Simple Policies for Dynamic Pricing with Imperfect Forecasts

We consider the “classical” single-product dynamic pricing problem allowing the “scale” of demand intensity to be modulated by an exogenous “market size” stochastic process. This is a natural model of dynamically changing market conditions. We show that for a broad family of Gaussian market-size pro...

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Main Authors: Chen, Yiwei, Farias, Vivek F.
Other Authors: Sloan School of Management
Format: Article
Language:en_US
Published: Institute for Operations Research and the Management Sciences (INFORMS) 2014
Online Access:http://hdl.handle.net/1721.1/87676
https://orcid.org/0000-0002-5856-9246
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author Chen, Yiwei
Farias, Vivek F.
author2 Sloan School of Management
author_facet Sloan School of Management
Chen, Yiwei
Farias, Vivek F.
author_sort Chen, Yiwei
collection MIT
description We consider the “classical” single-product dynamic pricing problem allowing the “scale” of demand intensity to be modulated by an exogenous “market size” stochastic process. This is a natural model of dynamically changing market conditions. We show that for a broad family of Gaussian market-size processes, simple dynamic pricing rules that are essentially agnostic to the specification of this market-size process perform provably well. The pricing policies we develop are shown to compensate for forecast imperfections (or a lack of forecast information altogether) by frequent reoptimization and reestimation of the “instantaneous” market size.
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spelling mit-1721.1/876762022-09-30T15:55:18Z Simple Policies for Dynamic Pricing with Imperfect Forecasts Chen, Yiwei Farias, Vivek F. Sloan School of Management Farias, Vivek F. We consider the “classical” single-product dynamic pricing problem allowing the “scale” of demand intensity to be modulated by an exogenous “market size” stochastic process. This is a natural model of dynamically changing market conditions. We show that for a broad family of Gaussian market-size processes, simple dynamic pricing rules that are essentially agnostic to the specification of this market-size process perform provably well. The pricing policies we develop are shown to compensate for forecast imperfections (or a lack of forecast information altogether) by frequent reoptimization and reestimation of the “instantaneous” market size. 2014-06-06T14:50:20Z 2014-06-06T14:50:20Z 2013-06 2010-03 Article http://purl.org/eprint/type/JournalArticle 0030-364X 1526-5463 http://hdl.handle.net/1721.1/87676 Chen, Yiwei, and Vivek F. Farias. “Simple Policies for Dynamic Pricing with Imperfect Forecasts.” Operations Research 61, no. 3 (June 2013): 612–624. https://orcid.org/0000-0002-5856-9246 en_US http://dx.doi.org/10.1287/opre.2013.1166 Operations Research Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute for Operations Research and the Management Sciences (INFORMS) MIT web domain
spellingShingle Chen, Yiwei
Farias, Vivek F.
Simple Policies for Dynamic Pricing with Imperfect Forecasts
title Simple Policies for Dynamic Pricing with Imperfect Forecasts
title_full Simple Policies for Dynamic Pricing with Imperfect Forecasts
title_fullStr Simple Policies for Dynamic Pricing with Imperfect Forecasts
title_full_unstemmed Simple Policies for Dynamic Pricing with Imperfect Forecasts
title_short Simple Policies for Dynamic Pricing with Imperfect Forecasts
title_sort simple policies for dynamic pricing with imperfect forecasts
url http://hdl.handle.net/1721.1/87676
https://orcid.org/0000-0002-5856-9246
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