Recommender Systems were created to support users in situations of information overload. However, users are consciously or unconsciously influenced by many factors in their decision making. Hence, we aim at exploring how these factors influence user choices in the context of online hotel search and booking. Specifically, we focused our study on (i) ranking position, (ii) price, (iii) rating, and (iv) number of reviews when analyzing users’ click behavior. The results showed that there were “two elephants in the room”: position and price, that heavily influenced the user decision-making and need to be taken into account when, for instance, trying to learn user preferences from offline data in order to bootstrap a recommender system.
Cavenaghi, E., Camaione, L., Minasi, P., Sottocornola, G., Stella, F., Zanker, M. (2022). An Analysis of User Click Behaviour in Online Hotel Search. In CEUR Workshop Proceedings. CEUR-WS.
An Analysis of User Click Behaviour in Online Hotel Search
Cavenaghi E.;Camaione L.;Sottocornola G.;Stella F.;
2022
Abstract
Recommender Systems were created to support users in situations of information overload. However, users are consciously or unconsciously influenced by many factors in their decision making. Hence, we aim at exploring how these factors influence user choices in the context of online hotel search and booking. Specifically, we focused our study on (i) ranking position, (ii) price, (iii) rating, and (iv) number of reviews when analyzing users’ click behavior. The results showed that there were “two elephants in the room”: position and price, that heavily influenced the user decision-making and need to be taken into account when, for instance, trying to learn user preferences from offline data in order to bootstrap a recommender system.
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