Modelling the factors affecting port time variability

Despite decades of attention to port performance measurement, prevailing benchmarking frameworks rely almost exclusively on mean turnaround time, systematically suppressing information about variance, the dimension most consequential for supply chain schedule reliability. This study addresses that gap by proposing Port Time Variability (PTV) as a standardised reliability metric, operationalised as the coefficient of variation of port time derived from high-frequency Automatic Identification System (AIS) data. Key factors are innovatively extracted from Automatic Identification System (AIS) data and country-level port data, capturing port dynamics and complex vessel flow network metrics. Structural equation modelling (SEM) is employed to assess their influence on port time variability, measured as the statistical dispersion of port call durations across 401 ports in 119 countries. The findings reveal that high-quality port infrastructure and geographically favourable locations enhance port logistics efficiency, leading to reduced port time variability. Additionally, port infrastructure quality, location conditions, and network connectivity positively influence port dynamic flow. Port network connectivity and dynamic flow partially mediate the relationship between location conditions and port time variability. Crucially, the analysis demonstrates that ports trapped in a vicious cycle of low investment, poor service responsiveness, and reduced vessel calls exhibit systematically higher PTV, a pattern consistent with rent-seeking dynamics identified in institutional port economics. These insights contribute to developing strategic port management approaches aimed at improving operational efficiency, reducing congestion and delays, and guiding long-term infrastructure investments to strengthen inter-port connectivity.