Portuguese automotive aftermarket forecast through time-series analysis and modelling

Bibliographic Details
Main Author: Machado, Pedro Maria De Castro Lopes E Figueira
Publication Date: 2021
Format: Master thesis
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/123452
Summary: The composition of the future car fleet is interesting tomany. The automotive aftermarket’s concerns rely on the diminishment of profitable segments and the growth of not-so-maintenance-intensive electric vehicles. This project develops time-series forecasting models, namely ARIMA models, predicting the Portuguese car fleet in 2030, which declines 11.6%, to around 5.4 million vehicles. Upon this knowledge, the consequences of the share of electric vehicles rising up to 16.7% are assessed, along with other external factors’, under three scenarios. One factor seemingly highly influential is car sharing services, as the vehicle segment typically associated with it is predicted to grow 65%.
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spelling Portuguese automotive aftermarket forecast through time-series analysis and modellingFleet modellingAutomotive aftermarketForecastArimaDomínio/Área Científica::Ciências Sociais::Economia e GestãoThe composition of the future car fleet is interesting tomany. The automotive aftermarket’s concerns rely on the diminishment of profitable segments and the growth of not-so-maintenance-intensive electric vehicles. This project develops time-series forecasting models, namely ARIMA models, predicting the Portuguese car fleet in 2030, which declines 11.6%, to around 5.4 million vehicles. Upon this knowledge, the consequences of the share of electric vehicles rising up to 16.7% are assessed, along with other external factors’, under three scenarios. One factor seemingly highly influential is car sharing services, as the vehicle segment typically associated with it is predicted to grow 65%.Santos, CarlosRUNMachado, Pedro Maria De Castro Lopes E Figueira2021-08-31T10:37:30Z2021-01-152021-01-042021-01-15T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10362/123452TID:202742318enginfo: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:RCAAP2024-05-22T17:55:26Zoai:run.unl.pt:10362/123452Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:26:26.819495Repositórios 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 Portuguese automotive aftermarket forecast through time-series analysis and modelling
title Portuguese automotive aftermarket forecast through time-series analysis and modelling
spellingShingle Portuguese automotive aftermarket forecast through time-series analysis and modelling
Machado, Pedro Maria De Castro Lopes E Figueira
Fleet modelling
Automotive aftermarket
Forecast
Arima
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
title_short Portuguese automotive aftermarket forecast through time-series analysis and modelling
title_full Portuguese automotive aftermarket forecast through time-series analysis and modelling
title_fullStr Portuguese automotive aftermarket forecast through time-series analysis and modelling
title_full_unstemmed Portuguese automotive aftermarket forecast through time-series analysis and modelling
title_sort Portuguese automotive aftermarket forecast through time-series analysis and modelling
author Machado, Pedro Maria De Castro Lopes E Figueira
author_facet Machado, Pedro Maria De Castro Lopes E Figueira
author_role author
dc.contributor.none.fl_str_mv Santos, Carlos
RUN
dc.contributor.author.fl_str_mv Machado, Pedro Maria De Castro Lopes E Figueira
dc.subject.por.fl_str_mv Fleet modelling
Automotive aftermarket
Forecast
Arima
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
topic Fleet modelling
Automotive aftermarket
Forecast
Arima
Domínio/Área Científica::Ciências Sociais::Economia e Gestão
description The composition of the future car fleet is interesting tomany. The automotive aftermarket’s concerns rely on the diminishment of profitable segments and the growth of not-so-maintenance-intensive electric vehicles. This project develops time-series forecasting models, namely ARIMA models, predicting the Portuguese car fleet in 2030, which declines 11.6%, to around 5.4 million vehicles. Upon this knowledge, the consequences of the share of electric vehicles rising up to 16.7% are assessed, along with other external factors’, under three scenarios. One factor seemingly highly influential is car sharing services, as the vehicle segment typically associated with it is predicted to grow 65%.
publishDate 2021
dc.date.none.fl_str_mv 2021-08-31T10:37:30Z
2021-01-15
2021-01-04
2021-01-15T00:00:00Z
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/10362/123452
TID:202742318
url http://hdl.handle.net/10362/123452
identifier_str_mv TID:202742318
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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