Logistics

23 pages, 639 KB

Open AccessArticle

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

Viewed by 497

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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33 pages, 1730 KB

Open AccessSystematic Review

Exploring the Interplay Between Green Practices, Resilience, and Viability in Supply Chains: A Systematic Literature Review

by Hamza Chajae, Moulay Ali El Oualidi, Ali Hebaz and Hasna Mharzi

Logistics 2026, 10(1), 23; https://doi.org/10.3390/logistics10010023 - 16 Jan 2026

Viewed by 333

Abstract

Background: In this new era, marked by increasing environmental concerns, geopolitical crises, and global disruptions, traditional efficiency-focused supply chains have shown significant vulnerabilities. As a result, the shift toward new strategies to maintain sustainability has become more crucial. Meanwhile, to withstand disruptions, [...] Read more.

Background: In this new era, marked by increasing environmental concerns, geopolitical crises, and global disruptions, traditional efficiency-focused supply chains have shown significant vulnerabilities. As a result, the shift toward new strategies to maintain sustainability has become more crucial. Meanwhile, to withstand disruptions, supply chains must develop robustness and resilience. More recently, attention has turned toward viability to enable sustainable supply chain operations over the long term under uncertainty. Methods: This study conducts a systematic literature review (SLR) to explore the links between green supply chain management (GSCM), supply chain resilience (SCRES), and supply chain viability (SCV), guided by the PRISMA framework and structured using the PICO approach as a high-level scoping tool. We reviewed 70 peer-reviewed journal articles published between 2010 and 2024. Result: The study identified widely adopted green practices and explored their impact on supply chain resilience and sustainable performance. Many studies address GSCM, SCRES, and SCV either separately or in pairs, but few integrate all three dimensions. GSCM fosters resilience, and when the three aspects are combined, they serve as the cornerstones of viable supply chains. However, their potential contribution to supply chain viability is still unexplored. Conclusions: These insights provide useful guidance for creating supply chains that balance long-term continuity, disruption-readiness, and environmental goals. They also suggest a future research agenda to better align these three priorities. Full article

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19 pages, 2936 KB

Open AccessArticle

Determining the Optimal Order Quantity for Perishable Products Affected by Stochastic Transportation Delays

by Banthita Kanchanasathita, Atchara Wangpa, Apisit Pitakcheun and Chirakiat Saithong

Logistics 2026, 10(1), 22; https://doi.org/10.3390/logistics10010022 - 15 Jan 2026

Viewed by 287

Abstract

Background: Transportation delays pose significant challenges for perishable products by reducing freshness, shortening selling duration, and causing lost sales during the delay. Methods: Motivated by the growing importance of transportation delays on perishable products, this study develops a single-period analytical expected profit expression [...] Read more.

Background: Transportation delays pose significant challenges for perishable products by reducing freshness, shortening selling duration, and causing lost sales during the delay. Methods: Motivated by the growing importance of transportation delays on perishable products, this study develops a single-period analytical expected profit expression to determine the optimal order quantity that maximizes expected profit. The model incorporates deterioration-driven price reductions, lost sales opportunities occurring during the delay, and the shortened selling duration resulting from delayed delivery, without imposing a specific probability distribution on the transportation delay duration. Results: Numerical experiments illustrate how key parameters influence the optimal order quantity and the corresponding expected profit. Deterioration reduces expected profit by primarily reducing the selling price. In addition, a higher disruption probability reduces both the optimal order quantity and the expected profit, while longer selling durations result in larger order quantities and yield higher expected profits. A low initial selling price can result in negative expected profit, indicating cases where placing the order is inappropriate. Conclusions: The findings offer managerial implications for determining optimal order quantities that maximize profit under transportation delays for perishable products. Full article

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30 pages, 2552 KB

Open AccessSystematic 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

Viewed by 476

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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22 pages, 671 KB

Open AccessArticle

The Impact of Digitization Transport Documents on the Competitiveness of Road Freight Transport Companies

by Miloš Poliak and Dominika Rovňaníková

Logistics 2026, 10(1), 20; https://doi.org/10.3390/logistics10010020 - 13 Jan 2026

Viewed by 303

Abstract

Background: The rapid digital transformation in logistics requires the adaptation of transport companies to electronic information management, particularly through the implementation of electronic consignment notes (e-CMR). This study examines how the digitization of transport documentation affects the competitiveness, operational efficiency, and environmental [...] Read more.

