Journal Description
Logistics
Logistics
is an international, scientific, peer-reviewed, open access journal of logistics and supply chain management published quarterly online by MDPI. The first issue has been released in December 2017.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, ESCI (Web of Science), RePEc, and other databases.
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 25.6 days after submission; acceptance to publication is undertaken in 4.9 days (median values for papers published in this journal in the first half of 2025).
- Journal Rank: JCR - Q2 (Operations Research and Management Science) / CiteScore - Q1 (Information Systems and Management)
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Impact Factor:
3.6 (2024);
5-Year Impact Factor:
3.8 (2024)
Latest Articles
Planning of Logistic Networks with Automated Transport Drones: A Systematic Review of Application Areas, Planning Approaches, and System Performance
Logistics 2025, 9(3), 111; https://doi.org/10.3390/logistics9030111 - 8 Aug 2025
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Background: The increasing integration of automated transport drones into logistics networks presents transformative potential for addressing contemporary logistics challenges, particularly in last-mile delivery, healthcare, disaster response, urban mobility, and postal services. However, their effective integration into varied logistics contexts remains hindered by
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Background: The increasing integration of automated transport drones into logistics networks presents transformative potential for addressing contemporary logistics challenges, particularly in last-mile delivery, healthcare, disaster response, urban mobility, and postal services. However, their effective integration into varied logistics contexts remains hindered by infrastructure, regulatory, and operational limitations. This study aims to explore how drone-based logistics systems can be systematically planned and evaluated across diverse operational environments. Methods: A structured literature review was conducted, employing thematic synthesis to analyze current research on drone logistics. The analysis focused on identifying the key planning dimensions and interrelated components that influence the deployment of drone-based transport systems. Results: The review identified seven central planning dimensions: areas of application, system components, transport configuration, geographic areas, optimization and analysis methods, logistical planning, and performance assessment. These dimensions inform a conceptual framework designed to guide the planning and assessment of drone logistics networks. Conclusions: While existing studies contribute valuable insights into route optimization and drone deployment strategies, they often overlook integrative approaches that account for societal and environmental factors. The study emphasizes the need for interdisciplinary collaboration and context-specific planning frameworks to enhance the sustainable and effective implementation of drone-based logistics systems.
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Open AccessArticle
A Multi-Agent Optimization Approach for Multimodal Collaboration in Marine Terminals
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Ilias Alexandros Parmaksizoglou, Alessandro Bombelli and Alexei Sharpanskykh
Logistics 2025, 9(3), 110; https://doi.org/10.3390/logistics9030110 - 8 Aug 2025
Abstract
Background: The rapid growth of international maritime trade has intensified operational challenges at marine terminals due to increased interaction between vessels, trucks, and trains. Key issues include berth congestion, inefficient truck arrivals, and underutilization of terminal resources. Ensuring coordinated planning among transport modes
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Background: The rapid growth of international maritime trade has intensified operational challenges at marine terminals due to increased interaction between vessels, trucks, and trains. Key issues include berth congestion, inefficient truck arrivals, and underutilization of terminal resources. Ensuring coordinated planning among transport modes and fostering collaboration between stakeholders such as vessel operators, logistics providers, and terminal managers is critical to mitigating these inefficiencies. Methods: This study proposes a multi-agent, multi-objective coordination model that synchronizes vessel berth allocation with truck appointment scheduling. A solution method combining prioritized planning with a neighborhood search heuristic is introduced to explore Pareto-optimal trade-offs. The performance of this approach is benchmarked against well-established multi-objective evolutionary algorithms (MOEAs), including NSGA-II and SPEA2. Results: Numerical experiments demonstrate that the proposed method generates a greater number of Pareto-optimal solutions and achieves higher hypervolume indicators compared to MOEAs. These results show improved balance among objectives such as minimizing vessel waiting times, reducing truck congestion, and optimizing terminal resource usage. Conclusions: By integrating berth allocation and truck scheduling through a transparent, multi-agent approach, this work provides decision-makers with better tools to evaluate trade-offs in port terminal operations. The proposed strategy supports more efficient, fair, and informed coordination in complex multimodal environments.
