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Editor’s Choice Articles

Editor’s Choice articles are based on recommendations by the scientific editors of MDPI journals from around the world. Editors select a small number of articles recently published in the journal that they believe will be particularly interesting to readers, or important in the respective research area. The aim is to provide a snapshot of some of the most exciting work published in the various research areas of the journal.

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30 pages, 7646 KB  
Article
Development of an Integrated Optimization Model for Container Relocation and Truck Appointment Scheduling (TAS)
by Yosi Agustina Hidayat and Fariz Affandi Harahap
Logistics 2026, 10(6), 128; https://doi.org/10.3390/logistics10060128 - 4 Jun 2026
Viewed by 985
Abstract
Background: The rise in global throughput has created major challenges for container terminals and depots, especially in managing limited storage space and unsynchronized truck pickup schedules from different companies. These conditions complicate the organization, retrieval, and relocation of containers, especially when target [...] Read more.
Background: The rise in global throughput has created major challenges for container terminals and depots, especially in managing limited storage space and unsynchronized truck pickup schedules from different companies. These conditions complicate the organization, retrieval, and relocation of containers, especially when target containers are located in the middle of stacks. This study aims to develop an integrated optimization model that combines Truck Appointment Scheduling (TAS) and Restricted Block Relocation Problem (RBRP) to minimize container relocations, coordinate pickup schedules, and improve operational efficiency. Methods: An integer programming model is formulated to integrate relocation and scheduling decisions by considering practical operational constraints, including maximum stack capacity, queue length, crane movement capacity, relocation validity, prevention of redundant movements, and efficient slot utilization. Two solution schemes are evaluated, simultaneous RPRP-TAS approaches and sequential TAS-then-RBRP approaches, to minimize relocations. Results: The results show that the simultaneous approach produces fewer relocation and more stable than the sequential approach. Sensitivity analysis also confirms that the simultaneous scheme is more robust to variations in the number of containers and crane movement capacity, while maintaining comparable pickup time-shift performance. Conclusions: The simultaneous integration of RBRP and TAS provides coordinated, practical, and efficient decision support for depot and terminal operations. Full article
(This article belongs to the Topic Decision Science Applications and Models (DSAM))
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17 pages, 867 KB  
Article
Energy and Logistics Cost Transmission in the Dairy Market: Evidence from Kazakhstan Using a Log-Linear ARDL Model
by Dauren Turarov, Zhumakul Abisheva, Aiman Issayeva, Madina Beisenova and Stefan Dyrka
Logistics 2026, 10(6), 121; https://doi.org/10.3390/logistics10060121 - 2 Jun 2026
Viewed by 1142
Abstract
Background: This study aims to evaluate the impact of energy and logistics factors on the milk producer price index to support evidence-based policies that maintain price stability at an optimal level. Methods: Annual data for 2000–2023 are used, including the milk producer price [...] Read more.
Background: This study aims to evaluate the impact of energy and logistics factors on the milk producer price index to support evidence-based policies that maintain price stability at an optimal level. Methods: Annual data for 2000–2023 are used, including the milk producer price index, milk production volume, transport CPI, diesel price, CO2 emissions from agriculture, and renewable energy consumption (percentage of total energy consumption). A log-linear ARDL model is applied to examine both short- and long-run asymmetric effects of diesel prices, transport costs, and agricultural CO2 emissions on milk production dynamics. Results: The research results indicate that energy expenses, logistics considerations, and environmental metrics have statistically significant asymmetric influences on milk production. This underscores the varying short-term adjustments and enduring long-term economic effects throughout the supply chain. Conclusions: Energy and cost factors on the supply side significantly influence the stability of milk markets. Therefore, improving transportation efficiency, encouraging the use of renewable energy sources, and addressing environmental impacts can contribute to consistent and sustainable pricing. Specific policies—including investments in transport infrastructure, subsidies for green energy targeting dairy producers, carbon pricing with support tailored to the sector, and digitalization of supply chains—can enhance resilience and ensure price stability. Full article
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32 pages, 464 KB  
Article
Demystifying the Digital Transformation of Humanitarian Supply Chains Through AidTech
by Apostolos Panagiotopoulos, Vasileios Karyotis, Georgios N. Dimitrakopoulos, Vassiliki Choleva-Tsiringkaki and Panos Kourouthanassis
Logistics 2026, 10(5), 110; https://doi.org/10.3390/logistics10050110 - 9 May 2026
Cited by 1 | Viewed by 1482
Abstract
Background: Humanitarian campaigns are more popular with more initiatives organized than ever by public and private bodies. Simultaneously, more peculiar challenges, such as zero-waste and transparency, are required compared to traditional supply chains. This work investigates the current technological landscape for shaping [...] Read more.
Background: Humanitarian campaigns are more popular with more initiatives organized than ever by public and private bodies. Simultaneously, more peculiar challenges, such as zero-waste and transparency, are required compared to traditional supply chains. This work investigates the current technological landscape for shaping the next generation of humanitarian aid management systems, focusing on algorithmic and operational aspects, matching them to a new architecture for a target-platform, called AidTech. Methods: The methodology follows a systematic literature coverage, identifying cross-disciplinary trends from operations research, computer science and sustainable logistics. We examine the convergence of optimization, artificial intelligence, and blockchain-enabled traceability toward efficient and transparent humanitarian logistics. The employed methods include adaptive scheduling, resource allocation algorithms and privacy–preserving collaboration for meeting special constraints imposed by the humanitarian scope. Results: The findings focus on the architectural perspective of humanitarian supply chains and highlight that modern humanitarian infrastructures will increasingly rely on hybrid optimization methods integrating graph theory, dynamic routing under stochastic demand, multi-criteria decision analysis and distributed ledger technologies. Conclusions: We conclude that these paradigms, when combined under a unified cyber–physical architecture, e.g., AidTech, can substantially improve responsiveness, equity and sustainability in crisis management, further shaping future humanitarian logistics. Full article
(This article belongs to the Section Humanitarian and Healthcare Logistics)
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24 pages, 390 KB  
Article
Medical Aesthetics Clinic Location Selection Using SMART Single-Valued Neutrosophic TOPSIS
by Napat Harnpornchai and Worrawat Saijai
Logistics 2026, 10(5), 106; https://doi.org/10.3390/logistics10050106 - 2 May 2026
Viewed by 1732
Abstract
Background: Location decision plays a key role in strategic logistics and business success. The beauty business in Thailand has continuously grown, and medical aesthetics clinic location is one of the critical factors for business success. The problem is also related to sustainable urban [...] Read more.
Background: Location decision plays a key role in strategic logistics and business success. The beauty business in Thailand has continuously grown, and medical aesthetics clinic location is one of the critical factors for business success. The problem is also related to sustainable urban service accessibility. Methods: This paper presents, for the first time, a systematic selection of medical aesthetics clinic location as a multi-criteria decision-making (MCDM) problem. The Simple Multi-Attribute Rating Technique (SMART) and Single-Valued Neutrosophic TOPSIS (SVN-TOPSIS) are combined to solve the location selection problem. SMART determines criterion weights, whereas SVN-TOPSIS evaluates alternatives using linguistic terms understandable to non-technical decision makers. Results: The proposed SMART SVN-TOPSIS is applied to a real investment problem in which two investors select the best clinic location from five alternatives with nine criteria. Siam Square—the heart of shopping, fashion, and youth culture in Bangkok—is recommended as the top location. Conclusions: The results indicate that the proposed method is capable of generating a consistent ranking of alternatives and differentiating between locations that exhibit similar evaluation characteristics. The findings may also support sustainable urban service planning and healthcare-related facility location decisions. Full article
(This article belongs to the Section Humanitarian and Healthcare Logistics)
19 pages, 2244 KB  
Article
Analysis of User Attitudes and Behavior in the Context of Traditional Delivery and the Use of Parcel Lockers
by Sreten Simović, Tijana Ivanišević and Aleksandar Trifunović
Logistics 2026, 10(4), 90; https://doi.org/10.3390/logistics10040090 - 14 Apr 2026
Viewed by 1846
Abstract
Background: The rapid development of e-commerce has led to significant changes in last-mile logistics, where innovative delivery solutions such as parcel lockers are increasingly considered to improve efficiency and flexibility. Methods: This study analyzes user attitudes and behavior toward traditional delivery and parcel [...] Read more.
Background: The rapid development of e-commerce has led to significant changes in last-mile logistics, where innovative delivery solutions such as parcel lockers are increasingly considered to improve efficiency and flexibility. Methods: This study analyzes user attitudes and behavior toward traditional delivery and parcel locker usage through a quantitative survey conducted in November 2024 in Serbia, on a sample of 420 respondents with diverse demographic characteristics. Results: The findings indicate that, despite recognized advantages such as flexibility, accessibility, and reduced risk of missed deliveries, parcel lockers remain underutilized. This is mainly due to limited user awareness, insufficient infrastructure, and a strong preference for traditional home delivery. Statistically significant differences were identified across demographic groups, including gender, age, education level, occupation, and place of residence. Conclusions: The results suggest that improving infrastructure, increasing user awareness, and implementing targeted communication strategies could significantly enhance the adoption of parcel lockers. The study contributes to a better understanding of user behavior and supports the development of more efficient and user-oriented last-mile delivery solutions. Full article
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20 pages, 1226 KB  
Article
Enabling Reuse and Recycling in Circular Supply Chains: A Game-Theoretic Analysis of Glass Bottle Refilling
by Ehsan Dehghan, Behzad Maleki Vishkaei and Pietro De Giovanni
Logistics 2026, 10(4), 83; https://doi.org/10.3390/logistics10040083 - 7 Apr 2026
Viewed by 1590
Abstract
Background: Circular economy (CE) practices, such as glass bottle refilling, are critical to the beverage industry’s sustainability. However, coordinating manufacturer marketing efforts with collector reverse logistics investment remains a strategic challenge. Methods: This study develops a Stackelberg game-theoretic model featuring a [...] Read more.