Background: The rapid digital transformation in logistics requires the adaptation of transport companies to electronic information management, particularly through the implementation of electronic consignment notes (e-CMR). This study examines how the digitization of transport documentation affects the competitiveness, operational efficiency, and environmental performance of road freight transport companies. Methods: A questionnaire survey was conducted among Slovak and Czech carriers to analyze their experience and readiness for adopting e-CMR. The collected data were evaluated using descriptive and comparative methods to quantify economic and ecological impacts, focusing mainly on invoicing efficiency and paper consumption. Results: The results show that only a small share of carriers currently use e-CMR, primarily due to high software costs and the lack of partner participation. Nevertheless, digitization can significantly shorten the average invoicing delay by approximately 11.5 days, releasing around 7% of tied-up working capital and improving cash flow. From an environmental perspective, the replacement of paper CMR forms could save millions of sheets annually, leading to a substantial reduction in CO₂ emissions and paper waste within the V4 region. Conclusions: The findings confirm that the adoption of e-CMR improves economic performance, increases transparency, and contributes to sustainability, representing a crucial step toward a more competitive and environmentally responsible road freight transport sector in Europe. Full article

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18 pages, 431 KB

Open AccessArticle

Measuring Environmental Efficiency of Ports Under Undesirable Outputs and Uncertainty

by Anjali Sonkariya and Anjali Awasthi

Logistics 2026, 10(1), 19; https://doi.org/10.3390/logistics10010019 - 12 Jan 2026

Viewed by 271

Abstract

Ports are the major gateways of cities. Background: Sustainable growth requires ports to prioritize efficiency while balancing economic, social, and environmental goals. There is limited synthesized evidence on the sustainability evaluation of ports, including those of North America. In this paper, we [...] Read more.

Ports are the major gateways of cities. Background: Sustainable growth requires ports to prioritize efficiency while balancing economic, social, and environmental goals. There is limited synthesized evidence on the sustainability evaluation of ports, including those of North America. In this paper, we propose a multi-step approach based on fuzzy DEA to evaluate the environmental performance of ports. Methods: In the first step, we identify indicators for environmental performance evaluation. The second step involves application of fuzzy DEA using the identified indicators to measure the environmental efficiency of ports. In the third step, a numerical illustration is provided using open data. The proposed model incorporates undesirable outputs and employs one set of constraints to make a production frontier. Results: The findings show wide differences in performance, ports reach higher scores when they use resources wisely plus keep emissions low, not merely when they expand. Conclusions: The proposed methodology provides a robust and comparable measurement of port environmental efficiency under uncertainty. Full article

(This article belongs to the Special Issue Decarbonization of Maritime Logistics and Global Supply Chains)

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47 pages, 4215 KB

Open AccessReview

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

Viewed by 359

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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24 pages, 4075 KB

Open AccessArticle

A Hybrid Formal and Optimization Framework for Real-Time Scheduling: Combining Extended Time Petri Nets with Genetic Algorithms

by Sameh Affi, Imed Miraoui and Atef Khedher

Logistics 2026, 10(1), 17; https://doi.org/10.3390/logistics10010017 - 12 Jan 2026

Viewed by 276

Abstract

In modern Industry 4.0 environments, real-time scheduling presents a complex challenge requiring both formal correctness guarantees and optimal performance. Background: Traditional approaches fail to provide an optimal integration between formal correctness guaranteeing and optimization, and such failure either produces suboptimal results or [...] Read more.

In modern Industry 4.0 environments, real-time scheduling presents a complex challenge requiring both formal correctness guarantees and optimal performance. Background: Traditional approaches fail to provide an optimal integration between formal correctness guaranteeing and optimization, and such failure either produces suboptimal results or a correct result lacking guarantee, and studies have indicated that poor scheduling decisions could cause productivity losses of up to 20–30% and increased operational costs of up to USD 2.5 million each year in medium-scale manufacturing facilities. Methods: This work proposes a new hybrid approach by integrating Extended Time Petri Nets (ETPNs) and Finite-State Automata (FSAs) with formal modeling, abstracting ETPNs by extending conventional Time Petri Nets to deterministic time and priority systems, accompanied by Genetic Algorithms (GAs) to optimize the solution to tackle a multi-objective optimization problem. Our solution tackles indeterministic problems by incorporating suitable priority resolution methods and GA to pursue optimal solutions to very complex scheduling problems and starting accurately from standard real-time scheduling-policy models such as DM, RM, and EDF-EDF. Results: Experimental evaluation has clearly verified performance gains up to 48% above conventional techniques, covering completely synthetic and practical case studies, including 31–48% improvement on synthetic benchmarks, 24% increase on resource allocation, and total elimination of constraint violations. Conclusions: The new proposed hybrid technique is, to a considerable extent, a dramatic advancement within real-time scheduling techniques and Industry 4.0, successfully and effectively integrating optimal correctness guaranteeing and favorable GA-aided optimization techniques, which particularly guarantee optimal correctness to safe-related applications and provide considerable improvements to support efficient and optimal performance, extremely helpful within Industry 4.0. Full article

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23 pages, 493 KB

Open AccessArticle

The Knowledge Pipeline: How Supply Chain Information Integration Fuels Green Absorptive Capacity, Employee Creativity, and Innovation Performance

by Safinaz H. Abourokbah, Mohammad Asif Salam and Nada Saleh Badawi

Logistics 2026, 10(1), 16; https://doi.org/10.3390/logistics10010016 - 8 Jan 2026

Viewed by 433

Abstract

Background: With increasing environmental concerns, achieving sustainability in supply chains (SCs) requires strong cooperation among partners. This raises the question of how supply chain information integration (SCII) fosters green supply chain innovation performance (GSCIP). Thus, this study examines the role of SCII [...] Read more.

