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Volume 9
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Logistics, Volume 9, Issue 4 (December 2025) – 41 articles

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30 pages, 1117 KB  
Article
Sustainable Procurement Barriers in Indonesian Food Manufacturing SMEs: An ISM–Fuzzy MICMAC Analysis
by Ilyas Masudin, Intan Dwi Lestari, Amelia Khoidir and Dian Palupi Restuputri
Logistics 2025, 9(4), 175; https://doi.org/10.3390/logistics9040175 - 1 Dec 2025
Viewed by 245
Abstract
Background: This study aims to examine the barriers hindering the implementation of sustainable procurement in Indonesian small and medium-sized enterprises (SMEs) and to identify their hierarchical relationships. Methods: A mixed-method approach was adopted, employing Interpretive Structural Modeling (ISM) to map the [...] Read more.
Background: This study aims to examine the barriers hindering the implementation of sustainable procurement in Indonesian small and medium-sized enterprises (SMEs) and to identify their hierarchical relationships. Methods: A mixed-method approach was adopted, employing Interpretive Structural Modeling (ISM) to map the causal structure of barriers and Fuzzy MICMAC analysis to classify them according to their influence and dependence. Data were collected through expert evaluations and secondary sources, providing both empirical depth and contextual validity. Results: The results reveal that financial constraints, particularly funding limitations, are the most critical and independent barrier driving the entire system of obstacles. The analysis further shows that systemic linkage barriers, such as minimal government incentives, limited availability of eco-friendly raw materials, and high import dependency, create a self-reinforcing cycle that amplifies cost challenges for SMEs. Dependent barriers, including regulatory inadequacies and weak supplier collaboration, are identified as outcomes of these structural constraints, while autonomous barriers like limited consumer awareness remain less influential but still significant. Conclusions: These findings demonstrate that sustainable procurement barriers are not isolated but interconnected, with financial viability acting as the foundational challenge. The study contributes to the literature by providing a relational perspective on sustainable procurement barriers, offering managerial insights for policy. Full article
(This article belongs to the Section Supplier, Government and Procurement Logistics)
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20 pages, 13220 KB  
Article
Prioritization Model for the Location of Temporary Points of Distribution for Disaster Response
by María Fernanda Carnero Quispe, Miguel Antonio Daza Moscoso, Jose Manuel Cardenas Medina, Ana Ysabel Polanco Aguilar, Irineu de Brito Junior and Hugo Tsugunobu Yoshida Yoshizaki
Logistics 2025, 9(4), 174; https://doi.org/10.3390/logistics9040174 - 29 Nov 2025
Viewed by 193
Abstract
Background: Disasters generate abrupt surges in humanitarian demand, requiring response strategies that balance operational performance with vulnerability considerations. This study examines how temporary Points of Distribution (PODs) can be planned and activated to support timely and equitable resource distribution after a high-magnitude earthquake. [...] Read more.
Background: Disasters generate abrupt surges in humanitarian demand, requiring response strategies that balance operational performance with vulnerability considerations. This study examines how temporary Points of Distribution (PODs) can be planned and activated to support timely and equitable resource distribution after a high-magnitude earthquake. Methods: A two-stage framework is proposed. First, a modular p-median model identifies POD locations and allocates modular capacity to minimize population-weighted distance under capacity constraints; travel-distance percentiles guide the selection of p. Second, a SMART-based multi-criteria model ranks facilities using operational metrics and vulnerability indicators, including seismic and economic conditions and the presence of at-risk groups. Results: Evaluation of p values from 3 to 30 shows substantial reductions in travel distances as PODs increase, with an elbow at p=12, where 50% of the residents are within 500 m, 75% within 675 m, and 95% within 1200 m. The SMART analysis forms three priority clusters: facilities 24 and 9 as highest priority; 23, 4, 12, and 22 as medium priority; and the remaining sites as lower priority. Sensitivity analysis shows that rankings are responsive to vulnerability weights, although clusters remain stable. Conclusions: The framework integrates optimization and multi-criteria decision analysis without increasing model complexity, enabling meaningful decision-maker involvement throughout the modeling process. Full article
(This article belongs to the Section Humanitarian and Healthcare Logistics)
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23 pages, 2760 KB  
Systematic Review
Supply Chain in the Age of Industry 4.0: A Literature Review
by Samia Haman, Anass Ben Abdelouahab, Younes El Bouzekri El Idrissi, Safae Merzouk and Aniss Moumen
Logistics 2025, 9(4), 173; https://doi.org/10.3390/logistics9040173 - 29 Nov 2025
Viewed by 512
Abstract
Background: The rapid digital transformation driven by Industry 4.0 technologies is reshaping manufacturing supply chains, yet comprehensive insights into how these technologies are integrated remain limited. Methods: This study addresses this research gap by conducting a systematic bibliometric analysis and literature review of [...] Read more.
Background: The rapid digital transformation driven by Industry 4.0 technologies is reshaping manufacturing supply chains, yet comprehensive insights into how these technologies are integrated remain limited. Methods: This study addresses this research gap by conducting a systematic bibliometric analysis and literature review of integrating Industry 4.0 technologies in the manufacturing supply chain. We used different scientific databases, Scopus and Web of Science, to elaborate this study. Results: Using advanced bibliometric methods, this study examines the evolution of academic discourse, identifies key themes, and maps the intellectual structure of this transformative research field. By leveraging bibliometric tools, the study names the most prolific authors, countries, and journals contributing to this domain. The findings of the first phase reveal the growing focus on topics like supply chain resilience and real-time decision-making, while also finding gaps in the literature related to technology integration. In the second phase, the literature review identified the most used adoption models in empirical studies such as resource-based view, dynamic capabilities view, and technology acceptance model, we also categorized the adoption drivers into technological, organizational, and environmental. Conclusions: This review emphasizes that although research on Industry 4.0 has expanded significantly, the majority of studies predominantly concentrate on technology adoption and quantitative analysis, with little examination of integration, contextual factors, and longitudinal effects. Full article
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20 pages, 2602 KB  
Article
Agent-Based Simulation Modeling of Multimodal Transport Flows in Transportation System of Kazakhstan
by Alisher Khussanov, Botagoz Kaldybayeva, Oleksandr Prokhorov, Zhakhongir Khussanov, Doskhan Kenzhebekov, Mukhamediyar Yevadilla and Dauren Janabayev
Logistics 2025, 9(4), 172; https://doi.org/10.3390/logistics9040172 - 28 Nov 2025
Viewed by 235
Abstract
Background: Kazakhstan’s transport system plays a key role in Eurasian logistics due to its position along the Middle Corridor. However, multimodal freight transport remains under-optimized due to infrastructure bottlenecks, uneven cargo flows, and limited digital tools for forecasting and planning. Methods: This study [...] Read more.
