Asia-Pacific Journal of Business (아태비즈니스연구)

KNU The Institute of Management & Economy Research (강원대학교 경영경제연구소)
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Forecasting short-term transportation demand at Gangchon Station in Chuncheon-si using time series model

시계열모형을 활용한 춘천시 강촌역 단기수송수요 예측

  • Chang-Young Jeon (Department of Tourism Administration, Kangwon National University) ;
  • Jia-Qi Liu (Department of Tourism Administration, Kangwon National University) ;
  • Hee-Won Yang (Department of Innovative Growth Research, Research Institute for Gangwon)
  • 전창영 (강원대학교 관광경영학과 ) ;
  • 유가기 (강원대학교 관광경영학과) ;
  • 양희원 (강원연구원 혁신성장실)
  • Received : 2023.11.30
  • Accepted : 2023.12.22
  • Published : 2023.12.31
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Abstract

Purpose - This study attempted to predict short-term transportation demand using trains and getting off at Gangchon Station. Through this, we present numerical data necessary for future tourist inflow policies in the Gangchon area of Chuncheon and present related implications. Design/methodology/approach - This study collected and analyzed transportation demand data from Gangchon Station using the Gyeongchun Line and ITX-Cheongchun Train from January 2014 to August 2023. Winters exponential smoothing model and ARIMA model were used to reflect the trend and seasonality of the raw data. Findings - First, transportation demand using trains to get off at Gangchon Station in Chuncheon City is expected to show a continuous increase from 2020 until the forecast period is 2024. Second, the number of passengers getting off at Gangchon Station was found to be highest in May and October. Research implications or Originality - As transportation networks are improving nationwide and people's leisure culture is changing, the number of tourists visiting the Gangchon area in Chuncheon City is continuously decreasing. Therefore, in this study, a time series model was used to predict short-term transportation demand alighting at Gangchon Station. In order to calculate more accurate forecasts, we compared models to find an appropriate model and presented forecasts.

Keywords

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