Factors influencing hotels’ online prices

Detalhes bibliográficos
Autor(a) principal: Moro, S.
Data de Publicação: 2018
Outros Autores: Rita, P., Oliveira, C.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/15412
Resumo: Digital corporations are creating new paths of business driven by consumers empowered by social media. Understanding the role that each feature drawn from online platforms has on price fluctuation is vital for leveraging decision making. In this study, 5603 simulations of online reservations from 23 Portuguese cities were gathered, including characterizing features from social media, web visibility and hotel amenities, from four renowned online sources: Booking.com, TripAdvisor, Google, and Facebook. After data preparation, including removal of irrelevant features in terms of modeling and outlier cleaning, a tuned dataset of 3137 simulations and 30 features (including the price charged per day) was used first for evaluating the modeling performance of an ensemble of multilayer perceptrons, and then for extracting valuable knowledge through the data-based sensitivity analysis. Findings show that all features from the encompassed factors (social media, online reservation, hotel characteristics, web visibility and city) play a significant role in price.
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spelling Factors influencing hotels’ online pricesOnline bookingPricingHotel reservationSocial mediaData miningDigital corporations are creating new paths of business driven by consumers empowered by social media. Understanding the role that each feature drawn from online platforms has on price fluctuation is vital for leveraging decision making. In this study, 5603 simulations of online reservations from 23 Portuguese cities were gathered, including characterizing features from social media, web visibility and hotel amenities, from four renowned online sources: Booking.com, TripAdvisor, Google, and Facebook. After data preparation, including removal of irrelevant features in terms of modeling and outlier cleaning, a tuned dataset of 3137 simulations and 30 features (including the price charged per day) was used first for evaluating the modeling performance of an ensemble of multilayer perceptrons, and then for extracting valuable knowledge through the data-based sensitivity analysis. Findings show that all features from the encompassed factors (social media, online reservation, hotel characteristics, web visibility and city) play a significant role in price.Taylor and Francis2018-03-21T10:06:30Z2019-09-21T00:00:00Z2018-01-01T00:00:00Z20182019-03-20T11:30:44Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/15412eng1936-862310.1080/19368623.2018.1395379Moro, S.Rita, P.Oliveira, C.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:59:38Zoai:repositorio.iscte-iul.pt:10071/15412Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:31:21.153415Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Factors influencing hotels’ online prices
title Factors influencing hotels’ online prices
spellingShingle Factors influencing hotels’ online prices
Moro, S.
Online booking
Pricing
Hotel reservation
Social media
Data mining
title_short Factors influencing hotels’ online prices
title_full Factors influencing hotels’ online prices
title_fullStr Factors influencing hotels’ online prices
title_full_unstemmed Factors influencing hotels’ online prices
title_sort Factors influencing hotels’ online prices
author Moro, S.
author_facet Moro, S.
Rita, P.
Oliveira, C.
author_role author
author2 Rita, P.
Oliveira, C.
author2_role author
author
dc.contributor.author.fl_str_mv Moro, S.
Rita, P.
Oliveira, C.
dc.subject.por.fl_str_mv Online booking
Pricing
Hotel reservation
Social media
Data mining
topic Online booking
Pricing
Hotel reservation
Social media
Data mining
description Digital corporations are creating new paths of business driven by consumers empowered by social media. Understanding the role that each feature drawn from online platforms has on price fluctuation is vital for leveraging decision making. In this study, 5603 simulations of online reservations from 23 Portuguese cities were gathered, including characterizing features from social media, web visibility and hotel amenities, from four renowned online sources: Booking.com, TripAdvisor, Google, and Facebook. After data preparation, including removal of irrelevant features in terms of modeling and outlier cleaning, a tuned dataset of 3137 simulations and 30 features (including the price charged per day) was used first for evaluating the modeling performance of an ensemble of multilayer perceptrons, and then for extracting valuable knowledge through the data-based sensitivity analysis. Findings show that all features from the encompassed factors (social media, online reservation, hotel characteristics, web visibility and city) play a significant role in price.
publishDate 2018
dc.date.none.fl_str_mv 2018-03-21T10:06:30Z
2018-01-01T00:00:00Z
2018
2019-09-21T00:00:00Z
2019-03-20T11:30:44Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10071/15412
url http://hdl.handle.net/10071/15412
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 1936-8623
10.1080/19368623.2018.1395379
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Taylor and Francis
publisher.none.fl_str_mv Taylor and Francis
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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