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(This article belongs to the Section Maritime and Transport Logistics)
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Integration of Data Analytics and Data Mining for Machine Failure Mitigation and Decision Support in Metal–Mechanical Industry
by
Sidnei Alves de Araujo, Silas Luiz Bomfim, Dimitria T. Boukouvalas, Sergio Ricardo Lourenço, Ugo Ibusuki and Geraldo Cardoso de Oliveira Neto
Logistics 2025, 9(3), 109; https://doi.org/10.3390/logistics9030109 - 7 Aug 2025
Abstract
Background: The growing complexity of production processes in the metal–mechanical industry demands ever more effective strategies for managing machine and equipment maintenance, as unexpected failures can incur high operational costs and compromise productivity by interrupting workflows and delaying deliveries. However, few studies
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Background: The growing complexity of production processes in the metal–mechanical industry demands ever more effective strategies for managing machine and equipment maintenance, as unexpected failures can incur high operational costs and compromise productivity by interrupting workflows and delaying deliveries. However, few studies have combined end-to-end data analytics and data mining methods to proactively predict and mitigate such failures. This study aims to develop and validate a comprehensive framework combining data analytics and data mining to prevent machine failures and support decision-making in a metal–mechanical manufacturing environment. Methods: First, exploratory data analytics were performed on the sensor and logistics data to identify significant relationships and trends between variables. Next, a preprocessing pipeline including data cleaning, data transformation, feature selection, and resampling was applied. Finally, a decision tree model was trained to identify conditions prone to failures, enabling not only predictions but also the explicit representation of knowledge in the form of decision rules. Results: The outstanding performance of the decision tree (82.1% accuracy and a Kappa index of 78.5%), which was modeled from preprocessed data and the insights produced by data analytics, demonstrates its ability to generate reliable rules for predicting failures to support decision-making. The implementation of the proposed framework enables the optimization of predictive maintenance strategies, effectively reducing unplanned downtimes and enhancing the reliability of production processes in the metal–mechanical industry.
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(This article belongs to the Special Issue Optimizations and Operations Management of Modern Logistic Systems and Supply Chains)
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Clustering of Countries Through UMAP and K-Means: A Multidimensional Analysis of Development, Governance, and Logistics
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Enrique Delahoz-Domínguez, Adel Mendoza-Mendoza and Delimiro Visbal-Cadavid
Logistics 2025, 9(3), 108; https://doi.org/10.3390/logistics9030108 - 7 Aug 2025
Abstract
Background: Growing disparities in development, governance, and logistics performance across countries pose challenges for global policymaking and Sustainable Development Goal (SDG) monitoring. This study proposes a classification of 137 countries based on multiple structural dimensions. The dataset for 2023 includes six components
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Background: Growing disparities in development, governance, and logistics performance across countries pose challenges for global policymaking and Sustainable Development Goal (SDG) monitoring. This study proposes a classification of 137 countries based on multiple structural dimensions. The dataset for 2023 includes six components of the Logistics Performance Index (LPI), six dimensions of the Worldwide Governance Indicators (WGIs), and four proxies of the Human Development Index (HDI). Methods: The Uniform Manifold Approximation and Projection (UMAP) technique was used to reduce dimensionality and allow for meaningful clustering. Based on the reduced space, the K-means algorithm was employed to group countries with similar development characteristics. Results: The classification process allowed the identification of three distinct groups of countries, supported by a Hopkins statistic of 0.984 and an explained variance ratio of 87.3%. These groups exhibit structural differences in the quality of governance, logistics capacity, and social development conditions. Internal consistency checks and multivariate statistical analyses (ANOVA and MANOVA) confirmed the robustness and statistical significance of the clustering. Conclusions: The resulting classification offers a practical analytical tool for policymakers to design differentiated strategies aligned with national contexts. Furthermore, it provides a data-driven approach for comparative monitoring of the SDGs from an integrated and empirical perspective.
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(This article belongs to the Special Issue Optimizations and Operations Management of Modern Logistic Systems and Supply Chains)
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Adaptive Intermodal Transportation for Freight Resilience: An Integrated and Flexible Strategy for Managing Disruptions
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Siyavash Filom, Satrya Dewantara, Mahnam Saeednia and Saiedeh Razavi
Logistics 2025, 9(3), 107; https://doi.org/10.3390/logistics9030107 - 6 Aug 2025
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Background: Disruptions in freight transportation—such as service delays, infrastructure failures, and labor strikes—pose significant challenges to the reliability and efficiency of intermodal networks. To address these challenges, this study introduces Adaptive Intermodal Transportation (AIT), a resilient and flexible planning framework that enhances
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Background: Disruptions in freight transportation—such as service delays, infrastructure failures, and labor strikes—pose significant challenges to the reliability and efficiency of intermodal networks. To address these challenges, this study introduces Adaptive Intermodal Transportation (AIT), a resilient and flexible planning framework that enhances Synchromodal Freight Transport (SFT) by integrating real-time disruption management. Methods: Building on recent advances, we propose two novel strategies: (1) Reassign with Delay Buffer, which enables dynamic rerouting of shipments within a user-defined delay tolerance, and (2) (De)Consolidation, which allows splitting or merging of shipments across services depending on available capacity. These strategies are incorporated into a re-planning module that complements a baseline optimization model and a continuous disruption-monitoring system. Numerical experiments conducted on a Great Lakes-based case study evaluate the performance of the proposed strategies against a benchmark approach. Results: Results show that under moderate and high-disruption conditions, the proposed strategies reduce delay and disruption-incurred costs while increasing the percentage of matched shipments. The Reassign with Delay Buffer strategy offers controlled flexibility, while (De)Consolidation improves resource utilization in constrained environments. Conclusions: Overall, the AIT framework demonstrates strong potential for improving operational resilience in intermodal freight systems by enabling adaptive, disruption-aware planning decisions.
