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Modelação da procura turística: um estudo comparativo entre redes neuronais artificiais e a metodologia de Box-Jenkins

Bibliographic Details
Main Author: Fernandes, Paula Odete
Publication Date: 2008
Other Authors: Teixeira, João Paulo, Ferreira, João José, Azevedo, Susana Garrido
Language: por
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10198/1035
Summary: The present research aims to explore and to evidence the utility of the methodology of Artificial Neural Networks (ANN) in the analysis of tourism demand as an alternative to the Box-Jenkins methodology. The first methodology has arising interest in the economic and business area since several researches have verified that methodology presents a valid alternative to classical methods of forecasting allowing giving answer to situations in which the traditional ones will be of difficult to apply (Thawornwong & Enke, 2004). According to Hill et al. (1996) and Hansen et al. (1999) ANN show capacity to improve the time-series forecasts through of additional information analysis decreasing their dimension and reducing their complexity. For that, each one of the referred methodologies focused in the treatment, analysis and modeling of the tourism time-series: Monthly Guest Nights in Hotels registered between January 1987 to December 2006, since it is one of the variables that better explain the effective tourism demand. The Study was performed for two regions of Portugal: North region and Centre region. Considering the results, and according to the Criteria of MAPE for model evaluation proposed by Lewis (1982), the ANN model presented acceptable statistical qualities and adjustments satisfied. Being so, it is adequate not only for the modelling but also to the prediction of times series, when compared to the model performed by Box- Jenkins methodology. We intended also to evaluate the performance and competiveness of the tourism destinations - North region and Center region of Portugal - by main origin markets and to analyse how it is distributed their portfolio of origin markets for the period of 1997 to 2006. The Market Share Analysis tool proposed by Faulkner (1997) was applied and it was observed an high dependency of the domestic market for both regions.
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spelling Modelação da procura turística: um estudo comparativo entre redes neuronais artificiais e a metodologia de Box-JenkinsArtificial neural networksARIMA modelsTime series forecastsTourism destinationsCompetitivenessMarket shareRedes neuronais artificiaisModelos ARIMAPrevisão de séries temporaisDestinos turísticosCompetitividadeQuotas de mercadoThe present research aims to explore and to evidence the utility of the methodology of Artificial Neural Networks (ANN) in the analysis of tourism demand as an alternative to the Box-Jenkins methodology. The first methodology has arising interest in the economic and business area since several researches have verified that methodology presents a valid alternative to classical methods of forecasting allowing giving answer to situations in which the traditional ones will be of difficult to apply (Thawornwong & Enke, 2004). According to Hill et al. (1996) and Hansen et al. (1999) ANN show capacity to improve the time-series forecasts through of additional information analysis decreasing their dimension and reducing their complexity. For that, each one of the referred methodologies focused in the treatment, analysis and modeling of the tourism time-series: Monthly Guest Nights in Hotels registered between January 1987 to December 2006, since it is one of the variables that better explain the effective tourism demand. The Study was performed for two regions of Portugal: North region and Centre region. Considering the results, and according to the Criteria of MAPE for model evaluation proposed by Lewis (1982), the ANN model presented acceptable statistical qualities and adjustments satisfied. Being so, it is adequate not only for the modelling but also to the prediction of times series, when compared to the model performed by Box- Jenkins methodology. We intended also to evaluate the performance and competiveness of the tourism destinations - North region and Center region of Portugal - by main origin markets and to analyse how it is distributed their portfolio of origin markets for the period of 1997 to 2006. The Market Share Analysis tool proposed by Faulkner (1997) was applied and it was observed an high dependency of the domestic market for both regions.O presente estudo pretende explorar e evidenciar a utilidade da metodologia das Redes Neuronais Artificiais como uma alternativa à metodologia de Box-Jenkins, na análise da procura turística. A primeira metodologia tem vindo a suscitar interesse na área das ciências económicas e empresariais, pois pelos trabalhos de investigação realizados tem-se verificado que a mesma apresenta uma alternativa válida a métodos clássicos de previsão, conseguindo dar resposta a situações que pelos métodos clássicos seriam de difícil tratamento (Thawornwong & Enke, 2004). Hill et al. (1996) e Hansen et al. (1999), referem que as ANN mostram capacidade para melhorar a previsão de séries temporais através da análise de informação adicional, diminuindo a sua dimensão e reduzindo a sua complexidade. Para tal, cada uma das metodologias referidas centrou-se no tratamento, análise e modelação da série temporal de turismo: “Dormidas Mensais nos Estabelecimentos Hoteleiros”, registadas no período de Janeiro de 1987 a Dezembro de 2006, uma vez que é uma das variáveis que melhor traduz a procura efectiva. O estudo foi realizado para as regiões Norte e Centro de Portugal. Os resultados obtidos, e tendo por base a classificação do MAPE proposto por Lewis (1982), revelaram que o modelo obtido, utilizando a metodologia das Redes Neuronais Artificiais, apresentou qualidades estatísticas e de ajustamento satisfatórias evidenciando ser adequado para a modelação e previsão da série de referência, quando comparado com o modelo produzido pela metodologia de Box-Jenkins. Pretendeu-se ainda, com este estudo, avaliar o desempenho e a competitividade dos