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 28.5 days after submission; acceptance to publication is undertaken in 5.6 days (median values for papers published in this journal in the second half of 2024).
- Journal Rank: JCR - Q2 (Operations Research and Management Science) / CiteScore - Q1 (Management Information Systems)
- 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 (2023);
5-Year Impact Factor:
3.7 (2023)
Latest Articles
Effect of Social Sustainability on Supply Chain Resilience Before, During, and After the COVID-19 Pandemic in Mexico: A Partial Least Squares Structural Equation Modeling and Evolutionary Fuzzy Knowledge Transfer Approach
Logistics 2025, 9(2), 50; https://doi.org/10.3390/logistics9020050 (registering DOI) - 2 Apr 2025
Abstract
Recent disruptions have led to a growing interest in studying the social dimension of sustainability and its relationship to resilience within supply chains. Social sustainability is characterized as complex, often offering anomalous data and confounding variables that are impossible to categorically define as
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Recent disruptions have led to a growing interest in studying the social dimension of sustainability and its relationship to resilience within supply chains. Social sustainability is characterized as complex, often offering anomalous data and confounding variables that are impossible to categorically define as true or false axioms. This work starts from an epistemological premise, in which non-parametric statistical methodologies and mathematical analytics are complementary perspectives to comprehensively understand the same social phenomenon. Second-generation predictive statistics, such as the PLS-SEM algorithm, have demonstrated robustness in treating multivariate social information, making it feasible to prepare data for knowledge transfer with mathematical techniques specialized for fuzzy data. This research aimed to analyze evolutionary fuzzy knowledge transfer pre-, during-, and post-pandemic COVID-19, and its effect on the relationship between social sustainability and supply chain resilience in representative cases from Mexico. Based on empirical data collected from supply chain managers in 2019 (n = 153), 2021 (n = 159), and 2023 (n = 119), the methodological technique involved three phases: (1) PLS-SEM modeling, (2) fuzzy-evolutionary predictive evaluation based on knowledge transfer between latent data, and (3) comparative analysis of the predictive effects of social attributes (labor rights, health and safety, inclusion, and social responsibility) on supply chain resilience. The results found a moderate significant variance in the pre-in-post-COVID-19 effect of social dimensions on supply chain resilience. Social and management implications are presented.
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(This article belongs to the Special Issue Tackling Disruptions in Supply Chain Networks Through Resilient, Sustainable and Innovative Methods and Practices)
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Open AccessArticle
Information and Communication Technology, and Supply Chains as Economic Drivers in the European Union
by
Davor Mance, Siniša Vilke and Borna Debelić
Logistics 2025, 9(2), 49; https://doi.org/10.3390/logistics9020049 - 1 Apr 2025
Abstract
Background: The adoption of information and communication technology (ICT) is transforming supply chains in the European Union, affecting logistical performance, economic integration and sustainability. This study examines the extent to which ICT adoption affects logistics efficiency in the 27 EU Member States.
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Background: The adoption of information and communication technology (ICT) is transforming supply chains in the European Union, affecting logistical performance, economic integration and sustainability. This study examines the extent to which ICT adoption affects logistics efficiency in the 27 EU Member States. Methods: Using panel data from the World Bank and UNCTAD (2008–2018), the analysis applies the Arellano–Bond Generalized Method of Moments estimator to assess the impact of ICT indicators, broadband penetration, mobile connectivity and digital skills on logistics performance. GDP per capita and trade openness are included as control variables. Results: The results show that a 1% increase in ICT usage correlates with a 0.12-point increase in the Logistics Performance Index. Higher ICT usage leads to more efficient supply chains, lower costs and higher customer satisfaction. However, there are still differences in digitalization: the ICT usage rate of SMEs is 28% in Bulgaria and 27% in Romania, compared to the EU average of 59%. Conclusions: Bridging the digital divide requires targeted investments in ICT infrastructure, harmonized regulatory frameworks and stronger public–private cooperation to foster regional economic cohesion. This study provides policy recommendations to drive digital transformation, strengthen the resilience of logistics and improve the sustainability of supply chains in the EU.
