Estimating Tourist Arrivals by User Generated Content Volume in Periods of Extraordinary Demand Fluctuations

Abstract In extraordinary situations, like the Covid-19 pandemic, irregular demand fluctuations can hardly be predicted by traditional forecasting approaches. Even current extent of decline is typically unknown since tourism statistics are only available with a time delay. This study presents an approach to benefit from user generated content (UGC) in form online reviews TripAdvisor as input estimate near real-time. The builds on additive series component model and linear regression tourist arrivals. Results indicate that proposed outperforms seasonal naïve when applied period caused crisis, Covid-19. further enables real-time monitoring benchmarking business times fluctuations.