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

The expansion of holiday rentals’ worldwide makes it relevant to confirm what are the determinants of these accommodations’ daily rates. This research aims to compare two models on estimating holiday rentals’ daily rate through variables that influence it; using artificial neural networks and hedonic pricing method, with the same cross-sectional dataset and variables with data obtained from Booking.com listings from Seville (Spain), a ‘cultural tourism’ large European city. Artificial neural networks estimations adapt better than the hedonic pricing method due to non-linear relations involved, although hedonic estimators have a clearer economic interpretation. Variables related to size, location and amenities appear as the most relevant in the models, including also seasonal and special events factors. The models presented, not only help to clarify these variables but also allow estimating a rental price congruent with the characteristics of the dwelling and season, being useful as an objective valuation method for the main agents of the accommodation sector: Owners, clients and peer-to-peer platforms. This study wants to highlight the convenience of using Booking.com listings as the main data source, as two variables presented as relevant for the models (size and location) are not available in other peer-to-peer platforms like Airbnb

The tourist apartments sector. Valuation methods

Estos últimos años han supuesto un cambio de paradigma en el sector de alojamientos turísticos. Frente a los convencionales, surgen desde la economía colaborativa nuevos tipos caracterizados como alquileres turísticos. Factores como el auge de internet han permitido a las plataformas peer-to-peer (P2P) como Airbnb o Booking.com, reunir a potenciales clientes y propietarios de estos nuevos tipos de alojamientos de forma masiva. Todo ello revela un interés en la investigación de este nuevo fenómeno, no sólo desde el punto de vista de la incidencia en el sector de alojamientos turísticos, sino también desde los criterios que determinan la estimación del precio de la estancia. Si bien constan numerosos estudios previos acerca de valoración inmobiliaria y de estancias en establecimientos hoteleros, aún son escasos los trabajos referidos a estas nuevas formas de alojamiento, debido a su reciente eclosión como fenómeno. Es por ello que este trabajo tiene como primer objetivo general analizar las causas del crecimiento, composición y consecuencias del alquiler turístico bajo múltiples prismas (internacional, nacional, regional, urbano, etc.). Como segundo, descubrir cuáles son los determinantes de valoración de los alquileres turísticos, para elaborar modelos de estimación del precio diario de la estancia en apartamentos turísticos (AT), viviendas con fines turísticos (VFT) y su conjunto (AT+VFT) mediante el método de precios hedónicos (MPH), y su posterior comparación con modelos elaborados mediante redes neuronales artificiales (RNA), tomando como ámbito de estudio una ciudad referente del turismo internacional en la que el fenómeno del alquiler turístico presenta una fuerte incidencia como Sevilla y utilizando Booking.com como principal fuente de datos. Como objetivos específicos, se presentan analizar la incidencia del fenómeno Airbnb desde un punto de vista bibliométrico, conocer cuáles son los portales web P2P más influyentes a nivel nacional para un posterior análisis de los mismos, así como descubrir las principales causas de éxito y dificultades afrontadas por los alquileres turísticos desde un punto de vista empresarial mediante entrevistas en profundidad a un gerente de AT y a un propietario de varias VFT, respectivamente. Para ello, el presente trabajo se estructura describiendo un análisis del fenómeno a nivel internacional (Capítulo 1), nacional (Capítulo 2), regional andaluz (Capítulo 3), urbano para la ciudad objeto de estudio (Capítulo 4), una revisión de la literatura referente a los métodos de valoración inmobiliarios y de alojamientos turísticos (Capítulo 5), las especificaciones y el análisis de la base de datos obtenida (Capítulo 6), los modelos obtenidos mediante el MPH y RNA así como su comparación (Capítulo 7), los casos de emprendimiento en AT y VFT (Capítulo 8) y, finalmente, las conclusiones extraídas.The recent years have brought a paradigm shift in the tourist accommodation sector. Compared to conventional ones, new types characterized as holiday rentals arise from the sharing economy. Factors such as the rise of the Internet have allowed peer-to-peer (P2P) platforms such as Airbnb or Booking.com making that potential clients and owners of these new types of accommodation massively bumping into. That reveals an interest in the research of this new phenomenon, not only approaching from the incidence in the tourist accommodation sector, but also from the criteria that determine the estimation of the holiday rentals’ daily rate. Although there are several previous studies on real estate valuation and hotel’s daily rates estimations, the works referred to these new forms of accommodation are still scarce, due to their recent appearance. Therefore, the present work has as its first main aim to analyse the causes of growth, composition and consequences of holiday rentals phenomenon under various approaches (international, national, regional, urban, etc.). As a second, discover what are the holiday rentals’ valuation determinants, in order to develop models for estimating the daily rate in this accommodation types, legally defined as apartamentos turísticos (AT) (i.e. complex or sets of apartments), viviendas con fines turísticos (VFT) (i.e. touristic dwellings) and its combination (AT+VFT) using the hedonic pricing method (referred as MPH during the present study) and its subsequent comparison with other models based on artificial neural networks (referred as RNA during the present study), selecting as a research field an international tourism baseline city where the holiday rentals phenomenon has experimented a strong impact as Seville and using Booking.com as the main data source. As specific aims, it is presented the incidence analysis of the Airbnb phenomenon from a bibliometric approach, the research on what are the most influential Spanish P2P webs regarding tourist accommodation for a later analysis of them, as well as to discover the main reasons of success and difficulties faced for holiday rentals from a business approach through in-depth interviews with an AT manager and an owner of various VFTs, respectively. To achieve this aims, the present work is structured describing an analysis of the phenomenon at international (Capítulo 1), Spanish (Capítulo 2), Andalusian (Capítulo 3), and urban for the city under study (Capítulo 4) approaches, a literature review regarding real estate and tourist accommodation valuation methodologies (Capítulo 5), the dataset analysis and its specifications (Capítulo 6), the models obtained by MPH and RNA as well as their comparison (Capítulo 7), the entrepreneurship’s cases in AT and VFT (Capítulo 8) and, finally, the conclusions drawn

