 6.1 Summary of Results and Research Process
• 6.2 Limitations and Future Outlook
• LIST OF NOMENCLATURE
• TABLE OF TABLES
• TABLE OF FIGURES
• REFERENCE
• APPENDIX
• Reformulation as a Linear Program

Zielsetzung und Themenschwerpunkte (Objectives and Key Themes)

This research investigates the optimal capacity auditing policy for a manufacturer in a principal-agent context, where the supplier possesses private information about their production capacity. The primary objective is to determine how the manufacturer can best utilize capacity audits to mitigate the risk of supplier opportunism and improve supply chain efficiency.

• Supply Chain Coordination and Efficiency
• Principal-Agent Relationships and Asymmetric Information
• Optimal Auditing Mechanisms
• Supplier Incentives and Contract Design
• Risk Management in Supply Chains

Zusammenfassung der Kapitel (Chapter Summaries)

The thesis begins by introducing the context and motivation for the research, highlighting the increasing importance of supply chain coordination and the challenges posed by asymmetric information. Chapter 2 provides a comprehensive literature review, exploring relevant concepts from the newsvendor model, principal-agent theory, and supplier auditing. Chapter 4 presents the mathematical model development, outlining the assumptions, variables, and equations used to analyze the manufacturer's optimal auditing policy. This chapter includes an in-depth analysis of the model's optimality conditions. Chapter 5 presents the results of a numerical study and sensitivity analysis, demonstrating the impact of various factors on the manufacturer's profit and the optimal auditing probability. The thesis concludes with a summary of the findings and a discussion of potential future research directions.

Schlüsselwörter (Keywords)

The research focuses on supply chain efficiency, supply chain coordination, newsvendor model, principal-agent theory, asymmetric information, and supplier capacity auditing. The key concepts explored include contract design, incentive compatibility, risk mitigation, and optimal auditing mechanisms. The research also draws on theoretical frameworks such as the BiLieF project, which provides insights into the dynamics of information asymmetry in supply chains.