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.

中文翻译：

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点对点旅游：通过人工神经网络的游客资料估计

点对点旅游是正在改变旅游业的全球趋势之一，在旅游的许多方面都带来了一些变化，例如旅行，在目的地停留或居住的方式。本研究旨在确定对点对点住宿感兴趣的游客的社会人口统计学特征与他们对“文化旅游”城市中此类旅游的各种动机因素的重视程度之间的关系。本研究中使用的方法是多层感知器类型的人工神经网络，用于根据预定输入值（包括先前对使用李克特型问题的答案）估算对等住宿游​​客用户的社会人口统计资料问卷。因此，模型得以发展，通过针对这些问题的定制答案集，可以基于社会人口统计学特征呈现点对点游客的“综合图片”。此功能对于根据潜在用户的喜好调整对等托管服务特别有趣。