Background: With increasing environmental concerns, achieving sustainability in supply chains (SCs) requires strong cooperation among partners. This raises the question of how supply chain information integration (SCII) fosters green supply chain innovation performance (GSCIP). Thus, this study examines the role of SCII in driving GSCIP through the sequential mediation of green absorptive capacity (GACAP) and employees’ green creativity (EGC). Building on the knowledge and resource-based views, this study highlights the importance of SCII, GACAP, and EGC as strategic priorities in sustainable innovation. Methods: Data were obtained from 162 SC managers in the Saudi manufacturing industry, and the proposed framework was tested using partial least squares structural equation modelling (PLS-SEM), complemented by importance–performance map analysis (IPMA) and necessary condition analysis (NCA). Results: SCII has a significant impact on GACAP, which in turn increases EGC, thereby enhancing GSCIP. The hypothesised sequential impact is validated, illustrating the crucial roles of GACAP and EGC in enabling firms to transform SCII into green innovation outcomes. IPMA identifies SCII as a high-impact driver of GSCIP, and NCA confirms that SCII is a necessary prerequisite for achieving GSCIP. This study contributes to the literature on green supply chains by demonstrating the practical and vital role of SCII in achieving sustainable competitive advantages and performance. Full article

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

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Graphical abstract

26 pages, 992 KB

Open AccessArticle

AI-Driven Metaverse Integration for Sustainable Manufacturing: The Mediating Role of Digital Supply Chain Resilience in Jordan’s Industrial Sector

by Ahmad Fathi Alheet

Logistics 2026, 10(1), 15; https://doi.org/10.3390/logistics10010015 - 8 Jan 2026

Viewed by 398

Abstract

Background: This study examines how AI-driven metaverse integration enhances sustainable manufacturing performance in Jordan’s industrial sector, with particular emphasis on the mediating role of digital supply chain resilience. Grounded in resource orchestration theory (ROT), the research explains how digital twin systems, predictive [...] Read more.

Background: This study examines how AI-driven metaverse integration enhances sustainable manufacturing performance in Jordan’s industrial sector, with particular emphasis on the mediating role of digital supply chain resilience. Grounded in resource orchestration theory (ROT), the research explains how digital twin systems, predictive AI analytics, and virtual collaboration technologies jointly support sustainability through improved supply chain agility, responsiveness, and continuity. Methods: Data were collected from 500 industrial managers, of which 415 valid responses were analyzed using partial least squares structural equation modeling (PLS-SEM). Results: The findings indicate that AI-powered metaverse dimensions have significant and positive effects on sustainable manufacturing performance, both directly and indirectly through digital supply chain resilience. The mediation analysis confirms that resilience serves as a critical mechanism linking metaverse-based technology adoption to sustainability outcomes. Conclusions: The study highlights the strategic importance of integrating advanced digital and virtual technologies into supply chains to address sustainability challenges, particularly in emerging economies such as Jordan. By extending resource orchestration theory to the metaverse context, this research contributes to theory development and offers practical insights for industrial managers seeking to leverage digital transformation as a source of sustainable competitive advantage. Full article

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24 pages, 647 KB

Open AccessArticle

How Does Big Data Analytics Drive Supply Chain Resilience in Pharmaceuticals? Exploring the Roles of Supply Chain Risk and Ambidexterity

by Sara Sami Al-Nuimat, Zu’bi M. F. Al-Zu’bi and Ayman Bahjat Abdallah

Logistics 2026, 10(1), 14; https://doi.org/10.3390/logistics10010014 - 7 Jan 2026

Viewed by 325

Abstract

Background: The primary objective of this study is to investigate the influence of big data analytics (BDA) on supply chain (SC) risk, SC ambidexterity, and SC resilience. It further examines the effects of SC risk and SC ambidexterity on SC resilience and [...] Read more.

