Dataset for holiday rentals’ daily rate pricing in a cultural tourism destination

Abstract

This data article describes a holiday rental dataset from a medium-size cultural city destination. Daily rate and variables related to location, size, amenities, rating, and seasonality are highlighted as the main features. The data was extracted from Booking.com, legal registration of the accommodation (RTA) and Google Maps, among other sources. This dataset contains data from 665 holiday rentals offered as entire flat (rent per room was discarded), with a total of 1623 cases and 28 variables considered. Regarding data extraction, RTA is ordered by registration number, which is taken and, through a Google search with the following structure: “apartment registration no. + Booking + Seville”, the holiday rental profile in Booking.com is found. Then, it is verified that both the address of the accommodation and the registration number match in RTA and Booking.com, proceeding with data extraction to a Microsoft Excel's file. Google Maps is used to determine the minutes spent walking from the accommodation to the spot of maximum tourist interest of the city. A price index based on the average price per square meter of real estate per district is also incorporated to the dataset, as well as a visual appeal rating made by the authors of every holiday rental based on its Booking.com photos profile. Only cases with complete data were considered. A statistics summary of all variables of the data collected is presented. This dataset can be used to develop an estimation model of daily prices of stay in holiday rentals through predetermined variables. Econometrics methodologies applied to this dataset can also allow testing which variables included affecting the composition of holiday rentals' daily rates and which not, as well as determining their respective influence on daily rates.

Valuation Models for Holiday Rentals’ Daily Rates: Price Composition Based on Booking.com

“…However, the previously established hypothesis about the district index was rejected in the current research. The average real estate price per m 2 in the districts in which the accommodations were located did not have a decisive impact on daily rates in Seville, as more than 80% of the dataset cases were concentrated in "Casco Antiguo" (the old town district) (see [50]). Other independent variables such as views, courtyard and number of photos, which were relevant in [44], also proved to be irrelevant in the present research.…”

“…In some cases, TAs include common areas (as in hotel establishments) with a reception, lounge, restaurant and/or swimming pool. Data for the study were based on Solano et al [50]. All VFTs registered as offering the full modality (i.e., the entire flat) in Seville were taken as a reference point for the total research population.…”

“…The per room modality was excluded from the sample due to the distortion that could occur in the models if different services were compared. VFTs regis- Data for the study were based on Solano et al [50]. All VFTs registered as offering the full modality (i.e., the entire flat) in Seville were taken as a reference point for the total research population.…”

Tourism Economics

“…However, the cited study included Booking.com's complete offer of hotels, hostels and apartments, so the focus was not exclusively on the sharing economy. Santos et al (2021) subsequently proposed a new HPM model for Booking.com holiday rentals using an extensive set of variables developed by Solano- Sánchez et al (2019) that were also used in the present comparative study (see Table 1).…”

Holiday Rentals in Cultural Tourism Destinations: A Comparison of Booking.com-Based Daily Rate Estimation for Seville and Porto

“…However, the cited study included Booking.com's complete offer of hotels, hostels and apartments, so the focus was not exclusively on the sharing economy. Santos et al (2021) subsequently proposed a new HPM model for Booking.com holiday rentals using an extensive set of variables developed by Solano-Sánchez et al (2019) that were also used in the present comparative study (see Table 1).…”