Tourist accommodation pricing through peer-to-peer platform: evidence from Seville (Spain)

Focal Points in Recent Tourism Price Research

“…The dimension of time is studied in two ways. One is the dimension of seasonal influence (Lévi et al, 2022) or booking date (Arzaghi et al, 2023;Solano-Sánchez et al, 2023;Sánchez-Lozano et al, 2021;Boto-García, 2022a). The study by Mitra (2020a) found no significant price differences due to the weekend effect and concluded that the weekend effect could be essentially location specific.…”

“…Furthermore, Gričar and Bojnec (2019) used a vector autoregressive model to demonstrate the importance of overnight stays by foreign tourists regarding their price behaviour. The second dimension is the time of booking or the booking horizon (Solano-Sánchez et al, 2023;Guizzardi et al, 2022;Sánchez-Lozano et al, 2021).…”

“…Fearne, 2022;Tong & Gunter, 2022;Benítez-Aurioles, 2018;Boto-Garcia & Leoni, 2023;Boto-García, 2022a) as well as the database Booking.com (e.g. Arzaghi et al, 2023;Solano-Sánchez et al, 2023;Sánchez-Lozano et al, 2021). Various online travel agents (Pawlitz & Napierala, 2017) and Tripadvisor (Soler, Gemar, & Guzman-Parra, 2019;Gordan et al, 2023) are also employed to collect data.…”

“…Early research on hedonic pricing research by Rosen (1974) was later followed by a broader application of hedonic pricing in tourism, as shown by Latinopoulus (2018) and . In addition to hedonic analysis, there is some research comparing the ubiquitous application of hedonic pricing research with the alternative method of artificial neural networks, which shows some strengths in pricing research (Solano-Sánchez et al, 2023), complementing hedonic pricing research with clustering method, which allows to classify pricing decisions (Espinet-Rius et al, 2021), quantile regression (Falk et al, 2019), hedonic pricing models with quantile regression (Wang & Nicolau, 2017;Wang et al, 2019), advanced machine learning regression models (Razavi & Israeli, 2019), structural equation method (Toader et al, 2022), multivariate adaptive regression splines (Mitra, 2020a). An artificial intelligence-based framework is already being used in pricing research to predict the prices of Airbnb listings (Ghosh et al, 2023).…”