Hiromi Kamata and Yuki Misui / Procedia - Social and Behavioral Sciences 175 ( 2015 ) 210 – 218
you can do sports or attend events as a group 0.72
you can enjoy mountain climbing or hiking 0.68
having and savoring interactions with unknown persons during your trip 0.51
being able to travel or experience something according to a theme you've determined yourself 0.42
Friendship 1.52 2.8 0.63
being able to spend time with friends 0.83
experiencing events together with your friends 0.78
being able to spend time with acquaintances 0.63
being able to spend time with your family -0.52
experiencing events together with your acquaintances 0.47
experiencing events together with your family -0.45
Pets 1.25 2.3 0.95
being able to spend time with your pets 0.90
experiencing events together with your pets 0.85
Total variance explained 54.2
Note: V.E. means Variance Explained. R.A. means Reliability Alpha.
We conducted cluster analysis (k-means) to segment the sample into 3-7 clusters according to respondent factor
scores. After comparing the results of these 3-7 clusters, we employed three clusters where statistical conditions
were significant. Table 3 shows the results of the cluster analysis. The motivation factors that received the highest
ratings among the three clusters were for the Soothing, Release, and Pets categories. Each cluster was named
according to the motivation factors within that cluster that received the highest ratings.
Table 3. Results of cluster analysis: weekend tourists.
Cluster (number of respondents/share)
1
Active and positive spa
tourists
2
Spa tourists who treasure time with
family and relatives
3
Spa tourists without
definite purpose
n = 33 n=145 n=136
Factor 10.5% 46.2% 43.3% F-ratio S.L.
Uniqueness 3.02 2.51 1.72 94.42 0.00
Soothing Quality 3.28 3.41 2.54 125.34 0.00
Release from Routine 3.39 3.32 2.13 127.04 0.00
Romance 3.09 1.89 1.23 111.54 0.00
Sports 3.00 1.70 1.44 92.69 0.00
Friendship 3.26 1.89 1.68 38.69 0.00
Pets 3.14 1.03 1.01 807.01 0.00
The results were also characterized by demographic variables and travel profile variables and compared using a
chi-square test to find statistical differences among the clusters. The summary of each cluster is as follows:
Cluster 1 (10.5%): We named this cluster “Active and positive spa tourists,” referring to tourists who had
expectations pertaining to all seven factors. These were mainly high-income male tourists aged 30–39. The party
numbers were small, and the members consisted mainly of either children or couples. These respondents made all
their travel arrangements personally and paid relatively high prices for the entire trip except for souvenirs.
Respondents were positive about wanting to travel and to post about their experiences on SNS.
Cluster 2 (46.2%): We named this cluster “Spa tourists who treasure time with family and relatives,” since
tourists in this cluster chose the spa as a destination to enjoy a relaxing time with family and relatives. The important
factors here were the Soothing and Release factors. Members of these parties consisted mainly of parents, spouses,
and relatives. Self-employed people made up a relatively large share of these people. They also paid relatively high
prices for accommodation.
Cluster 3 (43.3%): We named this cluster “Spa tourists without definite purpose,” since tourists in this cluster
went on the spa trip without any definite purpose; that is, none of the factors was of particular importance to them.
As shown in Table 5, “member of party decided” had a relatively high share among reasons for choosing a particular
spa. These tourists were mainly aged 60–69. Because they had no strong reason for choosing the spa, they also
expected nothing in particular from the spa experience.