The Structural Equation Model of Artificial Neural Networks for Thailand Domestic Tourists’ Image in Lifestyle Tourism : Case Study of Charoen Krung and Yaowarat Areas
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The objectives of this research were to study 1) The behavior of tourists that related to their image in lifestyle tourism 2) Causal Relationship Model and examine the coherence of the model with the empirical data of Thai tourists’ image in lifestyle tourism 3) Analyze the model of Artificial Neural Networks (ANN) for Thai tourists’ image in lifestyle tourism, case of Charoen Krung and Yaowarat areas. The quantitative data was conducted with the sample of 462 participants. The accidental sampling technique was applied to Thai tourists who traveled to the targeted area. The data were analyzed through the Structural Equation Model (SEM) and the Artificial Neural Networks (ANN).
The results found that, according to their tourism experience, they are enjoyed and impressed with the new things in destination, such as food and activities. Travel experience also increases self-awareness of tourists. The Causal Relationship Model and the coherence of the model were examined. It was found that (CMIN/DF) was 1.96, while the GFI was 0.92, CFI was 0.97, (RMSEA) was 0.04, and (NFI) was 0.95, which is greater than 0. 90. It shows that the result conforms to empirical data, and positively affecting the tourism experience and satisfaction. Therefore, image, travel experience and satisfaction of tourists are positively influence on their revisit intention and willingness to recommend the place to others. According to the number of input layers in a three-level of the ANN, were ranked in descending order of the importance, which are satisfaction, image, and experience, are affecting their intention and willingness to recommend to others, at statically significant level of 0.01.
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