역사문화관광지 온라인 리뷰 기반 관광매력속성과 추천의도의 영향 관계에 대한 탐색적인 접근: 해석수준이론의 관점에서 빅데이터 분석

From the perspective of Construal Level Theory, this study attempts to verify the influence relationship between the attractive attributes of online reviews and recommendation intentions, and the moderating effect of review and reviewer characteristics in these relationships. As for the research method, Gyeongbokgung Palace, Changdeokgung Palace, Jongmyo Shrine, and Suwon Hwaseong Fortress reviews were collected from TripAdvisor, an online review site, using Octoparse, a scraping program. In addition, text mining was performed after going through a data preprocessing process using a Tidyverse approach using the R program. After that, words, which are unstructured data, were refined and formalized. Finally, descriptive statistical analysis and negative binomial regression analysis were conducted. As a result of the study, social attributes, which are the attractive attributes of cultural heritage tourism destinations, influenced the recommendation intention, and the access factor and travel planning factor, which are the incidental attributes of tourism destinations, influenced the recommendation intention. The results of the study show that when a potential tourist decides to explore a tourism destination online and visit a cultural heritage tourism destination, the psychological distance becomes closer, showing more interest in the incidental attributes of the tourism destination. This study is of academic significance in that it explores the possibility of big data research in the academic field by collecting and analyzing actual online data and inferring whether Construal Level Theory can be confirmed in real life. In addition, when promoting a specific tourism destination, it is meaningful to draw practical implications that if the tourism destination is a well-known tourist destination, it is necessary to emphasize the incidental attributes of the tourism destination as a strategy to increase revisit.