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(This article belongs to the Special Issue Sustainable E-commerce, Supply Chains and Logistics)
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Croatia’s Economic Integration in EU’s Regional Supply Chains: Panel Data Quantile Regression
by
Davor Mance, Dora Šekimić and Borna Debelić
Logistics 2025, 9(2), 48; https://doi.org/10.3390/logistics9020048 - 1 Apr 2025
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Background: Recent global disruptions have exposed the vulnerability of international supply chains, prompting a shift toward regionalization to enhance economic resilience. As a European Union (EU) member, Croatia has an opportunity to strengthen its integration into EU regional value chains (RVCs), fostering
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Background: Recent global disruptions have exposed the vulnerability of international supply chains, prompting a shift toward regionalization to enhance economic resilience. As a European Union (EU) member, Croatia has an opportunity to strengthen its integration into EU regional value chains (RVCs), fostering economic stability and competitiveness. This study examines Croatia’s integration into EU RVCs and its economic impact. Methods: Using panel data from the UNCTAD–Eora database (2000–2019), this study applies panel data quantile regression (PDQR) to analyse Croatia’s trade relationships with EU Member States. Unlike traditional regression models, PDQR captures variations in trade dynamics across different levels of economic activity, providing a more detailed understanding of Croatia’s trade resilience. Results: The findings show that Croatia’s trade integration strengthens at higher economic quantiles (τ = 0.75–0.85), reflecting its ability to scale exports during economic expansions. Lower quantiles (τ = 0.05–0.25) display stable but less dynamic trade patterns, suggesting a need for targeted policy interventions to enhance supply chain resilience. Strong trade linkages with Germany, Austria, Slovenia, Hungary, and Italy highlight Croatia’s comparative advantage in high-value trade sectors. Conclusions: Croatia’s integration into EU RVCs supports economic resilience and competitiveness. These findings provide insights for policymakers to optimize trade participation and mitigate vulnerabilities. By demonstrating the benefits of quantile-based trade analysis, this study advances the discourse on regional economic integration.
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Open AccessReview
A Review of Supply Chain Digitalization and Emerging Research Paradigms
by
Xiaowen Lu and Atour Taghipour
Logistics 2025, 9(2), 47; https://doi.org/10.3390/logistics9020047 - 27 Mar 2025
Abstract
Background: The global supply chain landscape is undergoing a significant transformation with the increasing adoption of digital tools. Despite the potential benefits, many organizations struggle to effectively integrate these technologies due to a lack of systematic understanding and frameworks. At the same
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Background: The global supply chain landscape is undergoing a significant transformation with the increasing adoption of digital tools. Despite the potential benefits, many organizations struggle to effectively integrate these technologies due to a lack of systematic understanding and frameworks. At the same time, the academic literature on supply chain digitalization lacks a clear taxonomy and analysis of research paradigms that guide scholarly investigations. Methods: To address these gaps, this paper conducts a comprehensive literature review utilizing an analytic approach, based on abductive reasoning, that establishes an analytical framework to identify, assess, and examine the application of various digital technologies in supply chain management. Results: Based on this analysis, the authors propose new systematic dimensions for digitalization in supply chains, alongside emerging research paradigms in this field. Conclusions: The findings provide valuable insights into the current research landscape, offering a foundation for future investigations. Additionally, practical recommendations are presented for advancing research, education, and management practices, with the goal of promoting innovation and the effective implementation of digital technologies in supply chain management.
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(This article belongs to the Topic Sustainable Supply Chain Practices in A Digital Age)
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Using Entropy Metrics to Analyze Information Processing Within Production Systems: The Role of Organizational Constraints
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Frits van Merode, Henri Boersma, Fleur Tournois, Windi Winasti, Nelson Aloysio Reis de Almeida Passos and Annelies van der Ham
Logistics 2025, 9(2), 46; https://doi.org/10.3390/logistics9020046 - 26 Mar 2025
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Background: The literature on measuring the complexity of production systems employs the graph and information theory. This study analyzes these systems and their coordination under varying states of control, with a focus on the probability of unfavorable events and their temporal characteristics.
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Background: The literature on measuring the complexity of production systems employs the graph and information theory. This study analyzes these systems and their coordination under varying states of control, with a focus on the probability of unfavorable events and their temporal characteristics. Methods: Coordination systems are represented as temporal networks, using entropy and node influence metrics. Two case studies are presented: a factory operating under the principles of the Toyota Production System (TPS) with adjacent (local) coordination and andon (global) coordination and a university obstetrics clinic with only adjacent (local) coordination. Results: Adjacent coordination leads to zero entropy in 38.40% of all situations in the TPS example, contrasted to 76.62% in the same system with andon coordination. Degree centrality of nodes outside of zero-entropy situations exhibits higher average and maximum values in andon coordination networks, compared to those with adjacent coordination in TPS. Entropy values in the university obstetric clinic range from 0.92 to 2.23, average degrees vary between 3 and 4.08, and maximum degrees range from 7 to 9. Conclusions: Coordination systems modeled as temporal networks capture the evolving nature of centralizing and decentralizing coordination in production systems.