Background: Kazakhstan’s transport system plays a key role in Eurasian logistics due to its position along the Middle Corridor. However, multimodal freight transport remains under-optimized due to infrastructure bottlenecks, uneven cargo flows, and limited digital tools for forecasting and planning. Methods: This study presents the development of an agent-based simulation model for analyzing multimodal transportation in Kazakhstan. The model integrates railway, road, and maritime components, simulating cargo flows across export, import, and transit scenarios. Key agents include orders, transport vehicles, logistics hubs, and border checkpoints. The model is implemented in AnyLogic 8.9 and calibrated using a mix of official statistics, industry data, and field estimates. Results: The simulation replicates key logistics processes, identifies congestion points, and evaluates delivery performance under different scenarios. Experiments demonstrate how bottlenecks at terminals and border crossings affect delivery times, vehicle utilization, and hub load. The model allows testing infrastructure development options and scheduling policies. Conclusions: The approach enables a dynamic assessment of logistics efficiency under uncertainty and can support decision-making in transport planning. The novelty lies in the integrated simulation of multimodal freight flows with infrastructure constraints. The model serves as a foundation for digital twin applications and scenario-based planning. Full article
(This article belongs to the Section Artificial Intelligence, Logistics Analytics, and Automation)
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33 pages, 2265 KB  
Article
System Dynamics Modeling of the Jute Stick Charcoal (JSC) Supply Chain: Logistics and Policy Strategies for Sustainable Rural Industrialization in Bangladesh
by Mohammad Shamsuddoha, Ahamed Ismail Hossain, Irma Dewan and Kazi Farzana Nur
Logistics 2025, 9(4), 171; https://doi.org/10.3390/logistics9040171 - 25 Nov 2025
Viewed by 549
Abstract
Background: Jute, recognized as the ‘golden fiber’ of Bangladesh, produces a substantial amount of stick left over (waste), a byproduct of the fiber. Usually, unused jute sticks (JS) are thrown away or burned, since they are treated as landfill or unusable waste. [...] Read more.
Background: Jute, recognized as the ‘golden fiber’ of Bangladesh, produces a substantial amount of stick left over (waste), a byproduct of the fiber. Usually, unused jute sticks (JS) are thrown away or burned, since they are treated as landfill or unusable waste. Noteworthy research gaps exist in the farming process, infrastructure, [supply chains], unfavorable policies, government interference, and insufficient farmers’ knowledge of the export market. This research examines the potential of jute stick charcoal (JSC) as a sustainable and value-added product within the circular economy framework. Methods: This study employs a system dynamics (SD) modeling approach to examine how various factors, including agricultural output, supply chain process efficiency, trade flows, and relevant variables, influence JSC supply chain performance. Considering technologies, logistics, and policy variables, this study constructed a simulation model with three scenarios: current, worst-case, and improved, using Vensim DSS to identify system behavior under changing conditions. Results: The simulation indicates that optimizing idle jute resources, enhancing supply chain processes, and expanding markets can increase economic returns, reduce waste, and create more rural jobs, particularly for women. Conclusions: Enhanced coordination, technologies, and logistics can reduce carbon emissions, benefit farmers, support rural industries, and contribute to SDGs 8, 12, and 13. Full article
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19 pages, 1561 KB  
Article
Inventory Management and Its Influence on the Supply of High-Value Products: Case Study Evidence
by Ângela Silva, Márcia Silva and Ana Cristina Ferreira
Logistics 2025, 9(4), 170; https://doi.org/10.3390/logistics9040170 - 25 Nov 2025
Viewed by 1076
Abstract
Background: In the context of increasing supply chain complexity, efficient inventory management has become important in enhancing the performance of logistics systems and sustaining the competitiveness of companies. Real-time visibility, tracking, and control over stock levels ensure responsiveness, reduce waste, and support [...] Read more.
Background: In the context of increasing supply chain complexity, efficient inventory management has become important in enhancing the performance of logistics systems and sustaining the competitiveness of companies. Real-time visibility, tracking, and control over stock levels ensure responsiveness, reduce waste, and support strategic decision-making. Decision support systems that integrate demand analysis with inventory policies play a pivotal role in improving operational efficiency. This paper addresses the need for more efficient stock management to optimize purchasing and inventory costs within a manufacturing environment. Methods: Production planning processes were analyzed to determine material requirements, and a representative product was selected. The study involved ABC classification based on the average annual stock value of purchased parts, complemented by an XYZ analysis to evaluate demand variability. Afterwards, stock management policies were tested, namely, continuous and periodic review models. Each item was assessed to determine the most suitable inventory management method based on its consumption profile. Results: A comparison with the company’s existing approach revealed that for 9 out of the 13 materials studied, the application of stock management models led to improvements. Conclusions: The results show a potential cost reduction of 33% for the nine materials to which stock policies were successfully applied. Full article
(This article belongs to the Section Sustainable Supply Chains and Logistics)
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20 pages, 2015 KB  
Article
Logistical and Economic Feasibility in the Cheese Production Chain: A Study Using Monte Carlo Simulation
by Gustavo Alves de Melo, Luiz Gonzaga de Castro Júnior, Maria Gabriela Mendonça Peixoto, José Willer do Prado, Andre Luiz Marques Serrano and Thiago Henrique Nogueira
Logistics 2025, 9(4), 169; https://doi.org/10.3390/logistics9040169 - 25 Nov 2025
Viewed by 329
Abstract
Background: Agricultural production plays a vital role in the global economy by integrating different sectors and promoting capital circulation across industries. In this context, the dairy sector emerges as a promising avenue for investment. This study aims to assess the economic feasibility [...] Read more.
Background: Agricultural production plays a vital role in the global economy by integrating different sectors and promoting capital circulation across industries. In this context, the dairy sector emerges as a promising avenue for investment. This study aims to assess the economic feasibility of establishing a dairy plant for the production of parmesan and mozzarella cheeses in Lavras, MG, considering both deterministic and probabilistic scenarios. Methods: The analysis was conducted in three stages: data collection, deterministic economic feasibility analysis using traditional financial indicators (NPV, IRR, profitability rate, and payback), and a probabilistic assessment using the Monte Carlo simulation with 100,000 iterations to incorporate uncertainty into the model. Results: The deterministic results indicated a positive Net Present Value (NPV), Internal Rate of Return (IRR) exceeding the Minimum Attractiveness Rate (MAR), and a profitability rate above 1.5, validating the investment’s viability. The probabilistic analysis reinforced these findings, with over 80% of simulated scenarios resulting in a positive NPV and over 77% showing IRR above the MAR. Key variables influencing profitability included market share, Class AB cheese consumer percentage, parmesan markup, operational costs, and per capita cheese consumption. Conclusions: The study confirms the economic feasibility of implementing the proposed dairy plant. The integration of Monte Carlo Simulation enhanced the robustness of the analysis by accounting for uncertainty, providing valuable insights for strategic decision-making. The project presents strong potential for regional development, job creation, and income generation. Full article
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28 pages, 5150 KB  
Systematic Review
Bridging Theory and Practice: A Comprehensive Framework for Digital Supply Chain Orchestration Through Big Data Analytics
by Samrena Jabeen, Mudassar Khan, Sabeen Hussain Bhatti, Nohman Khan, Mohammad Falahat and Muhammad Imran Qureshi
Logistics 2025, 9(4), 168; https://doi.org/10.3390/logistics9040168 - 25 Nov 2025
Viewed by 429
Abstract
Background: Digital supply chain transformation research exhibits a critical gap, examining technologies in isolation rather than as integrated ecosystems. Methods: This study addresses this limitation by developing a comprehensive orchestration frame-work through PRISMA-guided systematic review of 96 publications (2012–2024) using bibliometric [...] Read more.