Background: Circular economy (CE) practices, such as glass bottle refilling, are critical to the beverage industry’s sustainability. However, coordinating manufacturer marketing efforts with collector reverse logistics investment remains a strategic challenge. Methods: This study develops a Stackelberg game-theoretic model featuring a manufacturer and a collector. The model incorporates communication effort as a demand driver and analyzes the role of bottle quality (damage rates) and the reusable bottle unit cost on the optimal decisions of the players and the collection rate. Results: Equilibrium analysis shows that the quality of the reusable bottle and the rate of bottle damage are crucial in reducing the operational costs of the refilling program. Additionally, these factors significantly influence the decisions made by manufacturers and collectors regarding their investments in communication and collection systems. Conclusions: The study demonstrates that successful refilling requires strategic coordination between manufacturers and collectors, particularly in terms of communication and investment in reverse logistics. Managerial insights indicate that investing in the quality of bottles is the key factor for achieving joint profitability. Full article
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27 pages, 532 KB  
Article
How Does AI Acceptance in Logistics Services Influence Value Co-Creation Behavior and Brand Loyalty Among Thai Gen Z Consumers?
by Anuman Chanthawong, Narinthon Imjai, Kanyarat Nimtrakool, Berto Usman and Somnuk Aujirapongpan
Logistics 2026, 10(4), 75; https://doi.org/10.3390/logistics10040075 - 1 Apr 2026
Viewed by 1806
Abstract
Background: Artificial intelligence (AI) is increasingly integrated into logistics services, yet limited research explains how AI acceptance translates into relational outcomes among Generation Z consumers. This study investigates the influence of AI acceptance in logistics services on value co-creation behavior and brand [...] Read more.
Background: Artificial intelligence (AI) is increasingly integrated into logistics services, yet limited research explains how AI acceptance translates into relational outcomes among Generation Z consumers. This study investigates the influence of AI acceptance in logistics services on value co-creation behavior and brand loyalty in Thailand. Methods: A quantitative approach was employed using a structured questionnaire administered to 461 Thai Generation Z consumers with experience in AI-enabled parcel delivery services. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results: The findings reveal that AI acceptance significantly and positively affects both value co-creation behavior and brand loyalty. Value co-creation behavior also exerts a strong positive effect on brand loyalty and partially mediates the relationship between AI acceptance and brand loyalty. The measurement and structural models demonstrated satisfactory reliability and validity. Conclusions: The results indicate that AI acceptance enhances brand loyalty both directly and indirectly through customer participation in value co-creation. These findings highlight the importance of designing AI-enabled logistics interfaces that promote user engagement and relational value, particularly for digitally native Generation Z consumers. Full article
(This article belongs to the Section Artificial Intelligence, Logistics Analytics, and Automation)
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24 pages, 1672 KB  
Article
Quantum Computing for Supply Chain Optimization: Algorithms, Hybrid Frameworks, and Industry Applications
by Fayçal Fedouaki, Mouhsene Fri, Kaoutar Douaioui and Amellal Asmae
Logistics 2026, 10(3), 67; https://doi.org/10.3390/logistics10030067 - 16 Mar 2026
Cited by 1 | Viewed by 5141
Abstract
Background: This paper investigates hybrid quantum–classical optimization approaches for addressing core supply chain management (SCM) problems. A unified hybrid framework is implemented and evaluated across five representative domains: vehicle routing, scheduling, facility location, inventory optimization, and demand forecasting. Methods: The framework [...] Read more.
Background: This paper investigates hybrid quantum–classical optimization approaches for addressing core supply chain management (SCM) problems. A unified hybrid framework is implemented and evaluated across five representative domains: vehicle routing, scheduling, facility location, inventory optimization, and demand forecasting. Methods: The framework integrates quantum algorithms—namely the Quantum Approximate Optimization Algorithm (QAOA), Quantum Annealing (QA), and the Variational Quantum Eigensolver (VQE)—with classical constraint-handling and local refinement procedures in an iterative workflow. Quantum solvers are employed for global solution exploration, while classical optimization ensures feasibility and convergence stability. Results: Experiments conducted on standardized synthetic benchmarks demonstrate that the proposed hybrid framework consistently outperforms classical-only and quantum-only baselines, achieving 12–18% reductions in operational costs and 20–35% faster convergence. In routing and fulfilment tasks, quantum-generated candidate solutions provide effective warm starts for classical refinement. Robustness analysis based on stochastic SCM simulations further indicates lower performance variance under uncertainty. Conclusions: These results demonstrate that hybrid quantum–classical optimization constitutes a practical and scalable strategy for near-term SCM decision-making under current Noisy Intermediate-Scale Quantum (NISQ) hardware constraints. Full article
(This article belongs to the Topic Sustainable Supply Chain Practices in A Digital Age)
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26 pages, 4675 KB  
Article
Examining Container Terminal Efficiency with Diverse Data Sources: Vessel, Truck, and Container Turnaround Times in Japanese Terminals
by Daigo Shiraishi, Wenru Zhang, Ryuichi Shibasaki and Yesim Elhan-Kayalar
Logistics 2026, 10(2), 51; https://doi.org/10.3390/logistics10020051 - 18 Feb 2026
Viewed by 2754
Abstract
Background: Improving container terminal efficiency requires a comprehensive understanding of the interactions between vessel, truck, and container operations, yet existing studies often analyzed these components separately. In Japanese container terminals, where digitalization initiatives are progressing, empirical evidence based on integrated operational data [...] Read more.
Background: Improving container terminal efficiency requires a comprehensive understanding of the interactions between vessel, truck, and container operations, yet existing studies often analyzed these components separately. In Japanese container terminals, where digitalization initiatives are progressing, empirical evidence based on integrated operational data remains limited. Methods: This study empirically analyzes turnaround times for vessels, trucks, and containers at five major Japanese container terminals using a composite dataset that integrates terminal operating system data, automatic identification system data, and liner service information. Descriptive statistical analyses and regression models are applied to examine vessel berthing time, truck arrival patterns and turnaround time, container dwell time within terminals, and container round-trip time outside terminals. Results: The analysis reveals distinct temporal patterns in terminal operations, including systematic morning–afternoon asymmetries and differences across cargo flows. Truck turnaround times increase with vessel calls and vary by time of day, while container dwell times are strongly influenced by terminal policies such as free-time rules. Regression analyses indicate that turnaround times are primarily affected by terminal-controlled factors. Conclusions: These findings demonstrate the importance of synchronizing quayside and landside operations. The study contributes integrated empirical evidence to the port digitalization literature and provides actionable insights for enhancing container terminal efficiency. Full article
(This article belongs to the Section Maritime and Transport Logistics)
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21 pages, 586 KB  
Article
The Role of AI-Driven Supply Chains in Shaping Agility, Adaptability, and Technology Adoption Under Market Turbulence
by Ahmed Adnan Zaid and Luay Jum’a
Logistics 2026, 10(2), 49; https://doi.org/10.3390/logistics10020049 - 17 Feb 2026
Cited by 5 | Viewed by 4487
Abstract
Background: This study examines the influence of AI-driven supply chains on the adoption of automation and robotics within Jordanian manufacturing firms, emphasizing the role of supply chain adaptability and agility as mediators and market turbulence as a moderator. Methods: Drawing on dynamic capabilities [...] Read more.
Background: This study examines the influence of AI-driven supply chains on the adoption of automation and robotics within Jordanian manufacturing firms, emphasizing the role of supply chain adaptability and agility as mediators and market turbulence as a moderator. Methods: Drawing on dynamic capabilities theory and institutional theory, the study develops a conceptual model and tests it using data collected from 337 managers through an online survey. The analysis was carried out through partial least squares structural equation modeling (PLS-SEM). Results: The results show that AI-driven supply chains significantly enhance both adaptability and agility. However, only agility has a direct and significant effect on the adoption of automation and robotics, while market turbulence significantly moderates the connection between supply chain adaptability and the adoption of automation and robotics, but not the relationship between agility and adoption. Conclusions: Theoretically, the study provides insight into the interplay among internal dynamic capabilities in shaping technology adoption under external uncertainty. These results provide actionable implications for managers operating in developing economies like Jordan, highlighting the significance of building agile capabilities and adopting AI technologies to support innovation. The study is limited by its focus on a single country and sector; future research should explore other industries and incorporate additional moderating or mediating variables. Full article
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22 pages, 559 KB  
Article
Tackling Supply Chain Disruptions Through Digital Agility: Evidence from the Hotel Industry
by Ahmed Mohamed Hasanein, Hazem Ahmed Khairy, Abdulaziz Aljoghaiman and Bassam Samir Al-Romeedy
Logistics 2026, 10(2), 34; https://doi.org/10.3390/logistics10020034 - 2 Feb 2026
Cited by 2 | Viewed by 2709
Abstract
Background: Digital transformation has become a vital driver of competitiveness in the hospitality industry. This study investigates the role of digital agility in enhancing competitive advantage in Egypt’s luxury hotel sector, focusing on the parallel mediating effects of supply chain agility and [...] Read more.
Background: Digital transformation has become a vital driver of competitiveness in the hospitality industry. This study investigates the role of digital agility in enhancing competitive advantage in Egypt’s luxury hotel sector, focusing on the parallel mediating effects of supply chain agility and supply chain resilience. Grounded in the Dynamic Capabilities Theory (DCT), the research explores how digital capabilities promote flexibility, responsiveness, and strategic performance. Methods: Data were collected from 325 senior managers in supply chain, procurement, operations, logistics, and digital transformation across luxury hotels in Egypt. The conceptual framework was analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via WarpPLS software. Results: Findings reveal that digital agility significantly enhances competitive advantage, as well as supply chain agility and resilience. Both supply chain agility and resilience positively influence competitive advantage and partially mediate the relationship between digital agility and competitiveness. Conclusions: The study highlights the strategic importance of digital agility in fostering agile and resilient supply chains, which serve as key mechanisms for achieving sustained competitive advantage in the luxury hotel industry. Investing in digital technologies and adaptive capabilities is essential for long-term success in a dynamic market environment. 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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19 pages, 1214 KB  
Article
The Impact of Digital Transformation on the Business Performance of Logistics Enterprises: A Multi-Criteria Approach
by Khanh Han Nguyen and Long Quang Pham
Logistics 2026, 10(2), 32; https://doi.org/10.3390/logistics10020032 - 26 Jan 2026
Cited by 2 | Viewed by 3320
Abstract
Background: In the era of rapid technological advancement, digital transformation has emerged as a pivotal strategy for enhancing operational efficiency and competitiveness in logistics enterprises, particularly amid globalization and post pandemic recovery; this study aims to evaluate its multifaceted impact on business [...] Read more.
