Using Time Series Analysis Forecast Post-Covid-19 Period Deep Sea Freight Transportation Index
DOI:
https://doi.org/10.54691/bcpbm.v34i.3154Keywords:
Time Series, Deep Sea Freight Transportation, Exponential Smoothing.Abstract
This paper is a study to predict the trend of the Deep Sea Freight Transportation Index after the end of COVID-19 using ETS modeling in the context of the abnormal increase in the Deep Sea Freight Transportation Index due to the COVID-19 epidemic using time series analysis. The purpose of the study is to help international supply chain practitioners and shipping companies to make risk assessments in advance at the decision-making level. In the methodology section, the primary dataset used is the US Deep Sea Freight Transportation Index and the secondary dataset is the WTI Crude Oil Index. The forecast result is that the U.S. Deep Sea Freight Transportation Index will remain high for the next two years, and the WTI Crude Oil Index supports the accuracy of this forecast in its forecast plot based on its correlation with the Deep Sea Freight Transportation Index. Therefore, this study suggests that international supply chain operators and shipping operators should respond to the continued high ocean shipping costs in the next two years to avoid inventory risk and profit decline.
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