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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)

Imprint Information Journal Flyer Open Access ISSN: 2305-6290

Latest Articles

21 pages, 7469 KiB

Open AccessArticle

Social Media and Logistics: Uncovering Challenges and Solutions Through YouTube Data

by Hisatoshi Naganawa and Enna Hirata

Logistics 2025, 9(2), 56; https://doi.org/10.3390/logistics9020056 - 23 Apr 2025

Background: Logistics challenges, such as driver shortages, are a major global issue, with many countries struggling to find effective solutions. YouTube, as a social networking platform, has a growing user base and is increasingly used not only for entertainment but also for [...] Read more.

Background: Logistics challenges, such as driver shortages, are a major global issue, with many countries struggling to find effective solutions. YouTube, as a social networking platform, has a growing user base and is increasingly used not only for entertainment but also for social interaction, such as commenting, searching, and browsing, and it can thus potentially be used as an indicator of the topic under discussion. Methods: This study collects YouTube data containing keywords related to logistics issues—particularly the 2024 problem—and applies natural language processing (NLP) techniques to explore potential solutions. It is the first study to analyze both subtitle and comment data extracted from YouTube audio as large-scale text data in the field of logistics. Results: The analysis identified four primary areas of concern in logistics: time management, driver welfare, technological investment, and policy transparency. Sentiment analysis revealed a predominant negative sentiment in user discussions, highlighting dissatisfaction with current logistics policies and operations. Conclusions: The findings provide new insights that could inform the development of effective logistics policies and improve services for logistics companies while also proposing innovative research methods using NLP. Full article

(This article belongs to the Section Artificial Intelligence, Logistics Analytics, and Automation)

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16 pages, 2678 KiB

Open AccessArticle

Demographic and Operational Factors in Public Transport-Based Parcel Locker Crowdshipping: A Mixed-Methods Analysis

by Mohammad Maleki, Scott Rayburg and Stephen Glackin

Logistics 2025, 9(2), 55; https://doi.org/10.3390/logistics9020055 - 18 Apr 2025

Background: The rapid rise of e-commerce has intensified last-mile logistics challenges, fueling the need for sustainable, efficient solutions. Parcel locker crowdshipping systems, integrated with public transport networks, show promise in reducing congestion, emissions, and delivery costs. However, operational and physical constraints (e.g., [...] Read more.

Background: The rapid rise of e-commerce has intensified last-mile logistics challenges, fueling the need for sustainable, efficient solutions. Parcel locker crowdshipping systems, integrated with public transport networks, show promise in reducing congestion, emissions, and delivery costs. However, operational and physical constraints (e.g., crowded stations) and liability complexities remain significant barriers to broad adoption. This study investigates the demographic and operational factors that influence the adoption and scalability of these systems. Methods: A mixed-methods design was employed, incorporating survey data from 368 participants alongside insights from 20 semi-structured interviews. Quantitative analysis identified demographic trends and operational preferences, while thematic analysis offered in-depth contextual understanding. Results: Younger adults (18–34), particularly gig-experienced males, emerged as the most engaged demographic. Females and older individuals showed meaningful potential if safety and flexibility concerns were addressed. System efficiency depended on locating parcel lockers within 1 km of major origins and destinations, focusing on moderate parcel weights (3–5 kg), and offering incentives for minor route deviations. Interviews emphasized ensuring that lockers avoid station congestion, clearly defining insurance/liability protocols, and allowing task refusals during peak passenger hours. Conclusions: By leveraging public transport infrastructure, parcel locker crowdshipping requires robust policy frameworks, strategic station-space allocation, and transparent incentives to enhance feasibility. Full article

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21 pages, 1819 KiB

Open AccessArticle

A Framework for Leveraging Digital Technologies in Reverse Logistics Actions: A Systematic Literature Review

by Sílvia Patrícia Rodrigues, Leonardo de Carvalho Gomes, Fernanda Araújo Pimentel Peres, Ricardo Gonçalves de Faria Correa and Ismael Cristofer Baierle

Logistics 2025, 9(2), 54; https://doi.org/10.3390/logistics9020054 - 16 Apr 2025

Background: The global climate crisis has intensified the demand for sustainable solutions, positioning Reverse Logistics (RL) as a critical strategy for minimizing environmental impacts. Simultaneously, Industry 4.0 technologies are transforming RL operations by enhancing their collection, transportation, storage, sorting, remanufacturing, recycling, and [...] Read more.

