Identification of Container Dwell Time Determinants Using Aggregate Data

This article, from a special issue on port pricing, describes the use of aggregate data to identify container dwell time in ports. The authors identify the key factors that affect the dwell time (DT) of containers. Using aggregate data that were collected from the Terminal Operation Systems (TOS) of three container terminals, two in the Middle East and one in Asia, the authors developed Poisson regression models for each terminal. They found that terminal charging/pricing policies and customs inspection affect DT, particularly in ports that impose storage fees from the first day and which use more efficient customs inspection methods. Other factors that have an impact on dwell time are: container weight, container status (full or empty), billable line, seasonality, and day of the week for pick-up. When information on the receiver of goods and the commodity was available and incorporated in the Poisson regression models, the results were higher R2 and better model applicability. The authors conclude that their model highlights the importance of collecting information on both the commodity and the receiver of the goods in order to develop models that enhance decision-making in port container terminals.

  • Availability:
  • Authors:
    • Kourounioti, Ioanna
    • Polydoropoulou, Amalia
  • Publication Date: 2017-12


  • English

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  • Accession Number: 01675873
  • Record Type: Publication
  • Files: TRIS
  • Created Date: Jul 23 2018 2:13PM