Tourism Analytics with Price and Room Booking Simulation

This work studies the impact of COVID-19 on tourism in Singapore. Based on the historical data, we apply time series techniques to make a prediction of the passenger numbers without COVID-19. Comparing this value with the actual value, we can easily find that Singapore’s tourism is suffering a significant hit by around 70% due to COVID-19. Combining this massive drop in tourist numbers with travel policies, we find a strong correlation: The policies responded to COVID-19 notably affect the number of flight arrivals and departures. The travel mode also changes: Aviation accounted for the lion’s share in travel mode and resumed gradually. Besides, we analyze the tourists’ characteristics, giving traveler profiles to summarize their features. In the second part, we analyze the hotel industry to provide an enterprise-level perspective. Clearly, the outbreak of COVID-19 has caused a great negative impact on the overall revenue of Singapore’s hotel industry from February to November 2020. We then work on factors that affect hotel performance and find that the decrease in revenue is mainly caused by the substantial drop in the average room price. Based on these findings, we use simulation to prepare and improve responses to the tough time caused by COVID-19. Compared to the hotels with quarantine arrangements and those that without, it is also clear that those with quarantine arrangements will have more bookings, therefore, have better revenue. According to our analysis and simulation, we provide short time advice and long-time advice for the tourism industry and the hotel industry. The feature of this report is that we use multiple analytical skills. We use visualization to give a visual representation of the influence of COVID-19 and related policies. Although we use simulation to provide evidence-based advice for tourism practitioners, our report is still subject to certain limitations that should be addressed. Because we lack the latest data and microdata, we couldn’t make further analysis on other players in tourism industry like travel intermediaries, airlines, and restaurants. Further study can be extended to the simulation model for the whole tourism market for pandemic.