Background: The global climate crisis has intensified the demand for sustainable solutions, positioning Reverse Logistics (RL) as a critical strategy for minimizing environmental impacts. Simultaneously, Industry 4.0 technologies are transforming RL operations by enhancing their collection, transportation, storage, sorting, remanufacturing, recycling, and disposal processes. Understanding the roles of these technologies is essential for improving efficiency and sustainability. Methods: This study employs a systematic literature review, following the PRISMA methodology, to identify key Industry 4.0 technologies applicable to RL. Publications from Scopus and Web of Science were analyzed, leading to the development of a theoretical framework linking these technologies to RL activities. Results: The findings highlight the fact that technologies like the Internet of Things (IoT), Artificial Intelligence (AI), Big Data Analytics, Cloud Computing, and Blockchain enhance RL by improving traceability, automation, and sustainability. Their application optimizes execution time, reduces operational costs, and mitigates environmental impacts. Conclusions: For the transportation and manufacturing sectors, integrating Industry 4.0 technologies into RL can streamline supply chains, enhance decision-making, and improve resource utilization. Smart tracking, predictive maintenance, and automated sorting systems reduce waste and improve operational resilience, reinforcing the transition toward a circular economy. By adopting these innovations, stakeholders can achieve economic and environmental benefits while ensuring regulatory compliance and long-term competitiveness. Full article

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22 pages, 1535 KiB

Open AccessArticle

From Adopting Industry 4.0 Technologies to Improving Operational Performance in Hospital Supply Chain: The Moderating Effect of HSC Complexity

by Ahmed Chtioui, Imane Bouhaddou and Asmaa Benghabrit

Logistics 2025, 9(2), 53; https://doi.org/10.3390/logistics9020053 - 15 Apr 2025

Background: The hospital supply chain (HSC) is one of the main levers for improving the performance of any healthcare organization. HSC stakeholders evolve in a dynamic environment marked by great complexity. This observation led us to conduct research, through which we examined [...] Read more.

Background: The hospital supply chain (HSC) is one of the main levers for improving the performance of any healthcare organization. HSC stakeholders evolve in a dynamic environment marked by great complexity. This observation led us to conduct research, through which we examined several factors enabling operational performance to be achieved within the HSC. Methods: For the empirical verification, we opted for a survey of a relevant sample composed of health professionals operating in different Moroccan hospitals, particularly in the logistics departments. Afterwards, the data were analyzed using a Partial Least Squares-Structural Equation Modeling (PLS-SEM) method to test the hypothesized relationships in this study. Results: The results show that the adoption of Industry 4.0 technologies improve collaborative aspects between logistics processes and flows, and thus ensure better integration of HSC. The research also highlights the moderating effect of HSC complexity in the relationship between HSC integration and HSC operational performance, i.e., HSC integration increases HSC operational performance in a context marked by high complexity. Conclusions: This paper explores the impact of Industry 4.0 technologies on HSC operational performance. The study provides hospital managers and practitioners with insights to improve HSC operational performance through integration initiatives, ultimately better meeting the needs of healthcare professionals and contributing to improve the quality of care. Full article

(This article belongs to the Section Humanitarian and Healthcare Logistics)

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33 pages, 1420 KiB

Open AccessArticle

Agent-Based Control of Interaction Areas in Intralogistics: Concept, Implementation and Simulation

by Felix Gehlhoff, Niklas Jobs and Vincent Henkel

Logistics 2025, 9(2), 52; https://doi.org/10.3390/logistics9020052 - 14 Apr 2025

Background: Intralogistics systems face growing challenges from globalization, individualization, and shorter product life cycles, demanding flexible and responsive solutions beyond traditional centralized control. Decentralized, agent-based approaches offer potential advantages, especially for Automated Guided Vehicle (AGV) systems where managing collisions in interaction areas [...] Read more.

