AIRBNB AND ESTIMATING ITS EFFECTS ON THE HOTEL INDUSTRY: THE CASE OF SINGAPORE

Abstract

This dissertation attempts to study the impact of Airbnb’s entry into and its activities in the hotel industry. In particular, the dissertation aims to study the impact that Airbnb has played on the hotel industry in the city of Singapore. Since the entry of Airbnb into the market in 2009, the REVPAR levels have been found to be consistently lower than the forecasted levels. This difference can be attributed to the impact that Airbnb has played, although not entirely, and not with 100% certainty. Therefore, the author hopes that this paper will serve as a comprehensive reference and starting point of many more in-depth and quantitative studies that can be done to observe Airbnb and its interaction with the local hotel industry. This dissertation utilizes time series data of the main hotel performance indicator, REVPAR and models it with four other explanatory variables that successfully accounts for 90.6% of the variances in REVPAR levels. REVPAR levels after Airbnb’s entry (after 2009) were forecasted using data from before Airbnb’s entry (2005 to 2008) and the forecasts were compared to the actual realized levels of REVPAR. The difference is noticeable and significant, suggesting that there are exogenous forces that has caused REVPAR levels to fall below that was expected, to which the author suggests to be attributable to the entry of Airbnb.