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Autonomous Last-Mile Logistics in Emerging Markets: A Study on Consumer Acceptance
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Emerson Philipe Sinesio, Marcele Elisa Fontana, Júlio César Ferro de Guimarães and Pedro Carmona Marques
Logistics 2025, 9(3), 106; https://doi.org/10.3390/logistics9030106 - 6 Aug 2025
Abstract
Background: Rapid urbanization has intensified the challenges of freight transport, particularly in last-mile (LM) delivery, leading to rising costs and environmental externalities. Autonomous vehicles (AVs) have emerged as a promising innovation to address these issues. While much of the existing literature emphasizes business
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Background: Rapid urbanization has intensified the challenges of freight transport, particularly in last-mile (LM) delivery, leading to rising costs and environmental externalities. Autonomous vehicles (AVs) have emerged as a promising innovation to address these issues. While much of the existing literature emphasizes business and operational perspectives, this study focuses on the acceptance of AVs from the standpoint of e-consumers—individuals who make purchases via digital platforms—in an emerging market context. Methods: Grounded in an extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), which is specifically suited to consumer-focused technology adoption research, this study incorporates five constructs tailored to AV adoption. Structural Equation Modeling (SEM) was applied to survey data collected from 304 e-consumers in Northeast Brazil. Results: The findings reveal that performance expectancy, hedonic motivation, and environmental awareness exert significant positive effects on acceptance and intention to use AVs for LM delivery. Social influence shows a weaker, yet still positive, impact. Importantly, price sensitivity exhibits a minimal effect, suggesting that while consumers are generally cost-conscious, perceived value may outweigh price concerns in early adoption stages. Conclusions: These results offer valuable insights for policymakers and logistics providers aiming to implement consumer-oriented, cost-effective AV solutions in LM delivery, particularly in emerging economies. The findings emphasize the need for strategies that highlight the practical, emotional, and environmental benefits of AVs to foster market acceptance.
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(This article belongs to the Section Last Mile, E-Commerce and Sales Logistics)
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Material Flow Analysis for Demand Forecasting and Lifetime-Based Inflow in Indonesia’s Plastic Bag Supply Chain
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Erin Octaviani, Ilyas Masudin, Amelia Khoidir and Dian Palupi Restuputri
Logistics 2025, 9(3), 105; https://doi.org/10.3390/logistics9030105 - 5 Aug 2025
Abstract
Background: this research presents an integrated approach to enhancing the sustainability of plastic bag supply chains in Indonesia by addressing critical issues related to ineffective post-consumer waste management and low recycling rates. The objective of this study is to develop a combined
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Background: this research presents an integrated approach to enhancing the sustainability of plastic bag supply chains in Indonesia by addressing critical issues related to ineffective post-consumer waste management and low recycling rates. The objective of this study is to develop a combined framework of material flow analysis (MFA) and sustainable supply chain planning to improve demand forecasting and inflow management across the plastic bag lifecycle. Method: the research adopts a quantitative method using the XGBoost algorithm for forecasting and is supported by a polymer-based MFA framework that maps material flows from production to end-of-life stages. Result: the findings indicate that while production processes achieve high efficiency with a yield of 89%, more than 60% of plastic bag waste remains unmanaged after use. Moreover, scenario analysis demonstrates that single interventions are insufficient to achieve circularity targets, whereas integrated strategies (e.g., reducing export volumes, enhancing waste collection, and improving recycling performance) are more effective in increasing recycling rates beyond 35%. Additionally, the study reveals that increasing domestic recycling capacity and minimizing dependency on exports can significantly reduce environmental leakage and strengthen local waste management systems. Conclusions: the study’s novelty lies in demonstrating how machine learning and material flow data can be synergized to inform circular supply chain decisions and regulatory planning.