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Open AccessArticle
Logistics Hub Surveillance: Optimizing YOLOv3 Training for AI-Powered Drone Systems
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Georgios Tepteris, Konstantinos Mamasis and Ioannis Minis
Logistics 2025, 9(2), 45; https://doi.org/10.3390/logistics9020045 - 24 Mar 2025
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Background: Integrating artificial intelligence in unmanned aerial vehicle systems may enhance the surveillance process of outdoor expansive areas, which are typical in logistics facilities. In this work, we propose methods to optimize the training of such high-performing systems. Methods: Specifically, we
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Background: Integrating artificial intelligence in unmanned aerial vehicle systems may enhance the surveillance process of outdoor expansive areas, which are typical in logistics facilities. In this work, we propose methods to optimize the training of such high-performing systems. Methods: Specifically, we propose a novel approach to tune the training hyperparameters of the YOLOv3 model to improve high-altitude object detection. Typically, the tuning process requires significant computational effort to train the model under numerous combinations of hyperparameters. To address this challenge, the proposed approach systematically searches the hyperparameter space while reducing computational requirements. The latter is achieved by estimating model performance from early terminating training sessions. Results: The results reveal the value of systematic hyperparameter tuning; indicatively, model performance varied more than 13% in terms of mean average precision (mAP), depending on the hyperparameter setting. Also, the early training termination method saved over 90% of training time. Conclusions: The proposed method for searching the hyperparameter space, coupled with early estimation of model performance, supports the development of highly efficient models for UAV-based surveillance of logistics facilities. The proposed approach also identifies the effects of hyperparameters and their interactions on model performance.
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Open AccessArticle
New Dimensions in the Study of Outsourcing Logistics Services: The Role of Digitalization in Enhancing Efficiency
by
Péter Tamás
Logistics 2025, 9(2), 44; https://doi.org/10.3390/logistics9020044 - 24 Mar 2025
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Background: Ensuring cost-efficient and high-quality processes for logistics tasks is a significant competitive factor for companies. This includes not only improving existing processes but also examining outsourcing opportunities. Current trends, such as the increasing variety of products, shorter product life cycles, and
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Background: Ensuring cost-efficient and high-quality processes for logistics tasks is a significant competitive factor for companies. This includes not only improving existing processes but also examining outsourcing opportunities. Current trends, such as the increasing variety of products, shorter product life cycles, and a dynamically changing economic environment, necessitate frequent reviews and, if needed, the reorganization of logistics activities. Methods: Modern digitalization technologies (e.g., digital twins, artificial intelligence, etc.) open new possibilities for (re)evaluating outsourcing decisions, such as improving process transparency and leveraging optimization opportunities. The currently applied solutions are fragmented and, in many cases, do not integrate digitalization technologies and standardized examination processes, necessitating the development of a new process development framework concept. The research follows an inductive–deductive methodology, combining practical industrial experience with a thorough literature review. Results: The framework presented in this study enables a faster and more efficient evaluation compared to previous approaches by incorporating the application of digitalization technologies. The validity of the developed concept is demonstrated through a case study. Conclusions: The findings highlight the importance of integrating digitalization technologies into logistics process development to enhance decision-making and efficiency. The proposed framework provides a structured approach that facilitates a more effective evaluation of outsourcing decisions and process improvements.
