Dynamic Pricing with an Unknown Demand Model: Asymptotically Optimal Semi-Myopic Policies
Operations Research, Vol. 62, No. 5, September-October 2014, pp. 1142-1167
52 Pages Posted: 3 Feb 2014 Last revised: 1 Oct 2018
Date Written: April 19, 2014
Abstract
We consider a monopolist who sells a set of products over a time horizon of T periods. The seller initially does not know the parameters of the products’ linear demand curve, but can estimate them based on demand observations. We first assume that the seller knows nothing about the parameters of the demand curve, and then consider the case where the seller knows the expected demand under an incumbent price. It is shown that the smallest achievable revenue loss in T periods, relative to a clairvoyant who knows the underlying demand model, is of order √T in the former case and of order logT in the latter case. To derive pricing policies that are practically implementable, we take as our point of departure the widely used policy called greedy iterated least squares (ILS), which combines sequential estimation and myopic price optimization. It is known that the greedy ILS policy itself suffers from incomplete learning, but we show that certain variants of greedy ILS achieve the minimum asymptotic loss rate. To highlight the essential features of well-performing pricing policies, we derive sufficient conditions for asymptotic optimality.
Keywords: Revenue management, pricing, sequential estimation, exploration-exploitation
Suggested Citation: Suggested Citation
Do you have a job opening that you would like to promote on SSRN?
Recommended Papers
-
On the Minimax Complexity of Pricing in a Changing Environment
By Omar Besbes and Assaf Zeevi
-
Demand Learning and Dynamic Pricing for Multi-Version Products
By Guillermo Gallego and Masoud Talebian
-
Dynamic Pricing Through Data Sampling
By Maxime C. Cohen, Ruben Lobel, ...
-
Optimal Pricing Policy in the Presence of Experience Effects
By Francis Clarke, Masako N. Darrough, ...
-
Pricing to Accelerate Demand Learning in Dynamic Assortment Planning for Perishable Products
By Masoud Talebian, Natashia Boland, ...
-
Dynamic Pricing – State-of-The-Art
By Jochen Gönsch, Robert Klein, ...
-
Non-Stationary Stochastic Optimization
By Omar Besbes, Yonatan Gur, ...
-
Dynamic Pricing Strategies in the Presence of Demand Shifts
By Omar Besbes and Denis Saure
-
Intertemporal Pricing under Minimax Regret
By Rene Caldentey, Ying Liu, ...