Background: In the era of rapid technological advancement, digital transformation has emerged as a pivotal strategy for enhancing operational efficiency and competitiveness in logistics enterprises, particularly amid globalization and post pandemic recovery; this study aims to evaluate its multifaceted impact on business performance using a multi-criteria framework focused on Vietnamese firms. Methods: Employing structural equation modeling on primary survey data from 346 middle and senior level managers, alongside the Malmquist productivity index derived from data envelopment analysis on secondary financial indicators spanning 2020 to 2024, the research integrates latent variables such as organizational capability, technological innovation capability, institutional pressure, digital transformation, and business performance. Results: Key findings reveal a strong positive correlation between technological innovation capability and organizational capability (path coefficient 0.522), with organizational capability directly influencing business performance (0.359), while institutional pressure positively affects digital transformation (0.321) but negatively impacts business performance (−0.152); overall, digital transformation exhibits limited optimization, contributing to modest productivity gains and a potential 23% cost reduction through technologies like Internet of Things and artificial intelligence. Conclusions: These results underscore the necessity for logistics enterprises to strengthen organizational integration and training to maximize digital transformation benefits, thereby fostering sustainable competitiveness in global supply chains. Full article
(This article belongs to the Special Issue Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics—2nd Edition)
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23 pages, 639 KB  
Article
AI-Powered Tools for Supply Chain Resilience: A Dynamic Capabilities Perspective from Jordanian Manufacturing Firms
by Hazim Haddad, Luay Jum’a, Ziad Alkalha and Hilda Madanat
Logistics 2026, 10(1), 24; https://doi.org/10.3390/logistics10010024 - 19 Jan 2026
Cited by 4 | Viewed by 3751
Abstract
Background: In an increasingly volatile global business environment, supply chain resilience has become a strategic imperative, particularly for firms operating in developing economies. Guided by Dynamic Capabilities Theory (DCT), this study examines how AI-powered tools foster an innovation culture comprising communication, creativity, and [...] Read more.
Background: In an increasingly volatile global business environment, supply chain resilience has become a strategic imperative, particularly for firms operating in developing economies. Guided by Dynamic Capabilities Theory (DCT), this study examines how AI-powered tools foster an innovation culture comprising communication, creativity, and learning, and how these dimensions enhance supply chain resilience measured through flexibility, efficiency, and velocity. Methods: A quantitative research design was employed using survey data collected from 270 supply chain and operations managers in Jordanian manufacturing firms. Twelve direct hypotheses were tested using Partial Least Squares Structural Equation Modeling. Results: The findings indicate that AI-powered tools significantly influence communication, creativity, and learning. Communication and creativity positively affect all three dimensions of supply chain resilience. Learning significantly improves efficiency but shows no significant effect on flexibility or velocity, indicating that learning is mainly utilized for process improvement rather than rapid adaptation. Conclusions: The study demonstrates that AI adoption alone is insufficient to build resilient supply chains unless supported by innovation-oriented cultural capabilities. The findings extend DCT by clarifying the differentiated role of learning in resilience building and provide actionable guidance for managers seeking to align AI investments with cultural development in resource-constrained manufacturing contexts and long-term competitive advantage. Full article
(This article belongs to the Special Issue Artificial Intelligence and Business Analytics Applications in Supply Chain Operations)
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30 pages, 2552 KB  
Systematic Review
A Conceptual Framework Toward the Sustainable Management of the Aquaculture Supply Chain: Insights and Future Research Directions
by Wahyu Andy Prastyabudi and Wei Deng Solvang
Logistics 2026, 10(1), 21; https://doi.org/10.3390/logistics10010021 - 14 Jan 2026
Cited by 1 | Viewed by 2697
Abstract
Background: Sustainable operations and management are imperative in many sectors, including aquaculture, to adapt to the increasing complexity and unprecedented challenges across the supply chain. Although research in sustainable supply chain management (SSCM) has grown significantly, it remains inadequate for fully addressing [...] Read more.
Background: Sustainable operations and management are imperative in many sectors, including aquaculture, to adapt to the increasing complexity and unprecedented challenges across the supply chain. Although research in sustainable supply chain management (SSCM) has grown significantly, it remains inadequate for fully addressing the distinct challenges of the aquaculture supply chain (ASC). Therefore, this paper aims to introduce the concept of the sustainable management of the aquaculture supply chain (SMASC) and identify research gaps for future research directions. Methods: This study conducts a systematic literature review using the Web of Science and Scopus databases to retrieve peer-reviewed articles published between 2000 and 2025. A total of 116 articles were subjected to an in-depth content analysis, leading to the conceptualization of SMASC. Results: The findings indicate that ASC exhibits considerable heterogeneity in structure and performance measures, reflecting the inherent diversity of species and culture systems. The proposed conceptual framework provides a coherent understanding of SMASC by extending generic SSCM to incorporate distinctive characteristics of aquaculture, while systematically identifying the core pillars and their interrelationships. Conclusions: The SMASC framework establishes a unified theoretical foundation for the comprehensive management of ASCs, offering conceptual and practical insights for both researchers and practitioners. Full article
(This article belongs to the Section Sustainable Supply Chains and Logistics)
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47 pages, 4215 KB  
Review
The Adoption of Digital Technologies in Circular Supply Chains: From Theoretical Developments to Practical Applications
by Mojdeh Morshedi, Vincent Hargaden, Nikolaos Papakostas and Pezhman Ghadimi
Logistics 2026, 10(1), 18; https://doi.org/10.3390/logistics10010018 - 12 Jan 2026
Cited by 7 | Viewed by 3637
Abstract
Background: Digital technologies are increasingly integrated into circular supply chains (CSCs) to enhance resource efficiency and extend product lifecycles. However, the practical adoption of intelligent circular supply chains (iCSCs) remains underexplored. Methods: This study provides a comprehensive review of how digital technologies enable [...] Read more.
Background: Digital technologies are increasingly integrated into circular supply chains (CSCs) to enhance resource efficiency and extend product lifecycles. However, the practical adoption of intelligent circular supply chains (iCSCs) remains underexplored. Methods: This study provides a comprehensive review of how digital technologies enable circular practices across industries. It systematically reviews 95 peer-reviewed articles from WoS and Scopus, identifying 107 real-world iCSC cases. The cases are categorized by (1) digital enablers including AI, Big Data, Blockchain, IoT, Digital Twin, Additive Manufacturing, Cloud Platforms, and Cyber-Physical Systems; (2) alignment with Circular Economy (CE); (3) sector-specific circular practices; and (4) mapping implementations to the EU Circular Economy Action Plan (CEAP). This study develops a conceptual model illustrating how digital technologies support data-driven decision-making, automation, and circular transitions. Results: The analysis shows IoT, Blockchain, and AI as the most frequently applied technologies, facilitating collaboration, traceability, sustainability, and cost efficiency. “Reduce” and “Recycle” dominate among CE strategies, while circular transition pathways such as sustainable design, waste prevention, and digital platforms link policy to practice. Conclusions: By integrating systematic evidence with a holistic framework, this work provides actionable insights, identifies key implementation gaps, and lays a foundation for advancing iCSCs in research and practice. Full article
(This article belongs to the Section Sustainable Supply Chains and Logistics)
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19 pages, 2104 KB  
Article
A Machine Learning and Multi-Criteria Decision-Making Approach to Cycle Counting
by Laura Vaccari, Elia Balugani, Francesco Lolli and Rita Gamberini
Logistics 2026, 10(1), 10; https://doi.org/10.3390/logistics10010010 - 29 Dec 2025
Cited by 3 | Viewed by 2601
Abstract
Background: Inventory record inaccuracy (IRI) causes discrepancies between physical and digital inventories, leading to production delays and customer dissatisfaction. Cycle counting, in this context, is a common corrective action. Pareto-based ABC analysis is widely used to decide which items to inspect, but it [...] Read more.
Background: Inventory record inaccuracy (IRI) causes discrepancies between physical and digital inventories, leading to production delays and customer dissatisfaction. Cycle counting, in this context, is a common corrective action. Pareto-based ABC analysis is widely used to decide which items to inspect, but it often oversimplifies inventory decisions, and recent studies suggest that multi-criteria decision-making (MCDM) and machine learning (ML) may offer more effective solutions. Methods: This study applies the analytic hierarchy process (AHP) method, combined with K-means (AHP-K), to classify stock-keeping units (SKUs) into three groups with distinct counting policies. A selection procedure is then applied to identify an optimal ML algorithm and compare its classification with the original AHP-K results; each model in this phase is trained on a subsets of 100 SKUs. A Veto method is also introduced to improve output consistency for both AHP-K and the best ML method, and a comparative cost evaluation is presented. Results: The ML-AHP-K-Veto classification achieves over 90% accuracy. Analysis of a dataset of 12,863 SKUs from a mechanical manufacturing company shows minimal cost differences between ML-based and MCDM classifications, but significant differences compared to Pareto-based costs. Conclusions: ML can effectively address IRI, supporting the development of pure ML applications, including decision-maker (DM) preferences, to manage cycle counting strategies. Full article
(This article belongs to the Section Artificial Intelligence, Logistics Analytics, and Automation)
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20 pages, 2602 KB  
Article
Agent-Based Simulation Modeling of Multimodal Transport Flows in Transportation System of Kazakhstan
by Alisher Khussanov, Botagoz Kaldybayeva, Oleksandr Prokhorov, Zhakhongir Khussanov, Doskhan Kenzhebekov, Mukhamediyar Yevadilla and Dauren Janabayev
Logistics 2025, 9(4), 172; https://doi.org/10.3390/logistics9040172 - 28 Nov 2025
Cited by 9 | Viewed by 3010
Abstract
Background: Kazakhstan’s transport system plays a key role in Eurasian logistics due to its position along the Middle Corridor. However, multimodal freight transport remains under-optimized due to infrastructure bottlenecks, uneven cargo flows, and limited digital tools for forecasting and planning. Methods: This study [...] Read more.
Background: Kazakhstan’s transport system plays a key role in Eurasian logistics due to its position along the Middle Corridor. However, multimodal freight transport remains under-optimized due to infrastructure bottlenecks, uneven cargo flows, and limited digital tools for forecasting and planning. Methods: This study presents the development of an agent-based simulation model for analyzing multimodal transportation in Kazakhstan. The model integrates railway, road, and maritime components, simulating cargo flows across export, import, and transit scenarios. Key agents include orders, transport vehicles, logistics hubs, and border checkpoints. The model is implemented in AnyLogic 8.9 and calibrated using a mix of official statistics, industry data, and field estimates. Results: The simulation replicates key logistics processes, identifies congestion points, and evaluates delivery performance under different scenarios. Experiments demonstrate how bottlenecks at terminals and border crossings affect delivery times, vehicle utilization, and hub load. The model allows testing infrastructure development options and scheduling policies. Conclusions: The approach enables a dynamic assessment of logistics efficiency under uncertainty and can support decision-making in transport planning. The novelty lies in the integrated simulation of multimodal freight flows with infrastructure constraints. The model serves as a foundation for digital twin applications and scenario-based planning. Full article
(This article belongs to the Section Artificial Intelligence, Logistics Analytics, and Automation)
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19 pages, 2081 KB  
Article
Digital Twins and Augmented Reality for Humanitarian Logistics in Urban Disasters: Framework Development
by Sepehr Abrishami and Reshma Jayaram
Logistics 2025, 9(4), 143; https://doi.org/10.3390/logistics9040143 - 10 Oct 2025
Cited by 4 | Viewed by 3567
Abstract
Background: Urban disasters expose persistent gaps in the operational picture and timely decision-making for response teams, which require user-centred systems that connect analysis to action. This study proposes and formatively validates an integrated framework that couples digital twins and augmented reality for [...] Read more.
