Statbel DataLab: new statistics, methods and data sources beta version
In 2023, online platforms accounted for 11,074,000 overnight stays in private accommodations
The rental of accommodations offered by private individuals via an online platform is well established, as demonstrated by the latest figures of Statbel, the Belgian statistical office. In 2023, 1,098,000 stays were booked via an online platform, with travellers spending a total of 11,074,000 nights. This is an increase of 17% compared to 2022 and the highest number of stays and nights in accommodations offered by individuals since the launch of this experimental statistic in 2018.
Nearly half of overnight stays took place in the Flemish Region
The Flemish Region registers the largest number of overnight stays in accommodations offered by private individuals and booked via an online platform. In 2023, 48% of all overnight stays took place in the Flemish Region, 32% in the Walloon Region and finally 20% in the Brussels-Capital Region.
Compared to 2022, the Brussels-Capital Region in particular sees a strong increase in overnight stays (+26%). In the Flemish and Walloon Regions, the number of overnight stays increases by 15% and 14% respectively on an annual basis.
Brussels-Capital is the most popular district, Mons registers the largest increase
At district level, Brussels-Capital remains the district with the largest number of overnight stays booked with a private individual via an online platform. Throughout the whole calendar year 2023, 2,207,000 overnight stays took place in the capital. The districts Ostend (983,000 overnight stays), Antwerp (911,000), Bruges (893,000) and Veurne (757,000) complete the top 5. In Wallonia, Verviers has the most overnight stays (744,000) and occupies the sixth place nationwide.
Compared to 2022, the district of Mons registers the strongest percentage increase in the number of overnight stays in private accommodations (+54%). Conversely, the Leuven district is the only one to see a decrease in the number of overnight stays, from 156,000 in 2022 to 141,000 in 2023 (-10%).
Foreigners account for 70% of overnight stays
In 2023, foreign tourists, i.e. travellers whose main residence is abroad, booked 70% of overnight stays in private accommodations. This is an increase of 4 percentage points compared to 2022 and 27 percentage points compared to 2021. Indeed, due to travel restrictions caused by the coronavirus crisis, Belgians accounted for a majority of overnight stays (57%) in 2021. Nevertheless, the share of foreign tourists in 2023 is still below the 2019 figure, as foreign tourists accounted for no less than 77% of overnight stays that year.
Finally, it is also possible to break down the number of overnight stays of foreign tourists by the traveller’s country of origin. This analysis shows that in 2023, the Dutch were, with 22%, the largest group of foreign tourists who booked an accommodation offered by a private individual via an online platform. The Germans (19%) and the French (17%) complete the top 3, and these three countries together account for almost 60% of foreign tourists' overnight stays in private accommodations in 2023.
Compared to 2022, private individuals renting accommodation saw the strongest increase in overnight stays by Australians and Turks. For both countries of origin, the number of overnight stays has doubled (+100%). The number of travellers from the People's Republic of China also experiences a strong rebound in 2023 (+77%), although the number of overnight stays still remains 53% below the pre-COVID level. The number of overnight stays only decreases for three countries of origin compared to 2022. Specifically, these are travellers from Ukraine (-14%), Russia (-13%) and the Czech Republic (-2%).
About these figures
Over the last decade, more and more Belgians booked their holidays on the Internet. But the owners of accommodations also liked to use an online platform to offer an apartment or holiday home for rent.
Due to this increasing success, Statbel, the Belgian statistical office, has been producing since 2018 an experimental statistic on the use of online platforms for the rental of private holiday accommodations. For this, Statbel uses the data it receives via Eurostat from four large platform companies. These four platforms, Airbnb, Booking.com, the Expedia Group and TripAdvisor, provide pseudonymised and aggregated data about all reservations and overnight stays that take place via their platforms on the Belgian territory.
This experimental statistic is limited to the accommodations that are offered by private individuals. Professional accommodation providers, like hotels, are excluded. The statistics on these professional providers are available in the official tourism statistics. More information about this experimental statistic and the data used is available in the tab ‘documents’.
In recent years, various apps have come into use that bring people into contact with each other to exchange goods and services. More and more consumers use an online platform to book a holiday home or have a meal delivered to their home by a bicycle courier. As a result, the economic importance of the sharing economy is growing rapidly.
That is why Statbel, the Belgian statistical office, in close cooperation with Eurostat and other national statistical institutes, is studying how the sharing economy can be integrated into public statistics. However, national statistical institutes face a considerable difficulty when analysing the platform companies. The largest platform companies are multinational players, often managing their activities in Belgium from a foreign head office. These companies are therefore rarely found in the regular business statistics or registers. In order to obtain the required data, national statistical institutes would therefore be obliged to contact all platform companies on a unilateral basis. This was a time-consuming and inefficient process for both the platform companies and the statistical institutes. Therefore, the European Commission decided to take these discussions into its own hands and request the data for all EU Member States via one agreement. These negotiations initially focused on the residential tourism sector and resulted in agreements with the platform companies Airbnb, Booking.com, TripAdvisor and Expedia . In the meantime, these companies have delivered the first data files to Eurostat. Eurostat then divides the microdata into 27 national pseudonymised and aggregated files, so that Statbel receives information on all reservations and overnight stays booked via these four online platforms on the Belgian territory.
With the agreements between the European Commission and the four platform companies, a first, important hurdle has been taken. But the methodological work is only just beginning. Based on the first files, the national statistical institutes and Eurostat still have to develop a harmonised approach to the methodological challenges. In particular, due to the lack of identification data in the microdata of the platform companies, double counting poses a considerable problem. This double counting, whereby an accommodation is contained in at least two different files, is a particular challenge for capacity determination. That is why this information is not included in the experimental statistics.
At the moment the national statistical institutes together with Eurostat are studying which techniques can best be used to solve the methodological problems. Innovative methods such as web scraping are particularly under consideration. Web scraping involves scraping relevant information from websites, which in combination with artificial intelligence is considered the best solution. Concretely, we study the following two approaches:
- text recognition: individuals who offer the same room on several online platforms usually use the same text. By looking for key words, such as the location of the accommodation, the size of the room, available facilities, etc., identical accommodations can be found automatically;
- Photo recognition: this technique automatically compares the photos that are placed with an advertisement in order to identify possible duplicates. However, this technique requires a large computer memory and is therefore rather kept in reserve as an alternative solution.
In time, the intention is to integrate the platform data into recurring statistics. The timing for this depends both on achieving a harmonised approach to the methodological problems and on faster data delivery by the platform companies.