Background: The primary objective of this study is to investigate the influence of big data analytics (BDA) on supply chain (SC) risk, SC ambidexterity, and SC resilience. It further examines the effects of SC risk and SC ambidexterity on SC resilience and explores their mediating roles in the BDA–SC resilience relationship. Despite growing interest in BDA and resilience, limited empirical research has addressed these linkages in pharmaceutical distribution, particularly in emerging economies such as Jordan. Methods: A quantitative research strategy was adopted, employing a survey-based methodology. Data were obtained from 204 managers in pharmaceutical distribution companies in Jordan. Results: The findings indicate that BDA reduces SC risk and positively influences SC ambidexterity and SC resilience. Furthermore, SC risk and SC ambidexterity positively affect SC resilience. Notably, both variables partially mediate the BDA–SC resilience relationship, with ambidexterity showing a stronger effect. Conclusions: Grounded in the resource-based view and the dynamic capability view, this study provides empirical evidence that BDA enhances SC resilience primarily by fostering ambidexterity and mitigating risks. By clarifying the distinct mediating roles of SC risk and SC ambidexterity, the research extends theory and offers practical insights for managers seeking to build more resilient pharmaceutical SCs. Full article

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33 pages, 852 KB

Open AccessArticle

The Vehicle Routing Problem with Time Window and Randomness in Demands, Travel, and Unloading Times

by Gilberto Pérez-Lechuga and Francisco Venegas-Martínez

Logistics 2026, 10(1), 13; https://doi.org/10.3390/logistics10010013 - 7 Jan 2026

Viewed by 401

Abstract

Background: The vehicle routing problem (VRP) is of great importance in the Industry 4.0 era because enabling technologies such as the internet of things (IoT), artificial intelligence (AI), big data, and geographic information systems (GISs) allows for real-time solutions to versions of the [...] Read more.

Background: The vehicle routing problem (VRP) is of great importance in the Industry 4.0 era because enabling technologies such as the internet of things (IoT), artificial intelligence (AI), big data, and geographic information systems (GISs) allows for real-time solutions to versions of the problem, adapting to changing conditions such as traffic or fluctuating demand. Methods: In this paper, we model and optimize a classic multi-link distribution network topology, including randomness in travel times, vehicle availability times, and product demands, using a hybrid approach of nested linear stochastic programming and Monte Carlo simulation under a time-window scheme. The proposed solution is compared with cutting-edge metaheuristics such as Ant Colony Optimization (ACO), Tabu Search (TS), and Simulated Annealing (SA). Results: The results suggest that the proposed method is computationally efficient and scalable to large models, although convergence and accuracy are strongly influenced by the probability distributions used. Conclusions: The developed proposal constitutes a viable alternative for solving real-world, large-scale modeling cases for transportation management in the supply chain. Full article

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39 pages, 2012 KB

Open AccessSystematic Review

Blockchain Technology and Maritime Logistics: A Systematic Literature Review

by Christian Muñoz-Sánchez, Jesica Menéndez-García, Jorge Alejandro Silva, Jose Arturo Garza-Reyes, Dulce María Monroy-Becerril and Eugene Hakizimana

Logistics 2026, 10(1), 12; https://doi.org/10.3390/logistics10010012 - 31 Dec 2025

Viewed by 831

Abstract

Background: Blockchain has been extensively discussed for enhancing transparency, traceability, and trust in general; however, there is fragmented empirical evidence available with respect to this issue within maritime logistics. The objective is to integrate and categorize peer-reviewed publications concerning applications of blockchain [...] Read more.

Background: Blockchain has been extensively discussed for enhancing transparency, traceability, and trust in general; however, there is fragmented empirical evidence available with respect to this issue within maritime logistics. The objective is to integrate and categorize peer-reviewed publications concerning applications of blockchain in maritime logistics and related supply chain domains. Methods: A systematic literature review with PRISMA 2020 was performed in Scopus database, and after a process of screening and eligibility, a total of 78 journal articles published mainly from September 2024 were incorporated. Descriptive and bibliometric analyses were conducted, and VOS viewer-based bibliographic coupling were employed to visualize thematic structure. Results: The review identifies seven research priorities for blockchain in maritime logistics: Technological Interoperability, Economic and Operational Impact, Cybersecurity and Privacy, Adoption and Scalability, Decision-Making and Trust, Environmental Sustainability, and Standardization and Regulatory Frameworks. Blockchain’s primary advantages are enhanced data integrity and visibility, whereas key challenges include interoperability, legal/regulatory uncertainty (e.g., e-doc recognition), high costs, scalability ceilings, integration with legacy systems, and data governance fears. Conclusions: The application of blockchain in maritime logistics depends on combined technical and institutional enabling conditions; an Integrated Blockchain Adoption Framework (IBAF) is suggested, and providing practical guides based on standardization, legal convergence, and hybrid governance modes. Full article

(This article belongs to the Special Issue Investment, Risk, and Sustainability in Maritime Logistics and Supply Chain)

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21 pages, 500 KB

Open AccessArticle

Cognitive Supply Chain Management and Risk Management in Pharmaceuticals: The Mediating Roles of Forecasting, Synchronization, and Transparency

by Ismail Abushaikha, Munirah Sarhan Alqahtani, Omar M. Bwaliez and Ola M. Bwaliez

Logistics 2026, 10(1), 11; https://doi.org/10.3390/logistics10010011 - 30 Dec 2025

Viewed by 436

Abstract

Background: This study examines the degree to which cognitive supply chain management (CSCM) indirectly enhances supply chain risk management (SCRM), addressing the lack of specific empirical research concerning the underlying mechanisms of this relationship. Specifically, this study tests the CSCM-SCRM relationship using [...] Read more.

