관광지 만족도를 평가하는 관광지 선택속성에 관한 연구

Abstract

The purpose of this study is to add to our understanding of actual traveler interest in the tourism market by investigating the causal conditions of tourist destination attributes on tourist satisfaction. Prior to proceeding, natural tourist destinations that were recommended 5 times in a row in South Korea's top 100 must-see tourist destinations were chosen as the study's target. Seoraksan National Park, Hallasan National Park, Suncheonman Wetland (Suncheonman National Garden), Nami Island, and Udo are among them. For an analysis of the online reviews of these five well-known tourist destinations, topic modeling was used, and the latent dirichlet allocation (LDA) technique with TF-IDF weight was used to create a comprehensive list of the topics posted by Tripadvisor reviewers. Making scientific inferences about nature tourism phenomena, such as Fuzzy-set Qualitative Comparative Analysis (FsQCA), to better predict and explain real-world nature tourism phenomena using a configurational approach, is becoming more popular. The purpose of this article is to identify the key contribution and knowledge structure of tourist destination selection attributes as well as their overall satisfaction research using complexity theory and FsQCA. The primary goal of this study is to investigate not only the influence of tourist destination selection attributes as a single variable in online reviews, but also how these selection attributes influence tourist satisfaction with various combinations of causal conditions. These findings are useful in understanding individual travelers' perceptions of tourist destinations as well as their overall satisfaction.