Logistics

20 pages, 10078 KB

Open AccessArticle

Strategic Optimization of Agricultural Supply Chains Based on the Integration of GIS and Multimodal Infrastructure Capacity in Kazakhstan

by Aisha Mussabekova, Vladislav Galyandin, Saltanat Massakova and Gulnara Ayazbayeva

Logistics 2026, 10(8), 189; https://doi.org/10.3390/logistics10080189 - 17 Aug 2026

Abstract

Background: Managing agrologistics supply chains under infrastructure scarcity requires integrative, spatially explicit decision-support tools. This study develops a macro-level digital twin of the multimodal agricultural supply chain in Kazakhstan’s Almaty region to optimize freight allocation and guide strategic investment planning. Methods: [...] Read more.

Background: Managing agrologistics supply chains under infrastructure scarcity requires integrative, spatially explicit decision-support tools. This study develops a macro-level digital twin of the multimodal agricultural supply chain in Kazakhstan’s Almaty region to optimize freight allocation and guide strategic investment planning. Methods: Our methodology integrates Earth observation data (ESA WorldCover 10 m) with a large-scale multimodal road–rail graph network (1.39 million nodes) to identify 135 crop production clusters. Using linear programming in MATLAB, we optimize the regional distribution of 322.2 thousand tons of seasonal maize, wheat, and soybeans while localizing new storage silos using Green Field Analysis. Results: The baseline simulation reveals a critical storage capacity deficit, yielding a Capacity Coverage Ratio of only 23.8%. However, implementing optimal multimodal rail-road routing mathematically reduces the Logistics Cost Index from 8,642,195 to 4,716,175 units, achieving overall cost savings of 45.4%. Conclusions: The proposed digital twin and its performance metrics provide a scientifically grounded, data-driven toolkit for public–private partnerships, ensuring robust infrastructure investment localization and facilitating the transition toward the Agriculture 4.0 paradigm. 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, 2nd Edition)

► Show Figures

Figure 1

24 pages, 654 KB

Open AccessArticle

Supply Chain Resilience and Total Factor Productivity: Evidence from Listed Manufacturing Firms

by Yue Zhao and Jingfeng Dong

Logistics 2026, 10(8), 188; https://doi.org/10.3390/logistics10080188 - 13 Aug 2026

Abstract

Background: Manufacturing productivity increasingly depends on reliable interorganizational flows, yet supply chain disruptions can interrupt materials, information, finance, and efficient use of productive inputs. Although supply chain resilience is widely treated as a continuity capability, its relationship with firm-level total factor productivity remains [...] Read more.

Background: Manufacturing productivity increasingly depends on reliable interorganizational flows, yet supply chain disruptions can interrupt materials, information, finance, and efficient use of productive inputs. Although supply chain resilience is widely treated as a continuity capability, its relationship with firm-level total factor productivity remains insufficiently established. Methods: This study uses 22,509 firm-year observations for Chinese A-share listed manufacturing firms from 2009 to 2024. An entropy-weighted resilience index is constructed from adaptability, resistance, recovery capacity, human capital, institutional support. Firm-level revenue productivity is estimated using the Olley Pakes method, and the analysis employs fixed effects regressions, robustness tests, a two-step selection correction test, mechanism regressions, heterogeneity analysis, and dimension-specific tests. Results: Supply chain resilience is positively associated with firm-level total factor productivity, and this association remains robust to alternative productivity and resilience measures, sample restrictions, industry-by-year fixed effects, and selection correction. Resilience is also associated with lower financing constraints and investment inefficiency. The association is stronger for firms with higher managerial incentives, high-technology industries, and competitive markets, while recovery capacity is negatively associated with contemporaneous productivity. Conclusions: Supply chain resilience supports efficient resource utilization, but its productivity value depends on capability composition, timing, and efficient resilience investment rather than maximizing resilience resources. Full article

► Show Figures

Graphical abstract

19 pages, 609 KB

Open AccessArticle

Factors Driving IoT Adoption and Its Impact on Supply Chain Performance in Ekurhuleni Public Health Facilities

by Joash Mageto, Makgosi Tlholwe and Hugo van den Berg

Logistics 2026, 10(8), 187; https://doi.org/10.3390/logistics10080187 - 12 Aug 2026

Abstract

Background: Population growth and rising healthcare demand increasingly strain public healthcare in emerging economies. Further, poor supply visibility, frequent stock-outs, and medicine expiry weaken healthcare supply chain performance (SCP) and patient outcomes. In response, the Internet of Things (IoT) offers promising ways to [...] Read more.