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Open AccessArticle
Emergency Supply Chain Resilience Enhanced Through Blockchain and Digital Twin Technology
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Marta Rinaldi, Mario Caterino, Stefano Riemma, Roberto Macchiaroli and Marcello Fera
Logistics 2025, 9(1), 43; https://doi.org/10.3390/logistics9010043 - 20 Mar 2025
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Background: Emergency scenarios present unprecedented challenges for supply chains worldwide, particularly in the management and distribution of critical supplies, where timely delivery and maintaining integrity are crucial. Methods: This article explores an innovative approach to enhance the emergency management of supply chains
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Background: Emergency scenarios present unprecedented challenges for supply chains worldwide, particularly in the management and distribution of critical supplies, where timely delivery and maintaining integrity are crucial. Methods: This article explores an innovative approach to enhance the emergency management of supply chains using blockchain technology and simulation-based modelling. The proposed methodology aims to tackle issues such as transparency, efficiency, and security, which are vital for managing logistics during crises. A case study involving a vaccine rollout is used to demonstrate how blockchain can optimise supply chain operations, reduce bottlenecks, and ensure better traceability and accountability throughout the process. The case study is specifically developed based on the distribution of COVID-19 vaccines in Italy. Results: The integration of blockchain technology not only enhances data integrity and security but also facilitates real-time monitoring and decision-making. Conslusions: The findings suggest that the proposed blockchain-based model can significantly improve supply chain resilience in emergency situations compared to traditional methods, thereby offering valuable insights for policymakers and supply chain managers facing future crises.
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Open AccessSystematic Review
Temporary Facility Location Problem in Humanitarian Logistics: A Systematic Literature Review
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María Fernanda Carnero Quispe, Lucciana Débora Chambilla Mamani, Hugo Tsugunobu Yoshida Yoshizaki and Irineu de Brito Junior
Logistics 2025, 9(1), 42; https://doi.org/10.3390/logistics9010042 - 20 Mar 2025
Abstract
Background: Facility location is a key challenge in humanitarian logistics, particularly in disaster response, where rapid and efficient resource deployment is crucial. Temporary facilities offer a cost-effective solution due to their rapid deployment and flexibility in addressing increased demand and the dynamic conditions
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Background: Facility location is a key challenge in humanitarian logistics, particularly in disaster response, where rapid and efficient resource deployment is crucial. Temporary facilities offer a cost-effective solution due to their rapid deployment and flexibility in addressing increased demand and the dynamic conditions of post-disaster environments. Methods: This study conducts a systematic literature review following PRISMA guidelines to analyze facility location problems involving temporary or modular facilities in humanitarian logistics. A total of 65 articles from Scopus and Web of Science were analyzed. Results: Most studies focus on temporary facilities like shelters and medical centers in earthquake-affected areas, with most applications in Asia. Despite being temporary, only 6% of the studies consider closure decisions. Recent research explores modular facilities that enhance adaptability through module relocation and capacity adjustments. Conclusions: Temporary facilities after sudden-onset disasters require advanced modeling approaches that include multi-period planning, modular design, and complex decision-making, requiring solutions through heuristics or relaxations. However, there is a lack of research on their application in slow-onset and human-induced disasters. Moreover, considering geographical, cultural, and political factors is essential to ensure effective solutions. Further studies are also needed on facilities functioning as collection and processing centers, given their critical role in the humanitarian supply chain.
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(This article belongs to the Section Humanitarian and Healthcare Logistics)
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A Multi-Objective Dynamic Resource Allocation Model for Search and Rescue and First Aid Tasks in Disaster Response by Employing Volunteers
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Emine Nisa Kapukaya and Sule Itir Satoglu
Logistics 2025, 9(1), 41; https://doi.org/10.3390/logistics9010041 - 14 Mar 2025
Abstract
Background: Each disaster has its specific resource requirements, varying based on its size, location, and the affected region’s socio-economic level. Pre-disaster planning and post-disaster dynamic resource allocation including material and human resources is essential. Methods: To address the resource allocation challenges
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Background: Each disaster has its specific resource requirements, varying based on its size, location, and the affected region’s socio-economic level. Pre-disaster planning and post-disaster dynamic resource allocation including material and human resources is essential. Methods: To address the resource allocation challenges in disaster response, a multi-objective two-stage stochastic programming model is developed for search and rescue and first aid activities. The model aims to minimize the total unmet human demand, the number of resources transferred between regions, and the total unmet material demand. The proposed model was solved for a real case of an expected earthquake in Istanbul’s Kartal district. The augmented epsilon constraint 2 algorithm was employed using the CPLEX solver. A sensitivity analysis was made. Results: Most of the unmet demand occurs in the first period. After that period, the unmet demand decreases with interregional transfers and additional resources. The model is robust to scenario probability and penalty value changes in the objectives. Conclusions: This is the first study that simultaneously and dynamically allocates renewable and non-renewable material resources and human resources, including the official rescue units and volunteers, for disaster response. Volunteers’ inclusion in teams considering their training and quitting behavior are unique aspects of the study.