destinos turísticos - Região Norte e Região Centro, de Portugal - por principais mercados emissores e analisar como se encontra distribuída a sua carteira de mercados emissores, para o período de 1997 a 2005. Utilizou-se para o efeito o instrumento de análise proposto por Faulkner (1997), tendo-se observado uma grande dependência do mercado interno, para ambas as regiões.Universidad de Baja CaliforniaBiblioteca Digital do IPBFernandes, Paula OdeteTeixeira, João PauloFerreira, João JoséAzevedo, Susana Garrido2009-02-05T16:18:24Z20082008-01-01T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersionapplication/pdfhttp://hdl.handle.net/10198/1035porFernandes, Paula O.; Teixeira, João Paulo; Ferreira, João José; Azevedo, Susana Garrido (2008). Modelação da procura turística: um estudo comparativo entre redes neuronais artificiais e a metodologia de Box-Jenkins. In XII Congreso Anual Internacional de Investigación en Ciencias Administrativas. Tijuana, México. ISBN 978-968-9356-02-8info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-02-25T11:54:31Zoai:bibliotecadigital.ipb.pt:10198/1035Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T11:15:48.618762Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Modelação da procura turística: um estudo comparativo entre redes neuronais artificiais e a metodologia de Box-Jenkins
title Modelação da procura turística: um estudo comparativo entre redes neuronais artificiais e a metodologia de Box-Jenkins
spellingShingle Modelação da procura turística: um estudo comparativo entre redes neuronais artificiais e a metodologia de Box-Jenkins
Fernandes, Paula Odete
Artificial neural networks
ARIMA models
Time series forecasts
Tourism destinations
Competitiveness
Market share
Redes neuronais artificiais
Modelos ARIMA
Previsão de séries temporais
Destinos turísticos
Competitividade
Quotas de mercado
title_short Modelação da procura turística: um estudo comparativo entre redes neuronais artificiais e a metodologia de Box-Jenkins
title_full Modelação da procura turística: um estudo comparativo entre redes neuronais artificiais e a metodologia de Box-Jenkins
title_fullStr Modelação da procura turística: um estudo comparativo entre redes neuronais artificiais e a metodologia de Box-Jenkins
title_full_unstemmed Modelação da procura turística: um estudo comparativo entre redes neuronais artificiais e a metodologia de Box-Jenkins
title_sort Modelação da procura turística: um estudo comparativo entre redes neuronais artificiais e a metodologia de Box-Jenkins
author Fernandes, Paula Odete
author_facet Fernandes, Paula Odete
Teixeira, João Paulo
Ferreira, João José
Azevedo, Susana Garrido
author_role author
author2 Teixeira, João Paulo
Ferreira, João José
Azevedo, Susana Garrido
author2_role author
author
author
dc.contributor.none.fl_str_mv Biblioteca Digital do IPB
dc.contributor.author.fl_str_mv Fernandes, Paula Odete
Teixeira, João Paulo
Ferreira, João José
Azevedo, Susana Garrido
dc.subject.por.fl_str_mv Artificial neural networks
ARIMA models
Time series forecasts
Tourism destinations
Competitiveness
Market share
Redes neuronais artificiais
Modelos ARIMA
Previsão de séries temporais
Destinos turísticos
Competitividade
Quotas de mercado
topic Artificial neural networks
ARIMA models
Time series forecasts
Tourism destinations
Competitiveness
Market share
Redes neuronais artificiais
Modelos ARIMA
Previsão de séries temporais
Destinos turísticos
Competitividade
Quotas de mercado
description The present research aims to explore and to evidence the utility of the methodology of Artificial Neural Networks (ANN) in the analysis of tourism demand as an alternative to the Box-Jenkins methodology. The first methodology has arising interest in the economic and business area since several researches have verified that methodology presents a valid alternative to classical methods of forecasting allowing giving answer to situations in which the traditional ones will be of difficult to apply (Thawornwong & Enke, 2004). According to Hill et al. (1996) and Hansen et al. (1999) ANN show capacity to improve the time-series forecasts through of additional information analysis decreasing their dimension and reducing their complexity. For that, each one of the referred methodologies focused in the treatment, analysis and modeling of the tourism time-series: Monthly Guest Nights in Hotels registered between January 1987 to December 2006, since it is one of the variables that better explain the effective tourism demand. The Study was performed for two regions of Portugal: North region and Centre region. Considering the results, and according to the Criteria of MAPE for model evaluation proposed by Lewis (1982), the ANN model presented acceptable statistical qualities and adjustments satisfied. Being so, it is adequate not only for the modelling but also to the prediction of times series, when compared to the model performed by Box- Jenkins methodology. We intended also to evaluate the performance and competiveness of the tourism destinations - North region and Center region of Portugal - by main origin markets and to analyse how it is distributed their portfolio of origin markets for the period of 1997 to 2006. The Market Share Analysis tool proposed by Faulkner (1997) was applied and it was observed an high dependency of the domestic market for both regions.
publishDate 2008
dc.date.none.fl_str_mv 2008
2008-01-01T00:00:00Z
2009-02-05T16:18:24Z
dc.type.driver.fl_str_mv conference object
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10198/1035
url http://hdl.handle.net/10198/1035
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv Fernandes, Paula O.; Teixeira, João Paulo; Ferreira, João José; Azevedo, Susana Garrido (2008). Modelação da procura turística: um estudo comparativo entre redes neuronais artificiais e a metodologia de Box-Jenkins. In XII Congreso Anual Internacional de Investigación en Ciencias Administrativas. Tijuana, México. ISBN 978-968-9356-02-8
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 Universidad de Baja California
publisher.none.fl_str_mv Universidad de Baja California
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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