Elasticity Based Demand Forecasting and Price Optimization for Online Retail

Elasticity Based Demand Forecasting and Price Optimization for Online Retail

We study a problem of an online retailer who observes the unit sales of a product, and dynamically changes the retail price, in order to maximize the expected revenue. Assuming the demand of the product is price sensitive, we are interested in the optimal pricing policy when future demand is uncerta...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:arXiv.org 2021-06
Hauptverfasser: Liu, Chengcheng, Sustik, Mátyás A
Format: Artikel
Sprache:eng
Schlagworte:
Demand
Economic forecasting
Inventory management
Optimization
Pricing
Pricing policies
Revenue
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page
container_issue
container_start_page
container_title arXiv.org
container_volume
creator Liu, Chengcheng
Sustik, Mátyás A
description We study a problem of an online retailer who observes the unit sales of a product, and dynamically changes the retail price, in order to maximize the expected revenue. Assuming the demand of the product is price sensitive, we are interested in the optimal pricing policy when future demand is uncertain. We build a system to investigate the relationship between retail price and demand and estimate the demand function. The system predicts demand and revenue at a given retail price. We formulate a revenue maximization problem over a discrete finite time horizon with discrete retail price. The optimal pricing policy is solved based on the predicted demand and revenue values. With computational experiments, we investigate the effect of optimal pricing policy to inventory management.
format Article
fullrecord <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2543473515</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2543473515</sourcerecordid><originalsourceid>FETCH-proquest_journals_25434735153</originalsourceid><addsrcrecordid>eNqNisEKgkAUAJcgSMp_eNBZ0F03O1dKh8CI7rLoM57oru2uh_r6EvqATsMws2ABFyKJ9innKxY618VxzHcZl1IE7JL3ynmqyb_goBw2cMJB6QYKY7Gek37A7FdLNUI5ehrorTwZDa2xUOqeNMINvaJ-w5at6h2GP67Ztsjvx3M0WvOc0PmqM5PV31RxmYo0EzKR4r_rAyluPTE</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2543473515</pqid></control><display><type>article</type><title>Elasticity Based Demand Forecasting and Price Optimization for Online Retail</title><source>Freely Accessible Journals</source><creator>Liu, Chengcheng ; Sustik, Mátyás A</creator><creatorcontrib>Liu, Chengcheng ; Sustik, Mátyás A</creatorcontrib><description>We study a problem of an online retailer who observes the unit sales of a product, and dynamically changes the retail price, in order to maximize the expected revenue. Assuming the demand of the product is price sensitive, we are interested in the optimal pricing policy when future demand is uncertain. We build a system to investigate the relationship between retail price and demand and estimate the demand function. The system predicts demand and revenue at a given retail price. We formulate a revenue maximization problem over a discrete finite time horizon with discrete retail price. The optimal pricing policy is solved based on the predicted demand and revenue values. With computational experiments, we investigate the effect of optimal pricing policy to inventory management.</description><identifier>EISSN: 2331-8422</identifier><language>eng</language><publisher>Ithaca: Cornell University Library, arXiv.org</publisher><subject>Demand ; Economic forecasting ; Inventory management ; Optimization ; Pricing ; Pricing policies ; Revenue</subject><ispartof>arXiv.org, 2021-06</ispartof><rights>2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>780,784</link.rule.ids></links><search><creatorcontrib>Liu, Chengcheng</creatorcontrib><creatorcontrib>Sustik, Mátyás A</creatorcontrib><title>Elasticity Based Demand Forecasting and Price Optimization for Online Retail</title><title>arXiv.org</title><description>We study a problem of an online retailer who observes the unit sales of a product, and dynamically changes the retail price, in order to maximize the expected revenue. Assuming the demand of the product is price sensitive, we are interested in the optimal pricing policy when future demand is uncertain. We build a system to investigate the relationship between retail price and demand and estimate the demand function. The system predicts demand and revenue at a given retail price. We formulate a revenue maximization problem over a discrete finite time horizon with discrete retail price. The optimal pricing policy is solved based on the predicted demand and revenue values. With computational experiments, we investigate the effect of optimal pricing policy to inventory management.</description><subject>Demand</subject><subject>Economic forecasting</subject><subject>Inventory management</subject><subject>Optimization</subject><subject>Pricing</subject><subject>Pricing policies</subject><subject>Revenue</subject><issn>2331-8422</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><recordid>eNqNisEKgkAUAJcgSMp_eNBZ0F03O1dKh8CI7rLoM57oru2uh_r6EvqATsMws2ABFyKJ9innKxY618VxzHcZl1IE7JL3ynmqyb_goBw2cMJB6QYKY7Gek37A7FdLNUI5ehrorTwZDa2xUOqeNMINvaJ-w5at6h2GP67Ztsjvx3M0WvOc0PmqM5PV31RxmYo0EzKR4r_rAyluPTE</recordid><startdate>20210616</startdate><enddate>20210616</enddate><creator>Liu, Chengcheng</creator><creator>Sustik, Mátyás A</creator><general>Cornell University Library, arXiv.org</general><scope>8FE</scope><scope>8FG</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>M7S</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope></search><sort><creationdate>20210616</creationdate><title>Elasticity Based Demand Forecasting and Price Optimization for Online Retail</title><author>Liu, Chengcheng ; Sustik, Mátyás A</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_25434735153</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Demand</topic><topic>Economic forecasting</topic><topic>Inventory management</topic><topic>Optimization</topic><topic>Pricing</topic><topic>Pricing policies</topic><topic>Revenue</topic><toplevel>online_resources</toplevel><creatorcontrib>Liu, Chengcheng</creatorcontrib><creatorcontrib>Sustik, Mátyás A</creatorcontrib><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Engineering Collection</collection><collection>Engineering Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Chengcheng</au><au>Sustik, Mátyás A</au><format>book</format><genre>document</genre><ristype>GEN</ristype><atitle>Elasticity Based Demand Forecasting and Price Optimization for Online Retail</atitle><jtitle>arXiv.org</jtitle><date>2021-06-16</date><risdate>2021</risdate><eissn>2331-8422</eissn><abstract>We study a problem of an online retailer who observes the unit sales of a product, and dynamically changes the retail price, in order to maximize the expected revenue. Assuming the demand of the product is price sensitive, we are interested in the optimal pricing policy when future demand is uncertain. We build a system to investigate the relationship between retail price and demand and estimate the demand function. The system predicts demand and revenue at a given retail price. We formulate a revenue maximization problem over a discrete finite time horizon with discrete retail price. The optimal pricing policy is solved based on the predicted demand and revenue values. With computational experiments, we investigate the effect of optimal pricing policy to inventory management.</abstract><cop>Ithaca</cop><pub>Cornell University Library, arXiv.org</pub><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier EISSN: 2331-8422
ispartof arXiv.org, 2021-06
issn 2331-8422
language eng
recordid cdi_proquest_journals_2543473515
source Freely Accessible Journals
subjects Demand
Economic forecasting
Inventory management
Optimization
Pricing
Pricing policies
Revenue
title Elasticity Based Demand Forecasting and Price Optimization for Online Retail
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-09T17%3A36%3A09IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=document&rft.atitle=Elasticity%20Based%20Demand%20Forecasting%20and%20Price%20Optimization%20for%20Online%20Retail&rft.jtitle=arXiv.org&rft.au=Liu,%20Chengcheng&rft.date=2021-06-16&rft.eissn=2331-8422&rft_id=info:doi/&rft_dat=%3Cproquest%3E2543473515%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2543473515&rft_id=info:pmid/&rfr_iscdi=true