Thesis/Capstone
Publication Date
Authored by
Pu Gao, Stephen Mei
Advisor(s): Chris Caplice
Topic(s) Covered:
  • Transportation
Abstract

Drayage, which involves transporting goods from ports to drop facilities, has become increasingly difficult to predict due to the volatility of macroeconomic conditions. As a result, our sponsor company, a third-party logistics (3PL), sought to identify the key macroeconomic indicators that affect drayage volume and whether these indicators vary by port. To do this, the study utilized SARIMAX, a time-series forecasting method that can incorporate external variables and capture trends, seasonality, and cycles in the data. The study revealed that Advanced Retail Sales, New Housing Units Built, Total Vehicle Sales, Unemployment Rate, Total Nonfarm, and CPI: Fuel were significant indicators on forecasting drayage volume. Moreover, the study found that these indicators varied across different ports. Leveraging SARIMAX and these macroeconomic indicators resulted in an average 21% increase in forecast accuracy compared with the seasonal Naïve method, which can help the company better allocate drayage capacity, improve resource planning, and reduce associated cost.

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