The effect of commonality on safety stock in a simple inventory model
Management Science
Component commonality with service level requirements
Management Science
Variability Reduction Through Operations Reversal
Management Science
Investment Strategies for Flexible Resources
Management Science
Price Versus Production Postponement: Capacity and Competition
Management Science
Integrating Replenishment Decisions with Advance Demand Information
Management Science
Commissioned Paper: Capacity Management, Investment, and Hedging: Review and Recent Developments
Manufacturing & Service Operations Management
Inventory Control with Limited Capacity and Advance Demand Information
Operations Research
Order-Based Cost Optimization in Assemble-to-Order Systems
Operations Research
Resource Flexibility with Responsive Pricing
Operations Research
Inventory Management with Advance Demand Information and Flexible Delivery
Management Science
Incentives and Commonality in a Decentralized Multiproduct Assembly System
Operations Research
Manufacturing & Service Operations Management
The Value of Component Commonality in a Dynamic Inventory System with Lead Times
Manufacturing & Service Operations Management
No-Holdback Allocation Rules for Continuous-Time Assemble-to-Order Systems
Operations Research
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We consider an assemble-to-order system in which multiple products are assembled from a common component and a set of product-dedicated components. Component capacities are chosen prior to a finite-horizon selling season, and the common component is allocated to the products based on observed demands. We propose a collection of allocation mechanisms involving varying degrees of demand aggregation, ranging from a scheme under which all demands are observed prior to making the allocation decision to allocations made for each arriving demand. In this context, we explore the impact of the allocation scheme on sales, profits, and capacity decisions, including the degree of capacity imbalance. We find that the benefit from increased demand aggregation is closely linked to the degree of capacity imbalance: profit gains from delayed allocation tend to be higher in systems in which the optimal capacity portfolio is highly unbalanced when the allocation decision is made after observing all demands. We develop insights into what detailed system parameters lead to the largest gains from demand aggregation and also explore the trade-offs associated with the choice of an allocation scheme when customers exhibit impatience if the allocation scheme forces them to wait to be served. This paper was accepted by Ananth Iyer, operations and supply chain management.