Holiday rentals in cultural tourism destinations: a comparison of booking.com-based daily rate estimation for Seville and Porto

Multiple variables determine holiday rentals’ price composition in cultural tourism destinations. This study sought, first, to test a model including the variables with the greatest impact on tourism accommodations’ prices in these destinations and, second, to demonstrate the proposed model’s applicability to cultural city destinations by identifying the adaptations needed to apply it to different contexts. Two cities were selected for the model application—Seville in Spain and Porto in Portugal—both of which are located in different countries and are well-known cultural tourism destinations. The data were extracted from Booking.com because this accommodations platform has adapted its offer to the sharing economy, becoming one of the most important players in the market, and because research on holiday rentals using data from Booking.com is scarce. The results show that the variables used are relevant and highlight the adaptations necessary for specific cultural tourism destinations, thereby indicating that the model can be applied to all cultural tourism destinations. The proposed approach can help holiday rental managers select the correct tools for determining their accommodation units’ daily rates according to their product and marketing context’s characteristics.info:eu-repo/semantics/publishedVersio

Estimating Optimal Military Spending Policy in DSGE Model: Empirical vs Theoretical Approach

193-196Public spending on defense has become one of the most recent and complex research topics in macroeconomic policy analysis, which affects both economic growth and the welfare of society. Literature demands works that address the optimal calculation of military spending. This paper tries to respond to the estimation approach used to calculate military spending. Both a DSGE model (theoretical approach), a VAR model (empirical approach) and a DSGE-VAR model (combined approach) are developed. Our results indicate that the DSGE-VAR model offers the most robust estimates with minor deviations, closely followed by the DSGE model

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

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.info:eu-repo/semantics/publishedVersio

