관광목적지 이미지와 온라인 리뷰 기반 지각된 유용성에 관한 빅데이터 연구의 계량적 접근 - 해석수준이론 관점에서 데이터마이닝 기법과 설문조사법의 비교 분석 -

초록

The purpose of this study was twofold: firstly, to provide a description of the phenomenon of text mining, and secondly, to investigate the possibility of big data research being used to establish causal relationships between objects in a manner similar to survey-based research methods. Therefore, in this study, correlation analysis and regression analysis were performed on Tripadvisor’s reviews of Seoul tourism attractions using datamining. In addition, survey data were collected for tourists who have visited Tokyo in Japan, and the results were compared by performing factor analysis, correlation analysis, and regression analysis. Looking at the results of the two studies, the same results were derived for the environmental factor among the high-level tourism attractiveness attributes, but different results were derived for cultural/historical factors. Next, among the low-level tourism attractiveness attributes, the same results were derived for transportation and travel planning factors, but different results were derived for cost factors. Finally, it was found that in both research methods, the higher-level cognitive image of the tourist destination had a positive effect on the lower-level image, supporting Hypothesis 2. Therefore, the significance of this study lies in exploring the potential academic utility of big data research. Thus, in future research, it is necessary to attempt quantitative research methods through various big data studies in order to further enhance its academic valu

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