Subjects Characteristics

All subjects were Pepperdine University students registering for the International program.

The subjects spent one or two terms in Lausanne, Switzerland. All but three cases used a computer located in the Pepperdine University campus in Lausanne. This measure reduced the possibility of interference caused by machines or network connections. Some of these study subjects started using the internet as early as 1997 when they were in the 6th grade.

Most subjects started using the internet before December 2001, providing them with at least 6

years of online experience. Table 4.2 summarizes when subjects started using the internet.

Table 4.2 Subjects Internet Experiences

Table 4.3 shows the subjects daily internet usage. All subjects used the internet for at least 1 hour, and up to 6 hours a day.

The subjects first online purchases included books, clothes, music downloads, and travels.

Table 4.4 shows subjects first online purchase categories.

Most subjects started using the internet before December 2001, but some of the first online purchases took place as late as December 2007. This is consistent with likely purchase power of second year University students. Table 4.5 shows the time period when subjects made their first online purchases.

Table 4.5 When did Subjects Make First Online iPurchase?

Frequency Percentage Cumulative Percentage

January, 2005 - December, 2007 11 25.6 % 25.6 %

January, 2002 - December, 2004 18 41.9% 67.4 %

January, 1999 - December, 2001 14 32.6 % 1 0 0.0 %

January, 1996-December, 1998 0 0 . 0 % 1 0 0.0 %

Total 43 1 0 0.0 % ^{1 0 0}.0 %

Most subjects consider themselves as having made online purchases “rarely” or “sometimes”.

Table 4.6 shows the perceived frequencies of online purchases.

Table 4.6 The Perceived Frequencies of Online Purchases

As noted above, the subjects considered themselves “rarely” or “sometimes” making online purchases, which is further confirmed by Table 4.7. In the past month, 17 subjects made 1-4 online purchases, which is at most once every three months. Twelve subjects made 5-8 online purchases, which is around once every two months. Only 14 subjects made online purchases as often as once every month.

Table 4.7 Subjects’ Online Purchase Experiences in the past 12 months

Frequency Percentage Cumulative Percentage informally observed that most of these study subjects travel around Europe on long weekends and school breaks to experience as much as possible during their International semester.

Table 4.8 shows the frequencies of using the internet to select a hotel to stay.

Table 4.8 The Frequencies of Using Internet to Select a Hotel to Stay reservations, following their selection process (see above). It is interesting to compare Table 4.9 with Table 4.6. Perceptions of online purchases are lower than perceptions of making hotel reservations online.

Table 4.9 The Frequencies o:"Using the Initemet to Make' Jotel Reservations Frequency Percentage Cumulative Percentage

Table 4.10 shows the time period when subjects made their first online hotel room purchase.

Table 4.10 provides a different perspective from the results of Table 4.8 and Table 4.9. Most subjects used the internet to select hotels and reserve hotel rooms online, but they only started making reservations in the past two years. Again, given the subjects are young, these results are not surprising. This table is also consistent with Table 4.5 findings.

Table 4.10 When did the Subjects Make the First Online Hotel Room Purchases?

Frequency Percentage Cumulative Percentage difference between the number of online purchases and the number of hotel rooms purchased.

However through observation of the subjects, when they answered this question, many counted their fingers. It is suspected subjects tried to recall their specific visited destinations in the past 12 months in order to answer this question. Therefore, it is proposed that Table 4.11 may provide a more accurate estimation than Table 4.7.

Table 4.11 The Number of Ho1:el Rooms Purchased Online in the Past 12 Months Frequency Percentage Cumulative Percentage

None 0 0 . 0 % 0 . 0 %

1-4 times 25 58.1 % 58.1 %

5-8 times 17 39.5 % 97.7 %

9-12 times 0 0 . 0 % 97.7 %

More than 12 times 1 2.3 % 1 0 0.0 %

Total 43 1 0 0 . 0 % 1 0 0.0 %

Based on Tables 4.8 to 4.11, the subjects are clearly comfortable using the internet to select and reserve hotels, even though they do not have many experiences in terms of the number of years and the number of reservations.

The Sorting Function and Comparison Function screenshots, as described in Chapter 3, were shown to subjects when given the instructions before conducting the hotel selection task.

When subjects answered questions regarding the awareness of both the Sorting function and Comparison function, the author confirmed subjects were aware of their applications.

