東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

FindBook

Google Book

Amazon

博客來

Analysing and Forecasting Tourism Demand in Vietnam with Artificial Neural Networks.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Analysing and Forecasting Tourism Demand in Vietnam with Artificial Neural Networks./
作者:	Quyen, Nguyen Le.
面頁冊數:	1 online resource (79 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-06, Section: A.
Contained By:	Dissertations Abstracts International84-06A.
標題:	Neural networks. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30204521click for full text (PQDT)
ISBN:	9798358422490

Analysing and Forecasting Tourism Demand in Vietnam with Artificial Neural Networks.
Quyen, Nguyen Le.

Analysing and Forecasting Tourism Demand in Vietnam with Artificial Neural Networks. - 1 online resource (79 pages)

Source: Dissertations Abstracts International, Volume: 84-06, Section: A.

Thesis (M.M.)--Instituto Politecnico de Braganca (Portugal), 2022.

Includes bibliographical references

Vietnam has experienced a tourism boom over the last decade with more than 18 million international tourists in 2019, compared to 1.5 million twenty-five years ago. Tourist spending has translated into rising employment and income for the tourism sector, making it the key driver to the socio-economic development of the country. Facing the COVID-19 pandemic, Vietnam´s tourism has suffered extreme economic losses. However, the number of international tourists is expected to reach the pre-pandemic levels in the next few years after the COVID-19 pandemic subsides.Forecasting tourism demand plays an essential role in predicting future economic development. Accurate predictions of tourism volume would facilitate decision-makers and managers to optimize resource allocation as well as to balance environmental and economic aspects. Various methods to predict tourism demand have been introduced over the years. One of the most prominent approaches is Artificial Neural Network (ANN) thanks to its capability to handle highly volatile and non-linear data. Given the significance of tourism to the economy, a precise forecast of tourism demand would help to foresee the potential economic growth of Vietnam.First, the research aims to analyse Vietnam´s tourism sector with a special focus on international tourists. Next, several ANN architectures are experimented with the datasets from 2008 to 2020, to predict the monthly number of international tourists traveling to Vietnam including COVID-19 lockdown periods. The results showed that with the correct selection of ANN architectures and data from the previous 12 months, the best ANN models can forecast the number of international tourists for next month with a MAPE between 7.9% and 9.2%. As the method proves its forecasting accuracy, it would serve as a valuable tool for Vietnam´s policymakers and firm managers to make better investment and strategic decisions to promote tourism after the COVID-19 situation.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2023

Mode of access: World Wide Web

ISBN: 9798358422490Subjects--Topical Terms:

