Temporal Alignment between Truck Booking Timeslots and Vessel Schedules

Container ports are characterised by an inherent coordination problem between seaside vessel operations and landside truck booking activity. While vessel schedules are theoretically the primary driver of import and export container flows, the empirical extent to which truck appointment bookings are temporally aligned with vessel arrivals and departures remains poorly understood, limiting the design of effective truck appointment systems (TAS) and demand management policies. This study explores this question using four months of operational TAS data combined with vessel schedule records for the same period from two container terminals at Port Botany, Sydney, Australia. Five complementary statistical methods are applied, including Autoregressive Distributed Lag (ARDL) models with Granger causality tests. Disaggregated analysis by commodity type reveals that dangerous goods containers exhibit significantly stronger and more concentrated vessel-schedule sensitivity than general, refrigerated, or empty containers, consistent with regulatory terminal storage constraints accelerating retrieval. To support practical application of the findings, an interactive prediction tool is provided that allows terminal operators and port planners to estimate the expected change in daily truck booking demand for any combination of vessel arrival and departure counts, with user-adjustable baseline demand and built-in validity indicators. The findings provide an empirical basis for calibrating container-availability-based booking reforms, informing terminal-specific and commodity-differentiated TAS design, and evaluating the trade-off between planning flexibility for transport operators and slot efficiency for terminal operators.