Facial-Expression Recognition: an emergent approach to the measurement of tourist satisfaction through emotions

Purpose - The employment of facial-expression recognition to analyse emotions constitutes a potential instrument for the measurement of customer satisfaction in the tourism sector. The study aims to assess the functionality of Artificial Intelligence to measure tourists’ emotions and hence their sat...

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Detalhes bibliográficos
Autores: González Rodríguez, María Rosario, Díaz Fernández, María del Carmen, Pacheco Gómez, Carmen
Formato: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2020
País:España
Recursos:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/160733
Acesso em linha:https://hdl.handle.net/11441/160733
https://doi.org/10.1016/j.tele.2020.101404
Access Level:acceso abierto
Palavra-chave:Artificial Intelligence
Facial-expression recognition
Emotions
Satisfaction
PLS-SEM
Emotionalyser
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spelling Facial-Expression Recognition: an emergent approach to the measurement of tourist satisfaction through emotionsGonzález Rodríguez, María RosarioDíaz Fernández, María del CarmenPacheco Gómez, CarmenArtificial IntelligenceFacial-expression recognitionEmotionsSatisfactionPLS-SEMEmotionalyserPurpose - The employment of facial-expression recognition to analyse emotions constitutes a potential instrument for the measurement of customer satisfaction in the tourism sector. The study aims to assess the functionality of Artificial Intelligence to measure tourists’ emotions and hence their satisfaction with the quality of the service provided on a guided tour when visiting a UNESCO heritage site. Design/methodology/approach - The methodology comprises the following stages. Firstly, the emotions are analysed through data recorded by using a software application on facial-expression recognition on a sample of tourists visiting a heritage site. Secondly, the tourists were asked to rate their overall satisfaction with the guided tour visit. Finally, a structural equation modelling approach is used to validate the strong relation between emotions and satisfaction. Findings - The results achieved confirm that the information obtained from facial-expression recognition demonstrated that it is as valid an instrument as that offered by the self-administered questionnaires for the measurement of customer satisfaction. The findings from the application reveal that a change in the scientific and professional field is emerging in the measurement of customer satisfaction focused on the emotions from a digital approach. Research limitations/implications - This research is mainly based on the use of specific software for facial-expression recognition with its intrinsic measurement of emotions with and in a specific heritage scenario. Other scenarios and software of a more sophisticated nature implemented in the tourism and hospitality industry are necessary for the in-depth comprehension of the significant role played by emotions in the improvement of service quality. Practical implications - The recent application of recording emotions in the Tourism Industry provides practitioners with useful insights for the detection of deficiencies in their services and therefore the means to boost their reputation and destination image. Originality/value- Artificial Intelligence presents a new paradigm in the measurement of satisfaction by substituting self-administered surveys with a method based on the use of innovative software that recognizes faces and detects emotions through facial expressions. The paper contributes to the literature by using an Artificial Intelligence approach to measure satisfaction through emotions in the tourism sector.ElsevierAdministración de Empresas y MarketingEconomía Aplicada IUniversidad de Sevilla2020info:eu-repo/semantics/articleinfo:eu-repo/semantics/acceptedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/160733https://doi.org/10.1016/j.tele.2020.101404reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésTelematics and Informatics, 51, 101404.González Rodríguez, M.R., Díaz Fernández, M.d.C. y Pacheco Gómez, C. (2025). Dataset of facial-expression recognition: An emergent approach to the measurement of tourist satisfaction through emotions. idUS (Depósito de Investigación de la Universidad de Sevilla). https://doi.org/10.12795/11441/177578VI PPIT-UShttps://doi.org/10.1016/j.tele.2020.101404info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1607332026-06-17T12:51:07Z
dc.title.none.fl_str_mv Facial-Expression Recognition: an emergent approach to the measurement of tourist satisfaction through emotions
title Facial-Expression Recognition: an emergent approach to the measurement of tourist satisfaction through emotions
spellingShingle Facial-Expression Recognition: an emergent approach to the measurement of tourist satisfaction through emotions
