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How Personality Traits Can Be Used To Shape Itinerary Factors in Recommender Systems for Young Travellers

Planning an itinerary is a complex activity, which includes the choice of a few places to see, coupled with information on timing, transferring methods and related activities. Intelligent tools such as recommender systems have been used in order to support these activities. While decisions regarding...

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Bibliographic Details
Published in:IEEE access 2023-01, Vol.11, p.1-1
Main Authors: Cena, Federica, Console, Luca, Likavec, Silvia, Micheli, Marta, Vernero, Fabiana
Format: Article
Language:English
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Summary:Planning an itinerary is a complex activity, which includes the choice of a few places to see, coupled with information on timing, transferring methods and related activities. Intelligent tools such as recommender systems have been used in order to support these activities. While decisions regarding the type of a trip to undertake are strongly influenced by tourists' personalities, currently only a few recommenders exploit information about this aspect. Our aim is to provide itinerary recommender system designers with some guidance on the integration of knowledge on personality traits and itinerary factors in a recommender. To do so, first we modeled the most important aspects of an itinerary, starting from the stateof- the-art literature on recommender systems for tourism. We identified thirteen factors, from the variety (in type and topic) of Points-of-Interest (POIs) to the expected duration of transfer times, grouped into three broader dimensions (POIs, time and choice modality). Then, we carried out a survey-based study on Generation Z (namely, the generation of people born between 1996/1997 and 2012) to investigate if the Big Five personality traits can affect the user's decision-making process when planning an itinerary, and, in particular, if they are related to user preferences for the itinerary factors in our model. Finally, we used our findings to define some guidelines for the design of advanced itinerary recommender systems.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2023.3285258