시계열분석을 통한 자연휴양림 계절별 이용수요 예측 : 계절ARIMA 모형과 지수평활 모형을 중심으로
A Forecasting Visitor Demand to Recreational Forest using Time Series Analysis : Focused on Seasonal ARIMA and Exponential Smoothing model
To cope with the rapidly increasing demand for Recreational Forest, the ability to provide accurate visitor flow forecasts became very important. The government would be able to invest properly and effectively to build various infrastructures and programs based on correct visitor demand forecasting. This study aims to identify the appropriate model and forecast visit demand of Recreational Forest, which is one of the representative infrastructures of forest recreation in Korea. In order to develop a forecasting model, the dataset of monthly visitors to Recreational Forest during 2009-2015 were used and two time series methods - Seasonal ARIMA and Exponential Smoothing - were employed. The results show that Winters Additive model was selected as the most appropriate model to forecast visit demand of Recreational Forest based on index of Mean Absolute Percentage Error. This study will make a great academic contribution to identify visit demand for Recreational forest by systematic and scientific methods. However, this model is not the only method available for forecasting demand. Since there are many other kinds of forest recreation infrastructures in accordance with different purposes, other kinds of forecasting methods should be adopted for better projection later on.
목차
ABSTRACT Ⅰ. 서론 Ⅱ. 이론적 배경 1. 관광여가활동지로서 자연휴양림 2. 관광수요예측 3. 자연휴양림 수요예측 Ⅲ. 연구설계 1. 연구대상 및 자료 2. 분석방법 Ⅳ. 분석결과 1. 계절 ARIMA 모형 2. 지수평활 모형 3. 예측결과 비교 Ⅴ. 결론 참고문헌
관광경영학을 실용학문의 체계로 확립하고 실천학문으로 정착시키기 위하여, 관광경영학문을 현실적응에 필요한 연구를 통해 국가관광정책의 방향을 제시하고, 관광사업자들에게는 실질적으로 도움이 되는 경영전략을 제공하며, 연구를 통하여 회원간의 친목도모와 정보교환을 함으로써 상호발전을 목적으로 한다.