Peer-to-Peer Tourism: Tourists’ Profile Estimation through Artificial Neural Networks
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Moral Cuadra, Salvador; Solano Sánchez, Miguel Ángel; López-Guzmán Guzmán, Tomás; Menor Campos, AntonioEditorial
MDPI
Materia
Sharing Economy Collaborative tourism Tourist profile Peer-to-peer accommodation Artificial neural networks Multilayer perceptron
Date
2021Referencia bibliográfica
Moral-Cuadra, S.; Solano-Sánchez, M.Á.; López-Guzmán, T.; Menor-Campos, A. Peer-to-Peer Tourism: Tourists’ Profile Estimation through Artificial Neural Networks. J. Theor. Appl. Electron. Commer. Res. 2021, 16, 1120–1135. https:// doi.org/10.3390/jtaer16040063
Abstract
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.