Clearance Pricing and Inventory Policies for Retail Chains
Management Science
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Manufacturing & Service Operations Management
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Management Science
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Management Science
A Partially Observed Markov Decision Process for Dynamic Pricing
Management Science
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Operations Research
Relative Entropy, Exponential Utility, and Robust Dynamic Pricing
Operations Research
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Operations Research
Dynamic Pricing with a Prior on Market Response
Operations Research
Dynamic Pricing with a Prior on Market Response
Operations Research
Pricing and inventory management in a system with multiple competing retailers under (r, Q) policies
Computers and Operations Research
Learning in stochastic machine scheduling
WAOA'11 Proceedings of the 9th international conference on Approximation and Online Algorithms
Dynamic Pricing with Financial Milestones: Feedback-Form Policies
Management Science
Clearance Pricing Optimization for a Fast-Fashion Retailer
Operations Research
Blind Network Revenue Management
Operations Research
Clearance Pricing Optimization for a Fast-Fashion Retailer
Operations Research
Blind Network Revenue Management
Operations Research
Bayesian Dynamic Pricing in Queueing Systems with Unknown Delay Cost Characteristics
Manufacturing & Service Operations Management
Optimal Dynamic Assortment Planning with Demand Learning
Manufacturing & Service Operations Management
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A retailer is endowed with a finite inventory of a nonperishable product. Demand for this product is driven by a price-sensitive Poisson process that depends on an unknown parameter that is a proxy for the market size. The retailer has a prior belief on the value of this parameter that he updates as time and available information (prices and sales) evolve. The retailer's objective is to maximize the discounted long-term average profits of his operation using dynamic pricing policies. We consider two cases. In the first case, the retailer is constrained to sell the entire initial stock of the nonperishable product before a different assortment is considered. In the second case, the retailer is able to stop selling the nonperishable product at any time and switch to a different menu of products. For both cases, we formulate the retailer's problem as a (Poisson) intensity control problem and derive structural properties of an optimal solution, and suggest a simple and efficient approximated solution. We use numerical computations, together with asymptotic analysis, to evaluate the performance of our proposed policy.