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(This article belongs to the Section Humanitarian and Healthcare Logistics)
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Open AccessArticle
Picker Routing and Batching in Multi-Block Parallel-Aisle Warehouses: An Application from the Logistics Service Provider
by
Ali Görener
Logistics 2025, 9(1), 40; https://doi.org/10.3390/logistics9010040 - 13 Mar 2025
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Background: In today’s business world, where competition lies between supply chains, customer expectations are changing dynamically. Effective order picking in warehouses has become a top concern given expectations for rapid delivery, a larger product range, and continuous support. Methods: In this study, it
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Background: In today’s business world, where competition lies between supply chains, customer expectations are changing dynamically. Effective order picking in warehouses has become a top concern given expectations for rapid delivery, a larger product range, and continuous support. Methods: In this study, it is aimed to find a simultaneous solution to the problems of picker routing and order batching, which have an important place in order picking. A genetic algorithm-based solution with group-based coding is proposed to minimize the travel time of pickers. Results: A new set of equations for rectangular warehousing systems with three or more blocks (multi-blocks) is presented to directly determine the shortest distances between order points. It is found that the proposed solution methodology gives better results than traditional approaches. Conclusions: The study is expected to contribute to the improvement of order picking, which is the most costly and repetitive activity in warehouses, within the scope of practical and academic applications.
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Open AccessArticle
Multi-Aspect Probability Model of Expected Profit Subject to Uncertainty for Managerial Decision-Making in Local Transport Problems
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Martin Holubčík, Lukáš Falát, Jakub Soviar and Juraj Dubovec
Logistics 2025, 9(1), 39; https://doi.org/10.3390/logistics9010039 - 13 Mar 2025
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Background: Governments face critical decisions regarding road remediation projects, requiring careful economic evaluation, especially in countries like Slovakia where road infrastructure is crucial for attracting foreign investment. These decisions are complex, involving short-term and long-term costs and revenues, along with inherent uncertainty
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Background: Governments face critical decisions regarding road remediation projects, requiring careful economic evaluation, especially in countries like Slovakia where road infrastructure is crucial for attracting foreign investment. These decisions are complex, involving short-term and long-term costs and revenues, along with inherent uncertainty about future outcomes. Traditional economic assessments often fail to capture the full scope of these factors, potentially leading to suboptimal choices. Methods: This study proposes four probability-based models: the Short-term Model (SM), Long-term-Short-term Model (LSM), Social Long-term-Short-term Model (SLSM), and Long-term-Short-term Model with a Time Aspect (TLSM). These models incorporate probabilistic functions to calculate expected costs and profits, considering various factors such as reparation costs, financial compensations, social costs, and time-related costs, as well as long-term benefits like increased investment and lives saved. Results: The proposed models were partially validated through an ex post analysis of a past road remediation project on road 1/18 (E50) under the Strecno castle cliff in Slovakia. The analysis demonstrated the models’ utility for multi-criteria decision-making in transportation problems, highlighting their ability to capture the complex interplay of economic and societal factors. Conclusions: The models enable governments to maximize societal benefit while mitigating potential risks, contributing to a more sustainable and efficient transportation sector. Future research could focus on refining the models and adapting them to other sectors beyond transportation.
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Open AccessArticle
Analyzing Airline Fleet Resilience Using the Disruption Funnel Framework
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H. A. Elhamy and A. B. Eltawil
Logistics 2025, 9(1), 38; https://doi.org/10.3390/logistics9010038 - 11 Mar 2025
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Background: Defining the optimal fleet portfolio is a crucial process in airline planning. The published efforts in literature provide ways to anticipate the disruption effects on the passenger demand; however, the proposed solution in this paper provides visibility on the impact of
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Background: Defining the optimal fleet portfolio is a crucial process in airline planning. The published efforts in literature provide ways to anticipate the disruption effects on the passenger demand; however, the proposed solution in this paper provides visibility on the impact of sustainable disruption and the way an airline can resist it. Methods: This paper proposes a two-stage methodology to find the best portfolio for airline operational requirements under the impact of disruption. The first stage considers optimization for normal airline operations under a specific fleet portfolio using an Integer Linear Programming (ILP) model. The second stage of the analysis is a mapping for the scenario-based methodology to find a way out for an airline subjected to some given disruption in operations. Results: The result of the two-stage analysis shall define the best fleet portfolio to withstand sustained disruptions by mapping the results in a disruption funnel and showing the impact of the supply and demand gap on the airline’s sustainable profitability. Conclusions: This paper provides a novel, practical way of evaluating strategic decisions to choose the best fleet portfolio and make airlines rely on the mapping of the disruption funnel to modify their network while increasing supply chain resilience.
