Personalization in recommender systems has typically been applied to the underlying algorithms. In contrast, the presentation of individual recommendations-specifically, the various ways in which it can be adapted to suit the user's needs in a more effective manner-has received relatively little attention by comparison. We present the results of an exploratory survey about users' choices regarding hotel recommendations and draw preliminary conclusions about whether these choices can influence the presentation of recommendations.
RELATED WORK
Some of the main research foci of personalization include
deciding, for a given recommendation, what information to
present, when to present it [
The survey was organized in six parts. The first four sections elicited answers regarding our participants’ demographics, trust in social media, experience with hotel booking portals, and travel behavior. A filter question was used to assign each participant to one of five travel scenarios: city break / short vacation (1-2 nights), short business trip (1-2 nights), long vacation (3+ nights), long business trip (3+ nights), or family vacation (with children). In each scenario, users were presented with an identical mockup of a hotel recommendation. First, participants were asked to rank each section of the mockup—overall rating, price, general description of the hotel, photos, a map showing the hotel’s location within the city, nearby transportation options, hotel and room amenities, and reviews from users—depending on how important they considered the information in that section to be. Second, they had to select up to 7 topics about which they would like to receive more information when looking at recommendations (e.g., proximity to public transport, room sizes and layouts, or fitness center equipment).
Finally, participants were asked 12 questions designed to determine their typical decision-making behavior during hotel booking. This section was modelled based on the Rational-Experiential Inventory [4], which is designed to 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 noticed a significant difference (p < 0.05) when comparing the business scenarios: Over 65% of participants whose typical travel scenario was “long business trip” reported a high or very high trust in online reviews, compared to only 48% in the “short business trip”. The availability of reviews was rated as very or extremely useful by 78% of participants (M=3.96, SD=0.75). Similarly, photos were considered very or extremely useful by 82% of respondents (M=4.17, SD=0.82). In both cases, we observed no significant differences between travel scenarios.
Certain patterns emerged with respect to users’ typical decision-making behavior during hotel booking. First, booking a hotel for vacation is considered more challenging than for business travel—especially for longer stays (p < 0.05). Second, people who typically go on longer vacations need more time to decide which recommendation to follow when prices are higher than they are used to. The difference was significant (p < 0.05) when compared to the answers from the “long business trip” scenario. Third, participants tend to revisit recommendations to ensure they do not miss important information. A significant difference (p < 0.01) was observed when comparing the scenarios “short vacation” and “short business”. These results suggest that the travel scenario can be a factor for personalizing the presentation of recommendations. However, its influence may be lower than predicted (Figure 1).
Contrary to our expectations, we observed almost no significant differences in terms of the importance of the mockup sections for the different scenarios. The sole exception (p < 0.01) was “general hotel description”, which proved particularly unimportant for respondents in the “long business” scenario. Similarly, the list of topics about which participants stated they would like to see more information when browsing recommendations did not exhibit significant differences across scenarios. Initial findings suggest that the motivation behind searching for a recommendation influences users’ decision processes. As ongoing work, we are investigating potential links between individual factors and presentation preferences. ACKNOWLEDGMENTS This work is supported by the German Research Foundation (DFG) under grant No. GRK 2167, Research Training Group "User-Centred Social Media".