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A comparative study on the accuracy of tourism forecasting models
Journal of the Korean Data & Information Science Society 2018;29:1629-41
Published online November 30, 2018
© 2018 Korean Data and Information Science Society.

Seong Sik Lim1

1College of Humanity and General Education, SeoKyeong University
Correspondence to: Professor, College of Humanity and General Education, SeoKyeong University, Seoul 02713, Korea. E-mail:
This Research was supported by Seokyeong University in 2018.
Received September 13, 2018; Revised October 31, 2018; Accepted November 4, 2018.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
This paper presents winters’ seasonal exponential smoothing model, seasonal ARIMA model and intervention analysis model as a demand forecasting model for tourists visiting Korea. The tourists is affected by external shock factors such as the tourism policies of the country or the domestic and international economic conditions. The purpose of this study is to find out the factors affecting the forecasting model and to find a time series model to predict the number of foreign tourists who visited Korea more efficiently. As a result of comparing the accuracy of forecasting models through empirical analysis, it was founded that the intervention analysis model reflecting the intervention effect was superior to the seasonal exponential smoothing model or the seasonal ARIMA model.
Keywords : Intervention model, seasonal ARIMA model, winters’ seasonal exponential smoothing model.