A study on demand forecasting for Jeju-bound tourists by travel purpose using seasonal ARIMA-Intervention model

Song, Junmo

doi:10.7465/jkdi.2016.27.3.725

HOME > Journal Browse > About Journal > Journal Vol & Issue > Full Record

A study on demand forecasting for Jeju-bound tourists by travel purpose using seasonal ARIMA-Intervention model

Journal title : Journal of the Korean Data and Information Science Society
Volume 27, Issue 3, 2016, pp.725-732
Publisher : Korean Data and Information Science Society
DOI : 10.7465/jkdi.2016.27.3.725

Title & Authors

A study on demand forecasting for Jeju-bound tourists by travel purpose using seasonal ARIMA-Intervention model
Song, Junmo;

Abstract

This study analyzes the number of Jeju-bound tourists according to travellers` purposes. We classify the travellers` purposes into three categories: "Rest and Sightseeing", "Leisure and Sport", and "Conference and Business". To see an impact of MERS outbreak occurred in May 2015 on the number of tourists, we fit seasonal ARIMA-Intervention model to the monthly arrivals data from January 2005 to March 2016. The estimation results show that the number of tourists for "Leisure and Sport" and "Conference and Business" were significantly affected by MERS outbreak whereas arrivals for "Rest and Sightseeing" were little influenced. Using the fitted models, we predict the number of Jeju-bound tourists.

Keywords

Forecasting tourist demand;intervention analysis;MERS outbreak;seasonal ARIMA model;

Language

Korean

Cited by

1time(s) in KSCD

개선된 유전자 역전파 신경망에 기반한 예측 알고리즘,윤여창;조나래;이성덕;

Journal of the Korean Data and Information Science Society, 2017. vol.28. 6, pp.1327-1336

References

Box, G. E. P. and Tiao, G. C. (1975). Intervention analysis with applications to economic and environmental problems. Journal of the American Statistical Association, 70, 70-79.

Cho, S., Sohn, Y. and Seong, B. (2016). Time series analysis, Yulgok book publishing Co., Seoul.

Choi, K. and Kim, J. (2001). A study on forecasting of overseas tour - Gravity model and regression model. Journal of the Korean Data & Information Science Society, 12, 103-111.

Cryer, J. D. and Chan, K. S. (2008). Time series analysis: With applications in R, Springer-Verlag, New York.

Han, G. H., Jung, J. and Yoo, J. K. (2014). A study on prediction for attendances of Korean pro baseball games using covariates. Journal of the Korean Data & Information Science Society, 25, 1481-1489.

Huh, H. J. and Kim, H. C. (2001). Forecasting demand for Jeju-bound tourist: An application of intervention method. Journal of Tourism Sciences, 25, 27-42.

Kim, S. and Lee, J. H. (2011). A Study on the seasonal effects of the tourism demand forecasting models. Korean Journal of Applied Statistics, 24, 93-102.

Kim, S. and Seong, B. (2011). Intervention analysis of Korea tourism data. Korean Journal of Applied Statistics, 24, 735-743.

Lee, C. K, Song, H. J and Mjelde J.W. (2008). The forecasting of international Expo tourism using quantitative and qualitative techniques. Tourism Management, 29, 1084-1098.

10.

Phillips, P. C. B. and Perron, P. (1988). Testing for a unit root in time series regression. Biometrika, 75, 335-346.

11.

Ryu, S. R. and Kim, J. T. (2013). Time series regression model for forecasting the number of elementary school teachers. Journal of the Korean Data & Information Science Society, 24, 321-332.

12.

Shin, Y. and Yoon, S. (2016). Electricity forecasting model using specific time zone. Journal of the Korean Data & Information Science Society, 27, 275-284.

13.

Song, D. Y. (2015). A study on forecasting the number of tourist in Jeju island focusing on travel purposes and types with seasonal ARIMA models, Master Thesis, Jeju national university, Jeju.

14.

Song, H. and Li, G. (2008). Tourism demand modelling and forecasting - A review of recent research. Tourism Management, 29, 203-220.