Background: Digital supply chain transformation research exhibits a critical gap, examining technologies in isolation rather than as integrated ecosystems. Methods: This study addresses this limitation by developing a comprehensive orchestration frame-work through PRISMA-guided systematic review of 96 publications (2012–2024) using bibliometric analysis, structural topic modeling, and thematic synthesis across Scopus and Web of Science databases. Results: Analysis revealed three distinct research clusters: Supply Chain Management (centrality: 14.95), Digital Transformation (centrality: 9.50, density: 101.05), and Big Data Analytics (density: 113.22), with substantial negative correlations (−0.48 to −0.54) indicating organizational evolution from fragmented adoption toward integration. Conclusions: Publications increased 78% year-over-year during 2021–2022, while Supply Chain Management dominated topic prevalence (41%) and Big Data Analytics declined from 0.9 to 0.15 as practices normalized. The Digital Supply Chain Orchestration Framework conceptualizes transformation as multi-layered with hierarchical relationships between foundational domains, technological enablers, integration mechanisms, and value creation dimensions. This framework provides structured approaches for organizations to assess digital maturity, identify technological gaps, and develop strategic roadmaps aligned with Sustainable Development Goals, bridging theory and practice for integrated, value-driven digital transformation. Full article
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25 pages, 1881 KB  
Article
RFID-Enhanced Modified Two-Bin System for Reducing Excess Inventory of FMCG Industry
by Shuvojit Das, Gazi Md. Mahbubul Alam Rajin, Md. Nazmul Hasan Sarker, Md. Mahraj Uddin, Golam Sakaline and Edit Süle
Logistics 2025, 9(4), 167; https://doi.org/10.3390/logistics9040167 - 24 Nov 2025
Viewed by 502
Abstract
Background: Globally, in the Fast-Moving Consumer Goods (FMCG) industry, excess inventory results from the bullwhip effect. Earlier, barcode-based two-bin systems were limited by manual scanning; hence, a more responsive system is needed to align the inventory with real-time demand. Prior studies have [...] Read more.
Background: Globally, in the Fast-Moving Consumer Goods (FMCG) industry, excess inventory results from the bullwhip effect. Earlier, barcode-based two-bin systems were limited by manual scanning; hence, a more responsive system is needed to align the inventory with real-time demand. Prior studies have predominantly concentrated on mitigating demand fluctuations and employed comparatively low-efficiency systems, hindering excess inventory (EI) reduction. Methods: This study proposes identifying research gaps, considering the distributor-manufacturer relationship, and developing an RFID-based modified two-bin system and mathematical model to reduce EI and control over manufacturers’ excessive cost. Results: This study tested through Python-based simulation using historical data from an FMCG manufacturer, and the proposed model achieved a reduction in 67% EI and 73% month-wise holding costs. Moreover, the integration of the Artificial Bee Colony algorithm optimizes rework rates within budget, including reworking shop-floor and holding costs, contributing to a monthly excessive cost reduction of 34–48%, alongside a corresponding 41–44% cumulative excessive cost reduction. Conclusions: Bringing significant implications on digitalized SCM, this study offers a practical and scalable solution for perishable FMCG items facing demand variability and budget constraints. Collectively, this novel perspective bridges research gaps and motivates future research for embedding trend-aligned parameters, enhancing the model’s performance through diverse SCM contexts like safety stock and backorder cost optimization. Full article
(This article belongs to the Special Issue Logistics and Supply Chain Challenges and Solutions in the Turbulent World)
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26 pages, 2310 KB  
Article
Probabilistic Analysis of Meat Distribution Logistics: Application of Monte Carlo Simulation
by Gustavo Alves de Melo, Luiz Gonzaga de Castro Júnior, Maria Gabriela Mendonça Peixoto, Samuel Borges Barbosa, André Luiz Marques Serrano, Caroline Cambraia Furtado Campos, Matheus Vanzela and Ana Paula Dalmagro Delai
Logistics 2025, 9(4), 166; https://doi.org/10.3390/logistics9040166 - 24 Nov 2025
Viewed by 486
Abstract
Background: The food sector plays a critical role in promoting population well-being and contributes significantly to economic, social, and environmental development. However, inefficiencies in distribution logistics often result in elevated operational costs, potentially compromising the viability of enterprises in this sector. This [...] Read more.
Background: The food sector plays a critical role in promoting population well-being and contributes significantly to economic, social, and environmental development. However, inefficiencies in distribution logistics often result in elevated operational costs, potentially compromising the viability of enterprises in this sector. This study focuses on evaluating the economic feasibility of a fresh beef and pork distribution center in the southern region of Minas Gerais, Brazil. Methods: A case study methodology with a quantitative approach was adopted. Methodological triangulation was applied by combining a traditional Economic Feasibility Analysis (EFA) with a Monte Carlo Simulation to incorporate uncertainty in key input variables. This approach enabled a comprehensive assessment of project viability under both deterministic and probabilistic conditions. Results: The results indicated that distribution price per kilogram, market share, population growth, and per capita meat consumption had a positive correlation with profitability. The economic analysis confirmed the viability of the proposed distribution center, with high expected profitability and a short payback period. The Monte Carlo Simulation revealed that market share, unit price, and consumption levels are the most influential drivers of financial performance, while logistics costs represent the main limiting factor. Conclusions: This study provides a robust, data-driven framework for investment decision-making in food logistics infrastructure. It demonstrates the value of integrating deterministic and probabilistic analyses to improve risk management and strategic planning in the food distribution sector. Full article
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37 pages, 818 KB  
Article
On the Optimality of State-Dependent Base-Stock Policies for an Inventory System with PH-Type Disruptions
by Davide Castellano
Logistics 2025, 9(4), 165; https://doi.org/10.3390/logistics9040165 - 21 Nov 2025
Viewed by 506
Abstract
Background: The management of inventory under realistic supply chain disruptions, which are often non-exponential, challenges classical control theory. This study addresses the critical question of whether the optimality of simple base-stock policies holds under the combined influence of non-exponential disruptions and random yield. [...] Read more.