Background: Urban disasters expose persistent gaps in the operational picture and timely decision-making for response teams, which require user-centred systems that connect analysis to action. This study proposes and formatively validates an integrated framework that couples digital twins and augmented reality for humanitarian logistics. Methods: A mixed methods design combined a structured literature synthesis with a practitioner survey across architecture, engineering, planning, BIM, and construction to assess perceived value and adoption conditions. Results: Findings indicate that practitioners prioritised digital twins for enhancing situational awareness (71.4%) and augmented reality for providing real-time information overlays (64.3%). A majority judged that integrating these technologies would yield substantial improvements in disaster response (67.9%), despite implementation challenges. Conclusions: The framework links live state estimation and short-horizon simulation to role-specific, in-scene AR cues, with the aim of reducing decision latency and improving coordination. Adoption depends primarily on human and organisational factors, including user accessibility, preparation needs, and clear governance. These results suggest a viable pathway to operationalise the bridge between analysis and field action and outline priorities for pilot evaluation. Full article
(This article belongs to the Section Humanitarian and Healthcare Logistics)
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22 pages, 2039 KB  
Article
ML and Statistics-Driven Route Planning: Effective Solutions Without Maps
by Péter Veres
Logistics 2025, 9(3), 124; https://doi.org/10.3390/logistics9030124 - 1 Sep 2025
Cited by 3 | Viewed by 4767
Abstract
Background: Accurate route planning is a core challenge in logistics, particularly for small- and medium-sized enterprises that lack access to costly geospatial tools. This study explores whether usable distance matrices and routing outputs can be generated solely from geographic coordinates without relying [...] Read more.
Background: Accurate route planning is a core challenge in logistics, particularly for small- and medium-sized enterprises that lack access to costly geospatial tools. This study explores whether usable distance matrices and routing outputs can be generated solely from geographic coordinates without relying on full map-based infrastructure. Methods: A dataset of over 5000 Hungarian postal locations was used to evaluate five models: Haversine-based scaling with circuity, linear regression, second- and third-degree polynomial regressions, and a trained artificial neural network. Models were tested on the full dataset, and three example routes representing short, medium, and long distances. Both statistical accuracy and route-level performance were assessed, including a practical optimization task. Results: Statistical models maintained internal consistency, but systematically overestimated longer distances. The ANN model provided significantly better accuracy across all scales and produced routes more consistent with map-based paths. A new evaluation method was introduced to directly compare routing outputs. Conclusions: Practical route planning can be achieved without GIS services. ML-based estimators offer a cost-effective alternative, with potential for further improvement using larger datasets, additional input features, and the integration of travel time prediction. This approach bridges the gap between simplified approximations and commercial routing systems. Full article
(This article belongs to the Section Artificial Intelligence, Logistics Analytics, and Automation)
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16 pages, 1251 KB  
Article
Carbon Pricing and the Truckload Spot Market
by Andrew Balthrop, Justin T. Kistler, Yemisi Bolumole, Alex Scott and Chad W. Autry
Logistics 2025, 9(3), 121; https://doi.org/10.3390/logistics9030121 - 28 Aug 2025
Cited by 2 | Viewed by 2354
Abstract
Background: Carbon pricing in the form of fuel taxes is an important tool for abating climate change. This study examines the impact and pass-through of fuel taxes in the truckload freight market. Methods: State-level truckload market data, integrated with retail diesel prices, are [...] Read more.
Background: Carbon pricing in the form of fuel taxes is an important tool for abating climate change. This study examines the impact and pass-through of fuel taxes in the truckload freight market. Methods: State-level truckload market data, integrated with retail diesel prices, are analyzed using fixed-effects regression modeling. Results: Taxes and fuel costs are not only passed on by diesel retailers to motor carriers; the results reveal the overshifting of diesel taxes from motor carriers to shippers. Conclusions: The findings are consistent with inelastic short-term demand for long-haul carriage, indicating that relatively large price increases will be necessary to reduce diesel consumption in the trucking industry. Full article
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14 pages, 849 KB  
Article
Autonomous Last-Mile Logistics in Emerging Markets: A Study on Consumer Acceptance
by Emerson Philipe Sinesio, Marcele Elisa Fontana, Júlio César Ferro de Guimarães and Pedro Carmona Marques
Logistics 2025, 9(3), 106; https://doi.org/10.3390/logistics9030106 - 6 Aug 2025
Cited by 4 | Viewed by 3597
Abstract
Background: Rapid urbanization has intensified the challenges of freight transport, particularly in last-mile (LM) delivery, leading to rising costs and environmental externalities. Autonomous vehicles (AVs) have emerged as a promising innovation to address these issues. While much of the existing literature emphasizes business [...] Read more.
Background: Rapid urbanization has intensified the challenges of freight transport, particularly in last-mile (LM) delivery, leading to rising costs and environmental externalities. Autonomous vehicles (AVs) have emerged as a promising innovation to address these issues. While much of the existing literature emphasizes business and operational perspectives, this study focuses on the acceptance of AVs from the standpoint of e-consumers—individuals who make purchases via digital platforms—in an emerging market context. Methods: Grounded in an extended Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), which is specifically suited to consumer-focused technology adoption research, this study incorporates five constructs tailored to AV adoption. Structural Equation Modeling (SEM) was applied to survey data collected from 304 e-consumers in Northeast Brazil. Results: The findings reveal that performance expectancy, hedonic motivation, and environmental awareness exert significant positive effects on acceptance and intention to use AVs for LM delivery. Social influence shows a weaker, yet still positive, impact. Importantly, price sensitivity exhibits a minimal effect, suggesting that while consumers are generally cost-conscious, perceived value may outweigh price concerns in early adoption stages. Conclusions: These results offer valuable insights for policymakers and logistics providers aiming to implement consumer-oriented, cost-effective AV solutions in LM delivery, particularly in emerging economies. The findings emphasize the need for strategies that highlight the practical, emotional, and environmental benefits of AVs to foster market acceptance. Full article
(This article belongs to the Section Last Mile, E-Commerce and Sales Logistics)
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16 pages, 470 KB  
Article
Digital Planning Tools in Intermodal Transport: Evidence from Poland
by Mateusz Zajac, Tomislav Rožić, Justyna Swieboda-Kutera and Martin Starčević
Logistics 2025, 9(3), 94; https://doi.org/10.3390/logistics9030094 - 11 Jul 2025
Cited by 2 | Viewed by 4303
Abstract
Background: The increasing complexity of global supply chains and environmental expectations has highlighted the strategic importance of digital transformation in the transport, forwarding, and logistics (TFL) sector. Despite a growing portfolio of available tools, adoption rates—particularly among small and medium-sized enterprises (SMEs) [...] Read more.
Background: The increasing complexity of global supply chains and environmental expectations has highlighted the strategic importance of digital transformation in the transport, forwarding, and logistics (TFL) sector. Despite a growing portfolio of available tools, adoption rates—particularly among small and medium-sized enterprises (SMEs) in Central and Eastern Europe—remain low. This study investigates the barriers and motivations related to the implementation of digital planning tools supporting intermodal transport planning. Methods: A structured online survey was conducted among 80 Polish TFL enterprises, targeting decision-makers responsible for operational and digital strategies. The questionnaire included 17 closed and semi-open questions grouped into three thematic sections: tool usage, implementation barriers, and digital readiness. Results: The findings indicate that only 20% of respondents use dedicated route planning tools, and merely 10% report satisfaction with their performance. Key barriers include lack of awareness, organizational inertia, and the prioritization of other initiatives, with financial cost cited less frequently. While environmental sustainability is declared as a priority by most enterprises, digital support for emission tracking is limited. The results highlight the need for targeted education, integration support, and differentiated platform functionalities for SMEs and larger firms. Conclusions: This study offers evidence-based recommendations for developers, policymakers, and logistics managers aiming to accelerate digital adoption in the intermodal logistics landscape. Full article
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40 pages, 3494 KB  
Article
Risk-Based Optimization of Multimodal Oil Product Operations Through Simulation and Workflow Modeling
by Catalin Popa, Ovidiu Stefanov, Ionela Goia and Dinu Atodiresei
Logistics 2025, 9(3), 79; https://doi.org/10.3390/logistics9030079 - 20 Jun 2025
Cited by 2 | Viewed by 3209
Abstract
Background: The transportation of petroleum products via multimodal logistics systems is a complex process subject to operational inefficiencies and elevated risk exposure. The efficient and resilient transportation of petroleum products increasingly depends on multimodal logistics systems, where operational risks and process inefficiencies [...] Read more.
Background: The transportation of petroleum products via multimodal logistics systems is a complex process subject to operational inefficiencies and elevated risk exposure. The efficient and resilient transportation of petroleum products increasingly depends on multimodal logistics systems, where operational risks and process inefficiencies can significantly impact safety and performance. This study addresses the research question of how an integrated risk-based and workflow-driven approach can enhance the management of oil products logistics in complex port environments. Methods: A dual methodological framework was applied at the Port of Midia, Romania, combining a probabilistic risk assessment model, quantifying incident probability, infrastructure vulnerability, and exposure, with dynamic business process modeling (BPM) using specialized software. The workflow simulation replicated real-world multimodal oil operations across maritime, rail, road, and inland waterway segments. Results: The analysis identified human error, technical malfunctions, and environmental hazards as key risk factors, with an aggregated major incident probability of 2.39%. BPM simulation highlighted critical bottlenecks in customs processing, inland waterway lock transit, and road tanker dispatch. Process optimizations based on simulation insights achieved a 25% reduction in operational delays. Conclusions: Integrating risk assessment with dynamic workflow modeling provides an effective methodology for improving the resilience, efficiency, and regulatory compliance of multimodal oil logistics operations. This approach offers practical guidance for port operators and contributes to advancing risk-informed logistics management in the petroleum supply chain. Full article
(This article belongs to the Special Issue Investment, Risk, and Sustainability in Maritime Logistics and Supply Chain)
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18 pages, 3805 KB  
Article
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
Cited by 9 | Viewed by 5323
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. [...] 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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25 pages, 2776 KB  
Review
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
Cited by 28 | Viewed by 14702
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 [...] 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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27 pages, 739 KB  
Systematic 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
Cited by 19 | Viewed by 7232
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 [...] 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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33 pages, 14554 KB  
Article
State of the Art of Digital Twins in Improving Supply Chain Resilience
by Eugenia-Alina Roman, Armand-Serban Stere, Eugen Roșca, Adriana-Valentina Radu, Denis Codroiu and Ilie Anamaria
Logistics 2025, 9(1), 22; https://doi.org/10.3390/logistics9010022 - 6 Feb 2025
Cited by 53 | Viewed by 29809
Abstract
Background: In today’s complex and rapidly changing global markets, supply chain resilience (SCR) has become critical for businesses aiming to maintain continuity and competitive advantage. Disruptions and challenges in the supply chain will always exist; therefore, preparing in advance and improving resilience [...] Read more.
