This study reviews 211 key papers published between 1968 and 2018, for a better
understanding of how the methods of tourism demand forecasting have evolved over time …

This study reviewed 72 studies in tourism demand forecasting during the period from 2008
to 2017. Forecasting models are reviewed in three categories: econometric, time series and …

This paper is to produce different scenarios in forecasts for international tourism demand, in
light of the COVID-19 pandemic. By implementing two distinct methodologies (the Long …

This paper investigates the expected results of the current COVID-19 outbreak to arrivals of
Chinese tourists to the USA and Australia. The growing market share of Chinese tourism …

The choice of the most promising algorithm to model and predict a particular phenomenon is
one of the most prominent activities of the temporal data forecasting. Forecasting (or …

Generic sentiment calculations cannot fully reflect tourists' preferences, whereas fine-
grained sentiment analysis identifies tourists' precise attitudes. This study forecasted visitor …

Timely tourist demand forecasting is essential for the operation of the tourism industry;
however, most studies focus on quarterly-or monthly-basis data, whose low-frequency …

Singular spectrum analysis (SSA) is a well-known methodology for analysis and forecasting
of time series. Since quite recently, SSA was also used to analyze digital images and other …

Forecasting tourism demand has important implications for both policy makers and
companies operating in the tourism industry. In this research, we applied methods and tools …

Tourism planners rely on accurate demand forecasting. However, despite numerous
advancements, crucial methodological issues remain unaddressed. This study aims to …