González Rodríguez, María Rosario
Artificial Intelligence
Facial-expression recognition
Emotions
Satisfaction
PLS-SEM
Emotionalyser
title_short Facial-Expression Recognition: an emergent approach to the measurement of tourist satisfaction through emotions
title_full Facial-Expression Recognition: an emergent approach to the measurement of tourist satisfaction through emotions
title_fullStr Facial-Expression Recognition: an emergent approach to the measurement of tourist satisfaction through emotions
title_full_unstemmed Facial-Expression Recognition: an emergent approach to the measurement of tourist satisfaction through emotions
title_sort Facial-Expression Recognition: an emergent approach to the measurement of tourist satisfaction through emotions
dc.creator.none.fl_str_mv González Rodríguez, María Rosario
Díaz Fernández, María del Carmen
Pacheco Gómez, Carmen
author González Rodríguez, María Rosario
author_facet González Rodríguez, María Rosario
Díaz Fernández, María del Carmen
Pacheco Gómez, Carmen
author_role author
author2 Díaz Fernández, María del Carmen
Pacheco Gómez, Carmen
author2_role author
author
dc.contributor.none.fl_str_mv Administración de Empresas y Marketing
Economía Aplicada I
Universidad de Sevilla
dc.subject.none.fl_str_mv Artificial Intelligence
Facial-expression recognition
Emotions
Satisfaction
PLS-SEM
Emotionalyser
topic Artificial Intelligence
Facial-expression recognition
Emotions
Satisfaction
PLS-SEM
Emotionalyser
description Purpose - The employment of facial-expression recognition to analyse emotions constitutes a potential instrument for the measurement of customer satisfaction in the tourism sector. The study aims to assess the functionality of Artificial Intelligence to measure tourists’ emotions and hence their satisfaction with the quality of the service provided on a guided tour when visiting a UNESCO heritage site. Design/methodology/approach - The methodology comprises the following stages. Firstly, the emotions are analysed through data recorded by using a software application on facial-expression recognition on a sample of tourists visiting a heritage site. Secondly, the tourists were asked to rate their overall satisfaction with the guided tour visit. Finally, a structural equation modelling approach is used to validate the strong relation between emotions and satisfaction. Findings - The results achieved confirm that the information obtained from facial-expression recognition demonstrated that it is as valid an instrument as that offered by the self-administered questionnaires for the measurement of customer satisfaction. The findings from the application reveal that a change in the scientific and professional field is emerging in the measurement of customer satisfaction focused on the emotions from a digital approach. Research limitations/implications - This research is mainly based on the use of specific software for facial-expression recognition with its intrinsic measurement of emotions with and in a specific heritage scenario. Other scenarios and software of a more sophisticated nature implemented in the tourism and hospitality industry are necessary for the in-depth comprehension of the significant role played by emotions in the improvement of service quality. Practical implications - The recent application of recording emotions in the Tourism Industry provides practitioners with useful insights for the detection of deficiencies in their services and therefore the means to boost their reputation and destination image. Originality/value- Artificial Intelligence presents a new paradigm in the measurement of satisfaction by substituting self-administered surveys with a method based on the use of innovative software that recognizes faces and detects emotions through facial expressions. The paper contributes to the literature by using an Artificial Intelligence approach to measure satisfaction through emotions in the tourism sector.
publishDate 2020
dc.date.none.fl_str_mv 2020
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/acceptedVersion
format article
status_str acceptedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/160733
https://doi.org/10.1016/j.tele.2020.101404
url https://hdl.handle.net/11441/160733
https://doi.org/10.1016/j.tele.2020.101404
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Telematics and Informatics, 51, 101404.
González Rodríguez, M.R., Díaz Fernández, M.d.C. y Pacheco Gómez, C. (2025). Dataset of facial-expression recognition: An emergent approach to the measurement of tourist satisfaction through emotions. idUS (Depósito de Investigación de la Universidad de Sevilla). https://doi.org/10.12795/11441/177578
VI PPIT-US
https://doi.org/10.1016/j.tele.2020.101404
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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