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(This article belongs to the Section Sustainable Supply Chains and Logistics)
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Analysis of Strategies to Combat Cargo Theft and Robbery in Peripheral Communities of São Paulo, Brazil, Using a Paraconsistent Expert System
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Kennya Vieira Queiroz, Jair Minoro Abe, João Gilberto Mendes dos Reis and Miguel Renon
Logistics 2025, 9(1), 37; https://doi.org/10.3390/logistics9010037 - 10 Mar 2025
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Background: Cargo theft represents a persistent challenge to last-mile logistics in the peripheral regions of São Paulo, Brazil, compromising transportation security and increasing operational costs. These high-crime areas disrupt supply chain stability and hinder e-commerce growth. Traditional security methods often fail to address
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Background: Cargo theft represents a persistent challenge to last-mile logistics in the peripheral regions of São Paulo, Brazil, compromising transportation security and increasing operational costs. These high-crime areas disrupt supply chain stability and hinder e-commerce growth. Traditional security methods often fail to address the complexity and uncertainty present in these environments, necessitating adaptive approaches. Methods: This study applies an Expert System based on Paraconsistent Annotated Evidential Logic Eτ to assess the effectiveness of security interventions. Logic Eτ is particularly suited for analyzing uncertain, incomplete, and contradictory data in complex logistics settings. A mixed-methods approach was employed, integrating evaluations from nine experts representing different hierarchical levels within a logistics company. Six key security measures, including GPS tracking, armed escorts, optimized delivery windows, and the hiring of local drivers, were analyzed using favorable degrees and unfavorable degrees for each parameter. Results: The results demonstrated that five measures were effective, contributing to a 58% reduction in security costs in Arujá and 75% in Cajamar, two major distribution hubs. Conclusions: This study highlights the potential of combining Expert Systems and Eτ Logic to enhance cargo transport security, offering a scalable decision support framework for companies operating in high-risk urban regions.
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Open AccessArticle
Industry 4.0-Enabled Supply Chain Performance: Do Supply Chain Capabilities and Innovation Matter?
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Ayman Bahjat Abdallah, Hamza Ahmad Almomani and Zu’bi M. F. Al-Zu’bi
Logistics 2025, 9(1), 36; https://doi.org/10.3390/logistics9010036 - 10 Mar 2025
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Background: The present study investigates Industry 4.0’s (I4.0) impact on supply chain capabilities (SCCs), supply chain innovation (SCI), and supply chain performance (SCP). The influence of SCCs and SCI on SCP is also explored. Additionally, the mediating impacts of SCCs and SCI
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Background: The present study investigates Industry 4.0’s (I4.0) impact on supply chain capabilities (SCCs), supply chain innovation (SCI), and supply chain performance (SCP). The influence of SCCs and SCI on SCP is also explored. Additionally, the mediating impacts of SCCs and SCI on the I4.0-SCP relationship are analyzed. Methods: The study’s population consisted of manufacturing companies located in Amman, Jordan. A purposive sample of 211 companies was selected. Self-administered questionnaires were completed by targeted managers in the participating companies. Results: The outcomes indicated that the total impact of I4.0 on SCP was significant and positive. I4.0 positively affected both SCCs and SCI. Additionally, SCCs and SCI were found to positively affect SCP. Finally, the results demonstrated a full mediating impact of SCCs and SCI on the I4.0-SCP relationship, with over two-thirds of the mediation impact attributed to SCCs. Conclusions: This research is among the earliest to examine I4.0’s impact on SCP. It also fills a research gap by exploring I4.0’s influence on both SCCs and SCI. To the best of our knowledge, the present study is the first to investigate the mediation effect of SCCs and SCI on the I4.0-SCP relationship, thus providing a valuable contribution to the existing literature.
