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Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):

J. Neidhardt, H. Werthner:
"Travellers and Their Joint Characteristics Within the Seven-Factor Model";
Vortrag: ENTER Conference 2017, Rome, Italy; 24.01.2017 - 26.01.2017; in: "ENTER Conference, Information and Communication Technologies in Tourism 2017", Springer, (2017), ISBN: 978-3-319-51167-2; S. 503 - 515.



Kurzfassung deutsch:
Recommender systems face specific challenges in the travel domain, as the tourism product is typically very complex. In addition, travelling can be seen as an emotional experience. Thus travel decisions are usually not only based on rational criteria but are rather implicitly given. Therefore sophisticated user models are required. In this paper it is analysed in detail whether the seven-factor model is capable of differentiating between different groups of users in an accurate way. Within this model each user is described with respect to seven travel behavioural patterns that account for both tourist roles and personality traits of a user. To identify groups of travellers, individual attributes are used and also a cluster analysis is conducted. With the help of statistical analyses clear evidence is provided that the seven-factor model is capable of distinguishing between different groups of users in a meaningful and effective way.

Kurzfassung englisch:
Recommender systems face specific challenges in the travel domain, as the tourism product is typically very complex. In addition, travelling can be seen as an emotional experience. Thus travel decisions are usually not only based on rational criteria but are rather implicitly given. Therefore sophisticated user models are required. In this paper it is analysed in detail whether the seven-factor model is capable of differentiating between different groups of users in an accurate way. Within this model each user is described with respect to seven travel behavioural patterns that account for both tourist roles and personality traits of a user. To identify groups of travellers, individual attributes are used and also a cluster analysis is conducted. With the help of statistical analyses clear evidence is provided that the seven-factor model is capable of distinguishing between different groups of users in a meaningful and effective way.


Elektronische Version der Publikation:
https://link.springer.com/chapter/10.1007/978-3-319-51168-9_36


Erstellt aus der Publikationsdatenbank der Technischen Universitšt Wien.