Background: This study examines the degree to which cognitive supply chain management (CSCM) indirectly enhances supply chain risk management (SCRM), addressing the lack of specific empirical research concerning the underlying mechanisms of this relationship. Specifically, this study tests the CSCM-SCRM relationship using the mediating roles of supply chain forecasting (SCF), supply chain synchronization (SCS), and supply chain transparency (SCT). Methods: For this quantitative research, a survey was conducted among 287 respondents of pharmaceutical companies operating in Saudi Arabia. Convenience sampling was conducted, and the collected data were then analyzed via partial least squares structural equation modeling (PLS-SEM) through SmartPLS 4 software. The dynamic capabilities theory (DCT) and information processing theory (IPT) were integrated to develop the conceptual framework of this study. Results: The findings indicate that CSCM does not exert a direct impact on SCRM. Instead, CSCM significantly enhances SCF, SCS, and SCT. Among these, both SCF and SCT have a direct positive impact on SCRM and act as significant mediators in the CSCM–SCRM relationship. In contrast, SCS neither directly impacts SCRM nor plays a mediating role in this relationship. Based on this study, the positive outcomes of CSCM on SCRM come about via SCF and SCT rather than SCS. Conclusions: This study contributes to the literature by empirically validating a model that integrates CSCM, SCF, SCS, SCT, and SCRM in the context of Saudi pharmaceutical companies. It further contributes to the pharmaceutical practitioners by establishing that CSCM exerts an indirect positive effect on SCRM via information-intensive capabilities. Full article

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

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49 pages, 1724 KB

Open AccessSystematic Review

Approaches, Challenges, and Opportunities in Humanitarian Logistics Integrated with Reverse Logistics and Sustainability

by Aline Monteiro Campos Garcia, Veridiana Souza da Silva Alves, Luiza Ribeiro Alves Cunha, Vívian Karina Bianchini, Carlos do Amaral Razzino, Bárbara Stolte Bezerra and Irineu de Brito, Jr.

Logistics 2026, 10(1), 9; https://doi.org/10.3390/logistics10010009 - 29 Dec 2025

Viewed by 601

Abstract

Background: Reverse Logistics (RL) can reduce waste, mitigate environmental impacts, and enhance operational efficiency in Humanitarian Operations (HOs). Nevertheless, it remains weakly institutionalised and insufficiently recognised as a structuring component of Humanitarian Logistics (HL), operating implicitly and reactively. Methods: A Systematic Literature [...] Read more.

Background: Reverse Logistics (RL) can reduce waste, mitigate environmental impacts, and enhance operational efficiency in Humanitarian Operations (HOs). Nevertheless, it remains weakly institutionalised and insufficiently recognised as a structuring component of Humanitarian Logistics (HL), operating implicitly and reactively. Methods: A Systematic Literature Review (SLR) was conducted in accordance with the PRISMA protocol, examining disaster types, methodological approaches, the roles of RL, and its integration with sustainability and digital technologies. Results: Scientific output increased after 2020, accounting for 66% of the studies. Practices aligned with RL exceed 80% of the publications; however, only 55% explicitly use the term, indicating a disconnect between concept and practice. Sustainability is explicitly addressed in 56% of the studies. Modelling, optimisation, and simulation predominate (27%), followed by reviews (25%) and conceptual analyses (19%). Four roles of RL were identified: environmental (33%), operational (19%), institutional (12%), and technological (19%). Conclusion: RL operates within HOs as a latent and non-formalised capability. As a contribution, this SLR proposes an integrated typology of RL roles in humanitarian contexts. It is recommended to formalise sorting and return protocols, incorporate indicators for reverse flows, assess the use of artificial intelligence to support decision-making, and expand empirical studies that quantify its impacts. Full article

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

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19 pages, 2104 KB

Open AccessEditor’s ChoiceArticle

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

Viewed by 445

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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21 pages, 1930 KB

Open AccessArticle

Targeting Toward Optimal Inventory in Automotive Industry—An Analysis Based on Six Sigma Methodology

by Ionela-Roxana Puiu, Ioana Mădălina Petre and Mircea Boșcoianu

Logistics 2026, 10(1), 8; https://doi.org/10.3390/logistics10010008 - 27 Dec 2025

Viewed by 429

Abstract

Background: This paper presents an analysis and a structured framework for improving inventory accuracy in an automotive factory, considering the current context of global disruptions. In 2023, the company recorded 20,340 inventory adjustments (1695 per month) and a 0.24% monthly net value [...] Read more.

