This research aims to determine the relationship between the sociodemographic characteristics (gender, age, income and educational level) of tourists interested in peer-to-peer (P2P) accommodation and the importance that they give to various motivational factors about this type of tourism in a city highlighted for its cultural tourism. The survey developed for this study takes as the basis the city of Córdoba, which is one of the main cultural tourist destinations in Spain due to the fact that it has four inscriptions as a World Heritage Site, among other reasons. The methodology used in this research is based on the use of an artificial neural network (ANN) of the multilayer perceptron type (MLP)—originally developed by Rumelhart et al. [1
]—to estimate a sociodemographic profile of the P2P accommodation tourist user based on predetermined input values consisting of the answers to the Likert-type questions previously made by a questionnaire. Thus, the model developed, through a customized set of answers to these questions, allows to present a "composite picture" of a P2P tourist based on sociodemographic characteristics. In fact, the analysis of travellers who visit a specific destination is essential to its development [2
]. Likewise, the network developed can quantify the variations produced in the Likert scale of each question concerning each of the analysed characteristics of the sociodemographic profile.
The use of neural networks in the tourism sector has been employed mainly in the analysis of the hotel offer, revealing the influence of the characteristics of the accommodation (location, number of stars, number of rooms, percentage of positive comments, etc.) with its respective Revenue Per Available Room (RevPar) [3
]. Thus, one of the main innovations of this research is to apply neural networks to the sociodemographic profile of tourists who visit a certain destination. In fact, neural networks have been used to analyse sociodemographic profiles of respondents, as well as different perceptions and attitudes of workers to their bosses and supervisors, to predict their willingness to use Web 2.0, mobile applications and the so-called “Internet of Things” [4
As stated, the objective of this paper is to stablish the associations among the sociodemographic characteristics of the sample’s profiles with the different motivational aspects about P2P tourism in cultural-tourism cities. Thus, the present study begins with a complete literature review on the topic, followed by the methodology implemented and the results obtained, and finally presents the conclusions and practical implications for the management of different private and public entities at the destination.
The sharing economy is based on the technical and communication capacities of Web 2.0. Its dependence on the technological factor is total: without technology, the information and coordination costs would make the activities that are currently developed in the field of the sharing economy unviable. Within the sharing economy, the two most important sectors are accommodation and transport, accounting for more than 72% of the profits generated and for almost 80% of the transactions carried out. Both sectors are closely related to tourism. The emergence of the sharing economy has led to important economic, social and cultural changes. There has been a paradigm shift: the transformation from a property-based economy to a use-based economy. It does not change the object; it changes the way of consuming. The causes or motives that drive this change are diverse: some of an altruistic nature and others more prosaic and selfish.
The most cited motivations in the field of P2P tourism are economic savings, the search for new experiences, the establishment of bonds with the local population and the recommendations of other tourists. These motivations can be classified into two groups: intrinsic and extrinsic. Among the former would be sustainability and empathy, while the latter would be financial benefits and reputation.
Tourist satisfaction is essential for the survival of a tourist destination. In P2P tourism case, it includes the services and experiences lived during the trip. Its influence lies in how it affects loyalty at the destination: the probability that the tourist would visit the destination again or that he/she would recommend it to other people.
Monetary factors are shown to be the most decisive in the profile of the P2P accommodation tourism user, both from the point of view of the total quantification of the trip expense and the low price as motivation to choose this type of accommodation. However, high income and older profiles imply an intention to spend more, and to give less importance to the low price of accommodation, and, on the contrary, to appreciate the historical heritage of the visited city more. Older age also implies a greater interest in accommodation space (and, thus, in comfort) and a willingness to use this type of accommodation again.
Consequently, and related to the latter, lower age and income make the low price of this type of accommodation more valued, as do the possible increase in the expense available for the trip derived from this saving, looking for destinations affordable to all budgets, and being near to their place of residence. Outside of the purely economic factors, there is a growing interest in those factors related to the use of the Internet among the profiles with a higher educational level in terms of a greater appreciation for accommodation pictures (shared here with the younger profiles), greater availability of offer, the comments of previous users, and even an interest in learning the local language. Finally, through the results obtained, it can be concluded that gender is not a relevant factor concerning the profile of the potential user of P2P accommodation.
The practical contribution of this research consists in, thanks to the ANN developed, the fact that a “composite picture” of the P2P accommodation tourist user can be obtained (specifying their age, gender, income, and educational level) based on the preferences granted to the different input values of the ANN, corresponding to the questions previously asked through the questionnaire. In this way, a customizable collection of answers will result in a specific profile type. This function is especially interesting to adapt the P2P hosting offer according to the preferences of its potential users or to public entities in order to configure its touristic offer based on the profile of the possible visitors.
The main limitation of this research is the time span in which the surveys were carried out; a fuller survey would have required fieldwork for a whole year. In this sense, when the field work is carried out during a full year, some type of different profile could be found, especially due to the fact that holidays in July and August tend to be of a more “family-nature”. Another limitation is the uncertainty of the effects that the actual situation with COVID-19 will have on tourism and, specifically, on peer-to-peer tourism.
Thus, a future line of research will be focused on the current health situation worldwide existing as a result of COVID-19, which acts as a "before and after" in the tourism sector; it is necessary to carry out researches that seek safer alternatives for tourist experiences. In this sense, P2P tourism is presented as a safe and reliable tourist typology, which very possibly will result in its use increasing in future years. Consequently, it is proposed to carry out a parallel study in post-pandemic conditions, in order to detect if there are differences in the profile of the traveller who uses this type of accommodation. Likewise, it should also be analysed whether there is a different profile between the tourist who wishes to stay in a hotel and the tourist who opts for P2P accommodation.