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A Study on Dynamic Change of Transportation Demand Using Seasonal ARIMA Model  

Lee, Jae-Min (경북대학교 경제통상학부)
Gwon, Yong-Jae (국민대학교 경영학부)
Publication Information
Journal of Korean Society of Transportation / v.29, no.5, 2011 , pp. 139-155 More about this Journal
Abstract
This study is to estimate the dynamic change of the regional railway passenger traffic and, based on the estimated, to forecast the future regional railway passenger traffic by using the Seasonal ARIMA model. The existing studies using ARIMA failed to consider seasonality nor the monthly or the quarterly data. It was attempted in this study to use the monthly regional railway passenger traffic data to propose a model that estimates dynamic change of demand. The authors employed the Seasonal ARIMA model previously developed and used (1) the numbers of monthly passenger data and (2) the monthly passenger-km data. The test results showed that the numbers of passengers in 2015 and 2020 would increase by 36% and 71%, respectively, compared to those in 2008. The numbers of passenger-kms in 2015 and 2020 would increase by 25% and 78%, respectively, compared to those in 2008.
Keywords
ARIMA; Seasonality; Seasonal ARIMA; Estimation; Forecast;
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