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Open AccessArticle
A Multi-Type Ship Allocation and Routing Model for Multi-Product Oil Distribution in Indonesia with Inventory and Cost Minimization Considerations: A Mixed-Integer Linear Programming Approach
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Marudut Sirait, Peerayuth Charnsethikul and Naraphorn Paoprasert
Logistics 2025, 9(1), 35; https://doi.org/10.3390/logistics9010035 - 6 Mar 2025
Abstract
Background: Indonesia is an archipelagic country with 17,508 islands spread over the Pacific and Indian Oceans, with thousands of inter-island routes requiring a large and engaged fleet. The vast expanse of the country also leads to challenges related to optimal fleet coverage,
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Background: Indonesia is an archipelagic country with 17,508 islands spread over the Pacific and Indian Oceans, with thousands of inter-island routes requiring a large and engaged fleet. The vast expanse of the country also leads to challenges related to optimal fleet coverage, routing, and oil distribution while maintaining cost-effectiveness and reliable supply. Methods: This study combined a mixed-integer linear-programming (MILP) model with a response surface methodology (RSM) approach to optimize vessel assignment, vessel routes, and inventory control simultaneously and comprehensively across three regional clusters (i.e., Western, Central, and Eastern Indonesia). The model takes into account a fleet of 28 vessels (13 medium range [MR] and 15 general purpose [GP]) that can distribute three oil products: gasoline, diesel, and kerosene. Results: The optimized solution yields 100% service reliability at an operational cost of $ 2.83 million per month—far lower than currently operating services. The model is robust against variations in demand (±20%), port congestion (±50%), and changing fuel prices (±50%), which is confirmed by a sensibility analysis. The close correlation coefficient (0.987) between the MILP and RSM results confirms the framework’s accuracy. At the same time, the critical performance factors were found to be vessel speed (13.5 knots), fleet size, and port operation time. Conclusions: The study offers a cost-efficient and data-intensive model that could be implemented as a maritime logistics framework, as well as potential areas for future work and insight for relevant stakeholders. Future research will have to integrate real-time data fusion, mainly due to the need for environmental and stochastic modeling methods to foster operational resilience in dynamic maritime business ecosystems.
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(This article belongs to the Section Maritime and Transport Logistics)
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Open AccessArticle
Tracking Patient Movements Using an IoT and RFID System—A Case Study in a Romanian Clinic
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Marian Stoica and Alexandru-Ionut Nitu
Logistics 2025, 9(1), 34; https://doi.org/10.3390/logistics9010034 - 5 Mar 2025
Abstract
Background: In a world increasingly shaped by technological innovation, the healthcare sector plays an important role in society’s sustainable advancement. This study explores the use of IoT and RFID technologies to improve hospital operations and modernize healthcare services. Methods: We propose
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Background: In a world increasingly shaped by technological innovation, the healthcare sector plays an important role in society’s sustainable advancement. This study explores the use of IoT and RFID technologies to improve hospital operations and modernize healthcare services. Methods: We propose a patient tracking system that uses RFID wristbands for real-time monitoring of patient movement. The paper describes the system’s design, components, installation process, and evaluation. Results: The system was implemented and tested by a private healthcare provider in Romania. The results show improvements in operational efficiency, accuracy in tracking, and overall patient care. Conclusions: The use of RFID technology in healthcare offers a practical approach to improving hospital operations. This system proves the potential for more efficient patient management and better overall healthcare delivery.
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(This article belongs to the Section Humanitarian and Healthcare Logistics)
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Open AccessArticle
Design of a Remanufacturing Line Applying Lean Manufacturing and Supply Chain Strategies
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Rosa Hilda Félix-Jácquez, Óscar Hernández-Uribe, Leonor Adriana Cárdenas-Robledo and Zaida Antonieta Mora-Alvarez
Logistics 2025, 9(1), 33; https://doi.org/10.3390/logistics9010033 - 20 Feb 2025
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Background: Remanufacturing products for sustainability involves layout and production planning, tools and equipment, material arrangement and handling, inventory management, technology integration, and more. This study presents an empirical vision through a discrete event simulation (DES) model integrating lean manufacturing (LM) and supply
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Background: Remanufacturing products for sustainability involves layout and production planning, tools and equipment, material arrangement and handling, inventory management, technology integration, and more. This study presents an empirical vision through a discrete event simulation (DES) model integrating lean manufacturing (LM) and supply chain (SC) strategies with industry 4.0 (I4.0) technologies, applied to a case in a railway company. Methods: The work presents scenarios following a methodology with an incremental approach to implement strategies of lean manufacturing (LM) and supply chain (SC) in the context of I4.0 and their effects represented in DES models with applicability in remanufacturing and production line management. Five simulation scenarios were analyzed according to strategies layered incrementally. Results: Behaviors and outcomes were compared across the scenarios considering the remanufactured engines, percentage of process time, human labor occupation, and the statistical analysis of the process capability. Scenario five achieved the objective of remanufacturing 40 engines in one year with a cycle time of 214.45 h. Conclusions: The purpose was to design an engine remanufacturing line incorporating LM and SC strategies via a DES model, highlighting the importance of their gradual adoption toward I4.0 implementation. The integration of previous strategies improves flexibility and productivity in manufacturing processes.
