European tourist perspective on destination satisfaction: a business analytics approach
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Tipo de documento: | Dissertação |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/13232 |
Resumo: | For many years that tourism information has been collected and stored, allowing increased interest in the data mining (DM) areas. This leads to a need of research and discovery of new patterns to develop automated procedures to improve the tourism knowledge management. The relationship between the tourist characteristics and preferences and the tourist satisfaction was never studied in order to provide useful knowledge to the tourism industry. Therefore, there was the need to investigate the explanatory factors of the tourist satisfaction with the destination to allow the tourism companies to define the correct assumptions about a certain travel. This dissertation used the data from Flash Eurobarometer 414 “Preferences of Europeans towards tourism 2015” with data from the 28 countries of the European Union (EU). A predictive model was obtained for the tourist satisfaction, through the discovery of existing patterns in the process of the tourist travel, using DM techniques on the data referred above. The definition of an explanatory model allowed to obtain useful knowledge for tourism agencies, enabling the development of marketing strategies according to the tourist profile and ensuring development of promotional messages for products and experiences, ensuring that correct assumptions are made about their customers. |
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European tourist perspective on destination satisfaction: a business analytics approachData miningBusiness intelligenceTourismTouristSatisfactionCRISP-DMInteligência empresarialTurismoEstratégias de marketingAvaliaçãoSatisfação do clienteFor many years that tourism information has been collected and stored, allowing increased interest in the data mining (DM) areas. This leads to a need of research and discovery of new patterns to develop automated procedures to improve the tourism knowledge management. The relationship between the tourist characteristics and preferences and the tourist satisfaction was never studied in order to provide useful knowledge to the tourism industry. Therefore, there was the need to investigate the explanatory factors of the tourist satisfaction with the destination to allow the tourism companies to define the correct assumptions about a certain travel. This dissertation used the data from Flash Eurobarometer 414 “Preferences of Europeans towards tourism 2015” with data from the 28 countries of the European Union (EU). A predictive model was obtained for the tourist satisfaction, through the discovery of existing patterns in the process of the tourist travel, using DM techniques on the data referred above. The definition of an explanatory model allowed to obtain useful knowledge for tourism agencies, enabling the development of marketing strategies according to the tourist profile and ensuring development of promotional messages for products and experiences, ensuring that correct assumptions are made about their customers.Desde há muito tempo que é recolhida e armazenada informação sobre turismo, permitindo captar o interesse das áreas de data mining (DM). Consequentemente, surgiu a necessidade de pesquisa e descoberta de novos padrões para desenvolver procedimentos automatizados, de forma a melhorar a gestão deste tipo de informação. A relação entre as características do turista, as suas preferências e a satisfação nunca foram estudadas extensivamente de forma a criar conhecimento útil para a indústria do turismo. Desta forma, havia a necessidade de investigar e estudar os fatores explicativos da satisfação do turista com o destino, para que seja possível às empresas de turismo traçar o perfil de turista adequado e transmitir as campanhas de marketing de forma assertiva e eficiente. Nesta dissertação foram utilizados os dados do Flash Eurobarometer 414 “Preferences of Europeans towards tourism 2015”, que contém dados dos 28 países da União Europeia. Através da descoberta de padrões existentes no processo de viagem do turista, utilizando técnicas de DM sobre os dados acima referidos, foi possível obter um modelo preditivo para a satisfação do turista. A definição de um modelo explicativo permitiu obter conhecimento útil para as empresas de turismo, facilitando o desenvolvimento de estratégias de marketing de acordo com o perfil do turista e de mensagens promocionais para produtos e experiências, garantindo que são definidos pressupostos adequados para os seus clientes.2017-05-05T14:02:25Z2016-11-19T00:00:00Z2016-11-192016-09info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfapplication/octet-streamhttp://hdl.handle.net/10071/13232TID:201608200engVieira, Lisa Maria Luísinfo: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:RCAAP2023-11-09T17:35:16Zoai:repositorio.iscte-iul.pt:10071/13232Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:15:57.605559Repositório 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 |
European tourist perspective on destination satisfaction: a business analytics approach |
title |
European tourist perspective on destination satisfaction: a business analytics approach |
spellingShingle |
European tourist perspective on destination satisfaction: a business analytics approach Vieira, Lisa Maria Luís Data mining Business intelligence Tourism Tourist Satisfaction CRISP-DM Inteligência empresarial Turismo Estratégias de marketing Avaliação Satisfação do cliente |
title_short |
European tourist perspective on destination satisfaction: a business analytics approach |
title_full |
European tourist perspective on destination satisfaction: a business analytics approach |
title_fullStr |
European tourist perspective on destination satisfaction: a business analytics approach |
title_full_unstemmed |
European tourist perspective on destination satisfaction: a business analytics approach |
title_sort |
European tourist perspective on destination satisfaction: a business analytics approach |
author |
Vieira, Lisa Maria Luís |
author_facet |
Vieira, Lisa Maria Luís |
author_role |
author |
dc.contributor.author.fl_str_mv |
Vieira, Lisa Maria Luís |
dc.subject.por.fl_str_mv |
Data mining Business intelligence Tourism Tourist Satisfaction CRISP-DM Inteligência empresarial Turismo Estratégias de marketing Avaliação Satisfação do cliente |
topic |
Data mining Business intelligence Tourism Tourist Satisfaction CRISP-DM Inteligência empresarial Turismo Estratégias de marketing Avaliação Satisfação do cliente |
description |
For many years that tourism information has been collected and stored, allowing increased interest in the data mining (DM) areas. This leads to a need of research and discovery of new patterns to develop automated procedures to improve the tourism knowledge management. The relationship between the tourist characteristics and preferences and the tourist satisfaction was never studied in order to provide useful knowledge to the tourism industry. Therefore, there was the need to investigate the explanatory factors of the tourist satisfaction with the destination to allow the tourism companies to define the correct assumptions about a certain travel. This dissertation used the data from Flash Eurobarometer 414 “Preferences of Europeans towards tourism 2015” with data from the 28 countries of the European Union (EU). A predictive model was obtained for the tourist satisfaction, through the discovery of existing patterns in the process of the tourist travel, using DM techniques on the data referred above. The definition of an explanatory model allowed to obtain useful knowledge for tourism agencies, enabling the development of marketing strategies according to the tourist profile and ensuring development of promotional messages for products and experiences, ensuring that correct assumptions are made about their customers. |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-11-19T00:00:00Z 2016-11-19 2016-09 2017-05-05T14:02:25Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/masterThesis |
format |
masterThesis |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/13232 TID:201608200 |
url |
http://hdl.handle.net/10071/13232 |
identifier_str_mv |
TID:201608200 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/octet-stream |
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 instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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 |
repository.mail.fl_str_mv |
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1799134717960781824 |