Forecasting Travel Sentiment under the Shock Effects of COVID-19 and Vaccination Using Grey Prediction Models

The tourism industry has become a major contributor to the economic growth. However, because of the outbreak of the coronavirus disease (COVID-19) pandemic, the year 2020 became an extremely difficult year for the global tourism industry. Since the development of the tourism industry depends largely...

Full description

Saved in:
Bibliographic Details
Main Authors: Cheng-Wen Lee, Peiyi Kong
Format: Article
Language:English
Published: Wiley 2023-01-01
Series:Journal of Mathematics
Online Access:http://dx.doi.org/10.1155/2023/7334544
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850120954941800448
author Cheng-Wen Lee
Peiyi Kong
author_facet Cheng-Wen Lee
Peiyi Kong
author_sort Cheng-Wen Lee
collection DOAJ
description The tourism industry has become a major contributor to the economic growth. However, because of the outbreak of the coronavirus disease (COVID-19) pandemic, the year 2020 became an extremely difficult year for the global tourism industry. Since the development of the tourism industry depends largely on changes in travel sentiment, it is important to analyze these changes in light of the pandemic. To determine the development trends of travel sentiment, a hybrid grey prediction model was used to predict travel sentiment globally and in the top 10 destination countries considering the shock effect of COVID-19 and vaccination. The results showed that the grey prediction models integrated with residual modification model contributed to improving the prediction accuracy. In addition, COVID-19 and vaccination were found to have opposite effects on travel sentiment. Based on the predictions, governments should strengthen pandemic prevention and control and administer vaccines to restore travel sentiment and promote tourism recovery.
format Article
id doaj-art-632b565da57040efaef5360e8a23ecde
institution OA Journals
issn 2314-4785
language English
publishDate 2023-01-01
publisher Wiley
record_format Article
series Journal of Mathematics
spelling doaj-art-632b565da57040efaef5360e8a23ecde2025-08-20T02:35:15ZengWileyJournal of Mathematics2314-47852023-01-01202310.1155/2023/7334544Forecasting Travel Sentiment under the Shock Effects of COVID-19 and Vaccination Using Grey Prediction ModelsCheng-Wen Lee0Peiyi Kong1Department of International BusinessPh.D. Program in BusinessThe tourism industry has become a major contributor to the economic growth. However, because of the outbreak of the coronavirus disease (COVID-19) pandemic, the year 2020 became an extremely difficult year for the global tourism industry. Since the development of the tourism industry depends largely on changes in travel sentiment, it is important to analyze these changes in light of the pandemic. To determine the development trends of travel sentiment, a hybrid grey prediction model was used to predict travel sentiment globally and in the top 10 destination countries considering the shock effect of COVID-19 and vaccination. The results showed that the grey prediction models integrated with residual modification model contributed to improving the prediction accuracy. In addition, COVID-19 and vaccination were found to have opposite effects on travel sentiment. Based on the predictions, governments should strengthen pandemic prevention and control and administer vaccines to restore travel sentiment and promote tourism recovery.http://dx.doi.org/10.1155/2023/7334544
spellingShingle Cheng-Wen Lee
Peiyi Kong
Forecasting Travel Sentiment under the Shock Effects of COVID-19 and Vaccination Using Grey Prediction Models
Journal of Mathematics
title Forecasting Travel Sentiment under the Shock Effects of COVID-19 and Vaccination Using Grey Prediction Models
title_full Forecasting Travel Sentiment under the Shock Effects of COVID-19 and Vaccination Using Grey Prediction Models
title_fullStr Forecasting Travel Sentiment under the Shock Effects of COVID-19 and Vaccination Using Grey Prediction Models
title_full_unstemmed Forecasting Travel Sentiment under the Shock Effects of COVID-19 and Vaccination Using Grey Prediction Models
title_short Forecasting Travel Sentiment under the Shock Effects of COVID-19 and Vaccination Using Grey Prediction Models
title_sort forecasting travel sentiment under the shock effects of covid 19 and vaccination using grey prediction models
url http://dx.doi.org/10.1155/2023/7334544
work_keys_str_mv AT chengwenlee forecastingtravelsentimentundertheshockeffectsofcovid19andvaccinationusinggreypredictionmodels
AT peiyikong forecastingtravelsentimentundertheshockeffectsofcovid19andvaccinationusinggreypredictionmodels