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Open AccessSystematic Review
Weather-Related Disruptions in Transportation and Logistics: A Systematic Literature Review and a Policy Implementation Roadmap
by
Dimos Touloumidis, Michael Madas, Vasileios Zeimpekis and Georgia Ayfantopoulou
Logistics 2025, 9(1), 32; https://doi.org/10.3390/logistics9010032 - 20 Feb 2025
Abstract
Background: The increasing frequency and severity of extreme weather events (EWEs) as a consequence of climate change pose critical challenges on the transport and logistics sector, hence requiring systematic evaluation and strategic adaptation. Methods: This study conducts a comprehensive systematic literature
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Background: The increasing frequency and severity of extreme weather events (EWEs) as a consequence of climate change pose critical challenges on the transport and logistics sector, hence requiring systematic evaluation and strategic adaptation. Methods: This study conducts a comprehensive systematic literature review (SLR) of 147 peer-reviewed articles and reports through a PRISMA framework to comprehensively identify key weather-induced challenges, quantify their operational, infrastructural and economic impacts, and explore alternative mitigation strategies. Results: With a greater focus on rainfall, flooding and snowfall, this study highlights their notable impacts causing reductions in transport efficiency, increased maintenance costs and substantial financial losses. Also, it emphasizes the role of advanced technologies, resilient infrastructure, and adaptive policy frameworks as critical enablers for enhancing sector resilience while simultaneously formulating a robust roadmap for cities and companies with actions ranging from direct operational adjustments to long-term transformational changes in policy and infrastructure. Conclusions: This work underscores the importance of using a data-driven approach to safeguard transport and logistics systems against evolving climate risks contributing to the broader goal of sustainable urban resilience and operational continuity.
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(This article belongs to the Special Issue Tackling Disruptions in Supply Chain Networks Through Resilient, Sustainable and Innovative Methods and Practices)
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Open AccessArticle
Multi-Criteria Decision Analysis for Sustainable Medicinal Supply Chain Problems with Adaptability and Challenges Issues
by
Alaa Fouad Momena, Kamal Hossain Gazi and Sankar Prasad Mondal
Logistics 2025, 9(1), 31; https://doi.org/10.3390/logistics9010031 - 14 Feb 2025
Abstract
Background: The supply chain refers to the full process of creating and providing a good or service, starting with the raw materials and ending with the final customer. It requires cooperation and coordination between many parties, including the suppliers, manufacturers, distributors, retailers, and
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Background: The supply chain refers to the full process of creating and providing a good or service, starting with the raw materials and ending with the final customer. It requires cooperation and coordination between many parties, including the suppliers, manufacturers, distributors, retailers, and customers. Methods: In the medicinal supply chain (MSC), the critical nature of these processes becomes more complicated. It requires strict regulation, quality control, and traceability to ensure patient safety and compliance with regulatory standards. This study is conducted to suggest a smooth channel to deal with the challenges and adaptability of the MSC. Different MSC challenges are considered as criteria which deal with various adaptation plans. Multi-criteria decision-making (MCDM) methodologies are taken as optimization tools and probabilistic linguistic term sets (PLTSs) are considered for express uncertainty. Results: The subscript degree function (SDF) and deviation degree function (DDF) are introduced to evaluate the crisp value of the PLTSs. An MSC model is constructed to optimize the sustainable medicinal supply chain and overcome various barriers to MSC problems. Conclusions: Additionally, sensitivity analysis and comparative analysis were conducted to check the robustness and flexibility of the system. Finally, the conclusion section determines the optimal weighted criteria for the MSC problem and identifies the best possible solutions for MSC using PLTS-based MCDM methodologies.
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(This article belongs to the Special Issue Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics)
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