Coordinating Pricing and Inventory Replenishment with Nonparametric Demand Learning

78 Pages Posted: 25 Nov 2015 Last revised: 13 Feb 2019

See all articles by Boxiao Chen

Boxiao Chen

University of Illinois at Chicago - College of Business Administration

Xiuli Chao

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering

Hyun-Soo Ahn

University of Michigan, Stephen M. Ross School of Business

Abstract

We consider a firm (e.g., retailer) selling a single nonperishable product over a finite-period planning horizon. Demand in each period is stochastic and price-dependent, and unsatisfied demands are backlogged. At the beginning of each period, the firm determines its selling price and inventory replenishment quantity, but it knows neither the form of demand dependency on selling price nor the distribution of demand uncertainty a priori, hence it has to make pricing and ordering decisions based on historical demand data. We propose a nonparametric data-driven policy that learns about the demand on the fly and, concurrently, applies learned information to determine replenishment and pricing decisions. The policy integrates learning and action in a sense that the firm actively experiments on pricing and inventory levels to collect demand information with the least possible profit loss. Besides convergence of optimal policies, we show that the regret, defined as the average profit loss compared with that of the optimal solution when the firm has complete information about the underlying demand, vanishes at the fastest possible rate as the planning horizon increases.

Keywords: dynamic pricing, inventory control, demand learning, nonparametric estimation, nonperishable products, asymptotic optimality

Suggested Citation

Chen, Boxiao and Chao, Xiuli and Ahn, Hyun-Soo, Coordinating Pricing and Inventory Replenishment with Nonparametric Demand Learning. Ross School of Business Paper No. 1294, Available at SSRN: https://ssrn.com/abstract=2694633 or http://dx.doi.org/10.2139/ssrn.2694633

Boxiao Chen (Contact Author)

University of Illinois at Chicago - College of Business Administration ( email )

601 S Morgan St
Chicago, IL 60607
United States

Xiuli Chao

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering ( email )

1205 Beal Avenue
Ann Arbor, MI 48109
United States

Hyun-Soo Ahn

University of Michigan, Stephen M. Ross School of Business ( email )

701 Tappan St
R5456
Ann Arbor, MI 48109-1234
United States

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