Background: The management of inventory under realistic supply chain disruptions, which are often non-exponential, challenges classical control theory. This study addresses the critical question of whether the optimality of simple base-stock policies holds under the combined influence of non-exponential disruptions and random yield. Methods: We model the system as a Piecewise Deterministic Markov Process (PDMP) with impulse control, using Phase-Type (PH) distributions to capture non-memoryless event timings. The analysis involves proving the existence of a solution to the Average Cost Optimality Equation (ACOE) via a vanishing discount approach, and the framework is validated with a numerical experiment. Results: Our primary finding is a rigorous proof that a state-dependent base-stock policy is optimal, a significant generalisation of classical theory. We establish this by demonstrating the value function’s convexity. The numerical experiment quantifies the significant cost penalties (over 12%) incurred by using simpler, memoryless models for supply disruptions. Conclusions: The study provides a crucial theoretical justification for the robustness of simple threshold-based control policies in complex, realistic settings. It highlights for managers the importance of modelling the variability of disruptions, not just their average duration, to avoid costly strategic errors. Full article
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23 pages, 2092 KB  
Article
A Data-Driven Framework for Agri-Food Supply Chains: A Case Study on Inventory Optimization in Colombian Potatoes Management
by Daniel Muñoz Rojas, Jairo R. Montoya-Torres and Diana M. Ayala Valderrama
Logistics 2025, 9(4), 164; https://doi.org/10.3390/logistics9040164 - 21 Nov 2025
Viewed by 644
Abstract
Background: Mitigating the negative impacts of climate change and ensuring food security are critical challenges for sustainable development. Potato crops play a key role in global food security, and optimizing their supply chains can improve yields, reduce waste, and stabilize farmer incomes. This [...] Read more.
Background: Mitigating the negative impacts of climate change and ensuring food security are critical challenges for sustainable development. Potato crops play a key role in global food security, and optimizing their supply chains can improve yields, reduce waste, and stabilize farmer incomes. This study focuses on the potato supply chain in Boyacá, Colombia, aiming to maximize profitability for smallholder farmers through a data-driven approach. Methods: We developed a hybrid framework combining the newsvendor model, Monte Carlo simulation, and machine learning to optimize inventory decisions under uncertain demand and price conditions. Historical data on potato demand and prices were analyzed to fit probability distributions, and simulation scenarios were run for three main potato varieties. Results: The results show that integrating these methods improves inventory decision-making, with the Criolla Colombia variety yielding positive profitability, while the Diacol Capiro and Pastusa Suprema varieties incur losses under current market conditions. The machine learning model enhances predictive accuracy and supports dynamic planning. Conclusions: The findings demonstrate the potential of advanced analytics to reduce waste, support sustainable practices, and inform agricultural policy. The proposed methodology offers a practical decision-support tool for stakeholders and can be adapted to other crops and regions facing similar operational challenges. Full article
(This article belongs to the Section Artificial Intelligence, Logistics Analytics, and Automation)
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15 pages, 1311 KB  
Article
Optimization of Engineering Vehicle Scheduling in Shipbuilding and Repair Yards Based on the Dual-Cycle Strategy
by Jianhua Zhou, Haifei Wu, Hailong Weng, Lijun He, Wenfeng Li and Taiwei Yang
Logistics 2025, 9(4), 163; https://doi.org/10.3390/logistics9040163 - 20 Nov 2025
Viewed by 353
Abstract
Background: As a labor-, capital-, and technology-intensive sector, shipbuilding supports water transportation, international trade, and marine development, driving economic growth and employment. Yet rising raw material/labor costs now bottleneck enterprise performance, making cost reduction and efficiency improvement urgent for shipbuilding and repair firms. [...] Read more.
Background: As a labor-, capital-, and technology-intensive sector, shipbuilding supports water transportation, international trade, and marine development, driving economic growth and employment. Yet rising raw material/labor costs now bottleneck enterprise performance, making cost reduction and efficiency improvement urgent for shipbuilding and repair firms. It is an effective way to improve logistics transportation efficiency for reducing the cost of shipbuilding and repair firms. However, there are still few methods specifically designed for logistics transportation scheduling in shipbuilding and repair firms. Methods: In this paper, a “dual-cycle” strategy is proposed to optimize material transportation and cut logistics vehicles’ empty-load rate in the shipbuilding and repair process. A mixed-integer programming model is built to minimize total empty travel time, considering task priorities and time windows. A genetic algorithm-based scheduling method is proposed to solve this complex scheduling model. Results: Simulation with real shipyard logistics data shows the proposed model and algorithm can effectively address the shipbuilding logistics vehicle scheduling problem. In addition, the proposed algorithm performs better than two other compared algorithms in handling the studied problem. Conclusions: This study aids shipbuilding and repair logistics managers in making scheduling plans and determining optimal vehicle numbers, supporting cost-efficiency improvement. Full article
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17 pages, 1626 KB  
Article
Modal Distribution Diversification and Intermodal Transport Analysis in Europe: A Comprehensive Investigation of Freight Transport Patterns
by Ana Castro, Gabriel Ludke, Vânia Dias, Sónia Longras, Edit Sule, Estela Vilhena and António Rocha
Logistics 2025, 9(4), 162; https://doi.org/10.3390/logistics9040162 - 18 Nov 2025
Viewed by 671
Abstract
Background: This study analyzes modal distribution patterns across Europe and 28 European countries, employing clustering analysis to identify trends in transport mode utilization. The research quantifies logistics diversification, examining extreme cases and addressing gaps in understanding modal transitions affecting environmental and economic [...] Read more.
Background: This study analyzes modal distribution patterns across Europe and 28 European countries, employing clustering analysis to identify trends in transport mode utilization. The research quantifies logistics diversification, examining extreme cases and addressing gaps in understanding modal transitions affecting environmental and economic performance. Methods: Statistical testing using compositional data transformations revealed significant differences between modal distributions (p < 0.001), justifying country-specific and European-level assessments. K-means clustering was applied to identify groups of countries with similar modal distribution patterns. Results: Maritime and road transport constitute the predominant modes across all analyzed countries in the study period. Among terrestrial modes, road transport dominates universally, exhibiting systematic growth, while rail transport experienced a corresponding decline. This trend directly contradicts European sustainability objectives promoting modal shift toward environmentally superior alternatives. Romania demonstrates the highest logistics diversification with the most balanced modal distribution, while Portugal exhibits the lowest diversification due to maritime transport dominance. K-means clustering positioned Portugal within a maritime-dominated group alongside Greece, Cyprus, and Ireland, reflecting similar geographical constraints and distribution patterns. Conclusions: The findings reveal critical aspects requiring further investigation concerning European modal distribution trends that challenge current policy effectiveness, highlighting the divergence between observed transport patterns and stated sustainability goals. These results provide essential insights for addressing persistent modal shift challenges in European transport systems. Full article
(This article belongs to the Special Issue Logistics and Supply Chain Challenges and Solutions in the Turbulent World)
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27 pages, 917 KB  
Systematic Review
The Impact of IoT-Enabled Routing Optimization on Waste Collection Distance: A Systematic Review and Meta-Analysis
by Rafael R. Maciel, Adler Diniz de Souza, Rodrigo M. A. Almeida and João Paulo R. R. Leite
Logistics 2025, 9(4), 161; https://doi.org/10.3390/logistics9040161 - 14 Nov 2025
Viewed by 679
Abstract
Background: Waste collection is a critical logistical challenge in urban management, and while Internet of Things (IoT) technologies are increasingly used to optimize collection routes, a systematic, quantitative synthesis of their impact is lacking. This study aims to bridge this gap by [...] Read more.
