Platform data in residential tourism
Description
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.
Resources
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Description |
Link |
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53 |
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https://statbel.fgov.be/en/themes/datalab/platform-data-residential-tourism |
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53 |
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https://statbel.fgov.be/nl/themas/datalab/platformdata-het-verblijfstoerisme |
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53 |
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https://statbel.fgov.be/fr/themes/datalab/donnees-des-plateformes-dans-le-secteur-du-tourisme-residentiel |