시계열분석을 통한 자연휴양림 계절별 이용수요 예측

• 영문명: A Forecasting Visitor Demand to Recreational Forest using Time Series Analysis: Focused on Seasonal ARIMA and Exponential Smoothing model
• 발행기관: 관광경영학회
• 저자명: 최가영 이정희 유리화
• 간행물 정보: 『관광경영연구』제21권 제3호, 271~289쪽, 전체 19쪽
• 주제분류: 사회과학 > 관광학
• 파일형태: PDF
• 발행일자: 2017.05.31

영문 초록

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

Ⅰ. 서론

Ⅱ. 이론적 배경

Ⅲ. 연구설계

Ⅳ. 분석결과

Ⅴ. 결론

참고문헌

키워드

Forecasting Demand Time Series ARIMA Exponential Smoothing Forest Recreation