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.
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
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