Background: Waste collection is a critical logistical challenge in urban management, and while Internet of Things (IoT) technologies are increasingly used to optimize collection routes, a systematic, quantitative synthesis of their impact is lacking. This study aims to bridge this gap by quantifying the effect of IoT-enabled routing optimization on waste collection distances. Methods: We conducted a systematic review and meta-analysis following the PRISMA protocol, searching the Scopus, IEEE Xplore, and ACM Digital Library databases. This process yielded 11 eligible studies, providing 21 distinct samples for quantitative synthesis. Results: The analysis reveals that IoT-enabled routing optimization reduces collection distance by a combined average of 21.51%. A significant disparity was found between study types, with simulation-based approaches reporting higher reductions (−39.79%) compared to real-world deployments (−12.37%). No statistically significant performance differences were observed across different routing algorithm categories or Vehicle Routing Problem (VRP) variants. Conclusions: These findings provide robust quantitative evidence of the significant efficiency gains from implementing IoT-based smart waste management systems. The gap between simulated and real-world results underscores the need for practitioners to set realistic expectations, while our analysis supports the adoption of these technologies for more sustainable urban logistics. Full article
(This article belongs to the Special Issue Optimizations and Operations Management of Modern Logistic Systems and Supply Chains)
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18 pages, 1635 KB  
Article
Agent-Based Simulation of Digital Interoperability Thresholds in Fragmented Air Cargo Systems: Evidence from a Developing Country
by Siska Amonalisa Silalahi, I Nyoman Pujawan and Moses Laksono Singgih
Logistics 2025, 9(4), 160; https://doi.org/10.3390/logistics9040160 - 13 Nov 2025
Viewed by 511
Abstract
Background: This study investigates how varying levels of digital interoperability affect coordination and performance in Indonesia’s decentralized air cargo system, reflecting the inefficiencies typical of fragmented digital infrastructures in developing economies. Methods: An Agent-Based Model (ABM) was developed to simulate interactions among shippers, [...] Read more.
Background: This study investigates how varying levels of digital interoperability affect coordination and performance in Indonesia’s decentralized air cargo system, reflecting the inefficiencies typical of fragmented digital infrastructures in developing economies. Methods: An Agent-Based Model (ABM) was developed to simulate interactions among shippers, freight forwarders, airlines, ground handlers, and customs agents along the CGK–SIN/HKG export corridor. Six simulation scenarios combined varying levels of digital adoption, operational friction, and behavioral adaptivity to capture emergent coordination patterns and threshold dynamics. Results: The simulation identified a distinct interoperability threshold at approximately 60%, beyond which performance improvements became non-linear. Once this threshold was surpassed, clearance times decreased by more than 40%, and capacity utilization exceeded 85%, particularly when adaptive decision rules were implemented among agents. Conclusions: Digital transformation in fragmented logistics systems requires both technological connectivity and behavioral adaptivity. The proposed hybrid framework—integrating Autonomous Supply Chains (ASC), Graph-Based Digital Twins (GBDT), and interoperability thresholds—provides a simulation-based decision-support tool to determine when digitalization yields system-wide benefits. The study contributes theoretically by linking behavioral adaptivity and digital interoperability within a unified modeling approach, and practically by offering a quantitative benchmark for policymakers and practitioners seeking to develop efficient and resilient logistics ecosystems. Full article
(This article belongs to the Topic New Technological Solutions, Research Methods, Simulation and Analytical Models That Support the Development of Modern Transport Systems, 2nd Edition)
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30 pages, 1416 KB  
Article
Applying Lean Six Sigma DMAIC to Improve Service Logistics in Tunisia’s Public Transport
by Mohamed Karim Hajji, Asma Fekih, Alperen Bal and Hakan Tozan
Logistics 2025, 9(4), 159; https://doi.org/10.3390/logistics9040159 - 6 Nov 2025
Viewed by 1175
Abstract
Background: This study deploys the Lean Six Sigma DMAIC framework to achieve systemic optimization of the school subscription process in Tunisia’s public transport service, a critical administrative operation affecting efficiency and customer satisfaction across the urban mobility network. Methods: Beyond conventional [...] Read more.
Background: This study deploys the Lean Six Sigma DMAIC framework to achieve systemic optimization of the school subscription process in Tunisia’s public transport service, a critical administrative operation affecting efficiency and customer satisfaction across the urban mobility network. Methods: Beyond conventional applications, the research integrates advanced analytical and process engineering tools, including capability indices, measurement system analysis (MSA), variance decomposition, and root-cause prioritization through Pareto–ANOVA integration, supported by a structured control plan aligned with ISO 9001:2015 and ISO 31000:2018 risk-management standards. Results: Quantitative diagnosis revealed severe process instability and nonconformities in information flow, workload balancing, and suboptimal resource allocation that constrained effective capacity utilization. Corrective interventions were modeled and validated through statistical control and real-time performance dashboards to institutionalize improvements and sustain process stability. The implemented actions led to a 37.5% reduction in cycle time, an 80% decrease in process errors, a 38.5% increase in customer satisfaction, and a 38.9% improvement in throughput. Conclusions: This study contributes theoretically by positioning Lean Six Sigma as a data-centric governance framework for stochastic capacity optimization and process redesign in public service systems, and practically by providing a replicable, evidence-based roadmap for operational excellence in governmental organizations within developing economies. Full article
(This article belongs to the Special Issue Optimizations and Operations Management of Modern Logistic Systems and Supply Chains)
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31 pages, 3077 KB  
Article
Logistics Hub Location for High-Speed Rail Freight Transport—Case Ottawa–Quebec City Corridor
by Yong Lin Ren and Anjali Awasthi
Logistics 2025, 9(4), 158; https://doi.org/10.3390/logistics9040158 - 4 Nov 2025
Viewed by 1061
Abstract
Background: This paper develops a novel, interdisciplinary framework for optimizing high-speed rail (HSR) freight logistics hubs in the Ottawa–Quebec City corridor, addressing critical gaps in geospatial mismatches, static optimization limitations, and narrow sustainability scopes found in the existing literature. Methods: The research [...] Read more.
