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Classical Forecasting of International Tourist Arrivals to Thailand
The objectives of this work are to find the suitable forecasting model and forecasting period of the number of foreign tourists traveling to Thailand. The monthly data is gathered during January 2008 to December 2019 and is divided into two sets. The first set is the data from January 2008 to Decemb...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8934021/ https://www.ncbi.nlm.nih.gov/pubmed/35340991 http://dx.doi.org/10.1007/s44199-022-00041-5 |
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author | Intarapak, Sukanya Supapakorn, Thidaporn Vuthipongse, Witchanee |
author_facet | Intarapak, Sukanya Supapakorn, Thidaporn Vuthipongse, Witchanee |
author_sort | Intarapak, Sukanya |
collection | PubMed |
description | The objectives of this work are to find the suitable forecasting model and forecasting period of the number of foreign tourists traveling to Thailand. The monthly data is gathered during January 2008 to December 2019 and is divided into two sets. The first set is the data from January 2008 to December 2018 for the modelling by the method of decomposition, Holt–Winter’s exponential smoothing method and the Box–Jenkins. The second is the monthly data in 2019 for comparing the performance of the forecasting models via the criteria of the lowest mean absolute percentage error (MAPE) and the root mean square error (RMSE). The results show that, in term of forecasting, the multiplicative decomposition is the most accurate technique for the short-term (3 months) forecasting period with the lowest MAPE and RMSE of 1.04% and 42,054.29 international tourists, respectively. |
format | Online Article Text |
id | pubmed-8934021 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-89340212022-03-21 Classical Forecasting of International Tourist Arrivals to Thailand Intarapak, Sukanya Supapakorn, Thidaporn Vuthipongse, Witchanee J Stat Theory Appl Research Article The objectives of this work are to find the suitable forecasting model and forecasting period of the number of foreign tourists traveling to Thailand. The monthly data is gathered during January 2008 to December 2019 and is divided into two sets. The first set is the data from January 2008 to December 2018 for the modelling by the method of decomposition, Holt–Winter’s exponential smoothing method and the Box–Jenkins. The second is the monthly data in 2019 for comparing the performance of the forecasting models via the criteria of the lowest mean absolute percentage error (MAPE) and the root mean square error (RMSE). The results show that, in term of forecasting, the multiplicative decomposition is the most accurate technique for the short-term (3 months) forecasting period with the lowest MAPE and RMSE of 1.04% and 42,054.29 international tourists, respectively. Springer Netherlands 2022-03-19 2022 /pmc/articles/PMC8934021/ /pubmed/35340991 http://dx.doi.org/10.1007/s44199-022-00041-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Research Article Intarapak, Sukanya Supapakorn, Thidaporn Vuthipongse, Witchanee Classical Forecasting of International Tourist Arrivals to Thailand |
title | Classical Forecasting of International Tourist Arrivals to Thailand |
title_full | Classical Forecasting of International Tourist Arrivals to Thailand |
title_fullStr | Classical Forecasting of International Tourist Arrivals to Thailand |
title_full_unstemmed | Classical Forecasting of International Tourist Arrivals to Thailand |
title_short | Classical Forecasting of International Tourist Arrivals to Thailand |
title_sort | classical forecasting of international tourist arrivals to thailand |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8934021/ https://www.ncbi.nlm.nih.gov/pubmed/35340991 http://dx.doi.org/10.1007/s44199-022-00041-5 |
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