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Logistics
Volume 10
Issue 7
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Logistics, Volume 10, Issue 7 (July 2026) – 2 articles

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24 pages, 1234 KB  
Article
Modeling the Resilience of Agricultural Intermodal Logistics in Kazakhstan Under Dynamic Export Demand and Infrastructure Constraints
by Aizhan Kamysbayeva, Alisher Khussanov, Botagoz Kaldybayeva, Oleksandr Prokhorov, Zhakhongir Khussanov, Saule Bekzhanova, Marat Sabyrkhanov and Aikerim Issayeva
Logistics 2026, 10(7), 143; https://doi.org/10.3390/logistics10070143 (registering DOI) - 24 Jun 2026
Abstract
Background: Agricultural logistics in Kazakhstan is critical for export-oriented supply chains, but its resilience is limited by infrastructure constraints, fluctuating export demand, and insufficient coordination between market and logistics processes. Methods: This study develops a conceptual multi-level model of the agricultural [...] Read more.
Background: Agricultural logistics in Kazakhstan is critical for export-oriented supply chains, but its resilience is limited by infrastructure constraints, fluctuating export demand, and insufficient coordination between market and logistics processes. Methods: This study develops a conceptual multi-level model of the agricultural logistics system and a hybrid simulation model combining system dynamics and discrete-event simulation to analyze intermodal transportation under demand and capacity constraints. The model integrates demand formation, storage, transport, and export operations, as well as feedback mechanisms between fulfilled demand, repeat orders, and logistics performance. The model is implemented in AnyLogic 8.9. Results: The conceptual model structures the interaction of key participants, logistics facilities, and infrastructure levels within Kazakhstan’s agricultural logistics system. Simulation experiments reproduce cyclic logistics behavior and show that reduced logistics capacity increases the demand gap and system pressure, while stronger market signals intensify demand and infrastructure load. The results confirm that resilience depends on the balance between demand activation, logistics capacity, and replenishment policy. Conclusions: The proposed approach provides a tool for analyzing the resilience of agricultural intermodal logistics in Kazakhstan and supports scenario-based evaluation of infrastructure and market factors. The novelty lies in combining a conceptual multi-level logistics model with hybrid simulation of demand and logistics flows. Full article
(This article belongs to the Special Issue Logistics and Supply Chain Challenges and Solutions in the Turbulent World)
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Article
Sustainable and Smart Logistics Transition in European Maritime–Port Systems: A Decision Tree Classification Approach
by Nicoletta González-Cancelas, Beatriz Molina-Serrano, Francisco Soler-Flores and Javier Vaca-Cabrero
Logistics 2026, 10(7), 142; https://doi.org/10.3390/logistics10070142 (registering DOI) - 23 Jun 2026
Abstract
Background: Sustainable and smart logistics transition requires tools that connect environmental, energy, social and digital performance with transport structure. This study proposes an exploratory classification framework for European maritime–port logistics systems using Eurostat-based country-year observations. Methods: A composite transition profile was constructed from [...] Read more.
Background: Sustainable and smart logistics transition requires tools that connect environmental, energy, social and digital performance with transport structure. This study proposes an exploratory classification framework for European maritime–port logistics systems using Eurostat-based country-year observations. Methods: A composite transition profile was constructed from environmental, energy, social and digital indicators using min–max normalization, equal weighting and tercile classification into low, medium and high profiles. A shallow decision tree classifier was applied to identify transport, modal structure and maritime–port activity variables that discriminate between profiles. Results: Road freight transport intensity was the main discriminator, followed by inland passenger modal structure variables. Maritime–port activity variables were included in the initial predictor set but were not retained by the final tree, indicating that transition profiles are more strongly differentiated by inland logistics and modal configuration at the country-year level. The model showed moderate performance, with a five-fold cross-validated accuracy of 0.561, above the majority-class baseline. Conclusions: The framework provides an interpretable diagnostic tool for identifying logistics-related transition patterns and supporting sustainable logistics planning. Its exploratory scope and data limitations are explicitly acknowledged. Full article
(This article belongs to the Section Maritime and Transport Logistics)
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