Abstract

This study examines tourism recovery patterns in the United Arab Emirates (UAE). The study utilized time series modeling to evaluate the monthly tourism data from the Department of Culture and Tourism (DCT) in Abu Dhabi, covering 2019 to Q1 2023. The LJung box test was used to assess the fit of the dataset with the five tourism parameters: Average Length of Stay (ALOS), Number of Guests (NOG), Revenue Per Available Room (RevPAR), Occupancy Rate (OR), and Tourism Revenue (TR). The presence of nonstationarity was discovered, necessitating the use of data differencing to achieve stationarity.

The results indicate that the model fits the data for the five tourism parameters. The study also reveals a significant decline in UAE tourism visitors, with a modest recovery projected in Q4 2021.The findings demonstrate a substantial decline in hotel occupancy rates (OR) during the COVID-19 pandemic, with a slower recovery rate expected for 2023-2024. The average length of stay (ALOS) in hotels is four nights from Q4 2020 to Q1 2022 and is expected to remain the same in 2023-2024. Revenue per available room (REVPAR) is expected to decline in Q1 2023 and peak in Q3 2023. However, projections for 2023 and 2024 show continued growth in tourism revenue (TR) in the UAE.

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