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(This article belongs to the Section Sustainable Supply Chains and Logistics)
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A Comprehensive Survey of Artificial Intelligence and Robotics for Reducing Carbon Emissions in Supply Chain Management
by
Mariem Mrad, Mohamed Amine Frikha and Younes Boujelbene
Logistics 2025, 9(3), 104; https://doi.org/10.3390/logistics9030104 - 4 Aug 2025
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Background: Artificial intelligence (AI) and robotics are increasingly pivotal for reducing carbon emissions in supply chain management (SCM); however, research exploring their combined potential from a sustainability perspective remains fragmented. This study aims to systematically map the research landscape and synthesize evidence
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Background: Artificial intelligence (AI) and robotics are increasingly pivotal for reducing carbon emissions in supply chain management (SCM); however, research exploring their combined potential from a sustainability perspective remains fragmented. This study aims to systematically map the research landscape and synthesize evidence on the applications, benefits, and challenges. Methods: A systematic scoping review was conducted on 23 peer-reviewed studies from the Scopus database, published between 2013 and 2024. Data were systematically extracted and analyzed for publication trends, application domains (e.g., transportation, warehousing), specific AI and robotic technologies, emissions reduction strategies, and implementation challenges. Results: The analysis reveals that AI-driven logistics optimization is the most frequently reported strategy for reducing transportation emissions. At the same time, robotic automation is commonly associated with improved energy efficiency in warehousing. Despite these benefits, the reviewed literature consistently identifies significant barriers, including the high energy demands of AI computation and complexities in data integration. Conclusions: This review confirms the transformative potential of AI and robotics for developing low-carbon supply chains. An evidence-based framework is proposed to guide practical implementation and identify critical gaps, such as the need for standardized validation benchmarks, to direct future research and accelerate the transition to sustainable SCM.
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Rethinking Routes: The Case for Regional Ports in a Decarbonizing World
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Dong-Ping Song
Logistics 2025, 9(3), 103; https://doi.org/10.3390/logistics9030103 - 4 Aug 2025
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Background: Increasing regulatory pressure for maritime decarbonization (e.g., IMO CII, FuelEU) drives adoption of low-carbon fuels and prompts reassessment of regional ports’ competitiveness. This study aims to evaluate the economic and environmental viability of rerouting deep-sea container services to regional ports in
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Background: Increasing regulatory pressure for maritime decarbonization (e.g., IMO CII, FuelEU) drives adoption of low-carbon fuels and prompts reassessment of regional ports’ competitiveness. This study aims to evaluate the economic and environmental viability of rerouting deep-sea container services to regional ports in a decarbonizing world. Methods: A scenario-based analysis is used to evaluate total costs and CO2 emissions across the entire container shipping supply chain, incorporating deep-sea shipping, port operations, feeder services, and inland rail/road transport. The Port of Liverpool serves as the primary case study for rerouting Asia–Europe services from major ports. Results: Analysis indicates Liverpool’s competitiveness improves with shipping lines’ slow steaming, growth in hinterland shipment volume, reductions in the emission factors of alternative low-carbon fuels, and an increased modal shift to rail matching that of competitor ports (e.g., Southampton). A dual-port strategy, rerouting services to call at both Liverpool and Southampton, shows potential for both economic and environmental benefits. Conclusions: The study concludes that rerouting deep-sea services to regional ports can offer cost and emission advantages under specific operational and market conditions. Findings on factors and conditions influencing competitiveness and the dual-port strategy provide insights for shippers, ports, shipping lines, logistics agents, and policymakers navigating maritime decarbonization.
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(This article belongs to the Section Maritime and Transport Logistics)
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Artificial Intelligence-Enabled Digital Transformation in Circular Logistics: A Structural Equation Model of Organizational, Technological, and Environmental Drivers
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Ionica Oncioiu, Diana Andreea Mândricel and Mihaela Hortensia Hojda
Logistics 2025, 9(3), 102; https://doi.org/10.3390/logistics9030102 - 1 Aug 2025
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Background: Digital transformation is increasingly present in modern logistics, especially in the context of sustainability and circularity pressures. The integration of technologies such as Internet of Things (IoT), Radio Frequency Identification (RFID), and automated platforms involves not only infrastructure but also a
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Background: Digital transformation is increasingly present in modern logistics, especially in the context of sustainability and circularity pressures. The integration of technologies such as Internet of Things (IoT), Radio Frequency Identification (RFID), and automated platforms involves not only infrastructure but also a strategic vision, a flexible organizational culture, and the ability to support decisions through artificial intelligence (AI)-based systems. Methods: This study proposes an extended conceptual model using structural equation modelling (SEM) to explore the relationships between five constructs: technological change, strategic and organizational readiness, transformation environment, AI-enabled decision configuration, and operational redesign. The model was validated based on a sample of 217 active logistics specialists, coming from sectors such as road transport, retail, 3PL logistics services, and manufacturing. The participants are involved in the digitization of processes, especially in activities related to operational decisions and sustainability. Results: The findings reveal that the analysis confirms statistically significant relationships between organizational readiness, transformation environment, AI-based decision processes, and operational redesign. Conclusions: The study highlights the importance of an integrated approach in which technology, organizational culture, and advanced decision support collectively contribute to the transition to digital and circular logistics chains.