Background: This paper presents an analysis and a structured framework for improving inventory accuracy in an automotive factory, considering the current context of global disruptions. In 2023, the company recorded 20,340 inventory adjustments (1695 per month) and a 0.24% monthly net value discrepancy (EUR 256,594 YTD), with a baseline absolute discrepancy of 2.21% of sales. The project aimed to reduce adjustments to below 700 per month and the net value discrepancy to 0.1%. Methods: The research followed the Six Sigma methodology’s Define, Measure, Analyze, Improve and Control (DMAIC) phases, integrating Root Cause Analysis (RCA) and Failure Mode and Effects Analysis (FMEA) to enhance inventory accuracy in manufacturing operations. Results: Implementation significantly improved inventory accuracy: monthly adjustments decreased from 1695 to 971, the highest RPN was reduced from 576 to 144, and the absolute discrepancy-to-sales ratio stabilized at 0.98% (a 56% improvement). Financial variance was reduced to EUR 1948.10 in Q4 2024, while organizational discipline, role clarity and process control also increased. Conclusions: The integrated DMAIC–RCA–FMEA framework proved effective and replicable, enabling systematic identification of root causes, targeted corrective actions and sustainable KPI-driven improvements. The results demonstrate a scalable approach to inventory optimization that supports operational resilience and supply chain performance. Full article

(This article belongs to the Special Issue Logistics and Supply Chain Challenges and Solutions in the Turbulent World)

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21 pages, 514 KB

Open AccessArticle

Sustainability Through Additive Manufacturing Operations: A Comparative Industrial Analysis with a Life Cycle Assessment Case Study of Türkiye

by Saliha Karadayi-Usta

Logistics 2026, 10(1), 7; https://doi.org/10.3390/logistics10010007 - 26 Dec 2025

Viewed by 418

Abstract

Background: Additive manufacturing (AM), commonly known as 3D printing, is transforming global production systems with sustainability at its core. The global AM market growth underscores the urgency of evaluating its environmental implications. Methods: This study aims to (1) identify Life Cycle [...] Read more.

Background: Additive manufacturing (AM), commonly known as 3D printing, is transforming global production systems with sustainability at its core. The global AM market growth underscores the urgency of evaluating its environmental implications. Methods: This study aims to (1) identify Life Cycle Assessment (LCA) factors influencing additively manufactured products across aerospace, automotive, medical devices, industrial equipment, energy, construction, and consumer electronics industries; (2) determine the relative importance of these factors using Adaptive Choice-Based Conjoint (ACBC) analysis within a Türkiye case study; and (3) assign sustainability levels for each industry via the PrOPPAGA technique. Since LCA quantifies environmental impacts throughout a product’s life cycle, from raw material extraction to end-of-life, this research assesses the sustainability dimensions of AM operations by examining energy consumption, emissions, and waste generation. Results: The findings provide practical and managerial insights for industry stakeholders seeking to enhance sustainable practices in AM. Conclusions: The study introduces a novel sustainability evaluation framework integrating ACBC and PrOPPAGA methods, offering a significant theoretical contribution to the literature on sustainable manufacturing. Full article

(This article belongs to the Special Issue New Progresses and Main Implications in Additive Manufacturing for Operations and Supply Chain Management)

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27 pages, 452 KB

Open AccessArticle

Evaluation of Digital Technologies in Food Logistics: MCDM Approach from the Perspective of Logistics Providers

by Aleksa Maravić, Vukašin Pajić and Milan Andrejić

Logistics 2026, 10(1), 6; https://doi.org/10.3390/logistics10010006 - 26 Dec 2025

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Abstract

Background: In the era of rapid digital transformation, efficient food logistics (FL) is critical for sustainability and competitiveness. Maintaining food quality, minimizing waste, and optimizing costs are complex challenges that advanced digital technologies aim to address, particularly amid growing e-commerce and last-mile delivery [...] Read more.

