Probability estimation model for the cancellation of container slot booking in long-haul transports of intercontinental liner shipping services

Hui Zhao, Qiang Meng, Yadong Wang

Research output: Journal article publicationJournal articleAcademic researchpeer-review

15 Citations (Scopus)

Abstract

The intercontinental liner shipping services transport containers between two continents and they are crucial for the profitability of a global liner shipping company. In the daily operations of an intercontinental liner shipping service, however, container slot bookings from customers can be freely cancelled during a booking period, which causes loss of revenue and low utilization of ship capacity. Though a pain-point of the liner shipping industry, the container slot cancellation problem has not yet been well investigated in the literature. To fill this research gap, this study aims to estimate the probability for the cancellation of container slot booking in the long haul transports of the intercontinental liner shipping service by considering the primary influential factors of cancellation behavior. To achieve the objective, a container slot booking data-driven model is developed by means of a time-to-event modeling technique. To incorporate the effect of booking region on the cancellation probability, we introduce the frailty term in the model to capture the regionality of the container shipping market. Our case study with real slot booking data shows that the developed model performs well in forecasting the loaded containers of the slot booking requests. In addition, we shed light on how the internal factors of slot booking and external factors of shipping market influence the probability of cancellation. © 2020 Elsevier Ltd
Original languageEnglish
JournalTransportation Research Part C: Emerging Technologies
Volume119
DOIs
Publication statusPublished - Oct 2020
Externally publishedYes

Keywords

  • Commerce
  • Containers
  • Probability
  • Container shippings
  • Data-driven model
  • Developed model
  • External factors
  • Influential factors
  • Internal factors
  • Long-haul transport
  • Probability estimation
  • container ship
  • estimation method
  • numerical model
  • probability
  • profitability
  • shipping
  • Ships

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