Social media impact of tourism managers: a decision tree approach in happiness, social marketing and sustainability

[EN] Purpose – This study aims to analyze communication from the perspective of social marketing, positive emotions, and the topics chosen by Spanish tourist destinations to show their destination image. Additionally, this research shows a message classification model, based on the aforementioned ch...

Descripción completa

Detalles Bibliográficos
Autores: Galiano Coronil, Araceli, Blanco Moreno, Sofía, Tobar Pesántez, Luis Bayardo, Gutiérrez Montoya, Guillermo Antonio
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:España
Institución:Universidad de León
Repositorio:BULERIA. Repositorio Institucional de la Universidad de León
OAI Identifier:oai:buleria.unileon.es:10612/23108
Acceso en línea:https://www.emerald.com/insight/content/doi/10.1108/jmd-04-2023-0131/full/html
https://hdl.handle.net/10612/23108
Access Level:acceso abierto
Palabra clave:Marketing
Social marketing
Twitter
CHAID
Tourism destination
Sustainable tourism
Happiness
id ES_eb306dd25ed5fda35c96acc4ec4ee506
oai_identifier_str oai:buleria.unileon.es:10612/23108
network_acronym_str ES
network_name_str España
repository_id_str
spelling Social media impact of tourism managers: a decision tree approach in happiness, social marketing and sustainabilityGaliano Coronil, AraceliBlanco Moreno, SofíaTobar Pesántez, Luis BayardoGutiérrez Montoya, Guillermo AntonioMarketingSocial marketingTwitterCHAIDTourism destinationSustainable tourismHappiness[EN] Purpose – This study aims to analyze communication from the perspective of social marketing, positive emotions, and the topics chosen by Spanish tourist destinations to show their destination image. Additionally, this research shows a message classification model, based on the aforementioned characteristics, that has generated a greater impact, offering clarity to tourism managers on the type of ontent they should publish to achieve greater visibility. Design/methodology/approach – The methodology used in this work combines content analysis and data mining techniques. The classification tree using the chi-square automatic interaction detector (CHAID) algorithm was selected to determine predictors of like behaviour. Findings – The results show that the predictor variables have been emotions, social marketing and topics. Also, the characteristics of the messages most likely to have a high impact are those related to emotions of joy or happiness, their purpose is behavioural, and they talk about rural, cultural issues, special dates, getaways, or highlights of a town or city for something specific. Originality/value – This study is the first to analyze the content of the tweets shared by destination tourism managers from a social marketing, positive emotions, and sustainability perspective, determining the possible predictors of likes on Twitter. The authors contribute to the literature by deepening the understanding of how social marketing and the positive emotions promoted drive a more significant impact in tourism communication campaigns on social media. The authors provide destination managers with a way better to understand the variables relevant to users in tourism contentSIEmeraldComercializacion e Investigacion de MercadosFacultad de Ciencias Economicas y Empresariales2023info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://www.emerald.com/insight/content/doi/10.1108/jmd-04-2023-0131/full/htmlhttps://hdl.handle.net/10612/23108reponame:BULERIA. Repositorio Institucional de la Universidad de Leóninstname:Universidad de LeónIngléshttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:buleria.unileon.es:10612/231082026-06-24T12:43:27Z
dc.title.none.fl_str_mv Social media impact of tourism managers: a decision tree approach in happiness, social marketing and sustainability
title Social media impact of tourism managers: a decision tree approach in happiness, social marketing and sustainability
spellingShingle Social media impact of tourism managers: a decision tree approach in happiness, social marketing and sustainability
Galiano Coronil, Araceli
Marketing
Social marketing
Twitter
CHAID
Tourism destination
Sustainable tourism
Happiness
title_short Social media impact of tourism managers: a decision tree approach in happiness, social marketing and sustainability
title_full Social media impact of tourism managers: a decision tree approach in happiness, social marketing and sustainability
title_fullStr Social media impact of tourism managers: a decision tree approach in happiness, social marketing and sustainability
title_full_unstemmed Social media impact of tourism managers: a decision tree approach in happiness, social marketing and sustainability
title_sort Social media impact of tourism managers: a decision tree approach in happiness, social marketing and sustainability
dc.creator.none.fl_str_mv Galiano Coronil, Araceli
Blanco Moreno, Sofía
Tobar Pesántez, Luis Bayardo
Gutiérrez Montoya, Guillermo Antonio
author Galiano Coronil, Araceli
author_facet Galiano Coronil, Araceli
Blanco Moreno, Sofía
Tobar Pesántez, Luis Bayardo
Gutiérrez Montoya, Guillermo Antonio
author_role author
author2 Blanco Moreno, Sofía
Tobar Pesántez, Luis Bayardo
Gutiérrez Montoya, Guillermo Antonio
author2_role author
author
author
dc.contributor.none.fl_str_mv Comercializacion e Investigacion de Mercados
Facultad de Ciencias Economicas y Empresariales
dc.subject.none.fl_str_mv Marketing
Social marketing
Twitter
CHAID
Tourism destination
Sustainable tourism
Happiness
topic Marketing
Social marketing
Twitter
CHAID
Tourism destination
Sustainable tourism
Happiness
description [EN] Purpose – This study aims to analyze communication from the perspective of social marketing, positive emotions, and the topics chosen by Spanish tourist destinations to show their destination image. Additionally, this research shows a message classification model, based on the aforementioned characteristics, that has generated a greater impact, offering clarity to tourism managers on the type of ontent they should publish to achieve greater visibility. Design/methodology/approach – The methodology used in this work combines content analysis and data mining techniques. The classification tree using the chi-square automatic interaction detector (CHAID) algorithm was selected to determine predictors of like behaviour. Findings – The results show that the predictor variables have been emotions, social marketing and topics. Also, the characteristics of the messages most likely to have a high impact are those related to emotions of joy or happiness, their purpose is behavioural, and they talk about rural, cultural issues, special dates, getaways, or highlights of a town or city for something specific. Originality/value – This study is the first to analyze the content of the tweets shared by destination tourism managers from a social marketing, positive emotions, and sustainability perspective, determining the possible predictors of likes on Twitter. The authors contribute to the literature by deepening the understanding of how social marketing and the positive emotions promoted drive a more significant impact in tourism communication campaigns on social media. The authors provide destination managers with a way better to understand the variables relevant to users in tourism content
publishDate 2023
dc.date.none.fl_str_mv 2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://www.emerald.com/insight/content/doi/10.1108/jmd-04-2023-0131/full/html
https://hdl.handle.net/10612/23108
url https://www.emerald.com/insight/content/doi/10.1108/jmd-04-2023-0131/full/html
https://hdl.handle.net/10612/23108
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.rights.none.fl_str_mv http://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv Emerald
publisher.none.fl_str_mv Emerald
dc.source.none.fl_str_mv reponame:BULERIA. Repositorio Institucional de la Universidad de León
instname:Universidad de León
instname_str Universidad de León
reponame_str BULERIA. Repositorio Institucional de la Universidad de León
collection BULERIA. Repositorio Institucional de la Universidad de León
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869423206028279808
score 15.812429