[HTML][HTML] Forecast reconciliation: A review
Collections of time series formed via aggregation are prevalent in many fields. These are
commonly referred to as hierarchical time series and may be constructed cross-sectionally …
commonly referred to as hierarchical time series and may be constructed cross-sectionally …
Present and prospective research themes for tourism and hospitality education post-COVID19: A bibliometric analysis
Academic research in tourism and hospitality sector adds value directly to the way the
industry grows and develops. Scholars in this area struggle with the pressures to publish in …
industry grows and develops. Scholars in this area struggle with the pressures to publish in …
[HTML][HTML] Economic impacts of COVID-19 on the tourism sector in Tanzania
The worldwide COVID-19 pandemic has affected the tourism sector by closing borders,
reducing both the transportation of tourists and tourist demand. Develo** countries, such …
reducing both the transportation of tourists and tourist demand. Develo** countries, such …
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 …
Tourism forecasting with granular sentiment analysis
Generic sentiment calculations cannot fully reflect tourists' preferences, whereas fine-
grained sentiment analysis identifies tourists' precise attitudes. This study forecasted visitor …
grained sentiment analysis identifies tourists' precise attitudes. This study forecasted visitor …
Tourism demand forecasting with spatiotemporal features
C Li, W Zheng, P Ge - Annals of Tourism Research, 2022 - Elsevier
Tourism demand forecasting is a crucial prerequisite for effective and efficient tourism
management. This study develops a novel model based on deep learning methods for …
management. This study develops a novel model based on deep learning methods for …
Application of machine learning to cluster hotel booking curves for hotel demand forecasting
Accurate demand forecasting is integral for data-driven revenue management decisions of
hotels, but an unprecedented demand environment caused by COVID-19 pandemic has …
hotels, but an unprecedented demand environment caused by COVID-19 pandemic has …
Forecasting hotel demand for revenue management using machine learning regression methods
This paper compares the accuracy of a set of 22 methods for short-term hotel demand
forecasting for lead times up to 14 days ahead. Machine learning models are compared with …
forecasting for lead times up to 14 days ahead. Machine learning models are compared with …
Tourism recovery amid COVID-19: The case of Lombardy, Italy
Travel restrictions and social distancing imposed to curb the spread of the new coronavirus
have been strongly hitting tourism since March 2020. Tourism forecasting literature …
have been strongly hitting tourism since March 2020. Tourism forecasting literature …