Tourist Loyalty Model for Tourist Attractions in Suphanburi Province
Abstract
This research aims to (1) explore the image of the tourist attractions in Suphanburi Province, service marketing mix, tourist satisfaction and tourist loyalty toward tourist attractions in Suphanburi Province. (2) analyze the components of the four latent variables. (3) analyze both direct and indirect effects of the tourist attractions in Suphanburi Province, service marketing mix, tourist satisfaction those affect tourist loyalty toward tourist attractions in Suphanburi Province (4)
find tourist loyalty model for tourist attractions in Suphanburi Province. This research is a quantitative research. The samples collected were 900. The data were analyzed by using descriptive statistics of percentage, arithmetic means, standard deviation. The inferential statistics consisted of confirmatory factor analysis, Path analysis and structural equation modeling. The research revealed that: (1) the image of the tourist attractions in Suphanburi Province, service marketing mix, tourist satisfaction and tourist loyalty toward tourist attractions in Suphanburi Province were mostly at high level.(2) the confirmatory factors analysis implied that the image of the tourist attractions in Suphanburi Province, service marketing mix, tourist satisfaction and tourist loyalty for tourist attractions in Suphanburi Province have the highest in the most impressive
elements values, service marketing mix have the highest in the most
people, tourist satisfaction have the highest in the most Service quality and tourist loyalty for tourist attractions in Suphanburi Province have the highest in the most Repeated use of the service. (3) the effect analysis found that the image of the tourist attractions in Suphanburi Province, service marketing mix has direct and indirect influence on tourist loyalty toward tourist attractions in Suphanburi Province (4) the constructed model corresponded with the empirical evidence of all variables (χ2=57.45, df=48, χ2/df=1.19, P=0.09, RMSEA=0.01).
