=Paper= {{Paper |id=Vol-1905/recsys2017_poster22 |storemode=property |title=Users' Choices About Hotel Booking: Cues for Personalizing the Presentation of Recommendations |pdfUrl=https://ceur-ws.org/Vol-1905/recsys2017_poster22.pdf |volume=Vol-1905 |authors=Catalin-Mihai Barbu,Jürgen Ziegler |dblpUrl=https://dblp.org/rec/conf/recsys/Barbu017a }} ==Users' Choices About Hotel Booking: Cues for Personalizing the Presentation of Recommendations== https://ceur-ws.org/Vol-1905/recsys2017_poster22.pdf

Users’ Choices About Hotel Booking: Cues for
Personalizing the Presentation of Recommendations
Catalin-Mihai Barbu Jürgen Ziegler
University of Duisburg-Essen University of Duisburg-Essen
Duisburg, Germany Duisburg, Germany
catalin.barbu@uni-due.de juergen.ziegler@uni-due.de

ABSTRACT EXPLORATORY STUDY
Personalization in recommender systems has typically been We conducted an exploratory online study to investigate
applied to the underlying algorithms. In contrast, the participants’ choices about hotel booking. In selecting the
presentation of individual recommendations—specifically, domain, we considered three aspects: 1) The choice should
the various ways in which it can be adapted to suit the carry a substantial amount of risk for the user; 2) the items
user’s needs in a more effective manner—has received should have a reasonable set of attributes that need to be
relatively little attention by comparison. We present the considered; and 3) there should be a large body of user-
results of an exploratory survey about users’ choices generated content available, in the form of reviews, photos,
regarding hotel recommendations and draw preliminary tags, and ratings, that can be leveraged for the presentation.
conclusions about whether these choices can influence the Because of the first criterion, we decided against using the
presentation of recommendations. more common domain of movie recommendations.
Author Keywords Study Design
Recommender systems; personalization; user study; tourism We theorize that the way in which people make decisions
about hotel booking, their trust in social media, and their
ACM Classification Keywords
H.5.2 [Information Interfaces and Presentation]: User travel habits influence the information they want to see in a
Interfaces—evaluation/methodology, graphical user recommendation (i.e. the type of personalization they
interfaces (GUI), user-centered. expect). Our aim for this study was to investigate whether
the travel scenario influences users’ decision-making
INTRODUCTION & MOTIVATION processes in ways that can be used to personalize the
Personalization is an important and well-studied topic in presentation of hotel recommendations.
recommender systems (RS). Previous research has noted
the positive effect of personalization on enhancing user The survey was organized in six parts. The first four
experience [5]. A relatively unexplored area concerns the sections elicited answers regarding our participants’
personalization of the presentation of recommendations. demographics, trust in social media, experience with hotel
Elicited user preferences can be used not only to offer booking portals, and travel behavior. A filter question was
personalized predictions, but also to customize the way in used to assign each participant to one of five travel
which these predictions are presented to the user. Adapting scenarios: city break / short vacation (1-2 nights), short
the presentation to fit individual needs has the potential to business trip (1-2 nights), long vacation (3+ nights), long
uncover novel interaction possibilities. We present the business trip (3+ nights), or family vacation (with children).
results of an exploratory study that investigated users’ In each scenario, users were presented with an identical
choices about the presentation of hotel recommendations mockup of a hotel recommendation. First, participants were
and our preliminary conclusions on whether these choices asked to rank each section of the mockup—overall rating,
could influence the presentation of recommendations. price, general description of the hotel, photos, a map
RELATED WORK showing the hotel’s location within the city, nearby
Some of the main research foci of personalization include transportation options, hotel and room amenities, and
deciding, for a given recommendation, what information to reviews from users—depending on how important they
present, when to present it [1], how much of it to present considered the information in that section to be. Second,
[2], and in what way [6]. Many existing approaches to they had to select up to 7 topics about which they would
personalizing the presentation of recommendations rely on like to receive more information when looking at
explanations (see, e.g., [7] for an in-depth analysis of the recommendations (e.g., proximity to public transport, room
effects). So-called “common sense” approaches, which use sizes and layouts, or fitness center equipment).
rules to determine what items to recommend and how to Finally, participants were asked 12 questions designed to
personalize the presentation have also been developed [3]. determine their typical decision-making behavior during
hotel booking. This section was modelled based on the
Copyright is held by the author(s). Rational-Experiential Inventory [4], which is designed to
RecSys 2017 Poster Proceedings, August 27-31, Como, Italy.
RecSys 2017 Poster Proceedings, August 27-31, Como, Italy Barbu and Ziegler

measure participants’ need for cognition and faith in
intuition, respectively. The questions addressed six
underlying factors: a) perceived effort required to complete
a hotel booking task; b) economic considerations; c)
clearness of mental goal; d) self-efficacy (i.e. trust in one’s
own choices); e) influenceability; and f) engagement. Two
questions (high and low loading) were asked per factor.
Study Results
The survey was published online in January 2017 and ran
for one month. A total of 159 participants (82 female;
median age in the interval 25-34 years) completed the
survey fully. Of the respondents, 123 (77.36%) were
employed and 24 (15.09%) were students. Furthermore, 139
(87,42%) had completed at least a Bachelor education. As
monetary incentive, all complete responses entered a raffle
for one of four Amazon gift vouchers, each worth 25 EUR.
Most participants (51%) rated their trust in online reviews
as high or very high on a 5-point Likert scale (M=3.53,
SD=0.71). These findings were similar across all scenarios.
After data analysis (ANOVAs with Fisher’s LSD), we Figure 1: Results of users’ decision-making behavior during
noticed a significant difference (p < 0.05) when comparing hotel booking. Error bars denote the 95% confidence interval.
the business scenarios: Over 65% of participants whose
typical travel scenario was “long business trip” reported a Initial findings suggest that the motivation behind searching
high or very high trust in online reviews, compared to only for a recommendation influences users’ decision processes.
48% in the “short business trip”. The availability of reviews As ongoing work, we are investigating potential links
was rated as very or extremely useful by 78% of between individual factors and presentation preferences.
participants (M=3.96, SD=0.75). Similarly, photos were ACKNOWLEDGMENTS
considered very or extremely useful by 82% of respondents This work is supported by the German Research Foundation
(M=4.17, SD=0.82). In both cases, we observed no (DFG) under grant No. GRK 2167, Research Training
significant differences between travel scenarios. Group "User-Centred Social Media".
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