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The good, the bad and the ugly on COVID-19 tourism recovery

This paper is to produce different scenarios in forecasts for international tourism demand, in light of the COVID-19 pandemic. By implementing two distinct methodologies (the Long Short Term Memory neural network and the Generalized Additive Model), based on recent crises, we are able to calculate t...

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Detalles Bibliográficos
Autores principales: Fotiadis, Anestis, Polyzos, Stathis, Huan, Tzung-Cheng T.C.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7832145/
https://www.ncbi.nlm.nih.gov/pubmed/33518847
http://dx.doi.org/10.1016/j.annals.2020.103117
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author Fotiadis, Anestis
Polyzos, Stathis
Huan, Tzung-Cheng T.C.
author_facet Fotiadis, Anestis
Polyzos, Stathis
Huan, Tzung-Cheng T.C.
author_sort Fotiadis, Anestis
collection PubMed
description This paper is to produce different scenarios in forecasts for international tourism demand, in light of the COVID-19 pandemic. By implementing two distinct methodologies (the Long Short Term Memory neural network and the Generalized Additive Model), based on recent crises, we are able to calculate the expected drop in the international tourist arrivals for the next 12 months. We use a rolling-window testing strategy to calculate accuracy metrics and show that even though all models have comparable accuracy, the forecasts produced vary significantly according to the training data set, a finding that should be alarming to researchers. Our results indicate that the drop in tourist arrivals can range between 30.8% and 76.3% and will persist at least until June 2021.
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spelling pubmed-78321452021-01-26 The good, the bad and the ugly on COVID-19 tourism recovery Fotiadis, Anestis Polyzos, Stathis Huan, Tzung-Cheng T.C. Ann Tour Res Research Article This paper is to produce different scenarios in forecasts for international tourism demand, in light of the COVID-19 pandemic. By implementing two distinct methodologies (the Long Short Term Memory neural network and the Generalized Additive Model), based on recent crises, we are able to calculate the expected drop in the international tourist arrivals for the next 12 months. We use a rolling-window testing strategy to calculate accuracy metrics and show that even though all models have comparable accuracy, the forecasts produced vary significantly according to the training data set, a finding that should be alarming to researchers. Our results indicate that the drop in tourist arrivals can range between 30.8% and 76.3% and will persist at least until June 2021. Elsevier Ltd. 2021-03 2020-12-13 /pmc/articles/PMC7832145/ /pubmed/33518847 http://dx.doi.org/10.1016/j.annals.2020.103117 Text en © 2020 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Research Article
Fotiadis, Anestis
Polyzos, Stathis
Huan, Tzung-Cheng T.C.
The good, the bad and the ugly on COVID-19 tourism recovery
title The good, the bad and the ugly on COVID-19 tourism recovery
title_full The good, the bad and the ugly on COVID-19 tourism recovery
title_fullStr The good, the bad and the ugly on COVID-19 tourism recovery
title_full_unstemmed The good, the bad and the ugly on COVID-19 tourism recovery
title_short The good, the bad and the ugly on COVID-19 tourism recovery
title_sort good, the bad and the ugly on covid-19 tourism recovery
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7832145/
https://www.ncbi.nlm.nih.gov/pubmed/33518847
http://dx.doi.org/10.1016/j.annals.2020.103117
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