INF 385G – Advanced Usability – HA Group 3
HomeAway and User Trust Research Overview Rachael H Lanham; Mallory Hill; Graeme Hamilton; Sherry Wu; Yiping Zhou
Eye-Tracking We conducted an eye-tracking study to determine if different reported attitudes of trust would reveal differences in how participants navigated accommodation websites. We looked for an even distribution of those who self-reported as trusting home booking sites (such as HomeAway) and those who did not trust. Our respondents who were willing to participate in the study did not ultimately fit the demographics we needed; all reported that they were either “very comfortable” or “completely comfortable” with peer-to-peer accommodation services, and all were within the ages of 21 and 40. We had 3 males and 2 females participate. Interviews Using the results from our Eye-Tracking and Screener Survey as a guide for where to dig further, we interviewed 10 participants. The participants broke down as 6 females and 4 males between the ages of 20 - 60 years old. These in-depth interviews were designed to gather additional data on user Trip Habits and Website Navigation, as well as more targeted information on the user experience when Booking Accommodations such as their top concerns. All participants had previous experience booking online; most noted AirBnB as their go-to, while one participant noted Hotel Booking websites. Utilizing the emotions scale that we created for our initial Screener Survey, we put together a single task, based on our Eye-Tracking Tasks, to get a holistic view of the user's emotional experience when booking with HomeAway. We asked users to answer three follow-up questions rating their feelings before, during and after completing their Task. In general, while using the platform, most users were either satisfied by the look and feel, or excited for something new. Most users were either Excited the whole way through or wound-up so by the time they reached the end. All users heavily commented on the number and quality of the photographs included in the listings. Survey and Model A survey was conducted to examine the importance of three categories, trust in brand, trust in peer and trust in the brand peer relationship, as well as their relationship to the overall trust a participant felt towards peer to peer platforms. A total of 725 complete responses were collected through Amazon Mturk with the resulting model being validated against 29 new responses collected through social media. The survey Contained 15 agree/disagree likert scales examining elements of trust and 4 likert scales asking about trust directly. The survey first asked the participant to select or name the last peer to peer company they had used, and then used text pipping to ask the rest of the questions about that company. This was done to gauge trust across the peer to peer sector and to minimize the chance of a respondent not having experience with a preselected company. Multiple regression was used to determine the influence of each question score on the participants self-reported level of trust in the platform as well as to create a pilot model of trust in peer to peer relationships. 3 passes of multiple regression were used with the target of matching a self-reported trust in the platform. The filtering level of significance was lowered each time. After 3 passes, all variables had p-values<0.05. After the eliminations 9 questions were used to create a composite score representing the predicted trust level, with the goal of being able to measure trust without directly asking about it. Questions which focused on trust in peer had the heaviest weight and were the largest plurality. 4 questions relating to trust in peer were included in the model while only 3 and 2 questions for trust in company and trust in company-peer relationship were kept respectively. The model was cross validated against the social responses and resulted in a correlation of about 0.61 between the predicted and self-reported levels of trust. The level of correlation between the self-reported score in the training data and the predicted score was of course much higher, at roughly 0.78. The biggest takeaway from the survey is that trust in peer is the most important piece in understanding how much an individual trusts a platform. This makes sense as the peer is the one with whom they will interact, and who poses the greatest risk. Since trust is irrelevant in situations without perceived risk, it makes sense that the riskiest part of the platform would have the strongest relationship to trust.