While an ongoing labor dispute at the Port of Los Angeles is on the path to being settled, seafood importers' woes are far from over. "The estimate on the backlog being cleared up is three months, ...
With its safe and efficient characteristics, container transportation has become vital for advancing the global economy. However, port congestion has become a significant obstacle to the container freight price system's stability. There is currently no dependable engineering solution to guarantee the stability of the maritime transport system in a port congestion scenario. Therefore, decision-makers must comprehend the changing characteristics of the container freight index in the context of port congestion. Using the Shanghai container freight index as a proxy, this paper investigated the effect of port congestion on container freight rates, proposing a container freight index forecasting model. This study compiled congestion data from the Shanghai, Busan, Los Angeles, and New York ports from January 1, 2016 to January 1, 2023, to predict a Shanghai container freight index (SCFI). With its high-precision fitting effect, the RBF neural network effectively predicted the change in SCFI, and the R2 reached 96%. We also confirmed the transfer effect of SCFI using the time-lag correlation model in a large congestion environment. The research results give container shipping organizations a decision-making foundation for planning shipping strategies and mitigating market risk.