Postponement Strategies in Supply Chain Management

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Edition: 1st
Format: Hardcover
Pub. Date: 2010-05-15
Publisher(s): Springer Verlag
List Price: $179.99

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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

Introductionp. 1
From Product Variety to Postponementp. 1
Product Varietyp. 1
Mass Customizationp. 2
Postponement Strategyp. 3
Classification of Postponementp. 3
Pull Postponementp. 4
Logistics Postponementp. 6
Form Postponementp. 7
Price Postponementp. 8
Implicationsp. 8
Advantages and Disadvantages of Postponementp. 9
Prerequisites for Postponement Strategy Developmentp. 10
Cost Models for Analyzing Postponement Strategiesp. 11
Stochastic Modelsp. 11
Heuristic Modelsp. 12
Descriptive Modelsp. 13
Performance Measuresp. 14
A Literature Review for Model Developmentp. 14
EOQ and EPQ Modelsp. 15
Lot Size-Reorder Point Modelp. 16
Markov Chainp. 16
Concluding Remarksp. 17
Analysis of Pull Postponement by EOQ-based Modelsp. 19
Postponement Strategy for Ordinary (Imperishable) Itemsp. 19
Proposed Model and Assumptionsp. 19
Case 1: Same Backorder Costp. 22
Case 2: Different Backorder Costsp. 26
A Numerical Examplep. 30
Postponement Strategy for Perishable Itemsp. 32
Notation and Assumptionsp. 33
Model Formulationp. 34
The Postponement and Independent Systemsp. 38
Numerical Examplesp. 39
Concluding Remarksp. 41
Analysis of Postponement Strategy by EPQ-based Modelsp. 43
Analysis of Postponement Strategy by an EPQ-based Model without Stockoutp. 43
Proposed Model and Assumptionsp. 43
2 Machines for 2 End-Productsp. 46
n Machines for n End-Productsp. 56
Analysis of Postponement Strategy by an EPQ-based Model with Planned Backordersp. 62
Proposed Model and Assumptionsp. 63
Demands Are Met Continuouslyp. 65
Demands Are Met After Production Is Completep. 71
Concluding Remarksp. 78
Evaluation of a Postponement System with an (r, q) Policyp. 81
The Proposed Models and Assumptionsp. 81
System Dynamics for a Non-postponement Systemp. 83
The Algorithm for Finding a Near Optimal Total Average Cost of an (r, q) Policyp. 84
The Markov Chain Developmentp. 84
The Algorithm for Finding a Near Optimal Total Average Costp. 99
System Dynamics for a Postponement Systemp. 102
Average Cost Comparison of the Two Systems When L = 0p. 103
Average Cost Comparison of the Two Systems When L ≥ 1p. 104
An Overview of the Simulation Resultsp. 104
Impacts of Parameters on Average Costp. 106
Concluding Remarksp. 107
Simulation of a Two-End-Product Postponement Systemp. 109
Proposed Model and Assumptionsp. 110
Notationp. 111
Model Assumptionsp. 111
Methodologyp. 112
System Dynamicsp. 112
The Simulation Modelp. 114
Customer Demand Distributionp. 114
Order Quantity and Reorder Pointp. 115
Summary of Parametersp. 115
Initial Conditionsp. 115
Simulation Results for Non-cost Parametersp. 117
Uniform Distributionp. 117
Poisson Distributionp. 118
Normal Distribution Ip. 119
Normal Distribution IIp. 120
Simulation Results for Cost Parametersp. 121
Concluding Remarksp. 123
Application of Postponement: Examples from Industryp. 125
A Case Study from Hong Kongp. 125
An Overview of the Companyp. 126
Implementation of Postponementp. 126
Benefits of Using Postponementp. 127
Implicationsp. 128
The Case of Taiwanese Information Technology Industryp. 129
The Hypothesisp. 129
Methodologyp. 130
Resultsp. 131
Implicationsp. 131
Concluding Remarksp. 132
Conclusions, Implications and Future Research Directionsp. 133
Conclusionsp. 133
Implications and Further Research Directionsp. 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 Analysisp. 155
Referencesp. 157
About the Authorsp. 163
Indexp. 165
Table of Contents provided by Ingram. All Rights Reserved.

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