Background: This paper develops a novel, interdisciplinary framework for optimizing high-speed rail (HSR) freight logistics hubs in the Ottawa–Quebec City corridor, addressing critical gaps in geospatial mismatches, static optimization limitations, and narrow sustainability scopes found in the existing literature. Methods: The research methodology integrates a hybrid graph neural network-reinforcement learning (GNN-RL) architecture that encodes 412 nodes into a dynamic graph with adaptive edge weights, fractal accessibility (α = 1.78) derived from fractional calculus (α = 0.75) to model non-linear urban growth patterns, and a multi-criteria sustainability evaluation framework embedding shadow pricing for externalities. Methodologically, the framework is validated through global sensitivity analysis and comparative testing against classical optimization models using real-world geospatial, operational, and economic datasets from the corridor. Results: Key findings demonstrate the framework’s superiority. Empirical results show an obvious reduction in emissions and lower logistics costs compared to classical models, with Pareto-optimal hubs identified. These hubs achieve the most GDP coverage of the corridor, reconciling economic efficiency with environmental resilience and social equity. Conclusions: This research establishes a replicable methodology for mid-latitude freight corridors, advancing low-carbon logistics through the integration of GNN-RL optimization, fractal spatial analysis, and sustainability assessment—bridging economic viability, environmental decarbonization, and social equity in HSR freight network design. Full article
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18 pages, 380 KB  
Article
Scheduling Jobs on Unreliable Machines Subject to Linear Risk
by Alessandro Agnetis and Ilaria Salvadori
Logistics 2025, 9(4), 157; https://doi.org/10.3390/logistics9040157 - 4 Nov 2025
Viewed by 445
Abstract
Background: This paper addresses a new class of scheduling problems in the context of machines subject to (unrecoverable) interruptions; i.e., when a machine fails, the current and subsequently scheduled work on that machine is lost. Each job has a certain processing time [...] Read more.
Background: This paper addresses a new class of scheduling problems in the context of machines subject to (unrecoverable) interruptions; i.e., when a machine fails, the current and subsequently scheduled work on that machine is lost. Each job has a certain processing time and a reward that is attained if the job is successfully completed. Methods: For the failure process, we considered the linear risk model, according to which the probability of machine failure is uniform across a certain time horizon. Results: We analyzed both the situation in which the set of jobs is given, and that in which jobs must be selected from a pool of jobs, at a certain selection cost. Conclusions: We characterized the complexity of various problems, showing both hardness results and polynomial algorithms, and pointed out some open problems. Full article
(This article belongs to the Special Issue Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics—2nd Edition)
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23 pages, 4802 KB  
Article
Exploring the Impact of Delivery Robots on Last-Mile Delivery Capacity Planning Using Simulation
by Raghavan Srinivasan and Joseph Szmerekovsky
Logistics 2025, 9(4), 156; https://doi.org/10.3390/logistics9040156 - 31 Oct 2025
Viewed by 1149
Abstract
Background: Over the past decade, the growth of ecommerce and omnichannel order fulfillment has led to a spike in last-mile delivery services. Last-mile delivery being the most expensive portion of the supply chain has resulted in process improvement initiatives by industry and academia [...] Read more.
Background: Over the past decade, the growth of ecommerce and omnichannel order fulfillment has led to a spike in last-mile delivery services. Last-mile delivery being the most expensive portion of the supply chain has resulted in process improvement initiatives by industry and academia targeting lower operational costs. Methods: In this study, we use simulation to account for the daily randomness regarding order quantities with missed deliveries being rolled over to the next period and attrition of the capacities used to meet the demand for each period. Further, to alleviate the impact on operations due to attrition, we consider the use of automation as a replacement for permanent capacity. Results: From the simulation results, we observe that the negative operational impact of employee turnover can be overcome with a combination of delivery robots and crowdsourcing with a payback period as short as 1.55 years. Conclusions: Optimal resource allocation is further refined by the use of simulation. The use of advanced automation such as robots seems to be a viable option for businesses to lower operational costs for some scenarios. Full article
(This article belongs to the Section Last Mile, E-Commerce and Sales Logistics)
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15 pages, 4227 KB  
Article
Danube Inland Navigation as a Strategic Corridor for Ukraine’s Post-Conflict Industrial Recovery
by Stanislav Blaško, Andrej Dávid and Adam Torok
Logistics 2025, 9(4), 155; https://doi.org/10.3390/logistics9040155 - 30 Oct 2025
Viewed by 1462
Abstract
Background: Inland waterway transport is characterised by its large loading capacity, low transport costs, and minimal negative environmental impact. Inland navigation is often the first choice as an alternative to special transport of goods, such as various oversized units and high-volume production. [...] Read more.
Background: Inland waterway transport is characterised by its large loading capacity, low transport costs, and minimal negative environmental impact. Inland navigation is often the first choice as an alternative to special transport of goods, such as various oversized units and high-volume production. The countries of Central Europe, especially those in the Danube region, which is traditionally linked to water transport, with the largest and most important river in Central and Southern Europe, have seen a significant decline in inland waterway freight transport over the last decade. Methods: Therefore, the most up-to-date, publicly available, open-source statistical data were collected and analysed. Water transport will play an irreplaceable role in the post-conflict reconstruction of Ukraine and its industry. Results: Ukraine maintains the same position, although the military conflict profoundly impacts Danube traffic. Conclusions: The possibility and potential for restoring large areas of land, utilising inland water transport, and combining suitable types of goods and means of transport will increase the volume of goods on the Danube and its importance as a transport artery. Of course, this is subject to the conditions of long-term sustainability. Full article
(This article belongs to the Section Maritime and Transport Logistics)
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26 pages, 1631 KB  
Review
Operational and Supply Chain Growth Trends in Basic Apparel Distribution Centers: A Comprehensive Review
by Luong Nguyen, Oscar Mayet and Salil Desai
Logistics 2025, 9(4), 154; https://doi.org/10.3390/logistics9040154 - 30 Oct 2025
Viewed by 1411
Abstract
Background: In a fast-changing sector, apparel distribution centers (DCs) are under increasing pressure to meet labor intensive operational requirements, short delivery windows, and variable demand in the rapidly changing apparel industry. Traditional labor forecasting methods often fail in dynamic environments, leading to inefficiencies, [...] Read more.
Background: In a fast-changing sector, apparel distribution centers (DCs) are under increasing pressure to meet labor intensive operational requirements, short delivery windows, and variable demand in the rapidly changing apparel industry. Traditional labor forecasting methods often fail in dynamic environments, leading to inefficiencies, inadequate staffing, and reduced responsiveness. Methods: This comprehensive review discusses AI-enhanced labor forecasting tools that support flexible workforce planning in apparel DCs using a PRISMA methodology. To provide proactive, data-driven scheduling recommendations, the model combines machine learning algorithms with workforce metrics and real-time operational data. Results: Key performance indicators such as throughput per work hour, skill alignment among employees, and schedule adherence were used to assess performance. Apparel distribution centers can significantly benefit from real-time, adaptive decision-making made possible by AI technologies in contrast to traditional models that depend on static forecasts and human scheduling. These include LSTM for time-series prediction, XGBoost for performance-based staffing, and reinforcement learning for flexible task assignments. Conclusions: The paper demonstrates the potential of AI in workforce planning and provides useful guidance for the digitization of labor management in the clothing distribution industry for dynamic and responsive supply chains. Full article
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26 pages, 36463 KB  
Article
Real-Time Warehouse Monitoring with Ceiling Cameras and Digital Twin for Asset Tracking and Scene Analysis
by Jianqiao Cheng, Connor Verhulst, Pieter De Clercq, Shannon Van De Velde, Steven Sagaert, Marc Mertens, Merwan Birem, Maithili Deshmukh, Neel Broekx, Erwin Rademakers, Abdellatif Bey-Temsamani and Jean-Edouard Blanquart
Logistics 2025, 9(4), 153; https://doi.org/10.3390/logistics9040153 - 28 Oct 2025
Viewed by 1534
Abstract
Background: Effective asset tracking and monitoring are critical for modern warehouse management. Methods: In this paper, we present a real-time warehouse monitoring system that leverages ceiling-mounted cameras, computer vision-based object detection, a knowledge-graph based world model. The system is implemented in [...] Read more.
