Tourism Recreation Research · 2020 · 180 citations · 43 references
ManagementBusiness EconomicsTourism ManagementForecastingPredictive AnalyticsTourismPandemic ResponseTourism EconomicsTourism ImpactsTourism Impacts ManagementTourism PlanningTourist FlowsArtificial Intelligence In TourismGlobal Financial CrisisMachine Learning In TourismPandemic Impacts On TourismTourism Demand ModellingTourism ForecastingTourism Revenue Forecasting
The novel coronavirus (COVID-19), which is one of its kind of humanitarian disasters, has affected people and businesses worldwide, triggering a global economic crisis. In this aspect, the tourism sector is not being left behind. The pandemic has not only affected the foreign exchange earnings (FEE) but also affected various regional developments, job opportunities, thereby disrupting the local communities as a whole. As there has been a substantial decline in the arrivals of overseas tourists in India in 2020, the paper aims to predict foreign tourists’ arrival in India and FEE using artificial neural networks (ANN). Furthermore, we analyse the impact of COVID-19 based on four scenarios considering with and without lockdown in terms of loss and gain in FEE. Lastly, the results obtained will help policymakers make necessary strategic and operational decisions, along with maximizing the FEE.
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Tourism demand forecasting: A deep learning approach
Rob Law, Gang Li, Davis Ka Chio Fong et al. · Annals of Tourism Research · 2019 · 443 citations · Full text
Forecasting Chinese tourist volume with search engine data
Xin Yang, Bing Pan, James A. Evans et al. · Tourism Management · 2014 · 431 citations