Please use this identifier to cite or link to this item:
http://hdl.handle.net/10071/21260Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Fernandes, E. | - |
| dc.contributor.author | Moro, S. | - |
| dc.contributor.author | Cortez, P. | - |
| dc.contributor.author | Batista, F. | - |
| dc.contributor.author | Ribeiro, R. | - |
| dc.date.accessioned | 2021-01-13T19:04:49Z | - |
| dc.date.issued | 2021 | - |
| dc.identifier.issn | 0278-4319 | - |
| dc.identifier.uri | http://hdl.handle.net/10071/21260 | - |
| dc.description.abstract | Restaurant management requires customer responsiveness to deal with increasingly higher expectations and market competitiveness. This study proposes an approach to simplify the decision-making process of restaurant managers by combining both live social media customer feedback and historical sales data in a sales forecast model (based on TripAdvisor data and the Bass model). Our approach was validated with internal and external (i.e., online reviews) data gathered from six restaurants. The collected data was processed using data analytics for developing a dashboard that provides value for restauranteurs by taking advantage of online reviews and sales forecast. Such dashboard was evaluated by restaurant management experts, which provided positive feedback, highlighting in particular the time saved in the decision-making process. | eng |
| dc.language.iso | eng | - |
| dc.publisher | Elsevier | - |
| dc.relation | UIDB/04466/2020 | - |
| dc.relation | UIDB/50021/2020 | - |
| dc.relation | UID/CEC/00319/2019 | - |
| dc.relation | UIDP/04466/2020 | - |
| dc.rights | openAccess | - |
| dc.subject | Restaurant management | eng |
| dc.subject | Business performance | eng |
| dc.subject | Customer relationship management | eng |
| dc.subject | Online review | eng |
| dc.subject | Text mining | eng |
| dc.subject | Data analytics | eng |
| dc.title | A data-driven approach to measure restaurant performance by combining online reviews with historical sales data | eng |
| dc.type | article | - |
| dc.peerreviewed | yes | - |
| dc.journal | International Journal of Hospitality Management | - |
| dc.volume | 94 | - |
| degois.publication.title | A data-driven approach to measure restaurant performance by combining online reviews with historical sales data | eng |
| dc.date.updated | 2021-01-13T19:03:17Z | - |
| dc.description.version | info:eu-repo/semantics/acceptedVersion | - |
| dc.identifier.doi | 10.1016/j.ijhm.2020.102830 | - |
| dc.subject.fos | Domínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informação | por |
| dc.subject.fos | Domínio/Área Científica::Ciências Sociais::Economia e Gestão | por |
| dc.subject.fos | Domínio/Área Científica::Ciências Sociais::Outras Ciências Sociais | por |
| dc.date.embargo | 2023-12-26 | - |
| iscte.subject.ods | Indústria, inovação e infraestruturas | por |
| iscte.subject.ods | Cidades e comunidades sustentáveis | por |
| iscte.identifier.ciencia | https://ciencia.iscte-iul.pt/id/ci-pub-77763 | - |
| iscte.alternateIdentifiers.scopus | 2-s2.0-85098105957 | - |
| Appears in Collections: | CTI-RI - Artigos em revistas científicas internacionais com arbitragem científica ISTAR-RI - Artigos em revistas científicas internacionais com arbitragem científica | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2020_IJHM-FernandesMoroCortezBatistaRibeiro-PostPrint.pdf | Versão Aceite | 657,66 kB | Adobe PDF | View/Open |
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