4. Results and discussion
4.1. Service quality factors
    It is primary for hotel business to comprehend the internal factors of service quality that influence delivery high quality of service experience. Principle component factor analysis with orthogonal varimax rotation was conducted to create new variable index and reduce the service quality questionnaires how subjects regard service quality variables to final dimensions. The rotated factor matrix identified seven underlying factors relating to the 75 service quality items.The seven factors of leisure travelers accounted for 65.3% of the variance and 73.2% of the variance for the hoteliers questionnaire. For each factors, reliability analysis with Cronbach’s Alpha was computed to examine the reliability and internal consistency. These factor domains, number of items, eigenvalues, explained variance, Cronbach’s Alpha, and factor loading range were shown in Table 2 and Table 3. The minimum Alpha value of 0.5 was considered acceptable as an indication of reliability and internal consistency for basic research (Nunnally, 1978).The Alpha values of the factors in both groups ranged from .74 to .99 and were considered good indicators of service quality perspectives in Taiwan. The table didn’t show the factor loadings that were greater then 0.5 and items because of there are 60 and 58 items eventually in these factors. The results of factor analysis showed there were seven different domains/factors to represent the service quality respectively for leisure travelers and hoteliers. The retained items of the seven factors decided the name of the factors for both groups.
Table2 Factor analysis of service quality perspective of leisure travelers Factor Number eigenvalues Percent Cronbach’s Factor loading Domain of Items of Variance Alpha Range
1. Server* 17 23.3 32.3% 0.94 .54--.76
2. Facility 17 6.6 11.5% 0.94 .52--.70
3. Management 7 3.8 7.6% 0.90 .53--.78
4. Appearance 8 2.1 5.2% 0.88 .50--.79
5. Promotion 4 1.9 3.8% 0.78 .51--.58
6. Speed of service* 5 1.7 3.3% 0.81 .56--.64
7. Information 2 1.2 1.6% 0.82 .80--.84
* The factor domains came from the second part of questionnaire.
Table3 Factor analysis of service quality perspective of hoteliers Factor Number eigenvalues Percent Cronbach’s Factor Loading Domain of Items of Variance Alpha Range
1. Server* 17 17.2 28.9% 0.99 .80--.97
2. Facility 22 13.1 19.1% 0.94 .51--.79
3. Management 7 5.1 8.3% 0.88 .59--.81
4. Speed of service* 4 3.2 5.8% 0.93 .86--.91
5. Appearance 3 2.1 4.2% 0.82 .55--.69
6. Safety 2 1.6 3.5% 0.74 .67--.74
7. Food service 3 1.4 3.3% 0.79 .54--.68
* The factor domains came from the second part of questionnaire.
The leisure travelers regarded Promotion and Information that the hotels can provide as the index of service quality. One possible explanation is that the leisure time increased suddenly in Taiwan because of a five-day workweek implementation and people didn’t know the purposes or destination of their travels. In addition,there were 50 percent of international tourist hotels have establish web sites but over four million people in Taiwan using the Internet to look for the information, including the hotel information (Wan, 2002). Therefore, they need the information and promotion activities from the hotels such as using the website of particular hotel.For the hoteliers, there were two different factors from leisure travelers’ perspectives. They were Safety and Food service that possibly came from the regulations such as HACCP and GSP. In addition, the food service in hotels was the largest part of net income and hoteliers thought the sanitation and quality of food as the important index of service quality assessment for customers.
4.2. The comparison of service quality perspectives between leisure travelers and hoteliers
    An independent sample t-test was conducted to assess the significant differences of hotel service quality perspectives between leisure travelers and hoteliers. The results showed that leisure travelers had different perspectives regarding to hotel service quality from the hoteliers (t = 3.66. P < .0001). Five factors in each group were same and they are Server, Speed of service, Facility,Management, and Appearance factors. The results also revealed that the Facility (t =-10.46, p < .0001), Management (t = 4.76, p < .0001), Speed of service (t = 5.19, p
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