Forecasting tourism demand for Lisbon´s region : a data mining approach

Bibliographic Details
Main Author: Ricardo, Hugo David dos Reis Barbosa
Publication Date: 2018
Format: Master thesis
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/31971
Summary: Project Work presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and Management
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spelling Forecasting tourism demand for Lisbon´s region : a data mining approachForecastTourism demandData miningModelLisbonProject Work presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and ManagementPortugal is conscious that the economic growth and development of its regions can be attained by investing in everything that boosts international tourism activity. The Government Program and the National’s Strategic Plan for Tourism shows that, besides the government, other tourism stakeholders such as passenger transport companies, accommodation establishments, restaurants, recreational businesses, among others, rely on tourism demand indicator’s forecasts to make decisions. Most of tourism demand forecasting models are time-series and econometric based. A real-world system like tourism industry is dynamic, thus not linear. Machine Learning methods have proven to be quite suitable for non-linear modelling. These methods are part of an interdisciplinary field named “Data Mining” which is known by the process of knowledge discovery in databases (KDD). The core drive of this project work is to enhance the available public sources of tourism forecast information and contribute to the tourism stakeholder’s strategy in Portugal. More specifically, to develop a multivariate model to forecast international tourism demand through a Data Mining approach. The model development was constrained to publicly available data and machine learning methods. The forecasted demand variable was the nights spent at tourist accommodation establishments in Lisbon’s region, one of the country’s main foreign tourist destinations. Instead of revealing a best forecasting method or model, as most of previous research sought to, the current project aimed at building the most accurate multivariate forecasting model, based on a database with minimum data assumptions. The objectives were achieved, as the selected model (SMOReg) was successful in generalization capability. The accuracy of the produced forecasts provides some evidence of the reliability of the proposed forecasting model. If institutions and decision makers have information regarding the evolution of the explanatory variables used in this model, the impact on Lisbon’s tourism demand can be assessed, even in case of an emerging recession.Gonçalves, Ivo Carlos PereiraCosta, Ana Cristina Marinho daRUNRicardo, Hugo David dos Reis Barbosa2018-03-07T19:35:47Z2018-02-202018-02-20T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/31971TID:201869780enginfo: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:RCAAP2024-05-22T17:31:13Zoai:run.unl.pt:10362/31971Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:02:19.169406Repositórios 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 Forecasting tourism demand for Lisbon´s region : a data mining approach
title Forecasting tourism demand for Lisbon´s region : a data mining approach
spellingShingle Forecasting tourism demand for Lisbon´s region : a data mining approach
Ricardo, Hugo David dos Reis Barbosa
Forecast
Tourism demand
Data mining
Model
Lisbon
title_short Forecasting tourism demand for Lisbon´s region : a data mining approach
title_full Forecasting tourism demand for Lisbon´s region : a data mining approach
title_fullStr Forecasting tourism demand for Lisbon´s region : a data mining approach
title_full_unstemmed Forecasting tourism demand for Lisbon´s region : a data mining approach
title_sort Forecasting tourism demand for Lisbon´s region : a data mining approach
author Ricardo, Hugo David dos Reis Barbosa
author_facet Ricardo, Hugo David dos Reis Barbosa
author_role author
dc.contributor.none.fl_str_mv Gonçalves, Ivo Carlos Pereira
Costa, Ana Cristina Marinho da
RUN
dc.contributor.author.fl_str_mv Ricardo, Hugo David dos Reis Barbosa
dc.subject.por.fl_str_mv Forecast
Tourism demand
Data mining
Model
Lisbon
topic Forecast
Tourism demand
Data mining
Model
Lisbon
description Project Work presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Information Analysis and Management
publishDate 2018
dc.date.none.fl_str_mv 2018-03-07T19:35:47Z
2018-02-20
2018-02-20T00:00:00Z
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/10362/31971
TID:201869780
url http://hdl.handle.net/10362/31971
identifier_str_mv TID:201869780
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
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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