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(This article belongs to the Special Issue Advancing Circular Supply Chains: Integrating Logistics, Supply Chain Management and Circular Economy Practices)
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Logistical Challenges in Home Health Care: A Comparative Analysis Between Portugal and Brazil
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William Machado Emiliano, Thalyta Cristina Mansano Schlosser, Vitor Eduardo Molina Júnior, José Telhada and Yuri Alexandre Meyer
Logistics 2025, 9(3), 101; https://doi.org/10.3390/logistics9030101 - 31 Jul 2025
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Background: This study aims to compare the logistical challenges of Home Health Care (HHC) services in Portugal and Brazil, highlighting the structural and operational differences between both systems. Methods: Guided by an abductive research approach, data were collected using a semi-structured
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Background: This study aims to compare the logistical challenges of Home Health Care (HHC) services in Portugal and Brazil, highlighting the structural and operational differences between both systems. Methods: Guided by an abductive research approach, data were collected using a semi-structured survey with open-ended questions, applied to 13 HHC teams in Portugal and 18 in Brazil, selected based on national coordination recommendations. The data collection process was conducted in person, and responses were analyzed using descriptive statistics and qualitative content analysis. Results: The results reveal that Portugal demonstrates higher productivity, stronger territorial coverage, and a more integrated inventory management system, while Brazil presents greater multidisciplinary team integration, more flexible fleet logistics, and more advanced digital health records. Despite these strengths, both countries continue to address key logistical aspects, such as scheduling, supply distribution, and data management, largely through empirical strategies. Conclusions: This research contributes to the theoretical understanding of international HHC logistics by emphasizing strategic and systemic aspects often overlooked in operational studies. In practical terms, it offers insights for public health managers to improve resource allocation, fleet coordination, and digital integration in aging societies.
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(This article belongs to the Section Humanitarian and Healthcare Logistics)
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From Mine to Market: Streamlining Sustainable Gold Production with Cutting-Edge Technologies for Enhanced Productivity and Efficiency in Central Asia
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Mohammad Shamsuddoha, Adil Kaibaliev and Tasnuba Nasir
Logistics 2025, 9(3), 100; https://doi.org/10.3390/logistics9030100 - 29 Jul 2025
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Background: Gold mining is a critical part of the industry of Central Asia, contributing significantly to regional economic growth. However, gold production management faces numerous challenges, including adopting innovative technologies such as AI, using improved logistical equipment, resolving supply chain inefficiencies and
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Background: Gold mining is a critical part of the industry of Central Asia, contributing significantly to regional economic growth. However, gold production management faces numerous challenges, including adopting innovative technologies such as AI, using improved logistical equipment, resolving supply chain inefficiencies and disruptions, and incorporating modernized waste management and advancements in gold bar processing technologies. This study explores how advanced technologies and improved logistical processes can enhance efficiency and sustainability. Method: This paper examines gold production processes in Kyrgyzstan, a gold-producing country in Central Asia. The case study approach combines qualitative interviews with industry stakeholders and a system dynamics (SD) simulation model to compare current operations with a technology-based scenario. Results: The simulation model shows improved outcomes when innovative technologies are applied to ore processing, waste refinement, and gold bar production. The results also indicate an approximate twenty-five percent reduction in transport time, a thirty percent decrease in equipment downtime, a thirty percent reduction in emissions, and a fifteen percent increase in gold extraction when using artificial intelligence, smart logistics, and regional smelting. Conclusions: The study concludes with recommendations to modernize equipment, localize processing, and invest in digital logistics to support sustainable mining and improve operational performance in Kyrgyzstan’s gold sector.