Background: Effective asset tracking and monitoring are critical for modern warehouse management. Methods: In this paper, we present a real-time warehouse monitoring system that leverages ceiling-mounted cameras, computer vision-based object detection, a knowledge-graph based world model. The system is implemented in two architectural configurations: a distributed setup with edge processing and a centralized setup. Results: Experimental results demonstrate the system’s capability to accurately detect and continuously track common warehouse assets such as pallets, boxes, and forklifts. This work provides a detailed methodology, covering aspects from camera placement and neural network training to world model integration and real-world deployment. Conclusions: Our experiments show that the system achieves high detection accuracy and reliable real-time tracking across multiple viewpoints, and it is easily scalable to large-scale logistics and inventory applications. Full article
(This article belongs to the Section Artificial Intelligence, Logistics Analytics, and Automation)
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22 pages, 826 KB  
Article
Integrating Machine Learning with Multi-Criteria Decision-Making Models for Sustainable Supplier Selection in Dynamic Supply Chains
by Osheyor Joachim Gidiagba, Lagouge Tartibu and Modestus Okwu
Logistics 2025, 9(4), 152; https://doi.org/10.3390/logistics9040152 - 24 Oct 2025
Cited by 1 | Viewed by 2065
Abstract
Background: Supplier evaluation and selection are pivotal processes in supply chain management, profoundly influencing organisational efficiency and sustainability. This study addresses the limitations of traditional multi-criteria decision-making approaches, particularly the Technique for Order Preference by Similarity to an Ideal Solution, which often [...] Read more.
Background: Supplier evaluation and selection are pivotal processes in supply chain management, profoundly influencing organisational efficiency and sustainability. This study addresses the limitations of traditional multi-criteria decision-making approaches, particularly the Technique for Order Preference by Similarity to an Ideal Solution, which often lacks dimensional reduction capability and assumes uniform weight distribution across criteria. Methods: To overcome these challenges, a hybrid model integrating non-negative matrix factorisation, random forest, and the Technique for Order Preference by Similarity to an Ideal Solution is developed for supplier evaluation in the pharmaceutical sector. The method first applies non-negative matrix factorisation to condense twenty-four evaluation criteria into eight core dimensions, enhancing analytical efficiency and reducing complexity. Random forest is then employed to derive data-driven weights for each criterion, ensuring accurate prioritisation. Finally, the Technique for Order Preference by Similarity to an Ideal Solution ranks suppliers and provides actionable insights for decision-makers. Results: Results from real-world pharmaceutical data validate the model’s effectiveness and demonstrate superior performance over conventional evaluation methods. Conclusions: The findings confirm that integrating machine learning techniques with established decision-making frameworks enhances precision, interpretability, and sustainability in supplier selection while requiring adequate data quality and computational resources for implementation. Full article
(This article belongs to the Special Issue Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics—2nd Edition)
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21 pages, 1526 KB  
Article
A Multi-Product and Multi-Period Inventory Planning Model to Optimize the Supply of Medicines in a Pharmacy in Barranquilla, Colombia
by Katherinne Salas-Navarro, Jousua Pardo-Meza, Juan Torres-Prentt and Juan Rivera-Alvarado
Logistics 2025, 9(4), 151; https://doi.org/10.3390/logistics9040151 - 21 Oct 2025
Viewed by 1478
Abstract
Background: Supply chains in pharmaceutical industry encounter constant challenges in balancing the availability of medicine with cost efficiency, particularly in developing regions with limited storage capacity, as regulatory constraints increase operational complexity. Methods: This research focuses on developing a multi-product, multi-period [...] Read more.
Background: Supply chains in pharmaceutical industry encounter constant challenges in balancing the availability of medicine with cost efficiency, particularly in developing regions with limited storage capacity, as regulatory constraints increase operational complexity. Methods: This research focuses on developing a multi-product, multi-period inventory planning model designed to optimize the supply process for a pharmacy located in Barranquilla, Colombia. The methodology involves conducting field studies within the pharmaceutical sector, which includes regular visits to pharmacies, interaction with employees, and analysis of historical data collected over a 16-month period. Results: The primary goal is to minimize costs while ensuring that products remain available to customers, considering various internal and external factors. Several scenarios will be examined to evaluate different alternatives for enhancing the supply process. Initial findings suggest that the proposed model could reduce inventory planning costs by approximately 15.78% by classifying antibiotics, which in turn leads to better resource utilization and improved order management. Conclusions: The proposed model minimizes the inventory planning costs associated with antibiotic management, ultimately leading to improved resource utilization and more accurate order management. Full article
(This article belongs to the Section Humanitarian and Healthcare Logistics)
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24 pages, 1993 KB  
Article
The Downstream Supply Chain for Electricity Generated from Renewables in Egypt: A Dynamic Analysis
by Islam Hassanin, Tariq Muneer and Matjaz Knez
Logistics 2025, 9(4), 150; https://doi.org/10.3390/logistics9040150 - 21 Oct 2025
Viewed by 750
Abstract
Background: Generating electricity from renewable sources continues to receive significant attention from both scholars and professional communities. This is mainly because traditional energy use harms public health, threatens biodiversity, and increases pollution, particularly in developing countries. Meanwhile, renewable technologies are considered one of [...] Read more.
Background: Generating electricity from renewable sources continues to receive significant attention from both scholars and professional communities. This is mainly because traditional energy use harms public health, threatens biodiversity, and increases pollution, particularly in developing countries. Meanwhile, renewable technologies are considered one of the most effective solutions to enrich energy security for future usage with clean practices and affordable prices. However, planning such applications may become complex due to the convolution of many technical, economic, environmental, and social dimensions, particularly from a supply chain management viewpoint. Methods: The paper identifies the dimensions affecting the supply chain variables of downstream processes in renewable energy supply systems, especially for generating electricity in Egypt. Also, this paper investigates the relationships between the dimensions of renewable energy supply systems and the downstream supply chain variables that are closely related to the Egyptian energy sector. Results: The different relationships between these indicators and downstream supply chain variables are revealed. Conclusions: This study employed conceptual causality diagramming to organize these relationships harmoniously, which helps to analyze the behavior of the supply chain during the transitions to renewable energy applications and its implications, whether at the managerial or policy and procedural levels. Full article
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24 pages, 1066 KB  
Article
Liner Schedule Reliability Problem: An Empirical Analysis of Disruptions and Recovery Measures in Container Shipping
by Jakov Karmelić, Marija Jović Mihanović, Ana Perić Hadžić and David Brčić
Logistics 2025, 9(4), 149; https://doi.org/10.3390/logistics9040149 - 20 Oct 2025
Viewed by 2184
Abstract
Background: Schedule reliability in container liner services is essential for the efficiency of maritime and inland transport, terminal operations, and the overall supply chain. Disruptions to vessel schedules can trigger a series of disruptions at other points, generating additional operational costs for carriers, [...] Read more.