Background: In today’s complex and rapidly changing global markets, supply chain resilience (SCR) has become critical for businesses aiming to maintain continuity and competitive advantage. Disruptions and challenges in the supply chain will always exist; therefore, preparing in advance and improving resilience for the upcoming consequences should be the utmost important goal. Methods: Digital twins (DTs) provide a comprehensive view of product performance, enabling companies to adopt an end-to-end approach to product management. To maximize product and service value, supply chains must also be managed holistically. Results: Therefore, companies will need smarter strategies to balance inventory costs, availability and lead times. The optimal setup of suppliers, manufacturing, logistics and stock locations will ensure high service levels and meet customer expectations. Additionally, supply chains must be resilient, and capable of maintaining performance during disruptions and adapting to demand changes. Conclusions: This paper aims to provide a comprehensive review of the state of the art in digital twin applications within supply chains, focusing on their role in improving visibility, agility and decision-making. This paper explores how digital twins might integrate with emerging technologies such as IoT, AI and blockchain, fostering a more adaptive and robust supply chain ecosystem. Full article
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24 pages, 2349 KB  
Review
Reverse Logistics as a Catalyst for Decarbonizing Forest Products Supply Chains
by Leonel J. R. Nunes
Logistics 2025, 9(1), 17; https://doi.org/10.3390/logistics9010017 - 21 Jan 2025
Cited by 15 | Viewed by 5265
Abstract
Background: The forest products industry plays a significant role in global carbon emissions, highlighting the need for sustainable practices to address the climate crisis. Reverse logistics (RL), focusing on the return, reuse, and recycling of materials, offers a promising approach to decarbonizing [...] Read more.
Background: The forest products industry plays a significant role in global carbon emissions, highlighting the need for sustainable practices to address the climate crisis. Reverse logistics (RL), focusing on the return, reuse, and recycling of materials, offers a promising approach to decarbonizing supply chains. However, its application within forest products supply chains remains underexplored. Methods: This study conducts a review of the literature on RL, its environmental implications, and its potential to reduce carbon emissions in forest products supply chains. Key areas examined include greenhouse gas reduction, waste management, and the promotion of circular economy principles. Additionally, the study evaluates case studies and models that integrate RL practices into forest-based industries. Results: The findings reveal that RL can significantly reduce greenhouse gas emissions by optimizing transportation routes, minimizing waste, and extending product life cycles. Incorporating these practices into forestry operations reduces the environmental impact and aligns with sustainable forestry goals. The study identifies gaps in current research, particularly regarding empirical data and the scalability of RL solutions. Conclusions: RL represents a critical strategy for decarbonizing forest products supply chains and advancing sustainable development. Future research should focus on developing standardized methodologies, enhancing technological integration, and fostering policy support to maximize its impact. These steps are essential to fully leverage RL as a tool for mitigating climate change and promoting a circular economy. Full article
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24 pages, 811 KB  
Article
The Impact of Digital Technology, Automation, and Data Integration on Supply Chain Performance: Exploring the Moderating Role of Digital Transformation
by Ahmad Ali Atieh, Alhareth Abu Hussein, Saheer Al-Jaghoub, Ahmad Fathi Alheet and Murad Attiany
Logistics 2025, 9(1), 11; https://doi.org/10.3390/logistics9010011 - 15 Jan 2025
Cited by 54 | Viewed by 26977
Abstract
Background: This study investigates digital transformation as a moderating variable in determining the effect of digital technologies, automation, and data integration of upstream and downstream providers on supply chain performance. By filling the existing research gap, the study reveals that more research regarding [...] Read more.
Background: This study investigates digital transformation as a moderating variable in determining the effect of digital technologies, automation, and data integration of upstream and downstream providers on supply chain performance. By filling the existing research gap, the study reveals that more research regarding how digital transformation interventions impact the effectiveness of these technologies for industrial supply chains must be understood. Methods: A structured survey was applied to 181 supply chain managers in manufacturing firms scattered across Jordan. Results: The findings using SmartPLS for statistical analysis indicated that automation has the strongest positive effect on supply chain performance, followed by data integration. But digital technology did not have a significant direct effect, unless it was accompanied by broader digital transformation initiatives. Conclusions: Theoretically, this study reinforces digital transformation theory as a vital framework, whereas in practice, it invokes the strategic deployment of automation and integrated data application designs to underpin supply chain efficiency and competitiveness. Finally, this study offers practical guidance for practitioners who seek to employ the use of digital transformation in the current dynamic business environment. Full article
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39 pages, 1459 KB  
Article
Impact of Supply Chain Management on Business Sustainability: Case of Water Bottling Companies in and Around Finfinnee, Ethiopia
by Tadesse Kenea Amentae, Girma Gebresenbet and Nuredin Jemal Abdela
Logistics 2025, 9(1), 5; https://doi.org/10.3390/logistics9010005 - 30 Dec 2024
Cited by 4 | Viewed by 6814
Abstract
Background: Effective supply chain management (SCM) is widely considered vital for enhancing business sustainability, yet empirical evidence across industries and contexts remains limited. This paper aims to address this gap by presenting empirical findings specific to a particular industry, business size, and [...] Read more.
Background: Effective supply chain management (SCM) is widely considered vital for enhancing business sustainability, yet empirical evidence across industries and contexts remains limited. This paper aims to address this gap by presenting empirical findings specific to a particular industry, business size, and economic setting. Methods: The data are collected from small- and medium-sized water bottling companies in Ethiopia utilizing a Likert scale questionnaire and analyzed using SPPS version 29 using multi-variable regression analysis. Results: The findings reveal a statistically significant positive influence of supply chain management practices on economic, environmental, and social sustainability business performances. Accordingly, supply chain internal practices and customer and supplier integration impact business economic sustainability, while customer and supplier integration affect business environmental sustainability performance. Customer integration, supplier integration, and supply chain internal practices significantly influence business social sustainability performance. Conclusions: These results highlight the potential for businesses to achieve holistic sustainability goals through targeted improvements in SCM practices. The research results are consistent with most previous studies on this topic, except for a few variations that may need further investigation. The discussion highlighted the intricate links between supply chain management practices and business sustainability, underscoring the need for comprehensive further empirical studies in various contexts. Full article
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18 pages, 414 KB  
Article
Adaptive Performance Evaluation of Container Terminals Through Normalization and Parameter Analysis
by Mateusz Zajac
Logistics 2025, 9(1), 2; https://doi.org/10.3390/logistics9010002 - 25 Dec 2024
Cited by 6 | Viewed by 3938
Abstract
Background: Container terminals are a pivotal part of global logistics networks, influencing supply chain reliability and port competitiveness. Traditional performance evaluation methods, such as KPI-based assessments or multi-criteria analyses, often fail in dynamic operational conditions with inherent uncertainty and variability. Methods: This study [...] Read more.
Background: Container terminals are a pivotal part of global logistics networks, influencing supply chain reliability and port competitiveness. Traditional performance evaluation methods, such as KPI-based assessments or multi-criteria analyses, often fail in dynamic operational conditions with inherent uncertainty and variability. Methods: This study proposes a normalization-based framework to evaluate container terminal performance by standardizing operational parameters, including availability, non-productive operations, operation time, energy consumption, and throughput. The methodology involves parameter definition, normalization, weight assignment, index calculation, and performance classification. Results: The findings demonstrate that normalization ensures a transparent and adaptable evaluation framework. Sample calculations show how parameter weights influence terminal assessments across varied scenarios, confirming the robustness of the proposed method in capturing dynamic operational changes. Conclusions: Normalization offers a practical tool for enhancing container terminal efficiency and competitiveness. It enables decision-makers to adapt strategies to changing priorities, such as throughput maximization or energy efficiency, ensuring comprehensive and reliable performance assessments. Full article
(This article belongs to the Special Issue Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics)
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18 pages, 910 KB  
Article
Competencies of a Healthcare Manager in the Context of Hospital and Ambulateral Diagnostic Imaging Centers
by Agnieszka Mierzwa, Magdalena Syrkiewicz-Świtała, Bernadeta Kuraszewska, Rafał Świtała, Jolanta Grzebieluch, Beata Detyna and Jerzy Dariusz Detyna
Logistics 2024, 8(4), 133; https://doi.org/10.3390/logistics8040133 - 19 Dec 2024
Cited by 1 | Viewed by 3828
Abstract
Background: Today’s healthcare requires a modern style of management that adapts to the needs of both patients and employees. Imaging diagnostics has its specificity in the entire area of hospital logistics and influences the organization of work and patient care. Modern managers [...] Read more.
Background: Today’s healthcare requires a modern style of management that adapts to the needs of both patients and employees. Imaging diagnostics has its specificity in the entire area of hospital logistics and influences the organization of work and patient care. Modern managers should have special competencies to meet the expectations of patients, employees, and organizations. Aim: The main purpose of article was to define the role, competencies, and skills that managers should have in the field of diagnostic imaging. Methods: In the research part, a questionnaire survey and in-depth interviewing were used. The research group consisted of 10 managers and 300 medical staff, i.e., radiologists, nurses, and electroradiology technicians. Results: The decision-making role of the manager and their interpersonal skills were recognized to be most crucial. According to the respondents, managers should ensure good work organization and provide safe working conditions. Employees appreciated the manager’s ability to react in crisis situations as well as their high professionalism. The ability to communicate and resolve conflicts in a team was considered the most important psychological and social competence. Conclusions: A good manager, in the opinion of the respondents, is a decision-making, empathetic, and flexible person with strong leadership characteristics. Full article
(This article belongs to the Section Humanitarian and Healthcare Logistics)
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35 pages, 6919 KB  
Article
Situational Awareness Errors in Forklift Logistics Operations: A Multiphase Eye-Tracking and Think-Aloud Approach
by Claudia Yohana Arias-Portela, Jaime Mora-Vargas, Martha Caro and David Ernesto Salinas-Navarro
Logistics 2024, 8(4), 124; https://doi.org/10.3390/logistics8040124 - 2 Dec 2024
Cited by 2 | Viewed by 5319
Abstract
Background: This study explores forklift operators’ situational awareness (SA) and human errors in logistic operations using a multiphase approach as an innovative methodology. Methods: Ethnography, eye tracking, error taxonomy, and retrospective think-aloud (RTA) were used to study the diverse cognitive, behavioral, [...] Read more.
