Postponement Strategies in Supply Chain Management

by Cheng, T. C. Edwin; Li, Jian; Wan, C. L. Johnny; Wang, Shouyang

• ISBN13: 9781441958365
• ISBN10: 1441958363
• Edition: 1st
• Format: Hardcover
• Copyright: 2010-05-15
• Publisher: Springer Verlag

Summary

Within supply chain management (SCM), postponement is a deliberate action to delay final manufacturing or distribution of a product until receipt of a customer order. This reduces the incidence of wrong manufacturing or incorrect inventory deployment. Postponement strategies and practices serve to reduce the anticipatory risk in a supply chain. It can be fine-tuned or staged so that only the generic parts shared by a firm’s various end products are warehoused, used only once orders come in for whichever products are selling, and will reduce inventory pressures throughout the firm. Despite much existing research in the area, no one book devoted solely to postponement has been published.At its core, Postponement Strategies in Supply Chain Management analyzes how both pull postponement strategy and form postponement strategy can be leveraged to yield substantial benefits to adopting firms in different competitive environments. The book is intended for researchers in supply chain management interested in conducting in-depth studies on postponement strategies. It is also intended for practitioners trying to understand the workings of postponement strategies and looking for guidance and decision support for the implementation of postponement strategies. Therefore, the book can be useful not only for researchers but also for practitioners and graduate students in operations management, management science, and business administration.

Table of Contents

Introduction	p. 1
From Product Variety to Postponement	p. 1
Product Variety	p. 1
Mass Customization	p. 2
Postponement Strategy	p. 3
Classification of Postponement	p. 3
Pull Postponement	p. 4
Logistics Postponement	p. 6
Form Postponement	p. 7
Price Postponement	p. 8
Implications	p. 8
Advantages and Disadvantages of Postponement	p. 9
Prerequisites for Postponement Strategy Development	p. 10
Cost Models for Analyzing Postponement Strategies	p. 11
Stochastic Models	p. 11
Heuristic Models	p. 12
Descriptive Models	p. 13
Performance Measures	p. 14
A Literature Review for Model Development	p. 14
EOQ and EPQ Models	p. 15
Lot Size-Reorder Point Model	p. 16
Markov Chain	p. 16
Concluding Remarks	p. 17
Analysis of Pull Postponement by EOQ-based Models	p. 19
Postponement Strategy for Ordinary (Imperishable) Items	p. 19
Proposed Model and Assumptions	p. 19
Case 1: Same Backorder Cost	p. 22
Case 2: Different Backorder Costs	p. 26
A Numerical Example	p. 30
Postponement Strategy for Perishable Items	p. 32
Notation and Assumptions	p. 33
Model Formulation	p. 34
The Postponement and Independent Systems	p. 38
Numerical Examples	p. 39
Concluding Remarks	p. 41
Analysis of Postponement Strategy by EPQ-based Models	p. 43
Analysis of Postponement Strategy by an EPQ-based Model without Stockout	p. 43
Proposed Model and Assumptions	p. 43
2 Machines for 2 End-Products	p. 46
n Machines for n End-Products	p. 56
Analysis of Postponement Strategy by an EPQ-based Model with Planned Backorders	p. 62
Proposed Model and Assumptions	p. 63
Demands Are Met Continuously	p. 65
Demands Are Met After Production Is Complete	p. 71
Concluding Remarks	p. 78
Evaluation of a Postponement System with an (r, q) Policy	p. 81
The Proposed Models and Assumptions	p. 81
System Dynamics for a Non-postponement System	p. 83
The Algorithm for Finding a Near Optimal Total Average Cost of an (r, q) Policy	p. 84
The Markov Chain Development	p. 84
The Algorithm for Finding a Near Optimal Total Average Cost	p. 99
System Dynamics for a Postponement System	p. 102
Average Cost Comparison of the Two Systems When L = 0	p. 103
Average Cost Comparison of the Two Systems When L ≥ 1	p. 104
An Overview of the Simulation Results	p. 104
Impacts of Parameters on Average Cost	p. 106
Concluding Remarks	p. 107
Simulation of a Two-End-Product Postponement System	p. 109
Proposed Model and Assumptions	p. 110
Notation	p. 111
Model Assumptions	p. 111
Methodology	p. 112
System Dynamics	p. 112
The Simulation Model	p. 114
Customer Demand Distribution	p. 114
Order Quantity and Reorder Point	p. 115
Summary of Parameters	p. 115
Initial Conditions	p. 115
Simulation Results for Non-cost Parameters	p. 117
Uniform Distribution	p. 117
Poisson Distribution	p. 118
Normal Distribution I	p. 119
Normal Distribution II	p. 120
Simulation Results for Cost Parameters	p. 121
Concluding Remarks	p. 123
Application of Postponement: Examples from Industry	p. 125
A Case Study from Hong Kong	p. 125
An Overview of the Company	p. 126
Implementation of Postponement	p. 126
Benefits of Using Postponement	p. 127
Implications	p. 128
The Case of Taiwanese Information Technology Industry	p. 129
The Hypothesis	p. 129
Methodology	p. 130
Results	p. 131
Implications	p. 131
Concluding Remarks	p. 132
Conclusions, Implications and Future Research Directions	p. 133
Conclusions	p. 133
Implications and Further Research Directions	p. 134
Simulation Results (Uniform Distribution)	p. 137
Simulation Results (Poisson Distribution)	p. 141
Simulation Results (Normal Distribution I)	p. 147
Simulation Results (Normal Distribution II)	p. 151
Simulation Results for Cost Analysis	p. 155
References	p. 157
About the Authors	p. 163
Index	p. 165
Table of Contents provided by Ingram. All Rights Reserved.