The need for a comprehensive and reliable logistics system performance has been driven by the interrelations and interactions among seaport/terminal operations, customs and border protection organizations, warehouses and fulfillment centers, and last-mile delivery. To report these events and handle the fast pace of events, each subsystem has high-velocity events such as AIS reports, gate operations, inspection notifications, scans, and GPS location updates. These events can now be used to produce a series of events for predicting the possible arrival times and reporting possible congestion. This systematic review collated and collated the study and analysis by collecting different articles and studies related to logistics performances in the period covered by this systematic review, namely, from 2020 to 2025, namely, related to: (i) two-stage ETA prediction models that can include sea and overland components, related to bottleneck analysis and explanation for causations for delay propagation, and related to logistics architectures to make simulations and facilitate systemization and deployment. To outline systematic reviews following the procedure by Page and associates in 2021 and extensions by Rethlefsen and associates in 2021, articles and the highest quality studies in logistics and related topics have been collated. Based on the systematic reviews, based on articles that this systematic review has collated, extremely valuable and practical approaches emphasize event and entity time and uncertainty analysis, traceability, and analysis based on governance structures.
Supply Chain Visibility; Control Tower; ETA Prediction; Port Congestion; Customs Risk Management; Warehouse Analytics; Last?Mile Delivery; Bottleneck Detection; Digital Twin; Systematic Review.
IRE Journals:
Syed Hassan "End-To-End Analytics Across Ports, Customs, Warehouses, Last-Mile; ETA Prediction and Bottleneck Detection at Scale" Iconic Research And Engineering Journals Volume 9 Issue 7 2026 Page 1997-2008 https://doi.org/10.64388/IREV9I7-1713908
IEEE:
Syed Hassan
"End-To-End Analytics Across Ports, Customs, Warehouses, Last-Mile; ETA Prediction and Bottleneck Detection at Scale" Iconic Research And Engineering Journals, 9(7) https://doi.org/10.64388/IREV9I7-1713908