Web Based Capacity Allocation Strategies for Customers with Heterogeneous Preferences
Electronic Commerce Research
Single-Period Multiproduct Inventory Models with Substitution
Operations Research
Management of Multi-Item Retail Inventory Systems with Demand Substitution
Operations Research
Stocking Retail Assortments Under Dynamic Consumer Substitution
Operations Research
A Modeling Framework for Category Assortment Planning
Manufacturing & Service Operations Management
Centralized and Competitive Inventory Models with Demand Substitution
Operations Research
Retail Assortment Planning in the Presence of Consumer Search
Manufacturing & Service Operations Management
Mass Customization vs. Mass Production: Variety and Price Competition
Manufacturing & Service Operations Management
Dynamic Pricing and Inventory Control of Substitute Products
Manufacturing & Service Operations Management
Standard vs. Custom Products: Variety, Lead Time, and Price Competition
Marketing Science
Metaheuristics for assortment problems with multiple quality levels
Computers and Operations Research
Assortment Planning and Inventory Decisions Under Stockout-Based Substitution
Operations Research
Leadtime-Variety Tradeoff in Product Differentiation
Manufacturing & Service Operations Management
The Role of Component Commonality in Product Assortment Decisions
Manufacturing & Service Operations Management
Computers and Operations Research
Optimal Algorithms for Assortment Selection Under Ranking-Based Consumer Choice Models
Manufacturing & Service Operations Management
Learning Consumer Tastes Through Dynamic Assortments
Operations Research
Manufacturing & Service Operations Management
Optimal Dynamic Assortment Planning with Demand Learning
Manufacturing & Service Operations Management
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We consider a single-period assortment planning and inventory management problem for a retailer, using a locational choice model to represent consumer demand. We first determine the optimal variety, product location, and inventory decisions under static substitution, and show that the optimal assortment consists of products equally spaced out such that there is no substitution among them regardless of the distribution of consumer preferences. The optimal solution can be such that some customers prefer not to buy any product in the assortment, and such that the most popular product is not offered. We then obtain bounds on profit when customers dynamically substitute, using the static substitution for the lower bound, and a retailer-controlled substitution for the upper bound. We thus define two heuristics to solve the problem under dynamic substitution and numerically evaluate their performance. This analysis shows the value of modeling dynamic substitution and identifies conditions in which the static substitution solution serves as a good approximation.