Peer-to-Peer TourismTourists’ Profile Estimation through Artificial Neural Networks

  1. Salvador Moral-Cuadra 1
  2. Miguel Ángel Solano-Sánchez 2
  3. Tomás López-Guzmán 2
  4. Antonio Menor-Campos 2
  1. 1 Universidad de Granada
    info

    Universidad de Granada

    Granada, España

    ROR https://ror.org/04njjy449

  2. 2 Universidad de Córdoba
    info

    Universidad de Córdoba

    Córdoba, España

    ROR https://ror.org/05yc77b46

Revue:
Journal of Theoretical and Applied Electronic Commerce Research

ISSN: 0718-1876

Année de publication: 2021

Volumen: 16

Número: 4

Pages: 1120-1135

Type: Article

DOI: 10.3390/JTAER16040063 DIALNET GOOGLE SCHOLAR lock_openAccès ouvert editor

D'autres publications dans: Journal of Theoretical and Applied Electronic Commerce Research

Résumé

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 “cultural-tourism” 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.