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(This article belongs to the Topic Sustainable Supply Chain Practices in A Digital Age)
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Achieving Sustainable Supply Chains: Applying Group Concept Mapping to Prioritize and Implement Sustainable Management Practices
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Thompson McDaniel, Edit Süle and Gyula Vastag
Logistics 2025, 9(3), 99; https://doi.org/10.3390/logistics9030099 - 28 Jul 2025
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Background: Sustainability in supply chain management (SCM) practices is becoming increasingly important as environmental responsibility and social concerns, as well as enterprises’ competitiveness in terms of innovation, risk, and economic performance, become increasingly urgent. This paper aims to identify and prioritize concepts
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Background: Sustainability in supply chain management (SCM) practices is becoming increasingly important as environmental responsibility and social concerns, as well as enterprises’ competitiveness in terms of innovation, risk, and economic performance, become increasingly urgent. This paper aims to identify and prioritize concepts for implementing sustainable supply chains, drawing on sustainable supply chain management (SSCM) and green supply chain management (GSCM) techniques. Corporate supply chain managers across various industries, markets, and supply chain segments brainstormed management practices to enhance the sustainability of their supply chains. Four industry sectors were surveyed across five different value chain segments. Methods: A group concept mapping (GCM) approach incorporating multi-dimensional scaling (MDS) and hierarchical cluster analysis (HCA) was used. A hierarchy of practices is proposed, and hypotheses are developed about achievability and impact. Results: A decision-making matrix prioritizes eight solution concepts based on two axes: impact (I) and ease of implementation (EoI). Conclusions: Eight concepts are prioritized based on the optimal effectiveness of implementing the solutions. Pattern matching reveals differences between emerging and developed markets, as well as supply chain segments, that decision-makers should be aware of. By analyzing supply chains from a multi-part perspective, this research goes beyond empirical studies based on a single industry, geographic region, or example case.
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(This article belongs to the Section Sustainable Supply Chains and Logistics)
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Prioritizing ERP System Selection Challenges in UAE Ports: A Fuzzy Delphi and Relative Importance Index Approach
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Nadin Alherimi, Alyaa Alyaarbi, Sara Ali, Zied Bahroun and Vian Ahmed
Logistics 2025, 9(3), 98; https://doi.org/10.3390/logistics9030098 - 23 Jul 2025
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Background: Selecting enterprise resource planning (ERP) systems for complex port environments is a significant challenge. This study addresses a key research gap by identifying and prioritizing the critical factors for ERP selection within the strategic context of United Arab Emirates (UAE) ports, which
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Background: Selecting enterprise resource planning (ERP) systems for complex port environments is a significant challenge. This study addresses a key research gap by identifying and prioritizing the critical factors for ERP selection within the strategic context of United Arab Emirates (UAE) ports, which function as vital hubs in global trade. Methods: A hybrid methodology was employed, first using the Fuzzy Delphi Method (FDM) to validate thirteen challenges with five industry experts. Subsequently, the Relative Importance Index (RII) was used to rank these challenges based on survey data from 48 UAE port professionals. Results: The analysis revealed “Cybersecurity concerns” as the highest-ranked challenge (RII = 0.896), followed by “Engagement with external stakeholders” (RII = 0.842), and both “Process optimization” and “Technical capabilities” (RII = 0.808). Notably, factors traditionally seen as critical in other sectors, such as “Organizational readiness” (RII = 0.746), were ranked significantly lower. Conclusions: The findings indicate a strategic shift in ERP selection priorities toward digital resilience and external integration rather than internal organizational factors. This research provides a sector-specific decision-support framework and offers actionable insights for port authorities, vendors, and policymakers to enhance ERP implementation in the maritime industry.
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(This article belongs to the Section Maritime and Transport Logistics)
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Centralized vs. Decentralized Black-Mass Production: A Comparative Analysis of Lithium Reverse Logistics Supply Chain Networks
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Oluwatosin S. Atitebi and Erick C. Jones, Jr.
Logistics 2025, 9(3), 97; https://doi.org/10.3390/logistics9030097 - 23 Jul 2025
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Background: The transition to renewable energy is intensifying demand for lithium-ion batteries (LIBs), thereby increasing the need for sustainable lithium sourcing. Traditional mining practices pose environmental and health risks, which can be mitigated through efficient end-of-life recycling systems. Methods: This study
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Background: The transition to renewable energy is intensifying demand for lithium-ion batteries (LIBs), thereby increasing the need for sustainable lithium sourcing. Traditional mining practices pose environmental and health risks, which can be mitigated through efficient end-of-life recycling systems. Methods: This study proposes a modified lithium reverse logistics network that decentralizes black-mass production at distributed facilities before centralized extraction, contrasting with conventional models that transport raw LIBs directly to central processing sites. Using the United States as a case study, two mathematical optimization (mixed-integer linear programming) models were developed to compare the traditional and modified networks in terms of cost efficiency and carbon emissions. Results: The model indicates that the proposed network significantly reduces both operational costs and emissions. Conclusions: This study highlights its potential to support a greener economy and inform policy development.
