Review of tourism forecasting research with internet data
Internet techniques significantly influence the tourism industry and Internet data have been
used widely used in tourism and hospitality research. However, reviews on the recent …
used widely used in tourism and hospitality research. However, reviews on the recent …
Progress in tourism demand research: Theory and empirics
To explore recent progress in tourism demand research, we comprehensively survey current
studies in the leading tourism and hospitality journals, asking six evaluative questions about …
studies in the leading tourism and hospitality journals, asking six evaluative questions about …
[图书][B] The economics of tourism destinations: Theory and practice
N Vanhove - 2022 - taylorfrancis.com
Revised and updated, the fourth edition of The Economics of Tourism Destinations provides
a guide to the economic aspects of tourism for students and practitioners to decipher the …
a guide to the economic aspects of tourism for students and practitioners to decipher the …
Search query and tourism forecasting during the pandemic: When and where can digital footprints be helpful as predictors?
During the COVID-19 pandemic, daily tourism demand forecasting provides actionable
insight on tourism operations amid intense uncertainty. This paper applies the lasso method …
insight on tourism operations amid intense uncertainty. This paper applies the lasso method …
Can multi-source heterogeneous data improve the forecasting performance of tourist arrivals amid COVID-19? Mixed-data sampling approach
Abstract The coronavirus disease (COVID-19) pandemic has already caused enormous
damage to the global economy and various industries worldwide, especially the tourism …
damage to the global economy and various industries worldwide, especially the tourism …
Machine learning in internet search query selection for tourism forecasting
Prior studies have shown that Internet search query data have great potential to improve
tourism forecasting. As such, selecting the most relevant information from large amounts of …
tourism forecasting. As such, selecting the most relevant information from large amounts of …
Identifying unreliable online hospitality reviews with biased user-given ratings: A deep learning forecasting approach
This study considers the review reliability problem by identifying biased user-given ratings
through rating prediction on the basis of the textual content. Deep learning approaches were …
through rating prediction on the basis of the textual content. Deep learning approaches were …
Forecasting tourism demand with an improved mixed data sampling model
Search query data reflect users' intentions, preferences and interests. The interest in using
such data to forecast tourism demand has increased in recent years. The mixed data …
such data to forecast tourism demand has increased in recent years. The mixed data …
Forecasting hourly attraction tourist volume with search engine and social media data for decision support
Developing a tourism forecasting function in decision support systems has become critical
for businesses and governments. The existing forecasting models considering spatial …
for businesses and governments. The existing forecasting models considering spatial …
Forecasting daily attraction demand using big data from search engines and social media
Purpose This paper aims to compare the forecasting performance of different models with
and without big data predictors from search engines and social media. Design/methodology …
and without big data predictors from search engines and social media. Design/methodology …