Background: This study explores forklift operators’ situational awareness (SA) and human errors in logistic operations using a multiphase approach as an innovative methodology. Methods: Ethnography, eye tracking, error taxonomy, and retrospective think-aloud (RTA) were used to study the diverse cognitive, behavioral, and operational aspects affecting SA. After analyzing 566 events across 18 tasks, this research highlighted eye tracking’s potential by offering real-time insights into operator behavior and RTA’s potential as a method for cross-checking the causal factors underlying errors. Results: Critical tasks, like positioning forklifts and lowering pallets, significantly impact incident occurrence, while high-cognitive demand tasks, such as hoisting and identifying pedestrians/obstacles, reduce SA and increase errors. Driving tasks are particularly vulnerable to errors and are the most affected by operator risk generators (ORGs), representing 42% of incident risk events. This study identifies driving, hoisting, and lowering loads as the tasks most influenced by system factors. Limitations include the task difficulty levels, managing physical risk, and training. Future research is suggested in autonomous industrial vehicles and advanced driver assistance systems (ADASs). Conclusions: This study provides valuable insights into how we may improve safety in logistics operations by proposing a multiphase methodology to uncover the patterns of attention, perception, and cognitive errors and their impact on decision-making. Full article
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28 pages, 9169 KB  
Article
Economic Justice in the Design of a Sugarcane-Derived Biofuel Supply Chain: A Fair Profit Distribution Approach
by Jimmy Carvajal, William Sarache and Yasel Costa
Logistics 2024, 8(4), 122; https://doi.org/10.3390/logistics8040122 - 18 Nov 2024
Cited by 3 | Viewed by 2594
Abstract
Background: In agricultural supply chains, unequal bargaining power often leads to economic inequality, particularly for farmers. The fair profit distribution (FPD) approach offers a solution by optimizing supply chain flows (materials, information, and money) to promote economic equity among members. However, our [...] Read more.
Background: In agricultural supply chains, unequal bargaining power often leads to economic inequality, particularly for farmers. The fair profit distribution (FPD) approach offers a solution by optimizing supply chain flows (materials, information, and money) to promote economic equity among members. However, our literature review highlights a gap in applying the FPD approach to the facility location-allocation problem in supply chain network design (SCND), particularly in sugarcane-derived biofuel supply chains. Methods: Consequently, we propose a multi-period optimization model based on FPD to design a sugarcane biofuel supply chain. The methodology involves four steps: constructing a conceptual model, developing a mathematical model, designing a solution strategy, and generating insights. This model considers both investment (crop development, biorefinery construction) and operational phases over a long-term planning horizon, focusing on farm location and crop allocation. Results: By comparing the FPD model to a traditional centralized planning supply chain (CSC) approach, we examine the impact of the planning horizon, number of farms, and sugarcane prices paid by biorefineries on financial performance. While the FPD model results in lower overall system profits, it fosters a fairer economic scenario for farmers. Conclusions: This study contributes to economic justice in supply chains and offers insights to promote fair trade among stakeholders. Full article
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25 pages, 5137 KB  
Article
A POMDP Approach to Map Victims in Disaster Scenarios
by Pedro Gabriel Villani and Paulo Sergio Cugnasca
Logistics 2024, 8(4), 113; https://doi.org/10.3390/logistics8040113 - 7 Nov 2024
Cited by 2 | Viewed by 3626
Abstract
Background: The rise in natural and man-made disasters has increased the need for effective search-and-rescue tools, particularly in resource-limited areas. Unmanned Aerial Vehicles (UAVs) are increasingly used for this purpose due to their flexibility and lower operational costs. However, finding the most [...] Read more.
Background: The rise in natural and man-made disasters has increased the need for effective search-and-rescue tools, particularly in resource-limited areas. Unmanned Aerial Vehicles (UAVs) are increasingly used for this purpose due to their flexibility and lower operational costs. However, finding the most efficient paths for these UAVs remains a challenge, as it is essential to maximize victim location and minimize mission time. Methods: This study presents an autonomous UAV-based approach for identifying victims, prioritizing high-risk areas and those needing urgent medical attention. Unlike other methods focused solely on minimizing mission time, this approach emphasizes high-risk zones and potential secondary disaster areas. Using a partially observable Markov decision process, it simulates victim detection through an image classification algorithm, enabling efficient and independent operation. Results: Experiments with real data indicate that this approach reduces risk by 66% during the mission’s first half while autonomously identifying victims without human intervention. Conclusions: This study demonstrates the capability of autonomous UAV systems to improve search-and-rescue efforts in disaster-prone, resource-constrained regions by effectively prioritizing high-risk areas, thereby reducing mission risk and improving response efficiency. Full article
(This article belongs to the Section Humanitarian and Healthcare Logistics)
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20 pages, 1686 KB  
Article
Analysing the Influence of Augmented Reality on Organization Performance via Supply and Logistics Value Chain Functions: A Hybrid ANN-PLS Model Assessment in the Gulf Cooperation Council Region
by Ahmad Aburayya
Logistics 2024, 8(4), 110; https://doi.org/10.3390/logistics8040110 - 5 Nov 2024
Cited by 7 | Viewed by 3409
Abstract
Background: Despite the resurgence of interest in augmented reality (AR) due to Industry 4.0 and its ability to resolve several challenges faced by current business models, comprehensive research examining the capabilities of AR in supply chain management (SCM) and logistics remains limited. [...] Read more.
Background: Despite the resurgence of interest in augmented reality (AR) due to Industry 4.0 and its ability to resolve several challenges faced by current business models, comprehensive research examining the capabilities of AR in supply chain management (SCM) and logistics remains limited. This article aims to investigate the potential effects of AR technology on organizational performance through the mediation role of SCM and logistics value chain functions to address the existing knowledge gap. Methods: This research employed a cross-sectional design and an explanatory survey as a deductive approach for hypothesis development. The primary data collection method involved the self-administration of a questionnaire to furniture suppliers located in the Gulf Cooperation Council (GCC), including six countries. Of the 656 questionnaires submitted to suppliers, 483 were considered usable, yielding a response rate of 73.6%. The research utilized partial least squares structural equation modelling (PLS-SEM) and artificial neural network (ANN) techniques to evaluate the gathered data. Results: The current paper’s statistical evidence demonstrates that AR implementation has a positive impact on the supply and logistics value chain activities and organizational performance of furniture suppliers in the GCC region. Moreover, it illustrates that the design and planning variable of supply chain value dominates as the primary predictor of organization performance. The results indicated that the ANN strategy provided a more comprehensive explanation of internally generated constructs compared to the PLS-SEM technique. Conclusions: This study demonstrates its usefulness by advising furniture industry decision-makers on what to avoid and what aspects to consider when creating plans and regulations. The report also suggests operations managers apply machine learning (ANN) for prediction and decision-making in supply and operations value chains. This essay looks at how the AR and resource-based supply value chain view may affect company performance across countries, firm sizes, and ages. Full article
(This article belongs to the Topic New Technological Solutions, Research Methods, Simulation and Analytical Models That Support the Development of Modern Transport Systems)
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25 pages, 3021 KB  
Article
Use of Smart Glasses for Boosting Warehouse Efficiency: Implications for Change Management
by Markus Epe, Muhammad Azmat, Dewan Md Zahurul Islam and Rameez Khalid
Logistics 2024, 8(4), 106; https://doi.org/10.3390/logistics8040106 - 17 Oct 2024
Cited by 7 | Viewed by 10123
Abstract
Background: Warehousing operations, crucial to logistics and supply chain management, often seek innovative technologies to boost efficiency and reduce costs. For instance, AR devices have shown the potential to significantly reduce operational costs by up to 20% in similar industries. Therefore, this paper [...] Read more.
Background: Warehousing operations, crucial to logistics and supply chain management, often seek innovative technologies to boost efficiency and reduce costs. For instance, AR devices have shown the potential to significantly reduce operational costs by up to 20% in similar industries. Therefore, this paper delves into the pivotal role of smart glasses in revolutionising warehouse effectiveness and efficiency, recognising their transformative potential. However, challenges such as employee resistance and health concerns highlight the need for a balanced trade-off between operational effectiveness and human acceptance. Methods: This study uses scenario and regression analyses to examine data from a German logistics service provider (LSP). Additionally, structured interviews with employees from various LSPs provide valuable insights into human acceptance. Results: The findings reveal that smart glasses convert dead time into value-added time, significantly enhancing the efficiency of order picking processes. Despite the economic benefits, including higher profits and competitive advantages, the lack of employee acceptance due to health concerns still needs to be addressed. Conclusions: After weighing the financial advantages against health impairments, the study recommends implementing smart glass technology in picking processes, given the current state of technical development. This study’s practical implications include guiding LSPs in technology adoption strategies, while theoretically, it adds to the body of knowledge on the human-technology interface in logistics. Full article
(This article belongs to the Special Issue Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics)
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26 pages, 868 KB  
Review
Current Advancements in Drone Technology for Medical Sample Transportation
by Noel Stierlin, Martin Risch and Lorenz Risch
Logistics 2024, 8(4), 104; https://doi.org/10.3390/logistics8040104 - 12 Oct 2024
Cited by 35 | Viewed by 20932
Abstract
Background: The integration of drone technology into healthcare logistics presents a significant opportunity to enhance the speed, reliability, and efficiency of medical sample transportation. Methods: This paper provides a narrative review of current advancements in drone technology, focusing on its application in the [...] Read more.
Background: The integration of drone technology into healthcare logistics presents a significant opportunity to enhance the speed, reliability, and efficiency of medical sample transportation. Methods: This paper provides a narrative review of current advancements in drone technology, focusing on its application in the rapid and secure delivery of medical samples, particularly in urban and remote regions where traditional transportation methods often face challenges. Drawing from recent studies and case reports, the review highlights the role of technologies such as artificial intelligence (AI)-driven navigation systems, real-time monitoring, and secure payload management in mitigating logistical barriers like traffic congestion and geographical isolation. Results: Based on findings from various case studies, the review demonstrates how drones can significantly reduce transportation time and costs, while improving accessibility to healthcare services in underserved areas. Conclusions: This paper concludes that, while challenges such as regulatory hurdles and privacy concerns remain, ongoing technological advancements and the development of supportive regulatory frameworks have the potential to revolutionize medical logistics, ultimately improving patient outcomes and healthcare delivery. Full article
(This article belongs to the Section Humanitarian and Healthcare Logistics)
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17 pages, 3545 KB  
Article
Framework for the Sustainable Modeling of Electric Truck Fleet Usage
by Irina Yatskiv (Jackiva), Jurijs Tolujevs and Vladimirs Petrovs
Logistics 2024, 8(4), 95; https://doi.org/10.3390/logistics8040095 - 26 Sep 2024
Cited by 1 | Viewed by 3167
Abstract
Background: As road transport companies increasingly integrate electric trucks (eTrucks) into urban fleets, evaluating their performance in real-world conditions is essential for effective fleet management and infrastructure planning. Methods: This study introduces TraPodSim, a simulation system designed to assess the key performance indicators [...] Read more.