Bullying in Adolescents Practising Sport: A Structural Model Approach

This article aims to analyse the relationship between the bullying aggressor and bullying victim profile related to practising or not practising sport in adolescents living in southern Spain. The research includes male and female participants aged between 12 and 16 years in different secondary schools in the provinces of Andalusia, Ceuta and Melilla in the period between February 2022 and June 2022. The study aims to extend the existing scientific, theoretical and empirical knowledge on the influence of playing sport or not on disruptive bullying attitudes in adolescents. To this end, two initial hypotheses were designed; the first hypothesises that bullying victim behaviours are associated with future bullying aggressor behaviours when practising sport; and the second states that victim behaviours are associated with future bullying aggressor behaviours when not practising sport. To verify them, SPSS software was used for the preliminary analysis of the scale and sociodemographic profile. Additionally, the study is based on structural equation modelling methodology and variance-based methods employing SmartPLS v3.3 software. The results show the importance of sport or physical activity to reduce the chances of carrying out bullying actions on other peers and/or classmates. Therefore, it is considered necessary to prevent bullying in the classroom by implementing sports intervention programmes in educational centres

Peer-to-Peer Tourism: Tourists’ Profile Estimation through Artificial Neural Networks

Peer-to-peer tourism is one of the great global trends that is transforming the tourism sector, introducing several changes in many aspects of tourism, such as the way of travelling, staying or living the experience in the destination. This research aims to determine the relationship between the sociodemographic characteristics of tourists interested in peer-to-peer accommodation and the importance they give to various motivational factors about this type of tourism in a “culturaltourism” city. The methodology used in this research is an artificial neural network of the multilayer perceptron type to estimate a sociodemographic profile of the peer-to-peer accommodation tourist user based on predetermined input values consisting of the answers to the Likert-type questions previously carried out using a questionnaire. Thus, the model developed, through a customized set of answers to these questions, allows the presentation of a “composite picture” of a peer-to-peer tourist based on sociodemographic characteristics. This function is especially interesting for adapting the peer-to-peer hosting offer according to the preferences of potential users

Segmentation of Foreign Tourists Based on Emotional Perception—The Case of Granada, Spain

The aim of the present research was to present the typologies of foreign tourists in the city of Granada, Spain, based on their emotional perception and interest in culture using different fieldwork methods. The main obtained results determine four segments of tourists: cultural, alternative, heritage, and emotional. The results also show that, in addition to cultural reasons, tourists presented other types of attractions that encouraged them to visit the city. Regarding the satisfaction variable, the obtained results show that satisfaction increased when cultural reasons had a strong influence on the tourists’ choice of destination. This research contributes to identifying the characteristics of the different visitor segments, with the aim of designing tourist and cultural products that can more efficiently satisfy their needs. This will have a positive impact on the economic development of the city of Granada with an increase in tourist spending, which will lead to an increase in employment and urban development

Ten Years of Airbnb Phenomenon Research: A Bibliometric Approach (2010–2019)

The interest in the Airbnb phenomenon is represented in the fast growth of publications indexed in the Web of Science (WoS) since the research inception of this topic in 2010. However, there are no studies that analyze the incidence of this phenomenon from a bibliometric approach using WoS. Therefore, this paper aims to quantify the incidence and composition of the Airbnb phenomenon through bibliometrics taken it as a data source. To achieve this aim, the WoS statistical instruments and the bibliometric tool VOSviewer are used. The results obtained, such as the number of articles and citations per year, the main categories of these articles, the nationalities of the authors, the most productive institutions, the sources and authors in terms of publications, and the H-Core of the most cited articles, are presented. Finally, concept maps are exposed, representing the relatedness of co-authorship and co-citation among authors, as well as the co-occurrence of the keywords in the articles analyzed. Satisfaction, trust, and innovation appear as the main research lines. This paper can be useful for academics and professionals, giving them a holistic overview of the topic, identifying new research areas, or as an objective manner to literary review approaches