Health, Wellness and Tourism: healthy tourists, healthy business ...

located in different administration districts in Kaohsiung who had international travel
experiences were participated to investigate the wellness tourism market.
Research Instruments:
The questionnaire of “the Perceived Travel Benefits Scale for Elderly” consists of 25 travel
benefit-related questions in 5-point Likert scale. The questionnaire is derived from Fu (2003)
who edited the scales of Jang, Morrison, and O’Leary (2002) and Arimond and Elfessi (2001).
Yu and Fu (2008) revised it and using 596 elder respondents for factor analysis and obtained
6 benefit factors: Family gathering and relationship enhancement, nature appreciation,
experiencing life, escape and relaxation, cultural understanding, and social interaction which
match Fu (2003) factor structure and explain 70.1 % of the variance in total. The
Cronbach’sαfor each factor and the total score are between .70 to .97 and show good
reliability.
After a well review of the definition of wellness, Mueller and Kaufmann (2001) revealed
important service categories in wellness tourism in hotel industry. They are: body/physical
fitness/ beauty care, relaxation: rest/mediation, health: nutrition/diet, mind: mental
activity/education, environmental sensitivity, and social contacts. In addition, to arouse
participants’ self-responsibility for wellness is essential for the services. In the study, to
investigate the elder market, questionnaires of “ the Perceived Importance of Wellness
Facilities in the Hotel (PIWFH; 11 questions in 3- point Likert scale)” and “Participation
Interests in Extended Wellness Activities (PIEWA; a checklist of 16 items) were derived from
the above Mueller and Kaufmann’s wellness market analysis framework to measure the
elders’ perceived importance and interests in wellness hotel and the extended services of
wellness activities. Using 596 elder respondents for reliability analysis obtained Cronbach’s
α= .873 for the PIWFH and Cronbach’s α =.743 for PIWAT. In addition, questions of
demographic factors, travel experiences, and health related behaviors were also included in
the questionnaire.
Data Processing
Cluster analysis was used to identify the groups of people who had similar travel benefit
perception among the elderly. Then, t-test and chi-square were applied to describe the
differences in their demographic backgrounds, travel experiences, health behaviors, their
perceived importance of hotel services, as well as their interests of the wellness activities
between the identified clusters.
Findings and Discussions
Two Identified Clusters: Active Benefits Seekers and Passive Benefits Seekers
The study used both hierarchical and non-hierarchical cluster analysis methods. Since the
hierarchical cluster analysis can only process less than 100 cases, about 10% of the samples
were randomly selected from the 596 cases and analyzed using the hierarchical method. The
tree diagrams and agglomeration step tables favored a two-cluster group solution. To further
determine the cluster solution, the next step cluster analysis and k-means were used which reconfirmed
the two-group solution. Also, a discrimination analysis was used to check the
cluster solutions with all variables (6 perceived travel benefit factors) used to create the
cluster, and the two-cluster solution was clearly confirmed. With a success rate of 96.5% and
above for each cluster and 97.3% for total clusters, the allocation was virtually perfect.
The elderly traveler cluster groups were named by comparing the mean values of the 6 major
travel benefit factors in each cluster groups to find out the characteristics that differ