Background: As road transport companies increasingly integrate electric trucks (eTrucks) into urban fleets, evaluating their performance in real-world conditions is essential for effective fleet management and infrastructure planning. Methods: This study introduces TraPodSim, a simulation system designed to assess the key performance indicators (KPIs) of eTrucks and other vehicle types. Using real geographic data, transportation routes, and technical vehicle specifications, the system simulates daily operations under user-defined conditions. Results: TraPodSim produces 20 physical indicators, providing detailed insights into the daily performance of each vehicle in the fleet. These indicators help evaluate fleet efficiency, energy consumption, and overall operational effectiveness. Conclusions: TraPodSim offers transport companies a valuable tool for optimizing fleet configurations and analyzing the use of private or public battery-charging stations, enabling the efficient integration of eTrucks into existing transportation networks. Full article
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13 pages, 882 KB  
Article
Risk Prediction Score for Thermal Mapping of Pharmaceutical Transport Routes in Brazil
by Clayton Gerber Mangini, Nilsa Duarte da Silva Lima and Irenilza de Alencar Nääs
Logistics 2024, 8(3), 84; https://doi.org/10.3390/logistics8030084 - 19 Aug 2024
Cited by 2 | Viewed by 3451
Abstract
Background: The global pharmaceutical industry is crucial for providing medications but faces challenges in distributing products safely, especially in tropical and remote areas. Pharmaceuticals require careful transport control to maintain quality; therefore, manufacturers must adopt optimal distribution strategies to ensure product quality [...] Read more.
Background: The global pharmaceutical industry is crucial for providing medications but faces challenges in distributing products safely, especially in tropical and remote areas. Pharmaceuticals require careful transport control to maintain quality; therefore, manufacturers must adopt optimal distribution strategies to ensure product quality throughout the supply chain. The current research focused on creating a model to assess risk levels and predict risk categorization (low, moderate, and high) associated with thermal mapping across pharmaceutical transportation pathways. Methods: Data from a company for pharmaceutical logistics in Brazil were used. The data had 85,261 instances and six attributes (season, origin, destination, route, temperature, and temperature excursion). The dataset consisted of critical destinations, including the shipment time, cargo temperature, and route information. The classification algorithms (CART-Decision Tree, NB-Naive Bayes, and MP-Multilayer Perceptron) were used to build up a model of rules for predicting risk levels in thermal mapping routes; Results: The MP model presented the best performance, indicating a better application probability. The machine learning model is the basis for an automated risk prediction for routes of pharmaceutical transportation; Conclusions: the developed MP model might automatically predict risk during the distribution of pharmaceutical products, which might lead to optimizing time and costs. Full article
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15 pages, 3535 KB  
Article
Optimal Network Design for Municipal Waste Management: Application to the Metropolitan City of Rome
by Marco Boresta, Anna Livia Croella, Claudio Gentile, Laura Palagi, Diego Maria Pinto, Giuseppe Stecca and Paolo Ventura
Logistics 2024, 8(3), 79; https://doi.org/10.3390/logistics8030079 - 7 Aug 2024
Cited by 8 | Viewed by 4246
Abstract
Background: This work is part of the regional research project PIPER—Intelligent Platform for the Optimization of Recycling Operations, which aims to develop a network design model for waste collection in the metropolitan city of Rome, Italy. The goal is to enhance the strategic [...] Read more.
Background: This work is part of the regional research project PIPER—Intelligent Platform for the Optimization of Recycling Operations, which aims to develop a network design model for waste collection in the metropolitan city of Rome, Italy. The goal is to enhance the strategic planning of treatment and disposal facilities by incorporating transshipment locations to improve the efficiency of waste collection. The motivation for this study stems from the stringent targets set by the European Green Deal to achieve near-zero emissions and the critical role of waste management in realizing circular economy practices. Methods: The problem is formulated as a mixed integer linear program (MILP) that includes constraints on vehicle allocation to shifts and driver requirements. An additional feature of the model is its ability to account for vehicle maintenance issues when deployed on consecutive shifts. Results: The model was tested against a real-world case study in Rome and demonstrated significant potential savings, with a reduction in total traveled distance exceeding 10%. The mathematical model was also used for evaluating strategic scenarios in a “what-if” analysis, allowing the municipal collection company to assess location options for depots, waste treatment facilities, and transshipment points, as well as to optimize the fleet composition and driver allocation during work shifts. Conclusions: This study presents a robust tool for strategic planning in waste collection operations, highlighting the benefits of using transshipment locations to improve efficiency. The findings indicate substantial potential for cost savings and operational improvements, making the model a valuable asset for municipal waste management planning. Full article
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14 pages, 5599 KB  
Article
Visualising Carrier Consolidation and Alternative Delivery Locations: A Digital Model of Last-Mile Delivery in England and Wales
by Maren Schnieder
Logistics 2024, 8(3), 77; https://doi.org/10.3390/logistics8030077 - 1 Aug 2024
Cited by 8 | Viewed by 4765
Abstract
Background: Various innovations have been proposed to improve the efficiency and sustainability of last-mile delivery in urban and rural environments. Notable examples of innovative delivery solutions are parcel lockers, cargo bicycles, crowdsourced delivery, and so on. Methods: This study contributes to [...] Read more.
Background: Various innovations have been proposed to improve the efficiency and sustainability of last-mile delivery in urban and rural environments. Notable examples of innovative delivery solutions are parcel lockers, cargo bicycles, crowdsourced delivery, and so on. Methods: This study contributes to the ongoing research by developing a large-scale digital model of England and Wales to evaluate a new generation of solutions for last-mile delivery challenges being faced in both rural areas and cities. The two innovations chosen for comparison in this study are (i) carrier consolidation and (ii) alternative delivery locations (i.e., delivery to the workplace instead of the home). As well as the effect on any individual locations, the digital model evaluates both the benefits for England and Wales as a whole. Furthermore, the influence of the market share on the results, as well as the effect of changing the number of depots, is assessed. Results: By delivering to the customer’s workplace instead of the home, the vehicle kilometres travelled (VKT) reduce slightly (less than 10%). Carrier consolidation shows significant potential in reducing the overall VKT (up to 53%). When looking at individual areas in isolation, the consolidation option reduces the VKT or changes it up and down all within tolerance. Naturally, the first option causes a significant shift in delivery activity across England and Wales. Areas of central London would see in-excess of a 10-fold increase in the number of parcels delivered, whereas the demand for parcels in rural areas is further, and significantly reduced. Conclusions: This study highlights the importance of large-scale and detailed digital models that not only calculate the overall benefits of an innovation but also their effect on each individual area. Full article
(This article belongs to the Special Issue Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics)
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21 pages, 3111 KB  
Article
Transforming E-Commerce Logistics: Sustainable Practices through Autonomous Maritime and Last-Mile Transportation Solutions
by Nistor Andrei, Cezar Scarlat and Alexandra Ioanid
Logistics 2024, 8(3), 71; https://doi.org/10.3390/logistics8030071 - 15 Jul 2024
Cited by 43 | Viewed by 11439
Abstract
The logistics landscape in e-commerce is undergoing a profound transformation toward sustainability and autonomy. This paper explores the implementation of autonomous maritime and last-mile transportation solutions to optimize the entire logistics chain from factory to customer. Building on the lessons learned from the [...] Read more.
The logistics landscape in e-commerce is undergoing a profound transformation toward sustainability and autonomy. This paper explores the implementation of autonomous maritime and last-mile transportation solutions to optimize the entire logistics chain from factory to customer. Building on the lessons learned from the maritime industry’s digital transformation, the study identifies key features and proposes a forward-looking autonomous maritime and last-mile transportation system. Emphasizing the role of geospatial technologies, the proposed system employs GIS-based electronic route optimization for efficient goods delivery, integrating onboard and ashore GIS-based sensors for enhanced location precision. A case study was built to analyze the implementation of autonomous means of transport along the route of a product from factory to customer. The integration of autonomous systems shows substantial improvements in logistics performance. Synchromodal logistics and smart steaming techniques can be utilized to optimize transportation routes, resulting in reduced fuel consumption and emissions. The findings reveal that autonomous maritime and last-mile transport systems can significantly enhance the efficiency, flexibility and sustainability of e-commerce logistics. The study emphasizes the need for advanced technological integration and provides a comprehensive framework for future research and practical applications in the logistics industry. Full article
(This article belongs to the Special Issue Sustainable E-commerce, Supply Chains and Logistics)
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35 pages, 1183 KB  
Article
Zero-Emission Heavy-Duty, Long-Haul Trucking: Obstacles and Opportunities for Logistics in North America
by Paul D. Larson, Robert V. Parsons and Deepika Kalluri
Logistics 2024, 8(3), 64; https://doi.org/10.3390/logistics8030064 - 27 Jun 2024
Cited by 20 | Viewed by 9761
Abstract
Background: Pressure is growing in North America for heavy-duty, long-haul trucking to reduce greenhouse gas (GHG) emissions, ultimately to zero. With freight volumes rising, improvement depends on zero-emissions technologies, e.g., battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs). However, emissions [...] Read more.
Background: Pressure is growing in North America for heavy-duty, long-haul trucking to reduce greenhouse gas (GHG) emissions, ultimately to zero. With freight volumes rising, improvement depends on zero-emissions technologies, e.g., battery electric vehicles (BEVs) and fuel cell electric vehicles (FCEVs). However, emissions reductions are constrained by technological and commercial realities. BEVs and FCEVs are expensive. Further, BEVs depend on existing electricity grids and FCEVs rely on steam–methane reforming (SMR) or electrolysis using existing grids to produce hydrogen. Methods: This study assembles publicly available data from reputable sources to estimate breakeven vehicle purchase prices under various conditions to match conventional (diesel) truck prices. It also estimates GHG emissions reductions. Results: BEVs face numerous obstacles, including (1) limited range; (2) heavy batteries and reduced cargo capacity; (3) long recharging time; and (4) uncertain hours-of-service (HOS) implications. On the other hand, FCEVs face two primary obstacles: (1) cost and availability of hydrogen and (2) cost of fuel cells. Conclusions: In estimating emissions reductions and economic feasibility of BEVs and FCEVs versus diesel trucks, the primary contributions of this study involve its consideration of vehicle prices, carbon taxes, and electricity grid capacity constraints and demand fees. As electricity grids reduce their emissions intensity, grid congestion and capacity constraints, opportunities arise for BEVs. On the other hand, rising electricity demand fees benefit FCEVs, with SMR-produced hydrogen a logical starting point. Further, carbon taxation appears to be less important than other factors in the transition to zero-emission trucking. Full article
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26 pages, 8688 KB  
Article
Performance Analysis of Automated Parcel Lockers in Urban Delivery: Combined Agent-Based–Monte Carlo Simulation Approach
by Eugen Rosca, Florin Rusca, Mircea Augustin Rosca and Aura Rusca
Logistics 2024, 8(2), 61; https://doi.org/10.3390/logistics8020061 - 14 Jun 2024
Cited by 13 | Viewed by 7007
Abstract
Background: The habitat structure, the environmental impact, the market acceptance, the changes in consumers’ preferences, and the pandemic urged for innovative solutions in urban last-mile delivery. Parcel lockers are among the most preferred solutions by customers due to their home proximity, time [...] Read more.