Background: Intralogistics systems face growing challenges from globalization, individualization, and shorter product life cycles, demanding flexible and responsive solutions beyond traditional centralized control. Decentralized, agent-based approaches offer potential advantages, especially for Automated Guided Vehicle (AGV) systems where managing collisions in interaction areas remains a critical issue. Methods: This study proposes two decentralized, agent-based control concepts for AGV systems in intralogistics. One uses a hierarchical model with an Intersection Manager to coordinate AGV agents, while the other employs a fully heterarchical system. For benchmarking, a First Come, First Served heuristic and a Mixed-Integer Linear Programming (MILP) method are also implemented. Simulations show both agent-based approaches effectively prevent collisions and uphold order prioritization and timing goals. While average delays are similar, the heterarchical system requires up to 2.7 times more communication. Priority-based control enhances timeliness for highpriority vehicles but can increase delays for lower-priority AGVs. The MILP method, though effective, is limited by impractical computation times. Results: The study confirms the viability of agent-based control for managing interaction areas in AGV systems, highlighting trade-offs between decentralization, efficiency, and communication. Conclusions: It offers a foundation for further research into hybrid models and real-world application of decentralized control strategies. Full article

(This article belongs to the Section Artificial Intelligence, Logistics Analytics, and Automation)

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23 pages, 2966 KiB

Open AccessArticle

Dynamical System Modeling for Disruption in Supply Chain and Its Detection Using a Data-Driven Deep Learning-Based Architecture

by Víctor Hugo de la Cruz Madrigal, Liliana Avelar Sosa, Jose-Manuel Mejía-Muñoz, Jorge Luis García Alcaraz and Emilio Jiménez Macías

Logistics 2025, 9(2), 51; https://doi.org/10.3390/logistics9020051 - 8 Apr 2025

Background: The COVID-19 was a determining factor in the disruption of supply chains in the automotive industry, exacerbating material shortages. This led to increased supplier order cancelations, longer lead times, and reduced safety inventory levels. Methods: This study analyzes and models supply chain [...] Read more.

Background: The COVID-19 was a determining factor in the disruption of supply chains in the automotive industry, exacerbating material shortages. This led to increased supplier order cancelations, longer lead times, and reduced safety inventory levels. Methods: This study analyzes and models supply chain disruptions using system dynamics as a key tool, focusing on the disruptions caused by delays in scheduled orders and their impact on service levels within automotive supply chains in Mexico. This approach allowed us to capture the dynamic relationships and cascading effects associated with inventory shrinkage at Tier 2 suppliers, highlighting how these delays affect the chain’s overall performance. In addition to modeling using system dynamics, a deep-learning-based network was proposed to detect disruptions using the data generated by the dynamic model. The network architecture integrates convolutional layers for feature extraction and dense layers for classification, thereby enhancing its ability to identify disruption-related patterns. Results: The performance of the proposed model was evaluated using the AUC metric and compared with alternative methods. The proposed network achieved an AUC of 0.87, outperforming the multilayer perceptron model (AUC = 0.76) and a Neyman–Pearson-based model (AUC = 0.63). These results confirm the superior discriminatory ability of our approach, demonstrating higher accuracy and reliability in detecting disruptions. Furthermore, the dynamical models reveal that the domino effect increases delays in order reception due to the reduction in raw material inventories at Tier 2 suppliers. Conclusions: This paper effectively evaluates the impact of disruptions by demonstrating how reduced service levels propagate through the supply chain. Full article

(This article belongs to the Section Supplier, Government and Procurement Logistics)

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32 pages, 1168 KiB

Open AccessArticle

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

by Miguel Reyna-Castillo, Alejandro Santiago, Ana Xóchitl Barrios-del-Ángel, Francisco Manuel García-Reyes, Fausto Balderas and José Ignacio Anchondo-Pérez

Logistics 2025, 9(2), 50; https://doi.org/10.3390/logistics9020050 - 2 Apr 2025

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 [...] Read more.