Background: In the era of rapid digital transformation, efficient food logistics (FL) is critical for sustainability and competitiveness. Maintaining food quality, minimizing waste, and optimizing costs are complex challenges that advanced digital technologies aim to address, particularly amid growing e-commerce and last-mile delivery demands. This underscores the need for a structured, quantitative evaluation of technological solutions to ensure operational reliability, efficiency, and sustainability. Methods: This study employs a Multi-Criteria Decision Making (MCDM) model combining Criterion Impact LOSs (CILOS) and Multi-Objective Optimization on the basis of Simple Ratio Analysis (MOOSRA) to evaluate key FL technologies: IoT, blockchain, Big Data analytics, automation and robotics, and cloud/edge computing. Nine evaluation criteria relevant to logistics providers were used, covering operational efficiency, flexibility, sustainability, food safety, data reliability, KPI support, scalability, costs, and implementation speed. CILOS determined criteria weights by considering interdependencies, and MOOSRA ranked technologies by benefits-to-costs ratios. Sensitivity analysis validated result robustness. Results: Automation and robotics ranked highest for enhancing efficiency, reducing errors, and improving handling and safety. Blockchain was second, supporting traceability and data security. Big Data analytics was third, enabling demand prediction and inventory optimization. IoT ranked fourth, providing real-time monitoring, while cloud/edge computing ranked fifth due to indirect operational impact. Conclusions: The CILOS–MOOSRA model enables transparent, structured evaluation, integrating quantitative metrics with logistics providers’ priorities. Results highlight technologies that enhance efficiency, reliability, and sustainability while revealing integration challenges, providing a strategic foundation for digital transformation in FL. Full article

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21 pages, 1222 KB

Open AccessArticle

Artificial Intelligence-Driven Supply Chain Agility and Resilience: Pathways to Competitive Advantage in the Hotel Industry

by Ibrahim A. Elshaer, Alaa M. S. Azazz, Abdulaziz Aljoghaiman, Mahmoud Mansor, Mahmoud Ahmed Salama and Sameh Fayyad

Logistics 2026, 10(1), 5; https://doi.org/10.3390/logistics10010005 - 26 Dec 2025

Cited by 1 | Viewed by 618

Abstract

Background: The extraordinary disturbances faced by the hotel industry, ranging from worldwide health problems to political instability and climate change, have highlighted the insistent need for more resilient and agile supply chain (SC) systems. This study explored how artificial intelligence (AI) capabilities [...] Read more.

Background: The extraordinary disturbances faced by the hotel industry, ranging from worldwide health problems to political instability and climate change, have highlighted the insistent need for more resilient and agile supply chain (SC) systems. This study explored how artificial intelligence (AI) capabilities can generate competitive advantage (CA) through supply chain agility (SCA) and supply chain resilience (SCR) as mediators and competitive pressure (CP) as a moderator. Methods: Drawing on the resource-based view (RBV) framework, we suggested and empirically tested the study model. Using data collected from 432 hotel managers and analyzed using Partial Least Squares Structural Equation Modelling (SEM-PLS). Results: the results reveal that AI-driven SC can significantly strengthen SCA and SCR. Furthermore, SCA and SCR can act as powerful mediators, and CP can strengthen the tested relationships (the links from AI adoption and CA) as a moderator. Conclusions: The study made several theoretical and practical contributions by integrating AI capabilities into SCR and SCA frameworks in the hotel and tourism context, and by providing practical evidence for professionals aiming to leverage AI-driven SC tools to navigate uncertainty and create sustainable CA. Full article

(This article belongs to the Special Issue Artificial Intelligence and Business Analytics Applications in Supply Chain Operations)

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22 pages, 1116 KB

Open AccessArticle

A Multi-Criteria Decision-Making Approach for Air Rescue Units Allocation During Disaster Response

by Sergio Rebouças, Daniel A. Pamplona, Rodrigo Arnaldo Scarpel and Mischel C. N. Belderrain

Logistics 2026, 10(1), 4; https://doi.org/10.3390/logistics10010004 - 25 Dec 2025

Viewed by 506

Abstract

Background: Despite advances in monitoring and forecasting systems, natural disasters continue to cause significant human losses. During the response phase, fast decisions are required to allocate limited resources, particularly rescue helicopters, which play a key role in reaching inaccessible areas. However, helicopter [...] Read more.

Background: Despite advances in monitoring and forecasting systems, natural disasters continue to cause significant human losses. During the response phase, fast decisions are required to allocate limited resources, particularly rescue helicopters, which play a key role in reaching inaccessible areas. However, helicopter allocation involves trade-offs between efficiency and operational safety under uncertain conditions. Methods: This study proposes a decision-support methodology based on Multi-Criteria Decision Analysis (MCDA) for allocating rescue helicopters during disaster response. The approach integrates Value-Focused Thinking (VFT) and Multi-Attribute Value Theory (MAVT) to structure objectives, assign weights, and evaluate alternatives using criteria related to mission safety, response time, and expected number of rescued victims. The method is illustrated through a simulated flood response scenario in a Brazilian regional context. Results: The results show that the model allows decision-makers to compare allocation scenarios and to make explicit the trade-offs between operational efficiency and safety. The application indicates that small reductions in efficiency may lead to relevant gains in operational safety, particularly under adverse weather conditions. Conclusions: The proposed approach provides a transparent and traceable structure for supporting helicopter allocation decisions during disaster response. It contributes to more consistent decision-making in critical operations, especially in contexts characterized by uncertainty and time pressure. Full article