677449
Neural networks.
Index Terms--Genre/Form:

542853
Electronic books.

Analysing and Forecasting Tourism Demand in Vietnam with Artificial Neural Networks.
LDR:05443nmm a2200361K 4500 001 2355458
005 20230512095521.5
006 m o d
007 cr mn ---uuuuu
008 241011s2022 xx obm 000 0 eng d
020 $a 9798358422490
035 $a (MiAaPQ)AAI30204521
035 $a (MiAaPQ)Portugal1019825039
035 $a AAI30204521
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Quyen, Nguyen Le. $3 3695883
245 1 0 $a Analysing and Forecasting Tourism Demand in Vietnam with Artificial Neural Networks.
264 0 $c 2022
300 $a 1 online resource (79 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 84-06, Section: A.
500 $a Advisor: Fernandes, Paula Odete ; Teixeira, Joao Paulo.
502 $a Thesis (M.M.)--Instituto Politecnico de Braganca (Portugal), 2022.
504 $a Includes bibliographical references
520 $a Vietnam has experienced a tourism boom over the last decade with more than 18 million international tourists in 2019, compared to 1.5 million twenty-five years ago. Tourist spending has translated into rising employment and income for the tourism sector, making it the key driver to the socio-economic development of the country. Facing the COVID-19 pandemic, Vietnam´s tourism has suffered extreme economic losses. However, the number of international tourists is expected to reach the pre-pandemic levels in the next few years after the COVID-19 pandemic subsides.Forecasting tourism demand plays an essential role in predicting future economic development. Accurate predictions of tourism volume would facilitate decision-makers and managers to optimize resource allocation as well as to balance environmental and economic aspects. Various methods to predict tourism demand have been introduced over the years. One of the most prominent approaches is Artificial Neural Network (ANN) thanks to its capability to handle highly volatile and non-linear data. Given the significance of tourism to the economy, a precise forecast of tourism demand would help to foresee the potential economic growth of Vietnam.First, the research aims to analyse Vietnam´s tourism sector with a special focus on international tourists. Next, several ANN architectures are experimented with the datasets from 2008 to 2020, to predict the monthly number of international tourists traveling to Vietnam including COVID-19 lockdown periods. The results showed that with the correct selection of ANN architectures and data from the previous 12 months, the best ANN models can forecast the number of international tourists for next month with a MAPE between 7.9% and 9.2%. As the method proves its forecasting accuracy, it would serve as a valuable tool for Vietnam´s policymakers and firm managers to make better investment and strategic decisions to promote tourism after the COVID-19 situation.
520 $a O Vietname conheceu um boom turistico na ultima decada com mais de 18 milhoes de turistas internacionais em 2019, em comparacao com 1,5 milhoes ha vinte e cinco anos. As despesas turisticas traduziram-se num aumento do emprego e de receitas no sector do turismo, tornando-o no principal motor do desenvolvimento socioeconomico do pais. Perante a pandemia da COVID-19, o turismo no Vietname sofreu perdas economicas extremas. Porem, espera-se que o numero de turistas internacionais, pos pandemia da COVID-19, atinja os niveis pre-pandemicos nos proximos anos.A previsao da procura turistica desempenha um papel essencial na previsao do desenvolvimento economico futuro. Previsoes precisas facilitariam os decisores e gestores a otimizar a afetacao de recursos, bem como o equilibrio entre os aspetos ambientais e economicos. Varios metodos para prever a procura turistica tem sido introduzidos ao longo dos anos. Uma das abordagens mais proeminentes assenta na metodologia das Redes Neuronais Artificiais (ANN) dada a sua capacidade de lidar com dados volateis e nao lineares. Dada a importancia do turismo para a economia, uma previsao precisa da procura turistica ajudaria a prever o crescimento economico potencial do Vietname.Em primeiro lugar, a investigacao tem por objetivo analisar o sector turistico do Vietname com especial incidencia nos turistas internacionais. Em seguida, varias arquiteturas de ANN sao experimentadas com um conjunto de dados de 2008 a 2020, para prever o numero mensal de turistas internacionais que se deslocam ao Vietname, incluindo os periodos de confinamento relacionados com a COVID-19. Os resultados mostraram, com a correta selecao de arquiteturas ANN e dados dos 12 meses anteriores, os melhores modelos ANN podem prever o numero de turistas internacionais para o proximo mes com uma MAPE entre 7,9% e 9,2%. Como o metodo evidenciou a sua precisao de previsao, o mesmo pode servir como uma ferramenta valiosa para os decisores politicos e gestores de empresas do Vietname, pois ira permitir fazer melhores investimentos e tomarem decisoes estrategicas para promover o turismo pos situacao da COVID-19.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2023
538 $a Mode of access: World Wide Web
650 4 $a Neural networks. $3 677449
650 4 $a Southeast Asian studies. $3 3344898
655 7 $a Electronic books. $2 lcsh $3 542853
690 $a 0800
690 $a 0501
690 $a 0222
710 2 $a ProQuest Information and Learning Co. $3 783688
710 2 $a Instituto Politecnico de Braganca (Portugal). $3 3695884
773 0 $t Dissertations Abstracts International $g 84-06A.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30204521 $z click for full text (PQDT)