최적 시계열 수요예측 모델선정에 관한 연구 = Selecting Most Appropriate Time Series Forecasting Model

다국어 초록 (Multilingual Abstract)

This study aims to develop four time-series models in order to select the best model among the time-series models based on MAPE(mean absolute percentage error). The time-series models include various ones including ARIMA model. The first three models have been most popularly used for forecasting tourism demand, whereas the last model of ARIMA Intervention is reported to be more logical and accurate than any other time-series models since special events such as terrorism and mega-events can be incorporated into the model. The results of model estimation indicate that all the four forecasting models were found most accurate in terms of MAPE(Lewis, 1982). Of them the ARIMA Intervention model(MAPE=4.48) appeared to perform best in terms of forecasting accuracy, followed by ARIMA(MAPE=4.96), Winters(5.67), and Stepwise Autoregressive(8.55).핵심용어(Key words):예측정확도(Forecasting accuracy), 윈터스지수평활모델(Winters Exponential Smoothing model), 단계적 자기회귀모델(Stepwise Autoregressive model), ARIMA모델(ARIMA model), ARIMA 개입모델(ARIMA Intervention model).

국문 초록 (Abstract)

방한 일본인 관광객은 외래관광객 중 가장 큰 비중을 차지하면서 총 방한 외래관광객의 증감에 주도적 영향을 미치고 있다. 또한, 최근 경제성장과 국가간 교류증가에 따라 중국인 관광객이 미국인 관광객을 제치고 제2의 인바운드 시장으로 부상하고 있는데, 이러한 추세는 <그림 1>을 통해서도 가시적으로 확인할 수 있다.<표 1> 방한 외래객 방문현황과 관광환경 변화연도외래관광객성장률관광환경 변화19902,958,8398.5%-19913,196,3408.0%걸프전19923,231,0811.1%-19933,331,2263.1%대전엑스포 개최19943,580,0247.5%한국방문의 해19953,753,1974.8%-19963,683,779-1.8%-19973,908,1406.1%아시아 금융위기와 IMF19984,250,2168.8%한국경제위기 및 원화약세 지속 19994,659,7859.6%-20005,321,79214.2%인천국제공항개항20015,147,204-3.3%9.11 테러 발생 및 한국방문의 해20025,347,4683.9%한일 월드컵 공동개최20034,753,604-11.1%SARS 발병, 이라크전쟁20045,818,13822.4%한류열풍20056,021,7643.5%한일공동방문의 해 20066,155,0462.2%

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