Tourism Prediction Analytics

Since the first case of COVID-19 reported in December 2019 at China, the virus has spread all over the world with a very high infection rate and changed people’s lifestyles entirely. As reported by the World Health Organization ( World Health Organization, https://covid19.who.int/ ), the total confirmed cases of COVID-19 worldwide have reached 100 million with 20 million deaths at the beginning of 2021. The large-scale quarantines, travel restrictions, and social-distancing measures result in a sharp fall in consumers and business expenditure, among which the tourism industry suffers the most. Tourism is a major source of revenue and employment in some countries, and accurate tourism demand forecasting is important for strategic and operational decisions. Considering the current climax of the pandemic, it is necessary to measure the losses due to the pandemic so that policies can be redesigned to manage tourism activities. The objective of this study is to have an overview on the impact of the occurrence of COVID-19 on the tourism industry in a country. The historical data about how the pandemic influenced the key metrics like hotel occupancy and tourists’ arrivals are collected and visualized. Then time series prediction models like ARIMA and SARIMA are applied on historical data to formulate how long will the influence of the pandemic lasts and measure the economic losses brought by COVID-19. Based on current data and prediction results, further analysis and suggestions are provided to inform the policymaker and businesses to make the right decision and mitigate the negative influence of COVID-19 on tourism in the country under study.