Please use this identifier to cite or link to this item: http://hdl.handle.net/10609/93192
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dc.contributor.authorvan de Geer, Ruben-
dc.contributor.authorden Boer, Arnoud V.-
dc.contributor.authorbayliss, christopher-
dc.contributor.authorCurrie, Christine S. M.-
dc.contributor.authorEllina, Andria-
dc.contributor.authorEsders, Malte-
dc.contributor.authorHaensel, Alwin-
dc.contributor.authorXiao, Lei-
dc.contributor.authorMaclean, Kyle D. S.-
dc.contributor.authorMartinez Sykora, Antonio-
dc.contributor.authorRiseth, Asbjorn Nilsen-
dc.contributor.authorOdegaard, Fredrik-
dc.contributor.authorZachariades, Simos-
dc.contributor.otherUniversitat Oberta de Catalunya (UOC)-
dc.contributor.otherVrije Universiteit Amsterdam-
dc.contributor.otherUniversity of Amsterdam-
dc.contributor.otherUniversity of Southampton-
dc.contributor.otherTechnische Universität Berlin-
dc.contributor.otherAdvanced Mathematical Solutions-
dc.contributor.otherColumbia University-
dc.contributor.otherIvey Business School-
dc.contributor.otherUniversity of Oxford-
dc.date.accessioned2019-04-15T11:37:12Z-
dc.date.available2019-04-15T11:37:12Z-
dc.date.issued2018-10-16-
dc.identifier.citationVan de Geer, R., Den Boer, Arnoud V. , Bayliss, C., Currie, C., Ellina, A., Esders, M., Haensel, A., Xiao, L., Maclean, K. D. S., Martínez Sykora, A., Riseth, A. N., Odegaard, F. & Zachariades, S. (2018). Dynamic pricing and learning with competition: insights from the dynamic pricing challenge at the 2017 INFORMS RM & pricing conference. Journal of Revenue and Pricing Management, (), 1-19. doi: 10.1057/s41272-018-00164-4-
dc.identifier.issn1476-6930MIAR
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dc.identifier.issn1477-657XMIAR
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dc.identifier.urihttp://hdl.handle.net/10609/93192-
dc.description.abstractThis paper presents the results of the Dynamic Pricing Challenge, held on the occasion of the 17th INFORMS Revenue Management and Pricing Section Conference on June 29-30, 2017 in Amsterdam, The Netherlands. For this challenge, participants submitted algorithms for pricing and demand learning of which the numerical performance was analyzed in simulated market environments. This allows consideration of market dynamics that are not analytically tractable or can not be empirically analyzed due to practical complications. Our findings implicate that the relative performance of algorithms varies substantially across different market dynamics, which confirms the intrinsic complexity of pricing and learning in the presence of competition.en
dc.language.isoeng-
dc.publisherJournal of Revenue and Pricing Management-
dc.relation.ispartofJournal of Revenue and Pricing Management, 2018 ()-
dc.relation.urihttps://doi.org/10.1057/s41272-018-00164-4-
dc.rightsCC BY-NC-ND-
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/-
dc.subjectmarketplacesen
dc.subjectmercadoses
dc.subjectmercatsca
dc.subjectalgorithmsen
dc.subjectalgoritmoses
dc.subjectalgorismesca
dc.subjectcompetitive environmenten
dc.subjectentorno competitivoes
dc.subjectlearningen
dc.subjectentorn competitiuca
dc.subjectaprendizajees
dc.subjectaprenentatgeca
dc.subject.lcshComputer algorithmsen
dc.titleDynamic pricing and learning with competition: insights from the dynamic pricing challenge at the 2017 INFORMS RM & pricing conference-
dc.typeinfo:eu-repo/semantics/article-
dc.subject.lemacAlgorismes computacionalsca
dc.subject.lcshesAlgoritmos computacionaleses
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess-
dc.identifier.doi10.1057/s41272-018-00164-4-
dc.gir.idAR/0000006856-
dc.relation.projectIDinfo:eu-repo/grantAgreement/EP/N006461/1-
dc.relation.projectIDinfo:eu-repo/grantAgreement/EP/L015803/1-
dc.type.versioninfo:eu-repo/semantics/submittedVersion-
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