외래 관광객의 관광 주목적별 관광지 선택 연관성 규칙 분석 : 2013년 외래 관광객의 휴가ㆍ레저 및 비즈니스 집단별 비교 연구

Abstract

Applying data mining method to tourist spatial behaviors, the present study were to identify association rules of leisure and business tourist groups using dataset of 2013 international visitor survey. Associative rule mining is the most frequently used method in data mining, and this method is useful to explore an associative relationship between two items out of massive volume of data. In retail setting, this method is often used to demonstrate new findings of consumer behavior patterns. By utilizing SAS E-Miner, this study distinguish associative rules between leisure and business tourist groups with support, confidence, and lift of rules. According to the survey collected by the Ministry of Culture, and Tourism in Korea, leisure and business tourist groups were highly occupied among international tourists from the main purpose of foreign tourists. This study revealed that two tourist groups had a different tendency in visiting tourist attractions in Korea. The academic and practical implications of this study were discussed in this present study.