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Open AccessArticle
Cost Modeling for Pickup and Delivery Outsourcing in CEP Operations: A Multidimensional Approach
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Ermin Muharemović, Amel Kosovac, Muhamed Begović, Snežana Tadić and Mladen Krstić
Logistics 2025, 9(3), 96; https://doi.org/10.3390/logistics9030096 - 17 Jul 2025
Abstract
Background: The growth of parcel volumes in urban areas, largely driven by e-commerce, has increased the complexity of pickup and delivery operations. To meet demands for cost efficiency, flexibility, and sustainability, CEP (Courier, Express, and Parcel) operators increasingly outsource segments of their
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Background: The growth of parcel volumes in urban areas, largely driven by e-commerce, has increased the complexity of pickup and delivery operations. To meet demands for cost efficiency, flexibility, and sustainability, CEP (Courier, Express, and Parcel) operators increasingly outsource segments of their last-mile networks. Methods: This study proposes a novel multidimensional cost model for outsourcing, integrating five key variables: transport unit type (parcel/pallet), service phase (pickup/delivery), vehicle category, powertrain type, and delivery point type. The model applies correction coefficients based on internal operational costs, further adjusted for location and service quality using a bonus/malus mechanism. Results: Each cost component is calculated independently, enabling full transparency and route-level cost tracking. A real-world case study was conducted using operational data from a CEP operator in Bosnia and Herzegovina. The model demonstrated improved accuracy and fairness in cost allocation, with measurable savings of up to 7% compared to existing fixed-price models. Conclusions: The proposed model supports data-driven outsourcing decisions, allows tailored cost structuring based on operational realities, and aligns with sustainable last-mile delivery strategies. It offers a scalable and adaptable tool for CEP operators seeking to enhance cost control and service efficiency in complex urban environments.
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(This article belongs to the Special Issue Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics—2nd Edition)
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Open AccessReview
The Effects of Environmental Legislation via Green Procurement Strategies: A Systematic Literature Review
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Lonneke Vocks, Victor Verboeket and Bart Vos
Logistics 2025, 9(3), 95; https://doi.org/10.3390/logistics9030095 - 14 Jul 2025
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Background: EU environmental legislations affecting global supply chains have come into force since 2022. As procurement plays a direct role effectuating this, the result of these legislations via procurement becomes relevant. Methods: A systematic literature review is used to synthesize 152 articles from
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Background: EU environmental legislations affecting global supply chains have come into force since 2022. As procurement plays a direct role effectuating this, the result of these legislations via procurement becomes relevant. Methods: A systematic literature review is used to synthesize 152 articles from managerial, business administrative, and supply chain journals. The Context–Intervention–Mechanism–Output framework (CIMO) is used as the lens by which the articles are analyzed. The articles present findings from diverse methodologies and combine green business-to-business procurement with at least one element from the CIMO framework. Results: Five conceptual frameworks of different green procurement strategies are developed, each explaining the strategy and its expected result. The strategies increasingly collaborate and by this increasingly reduce environmental impact. A comparison of the strategies identified variables which strengthen the working of environmental legislation as they contribute to collaboration. Conclusions: Customer demand is crucial for collaborative green procurement. Without this, environmental legislation will only achieve limited environmental objectives. Propositions are formulated on variables which, next to the business case, strengthen the working of environmental legislation. This article adds to the science by synthesizing the existing knowledge base into propositions and future research directions. The findings may also support policymakers in understanding the effectiveness of legislation.