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

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1 pages, 122 KB

Open AccessCorrection

Correction: Alaydi et al. The Role of Air Traffic Controllers’ Mindfulness in Enhancing Air Traffic Safety: JDR Theory in the Saudi Arabian Aviation Context. Logistics 2025, 9, 117

by Bader Alaydi, Siew-Imm Ng and Xin-Jean Lim

Logistics 2026, 10(1), 3; https://doi.org/10.3390/logistics10010003 - 22 Dec 2025

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Abstract

The authors would like to make the following corrections to the published paper [...] Full article

26 pages, 626 KB

Open AccessArticle

Beyond Average Effects: Performance-Dependent Logistics Challenges in Emerging Asian Transportation Trade

by Audai Al-Majali, Ahmad Alsarayreh and Huthaifa Alqaralleh

Logistics 2026, 10(1), 2; https://doi.org/10.3390/logistics10010002 - 22 Dec 2025

Cited by 1 | Viewed by 589

Abstract

Background: Emerging Asian economies face a critical policy dilemma: macroeconomic and sustainability factors affect high-performing and struggling logistics exporters in fundamentally different ways. Methods: Analysing transportation trade data from China, South Korea, India, Vietnam, Malaysia, and Indonesia (2000–2023) using Panel Quantile [...] Read more.

Background: Emerging Asian economies face a critical policy dilemma: macroeconomic and sustainability factors affect high-performing and struggling logistics exporters in fundamentally different ways. Methods: Analysing transportation trade data from China, South Korea, India, Vietnam, Malaysia, and Indonesia (2000–2023) using Panel Quantile Autoregressive Distributed Lag (P-QARDL) methodology, this study investigates asymmetric relationships between macroeconomic indicators (real GDP, inflation, real effective exchange rate), sustainability variables (energy intensity, energy prices, CO₂ emissions), and logistics performance measured through transportation trade flows. Results: The results reveal striking performance-dependent heterogeneities that conventional approaches overlook. Economic growth provides 55% larger benefits to high performers (0.345) versus strugglers (0.222), confirming scale advantages. Energy constraints intensify for successful exporters, with energy intensity penalties 12% larger in upper quantiles. CO₂ emissions correlate positively with logistics performance, with effects doubling from lower (0.142) to upper quantiles (0.341), highlighting an intensifying sustainability trade-off. Error correction operates 39% faster during high-performance periods. Conclusions: These asymmetric relationships challenge one-size-fits-all policies, necessitating targeted energy efficiency interventions for high performers and growth-enabling support for struggling exporters. Full article

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27 pages, 2179 KB

Open AccessReview

The Nearshoring Loop: A Review of Triggers, Location Choice, and Captured Outcomes

by Alejandro Platas-López and Oliverio Cruz-Mejía

Logistics 2026, 10(1), 1; https://doi.org/10.3390/logistics10010001 - 22 Dec 2025

Viewed by 1252

Abstract

Background: Nearshoring has risen after shocks and policy shifts. We synthesize evidence in a compact loop linking triggers (trade frictions, supply-chain risk, new agreements) to location choices mediated by multidimensional proximity (geographic, institutional, organizational, social, cognitive, functional) to components (manufacturing footprint, Foreign Direct [...] Read more.

Background: Nearshoring has risen after shocks and policy shifts. We synthesize evidence in a compact loop linking triggers (trade frictions, supply-chain risk, new agreements) to location choices mediated by multidimensional proximity (geographic, institutional, organizational, social, cognitive, functional) to components (manufacturing footprint, Foreign Direct Investment (FDI), employment) and outcomes (spillovers, productivity, innovation) conditioned by absorptive capacity and institutions. Methods: We conducted a literature review using major bibliographic databases. A staged screening pipeline (deduplication, pre-eligibility, and title–abstract screening) preceded full-text coding aligned with the review framework (triggers, proximity, components, outcomes, mediators). Studies were appraised with a five-criterion checklist, and themes were consolidated with basic bibliometric checks. Results: Evidence is North Atlantic and manufacturing-centric. Supply-chain disruptions dominate triggers; non-geographic proximity strongly moderates relocation. FDI anchors ecosystems, while employment effects are lagged and compositional. Strong capability and policy mixes yield broader spillovers; otherwise, benefits remain enclave-like. Sustainability and transformative outcomes are rarely assessed. Conclusions: The loop clarifies feedback from outcomes to future siting. Firms should build proximity beyond geography and pair early FDI with supplier and skills upgrading; policymakers should align instruments to governance, capability formation, and logistics. Research should expand Global South coverage and integrate environmental and inclusion metrics. Full article

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Logistics, Volume 10, Issue 1 (January 2026) – 24 articles

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