Background: The habitat structure, the environmental impact, the market acceptance, the changes in consumers’ preferences, and the pandemic urged for innovative solutions in urban last-mile delivery. Parcel lockers are among the most preferred solutions by customers due to their home proximity, time availability, and cost efficiency. Methods: This paper introduces an agent-based model (ABM) and a Monte Carlo simulation program to analyze in detail the activity of parcel locker points. The ABM describes the behavior of the agents (customers, parcels, lockers, delivery agents). The simulation is realized using ARENA 12 software. Two scenarios are created based on the number of daily delivery shifts; for each scenario, 300 simulation experiments with various input data are conducted. Results: Three measures of performance (MOPs) are selected to assess the system activity: the number of daily delivered parcels, the delivery time of an order, and the daily delayed orders. The simulation outputs reveal significant predictors of MOPs and disclose moments when actions need to be taken to increase system capacity or change customer behavior. Conclusions: The versatility of the simulation model in terms of input variables makes it a useful decision support tool for planning by highlighting quantitative assessments, organizing delivery activity, along with influences due to customer behavior changes. Full article
(This article belongs to the Special Issue Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics)
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24 pages, 3794 KB  
Article
The Development of Risk Assessments and Supplier Resilience Models for Military Industrial Supply Chains Considering Rare Disruptions
by Anna Urmston, Dongping Song and Andrew Lyons
Logistics 2024, 8(2), 57; https://doi.org/10.3390/logistics8020057 - 4 Jun 2024
Cited by 3 | Viewed by 5382
Abstract
Background: Supply chain risk and resilience in non-profit-seeking industries involving governmental agencies and quasi-governmental agencies have been under-studied. This paper focuses on the military industrial supply chain to demonstrate the development of risk assessment and supplier resilience models considering one-off disruption events [...] Read more.
Background: Supply chain risk and resilience in non-profit-seeking industries involving governmental agencies and quasi-governmental agencies have been under-studied. This paper focuses on the military industrial supply chain to demonstrate the development of risk assessment and supplier resilience models considering one-off disruption events such as the COVID-19 disruption. Methods: We establish relevant resilience-based categories through a literature review, supported by the experiences of supply chain experts within the military industry. We quantify the severity of the identified resilience categories, their detectability, and their occurrence probabilities. The failure modes and effects analysis technique is used to evaluate the risk priorities for the resilience categories to develop a risk assessment model. The risk assessment model is then extended to a supplier resilience model by incorporating specific rare disruption factors, which can act as a scenario planning tool. Results: It is found that (i) the top four resilience sub-categories are financial, topical data, business continuity planning, and supply chain mapping, while cost reduction strategies and green material usage are the least important; (ii) the main areas requiring focus are topical data, supply chain depth awareness, business continuity management, and internal risk management; and (iii) suppliers have least resilience in the areas of ‘topical information’ and ‘business continuity strategy’. Conclusions: The tool developed can help military industrial supply chains identify the main areas to enhance resilience from multiple perspectives of severity, occurrence probability, detectability, and suppliers. Full article
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16 pages, 1061 KB  
Article
Artificial Intelligence Capabilities for Demand Planning Process
by Claudia Aparecida de Mattos, Fernanda Caveiro Correia and Kumiko Oshio Kissimoto
Logistics 2024, 8(2), 53; https://doi.org/10.3390/logistics8020053 - 10 May 2024
Cited by 14 | Viewed by 9483
Abstract
Background: Technological advancements, particularly in Artificial Intelligence (AI), are revolutionizing operations management, especially in the domain of supply chain management. This paper delves into the application of AI in demand planning processes within the supply chain context. Drawing upon a comprehensive review [...] Read more.
Background: Technological advancements, particularly in Artificial Intelligence (AI), are revolutionizing operations management, especially in the domain of supply chain management. This paper delves into the application of AI in demand planning processes within the supply chain context. Drawing upon a comprehensive review of the existing literature, the main objective of this study is to analyze how AI is being applied and adopted in the demand planning process, identifying the resources needed to build the capacity of AI in the demand process, as well as the mechanisms and practices contributing to AI capability’s advancement and formation. Methodology: The approach was qualitative, and case studies of three different companies were conducted. Results: This study identified crucial resources necessary for fostering AI capabilities in demand planning. Our study extends the literature on AI capability in several ways. First, we identify the resources that are important in the formation of the capacity to implement AI in the context of demand planning. Conclusions: This study’s practical contributions underscore the multifaceted nature of AI implementation for demand planning, emphasizing the importance of resource allocation, human capital development, collaborative relationships, organizational alignment, and relational capital and AI. Full article
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29 pages, 5234 KB  
Article
Optimizing Last-Mile Delivery: A Multi-Criteria Approach with Automated Smart Lockers, Capillary Distribution and Crowdshipping
by Bartosz Sawik
Logistics 2024, 8(2), 52; https://doi.org/10.3390/logistics8020052 - 8 May 2024
Cited by 56 | Viewed by 22735
Abstract
Background: This publication presents a review, multiple criteria optimization models, and a practical example pertaining to the integration of automated smart locker systems, capillary distribution networks, crowdshipping, last-mile delivery and supply chain management. This publication addresses challenges in logistics and transportation, aiming [...] Read more.
Background: This publication presents a review, multiple criteria optimization models, and a practical example pertaining to the integration of automated smart locker systems, capillary distribution networks, crowdshipping, last-mile delivery and supply chain management. This publication addresses challenges in logistics and transportation, aiming to enhance efficiency, reduce costs and improve customer satisfaction. This study integrates automated smart locker systems, capillary distribution networks, crowdshipping, last-mile delivery and supply chain management. Methods: A review of the existing literature synthesizes key concepts, such as facility location problems, vehicle routing problems and the mathematical programming approach, to optimize supply chain operations. Conceptual optimization models are formulated to solve the complex decision-making process involved in last-mile delivery, considering multiple objectives, including cost minimization, delivery time optimization, service level minimization, capacity optimization, vehicle minimization and resource utilization. Results: The multiple criteria approaches combine the vehicle routing problem and facility location problem, demonstrating the practical applicability of the proposed methodology in a real-world case study within a logistics company. Conclusions: The execution of multi-criteria models optimizes automated smart locker deployment, capillary distribution design, crowdshipping and last-mile delivery strategies, showcasing its effectiveness in the logistics sector. Full article
(This article belongs to the Special Issue Multi-Criteria Decision-Making and Its Application in Sustainable Smart Logistics)
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23 pages, 2607 KB  
Article
Implementing Additive Manufacturing in Orthopedic Shoe Supply Chains—Cost and Lead Time Comparison
by Victor Verboeket, Harold Krikke and Mika Salmi
Logistics 2024, 8(2), 49; https://doi.org/10.3390/logistics8020049 - 7 May 2024
Cited by 9 | Viewed by 5815
Abstract
Background: Additive manufacturing (AM) for patient-specific medical care products offers great opportunities. However, evidence about the supply chain (SC) performance impact based on empirical data is limited. Methods: In this case study, we gathered real-life data about a traditional manufacturing orthopedic [...] Read more.
Background: Additive manufacturing (AM) for patient-specific medical care products offers great opportunities. However, evidence about the supply chain (SC) performance impact based on empirical data is limited. Methods: In this case study, we gathered real-life data about a traditional manufacturing orthopedic shoe SC and developed future scenarios in which AM is introduced at various points and with different degrees of penetration in the SC. Results: Presently, AM can only replace traditional manufacturing of tools and shoe components at a higher total cost. However, with maturing technology, the complete AM production of orthopedic shoes is expected to become feasible. Theoretically, that could disrupt existing SCs, eliminating 70% of the SC steps, improving SC lead time by 90%, and altering SC relations. However, certain thresholds currently prevent disruption. Specifically, the AM of complete orthopedic shoes has to become possible, manufacturing prices have to drop, and traditional craftsmanship has to be integrated into the digital product design. Conclusions: A framework for transition pathways, including directions for future research, is formed. Findings provide valuable insights for scholars and decision makers in the patient-specific products industry, health insurance providers, and healthcare policy makers to be better prepared by adjusting SC designs, relationships, and remuneration programs while AM technology develops towards maturity. Full article
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20 pages, 813 KB  
Article
A Novel Auction-Based Truck Appointment System for Marine Terminals
by Ilias Alexandros Parmaksizoglou, Alessandro Bombelli and Alexei Sharpanskykh
Logistics 2024, 8(2), 40; https://doi.org/10.3390/logistics8020040 - 10 Apr 2024
Cited by 2 | Viewed by 4531
Abstract
Background: Increased maritime trade has led to a surge in drayage operations, causing congestion and environmental issues in port areas. Truck Appointment Systems (TASs) are commonly used to manage truck arrival rates, yet transparency and equity in slot allocation remain problematic, fostering distrust [...] Read more.
Background: Increased maritime trade has led to a surge in drayage operations, causing congestion and environmental issues in port areas. Truck Appointment Systems (TASs) are commonly used to manage truck arrival rates, yet transparency and equity in slot allocation remain problematic, fostering distrust between Licensed Motor Carriers (LMCs) and Marine Terminal Operators (MTOs). Methods: This study proposes a polycentric approach to improve truck scheduling and ensure that those impacted by decisions are involved in the decision-making process. A single-round auction mechanism focused on optimizing the truck hauling process through a pricing policy that promotes sincere bidding is introduced. The proposed approach employs an optimization strategy to achieve equitable coordination in truck synchronization through means of adaptable capacity management. Results: Numerical experiments assessing scenarios of noncollaborative behavior against partial collaboration between MTOs and LMCs demonstrate the effectiveness of the proposed approach in enhancing user satisfaction and terminal conditions for a case study focused on a medium-sized terminal. Collaboration between trucking companies is shown to increase utility per monetary unit spent on slot acquisition. Conclusions: The polycentric strategy offers a solution to TAS limitations by ensuring stakeholder participation with respect to flexibility and transparency by ensuring that those impacted by decisions are involved in the decision-making process. Full article
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