Background: Schedule reliability in container liner services is essential for the efficiency of maritime and inland transport, terminal operations, and the overall supply chain. Disruptions to vessel schedules can trigger a series of disruptions at other points, generating additional operational costs for carriers, terminal operators, inland transport providers, and ultimately, for importers, exporters, and end consumers. Methods: The research paper combines literature reviews and shipping company data. A qualitative analysis contains specific causes of vessel delays and corrective actions used to realign schedules with the pro forma plan. The analysis was expanded to include transport of cargo in containers from origin to the final inland destination. Results: Disruption factors are identified and classified by their place of occurrence: (1) inland transport, (2) anchorage, (3) ports, and (4) navigation between ports. The research produced several new disruptive factors previously not identified and published. It has been confirmed that port congestion acts as the principal cause of delay in liner service. Conclusions: The findings indicate that while the number and complexity of disruptive factors are increasing due to global and regional dynamics, the range of recovery measures remains narrow. A deeper understanding of these causes enables more effective prevention, aiming to minimize supply chain disruptions and costs and increase the reliability of door-to-door container transport. Full article
(This article belongs to the Special Issue Investment, Risk, and Sustainability in Maritime Logistics and Supply Chain)
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25 pages, 2325 KB  
Article
The Role of Spare Parts Supply Chains in the Success of New Computer Technology Products
by Maria Sashkova Vodenicharova and Yulia Genova
Logistics 2025, 9(4), 148; https://doi.org/10.3390/logistics9040148 - 20 Oct 2025
Viewed by 1531
Abstract
The purpose of this study is to examine the spare parts supply chain when introducing new computer technology products to the market. Background: Despite the growing importance of after-sales service, the supply chain for spare parts for ICT (information and communications technology) [...] Read more.
The purpose of this study is to examine the spare parts supply chain when introducing new computer technology products to the market. Background: Despite the growing importance of after-sales service, the supply chain for spare parts for ICT (information and communications technology) products often receives insufficient attention. Materials and Methods: The data was obtained from an analysis of operational service logs encompassing 149,937 warranty service requests and associated Service Level Agreements, augmented by feedback from 1572 surveyed computer equipment customers regarding their after-sales service experience. The data refers to a period of one year (1 January 2023 to 1 January 2024) and takes into account all new products launched in the computer category during this period (116 new products), primarily focusing on equipment such as servers, and the product tree for each of these products. Results: The results are related to increasing requirements for after-sales service, in particular, the supply chain for spare parts, which is of great importance for the development and success of companies producing computing equipment. Conclusions: The study contains original results obtained during scientific research conducted by the authors in the field of logistics and supply chain for spare parts. Full article
(This article belongs to the Special Issue Advancements in Building Resilient Reverse Supply Chains: Strategies, Technologies, and Sustainable Practices)
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17 pages, 673 KB  
Article
Impact of Logistics on Global Economic Growth: Beta and Sigma Convergence During the Period 2007–2022
by Pablo Coto-Millán, David Paz Saavedra and Marta De la Fuente
Logistics 2025, 9(4), 147; https://doi.org/10.3390/logistics9040147 - 20 Oct 2025
Viewed by 1186
Abstract
Background: Logistics plays a key role in economic performance, yet its contribution to global growth and convergence remains underexplored. This study examines how different logistics dimensions have influenced GDP per worker across countries over the period 2007–2022. Methods: Using econometric panel data [...] Read more.
Background: Logistics plays a key role in economic performance, yet its contribution to global growth and convergence remains underexplored. This study examines how different logistics dimensions have influenced GDP per worker across countries over the period 2007–2022. Methods: Using econometric panel data techniques and convergence models (β and σ), data from 86 countries are analysed by incorporating logistics performance indicators—such as infrastructure quality, customs efficiency, and shipment traceability—into an endogenous growth framework. Results: The analysis confirms the existence of both β- and σ-convergence, suggesting that lower-income countries are catching up with higher-income ones. Improvements in logistics competence and tracking systems positively affect economic growth, while inefficiencies in shipping services and delivery timeliness negatively impact convergence. Conclusions: These findings highlight the dual role logistics can play in fostering or hindering growth. Enhancing logistics infrastructure and services through targeted policies is essential to promote sustained economic development and reduce global income disparities. Full article
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24 pages, 2054 KB  
Article
Post-Harvest Cold Chain Efficiency in Pome Fruit Operations: Analysing Time and Process Bottlenecks
by Stefan Le Roux and Leila Louise Goedhals-Gerber
Logistics 2025, 9(4), 146; https://doi.org/10.3390/logistics9040146 - 16 Oct 2025
Viewed by 1716
Abstract
Background: South Africa’s pome fruit industry serves over 60 international markets, competing with Chile, New Zealand, and the United States. Inefficiencies in the beginning stages of South Africa’s pome fruit supply chain compromise competitiveness as global quality standards rise and consumers demand [...] Read more.
Background: South Africa’s pome fruit industry serves over 60 international markets, competing with Chile, New Zealand, and the United States. Inefficiencies in the beginning stages of South Africa’s pome fruit supply chain compromise competitiveness as global quality standards rise and consumers demand premium fruit with an extended shelf life. This research identifies operational bottlenecks in the post-harvest handling and processing of pome fruit, focusing on temperature control, lead times, and infrastructure constraints. Methods: A mixed-methods case study approach of Company X, combining on-site observations, semi-structured interviews, and analysis of Company X’s processing data. Findings were triangulated with Hortgro and PPECB sources for validity. Results: Prolonged ambient temperature exposure from packhouse processing bottlenecks resulted in increased fruit pulp temperatures, with congestion, inefficient practices, and poor communication exacerbating problems. Pre-cooling proved most inefficient, with pulp temperatures averaging 1.9 °C (peak season: 3.2–3.5 °C), far exceeding the −0.5 °C industry standard required for international markets and resulting in a downgrade from Class 1 to Class 2 fruit. Conclusions: This research identifies cold chain bottlenecks affecting South Africa’s global competitiveness. Recommended solutions include hydrocooling, infrastructure upgrades, and enhanced stakeholder coordination to strengthen the country’s position in international pome fruit markets. Full article
(This article belongs to the Special Issue Supply Chain Management for Reducing Food Waste)
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