The Annals of Applied Statistics

Optimal pricing using online auction experiments: A Pólya tree approach

Edward I. George and Sam K. Hui

Full-text: Open access

Abstract

We show how a retailer can estimate the optimal price of a new product using observed transaction prices from online second-price auction experiments. For this purpose we propose a Bayesian Pólya tree approach which, given the limited nature of the data, requires a specially tailored implementation. Avoiding the need for a priori parametric assumptions, the Pólya tree approach allows for flexible inference of the valuation distribution, leading to more robust estimation of optimal price than competing parametric approaches. In collaboration with an online jewelry retailer, we illustrate how our methodology can be combined with managerial prior knowledge to estimate the profit maximizing price of a new jewelry product.

Article information

Source
Ann. Appl. Stat., Volume 6, Number 1 (2012), 55-82.

Dates
First available in Project Euclid: 6 March 2012

Permanent link to this document
https://projecteuclid.org/euclid.aoas/1331043388

Digital Object Identifier
doi:10.1214/11-AOAS503

Mathematical Reviews number (MathSciNet)
MR2951529

Zentralblatt MATH identifier
1236.91077

Keywords
Bayesian nonparametrics Pólya tree distribution second-price auctions internet auctions optimal pricing

Citation

George, Edward I.; Hui, Sam K. Optimal pricing using online auction experiments: A Pólya tree approach. Ann. Appl. Stat. 6 (2012), no. 1, 55--82. doi:10.1214/11-AOAS503. https://projecteuclid.org/euclid.aoas/1331043388


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Supplemental materials

  • Supplementary material: Web Appendix for “Optimal pricing using online auction experiments: A Pólya tree approach”. Robustness checks for the left telescoping hierarchy and the IPV assumption can be found in the supplemental article.