Figure 4.3 Sorting and Comparison Screenshots

Sorting Function Comparison Function

209

Adjust ratings and pries ranees to narrow hots! ss I actions.

$1 9*52/2

; hotste match

>e„r*JedO!S T

S eieot additions! p referen ces to further narrow p u r search.

Table 4.12 shows that more than half o f the subjects had seen the sorting function before this study on other web sites. However 47 out o f total study sample o f 52 subjects actually used some sorting functions during the experimental stage, even though some subjects reported in the questionnaire as not being aware o f the sorting function.

Table 4.12 Subjects’ Awareness o f the Sorting Function

Frequency Percentage Cumulative Percentage

No 17 39.5 % 39.5 %

Yes 26 60.5 % 100.0%

Total 43 100.0% 100.0%

Table 4.13 shows subjects’ awareness o f the Comparison function. More than h alf o f the subjects reported have seen the comparison function before this study. On the other hand, 37 out o f total 52 subjects actually used the comparison function in the hotel selection task.

Table 4.13 Subjects’ Awareness of the Comparison Function

Frequency Percentage Cumulative Percentage

No 16 37.2 % 37.2 %

Yes 27 62.8 % 1 0 0.0 %

Total 43 1 0 0.0 % 1 0 0.0 %

Table 4.14 shows the perceived frequencies of reading online customer reviews. Most subjects at least “sometimes” read online customer reviews before making purchase decisions.

Table 4.14 The Perceived Frequencies of heading Online Customer Reviews Frequency Percentage Cumulative Percentage

Table 4.15 shows the frequencies of posting online customer reviews. Comparing to Table 4.14, it is interesting to note that these subjects are online customer review readers, or information users; not online review posters, or content generators. Subjects were asked for the reasons for not posting reviews. Subjects’ answers included; “I read reviews before I make purchases, but do not think about reviews after my purchases”, or “Only when I have extremely good or bad experiences, I will want to post reviews”.

Table 4.15 The Perceived Frequencies of Posting Online Customer Reviews Frequency Percentage Cumulative Percentage

Table 4.16 shows the perceived importance of customer online reviews. Most subjects perceived online reviews are at least “moderately important” or “ important” .

Table 4. 16 The Perceived Importance of Customer Online Reviews

Frequency Percentage Cumulative Percentage

Unimportant 1 2.3 % 2.3 %

Of little important 3 7.0 % 9.3 %

Moderately important 17 39.5 % 48.8 %

Important 18 41.9% 90.7 %

Very important 4 9.3 % 100.0 5

Total 43 1 0 0 . 0 % 1 0 0 . 0 %

Table 4.17 shows whether subjects read online customer reviews when they made their last online purchase.

Table 4. 17

Percentage of Subjects who Read Online Reviews before last Online Purchase Frequency Percentage Cumulative Percentage

No 8 18.6% 18.6%

Yes 35 81.4% 1 0 0.0 %

Total 43 1 0 0.0 % 1 0 0.0 %

In summary, Tables 4.2 to Table 4.17 present the subject characteristics. Most subjects, at the time of the study, had at least 6 years of online experience, used the internet between 1 to 4 hours daily, and made their first online purchase in the past 2-4 years. They rarely or sometimes purchased online. Most made online purchases once every 2-3 months. They often used the internet to select a hotel in which to stay, but not always to make online hotel reservations. Although most made the first online hotel reservation in the past 2 years, they accumulated the experiences intensively in the past 12 months. The majority often read online reviews, but more than half of them never posted online reviews. The majority considered online reviews as important and read online reviews before they made last online purchase.

Even though most subjects claimed to read online reviews when they made their last online purchase, as seen above, only 23 out of 52 subjects actually read online reviews when they did the hotel selection task. On the other hand, the conjoint analysis shows ‘review’ is the most important attribute in ranking a hotel. One explanation for this is that the estimated frequency count of 23 in the hotel selection task is underestimated because only recognized

review usage through clicks counted from the videos. For example, a subject can look at a screenshot of a hotel and read the customer review without clicking on it. In this case, the use of Review will not be recognized. The same argument can be made for price and star- ratings. These too may be underestimated, as the information can be accessed without clicks.

These diverse findings from the survey, the actual behaviour, and the conjoint analysis demonstrate the importance of verifying a question from different perspectives and the need for further research.