A comparative study of univariate models for container throughput forecasting of major ports in Asia. (February 2022)

• Record Type: Journal Article
• Authors: Huang, Juan; Chu, Ching-Wu; Hsu, Hsiu-Li
• Is Part Of: Proceedings of the Institution of Mechanical Engineers. Volume 236:Number 1(2022)
• Page Start: 160
• Page End: 173
• Publication Date: 2022-02
• Subjects: Container throughput forecasting -- univariate forecasting models -- forecasting accuracy comparison; Marine engineering -- Periodicals; 623.805
• DOI: 10.1177/14750902211023662
• Languages: English
• ISSNs: 1475-0902

Abstract

This study aims to make comparisons on different univariate forecasting methods and provides a more accurate short-term forecasting model on the container throughput for rendering a reference to relevant authorities. We collected monthly data regarding container throughput volumes for three major ports in Asia, Shanghai, Singapore, and Busan Ports. Six different univariate methods, including the grey forecasting model, the hybrid grey forecasting model, the multiplicative decomposition model, the trigonometric regression model, the regression model with seasonal dummy variables, and the seasonal autoregressive integrated moving average (SARIMA) model, were used. We found that the hybrid grey forecasting model outperforms the other univariate models. This study's findings can provide a more accurate short-term forecasting model for container throughput to create a reference for port authorities.