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. Full article

(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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18 pages, 3805 KiB

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

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. [...] Read more.

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. Full article

(This article belongs to the Special Issue Sustainable E-commerce, Supply Chains and Logistics)

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19 pages, 5271 KiB

Open AccessArticle

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

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 [...] Read more.

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. Full article

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25 pages, 2776 KiB

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

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 [...] Read more.

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. Full article

(This article belongs to the Topic Sustainable Supply Chain Practices in A Digital Age)

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24 pages, 4145 KiB

Open AccessArticle

Using Entropy Metrics to Analyze Information Processing Within Production Systems: The Role of Organizational Constraints

by 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

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. [...] Read more.

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. Full article

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27 pages, 5567 KiB

Open AccessArticle

Logistics Hub Surveillance: Optimizing YOLOv3 Training for AI-Powered Drone Systems

by Georgios Tepteris, Konstantinos Mamasis and Ioannis Minis

Logistics 2025, 9(2), 45; https://doi.org/10.3390/logistics9020045 - 24 Mar 2025

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 [...] Read more.

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. Full article

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24 pages, 3256 KiB

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

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 [...] Read more.

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. Full article

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24 pages, 2930 KiB

Open AccessArticle

Emergency Supply Chain Resilience Enhanced Through Blockchain and Digital Twin Technology

by 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

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 [...] Read more.

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. Full article

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27 pages, 739 KiB

Open AccessSystematic Review

Temporary Facility Location Problem in Humanitarian Logistics: A Systematic Literature Review

by 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

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 [...] Read more.

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. Full article

(This article belongs to the Section Humanitarian and Healthcare Logistics)

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30 pages, 1303 KiB

Open AccessArticle

A Multi-Objective Dynamic Resource Allocation Model for Search and Rescue and First Aid Tasks in Disaster Response by Employing Volunteers

by Emine Nisa Kapukaya and Sule Itir Satoglu

Logistics 2025, 9(1), 41; https://doi.org/10.3390/logistics9010041 - 14 Mar 2025

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 [...] Read more.

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. Full article

(This article belongs to the Section Humanitarian and Healthcare Logistics)

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27 pages, 3310 KiB

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

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 [...] Read more.

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. Full article

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27 pages, 1539 KiB

Open AccessArticle

Multi-Aspect Probability Model of Expected Profit Subject to Uncertainty for Managerial Decision-Making in Local Transport Problems

by Martin Holubčík, Lukáš Falát, Jakub Soviar and Juraj Dubovec

Logistics 2025, 9(1), 39; https://doi.org/10.3390/logistics9010039 - 13 Mar 2025

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 [...] Read more.

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. Full article

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23 pages, 2574 KiB

Open AccessArticle

Analyzing Airline Fleet Resilience Using the Disruption Funnel Framework

by H. A. Elhamy and A. B. Eltawil

Logistics 2025, 9(1), 38; https://doi.org/10.3390/logistics9010038 - 11 Mar 2025

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 [...] Read more.

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. Full article

(This article belongs to the Section Sustainable Supply Chains and Logistics)

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17 pages, 1528 KiB

Open AccessArticle

Analysis of Strategies to Combat Cargo Theft and Robbery in Peripheral Communities of São Paulo, Brazil, Using a Paraconsistent Expert System

by 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

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 [...] Read more.

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. Full article

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