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(This article belongs to the Section Sustainable Supply Chains and Logistics)
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Open AccessArticle
Digital Planning Tools in Intermodal Transport: Evidence from Poland
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Mateusz Zajac, Tomislav Rožić, Justyna Swieboda-Kutera and Martin Starčević
Logistics 2025, 9(3), 94; https://doi.org/10.3390/logistics9030094 - 11 Jul 2025
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Background: The increasing complexity of global supply chains and environmental expectations has highlighted the strategic importance of digital transformation in the transport, forwarding, and logistics (TFL) sector. Despite a growing portfolio of available tools, adoption rates—particularly among small and medium-sized enterprises (SMEs)
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Background: The increasing complexity of global supply chains and environmental expectations has highlighted the strategic importance of digital transformation in the transport, forwarding, and logistics (TFL) sector. Despite a growing portfolio of available tools, adoption rates—particularly among small and medium-sized enterprises (SMEs) in Central and Eastern Europe—remain low. This study investigates the barriers and motivations related to the implementation of digital planning tools supporting intermodal transport planning. Methods: A structured online survey was conducted among 80 Polish TFL enterprises, targeting decision-makers responsible for operational and digital strategies. The questionnaire included 17 closed and semi-open questions grouped into three thematic sections: tool usage, implementation barriers, and digital readiness. Results: The findings indicate that only 20% of respondents use dedicated route planning tools, and merely 10% report satisfaction with their performance. Key barriers include lack of awareness, organizational inertia, and the prioritization of other initiatives, with financial cost cited less frequently. While environmental sustainability is declared as a priority by most enterprises, digital support for emission tracking is limited. The results highlight the need for targeted education, integration support, and differentiated platform functionalities for SMEs and larger firms. Conclusions: This study offers evidence-based recommendations for developers, policymakers, and logistics managers aiming to accelerate digital adoption in the intermodal logistics landscape.
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Open AccessArticle
The Impact of Industry 4.0 Practices on Sustainable Performance in Jordan’s Retail Sector: The Moderating Role of Environmental Dynamism
by
Toqa Amoush and Luay Jum’a
Logistics 2025, 9(3), 93; https://doi.org/10.3390/logistics9030093 - 10 Jul 2025
Abstract
Background: The retail sector in Jordan is adopting Industry 4.0 (I4.0) technologies to enhance efficiency and sustainability. Nevertheless, there is a lack of empirical evidence to inform retail managers regarding the impact of I4.0 adoption on environmental, economic, and social sustainability, particularly
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Background: The retail sector in Jordan is adopting Industry 4.0 (I4.0) technologies to enhance efficiency and sustainability. Nevertheless, there is a lack of empirical evidence to inform retail managers regarding the impact of I4.0 adoption on environmental, economic, and social sustainability, particularly in dynamic contexts. Therefore, this study aims to investigate the impact of Industry 4.0 on the three types of sustainable performance, with the moderating effect of environmental dynamism. Methods: This quantitative study collected data using a cross-sectional survey of 100 retail professionals from large companies that was analyzed using structural equation modeling (SEM) to test the hypotheses. Results: I4.0 practices improved retail environmental, economic, and social sustainability. Additionally, environmental dynamism moderated the relationship between I4.0 and environmental sustainability, suggesting that dynamic environments may reduce the effectiveness of I4.0 technologies in driving environmental performance. Economic and social sustainability had no significant moderating effects. Conclusions: This study examines the sustainability benefits of I4.0 adoption in an unexplored developing economy. It emphasizes the strategic importance of digital transformation for retail sustainability and provides practical recommendations for dynamic markets. The findings support I4.0 technologies role in sustainable growth and lay the groundwork for digital transformation research in emerging markets.
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(This article belongs to the Section Sustainable Supply Chains and Logistics)
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Open AccessArticle
Towards a Concept for a Multifunctional Mobility Hub: Combining Multimodal Services, Urban Logistics, and Energy
by
Jonas Fahlbusch, Felix Fischer, Martin Gegner, Alexander Grahle and Lars Tasche
Logistics 2025, 9(3), 92; https://doi.org/10.3390/logistics9030092 - 10 Jul 2025
Abstract
Background: This paper proposes a conceptual framework for a multifunctional mobility hub (MMH) that co-locates shared e-mobility services, urban logistics, and charging/storage infrastructure within a single site. Aimed at high-density European cities, the MMH model addresses current gaps in both research and practice,
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Background: This paper proposes a conceptual framework for a multifunctional mobility hub (MMH) that co-locates shared e-mobility services, urban logistics, and charging/storage infrastructure within a single site. Aimed at high-density European cities, the MMH model addresses current gaps in both research and practice, where multimodal mobility services, logistics, and energy are rarely planned in an integrated manner. Methods: A mixed-methods approach was applied, including a systematic literature review (PRISMA), expert interviews, case studies, and a stakeholder workshop, to identify synergies across fleet types and operational domains. Results: The analysis reveals key design principles for MMHs, such as interoperable charging, the functional separation of passenger and freight flows, and modular, scalable infrastructure adapted to urban constraints. Conclusions: The MMH serves as a preliminary concept for planning next-generation mobility stations. It offers qualitative insights for urban planners, operators, and policymakers into how multifunctional hubs may support lower emissions, more efficient operations, and shared infrastructure use.
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(This article belongs to the Section Sustainable Supply Chains and Logistics)
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