Background: Population growth and rising healthcare demand increasingly strain public healthcare in emerging economies. Further, poor supply visibility, frequent stock-outs, and medicine expiry weaken healthcare supply chain performance (SCP) and patient outcomes. In response, the Internet of Things (IoT) offers promising ways to improve the monitoring, distribution, and management of medical supplies. However, empirical evidence on how technological, organisational, and environmental factors influence IoT adoption and its effect on public healthcare SCP remains limited. This study examined factors influencing IoT adoption and its effect on supply chain performance in public healthcare facilities. Methods: Data were collected from 102 respondents drawn from 90 public healthcare facilities. Results: Factors associated with technological factors have the most significant influence on the adoption of IoT in public healthcare SCs. The lack of significance of organisational and environmental factors may be attributed to the early stage of IoT adoption in public healthcare SCs. Conclusions: This study contributes to the theoretical understanding of IoT adoption by highlighting the dominant role of technological factors over organisational and environmental considerations in resource-constrained public healthcare settings. From a practical perspective, the findings encourage policymakers and healthcare managers to prioritise investments in relevant ICT infrastructure to accelerate IoT adoption. Full article

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

► Show Figures

Figure 1

24 pages, 2100 KB

Open AccessArticle

Barriers to the Adoption of Industry 5.0 in the Downstream Oil and Gas Value Chain: A Fuzzy ISM-MICMAC Analysis

by Jugendra Singh, Amit Kumar Gupta and Imlak Shaikh

Logistics 2026, 10(8), 186; https://doi.org/10.3390/logistics10080186 - 12 Aug 2026

Abstract

Background: The downstream oil and gas processing industry faces substantial environmental, regulatory, safety, and operational risks. Advanced technologies can reduce these risks and improve productivity, compliance, sustainability, and worker safety. However, despite adopting AI, analytics, machine learning, and IoT, Indian firms continue to [...] Read more.

Background: The downstream oil and gas processing industry faces substantial environmental, regulatory, safety, and operational risks. Advanced technologies can reduce these risks and improve productivity, compliance, sustainability, and worker safety. However, despite adopting AI, analytics, machine learning, and IoT, Indian firms continue to lag behind their global counterparts, and Industry 5.0 adoption in this sector remains underexplored. Methods: This study examines Industry 5.0 adoption barriers using data from an Indian public-sector oil and gas organisation. Guided by the Resource-Based View and supply chain integration perspective, it applies a mixed-methods design combining a literature review, focus group discussion, Delphi analysis, and Fuzzy ISM–MICMAC. Forty-two barriers were identified and reduced to eight critical barriers. Results: Low technological maturity and lack of value-chain integration emerged as the principal driving barriers, influencing implementation failure, organisational technological readiness, and management commitment, which subsequently affect data quality. Geopolitics emerged as an autonomous barrier with both positive and adverse effects. Conclusions: This study develops a sector-specific framework explaining the hierarchical relationships among technological, organisational, sociotechnical, and value-chain barriers. It extends Industry 5.0 research in hazardous, human–technology-dependent operations and offers practical guidance for a human-centric, sustainable, and resilient transformation. Full article

(This article belongs to the Special Issue Supply Chain 4.0: Lean, Agile, Green Practices)

► Show Figures

Figure 1

15 pages, 1541 KB

Open AccessArticle

Information Flow and Logistics Coordination Challenges in Saudi Arabian Construction Projects: A SCOR-Based Qualitative Investigation

by Ruaa BinSaddig, Abdulla Subhi Ruzieh, Bahaa Subhi Razia, Reem Khamis and Bahaa Subhi Awwad

Logistics 2026, 10(8), 185; https://doi.org/10.3390/logistics10080185 - 11 Aug 2026

Abstract

Background: This study investigates information-flow and logistics coordination challenges in Saudi Arabian construction projects within the context of ongoing national infrastructure developments, severe climatic conditions, and evolving labor regulations. Methods: Utilizing the Supply Chain Operations Reference (SCOR) framework, semi-structured interviews were [...] Read more.

Background: This study investigates information-flow and logistics coordination challenges in Saudi Arabian construction projects within the context of ongoing national infrastructure developments, severe climatic conditions, and evolving labor regulations. Methods: Utilizing the Supply Chain Operations Reference (SCOR) framework, semi-structured interviews were conducted with 29 construction professionals spanning site-level engineers, logistics managers, project executives, and material suppliers over an extended 20-month monitoring period (March 2024–October 2025). Data were analyzed using thematic coding and mapped across the SCOR domains. Results: The findings reveal that logistics vulnerabilities stem predominantly from systemic information-sharing deficiencies, fragmented digital workflows, and weak stakeholder integration rather than standalone material constraints. Operational disruptions across Plan, Source, Make, Deliver, and Return are compounded by region-specific barriers including extreme thermal stress, migrant labor turnover, and high administrative fees for reverse logistics. Conclusions: To address these challenges, the study formulates a tiered, context-adjusted deployment framework for digital integration (BIM, IoT, and real-time tracking) tailored for both large infrastructure schemes and small-to-medium contractors. Staged implementation pathways and policy recommendations are provided to enhance supply chain resilience. Full article

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

► Show Figures

Figure 1

34 pages, 2036 KB

Open AccessReview

A Scoping Review on Digital Technology-Enabled Food Supply Chain Traceability for Food Fraud Prevention

by Evripidis P. Kechagias, Nikolaos A. Panayiotou, Sotiris P. Gayialis and Georgios A. Papadopoulos

Logistics 2026, 10(8), 184; https://doi.org/10.3390/logistics10080184 - 10 Aug 2026

Abstract

Background: Global food supply chains have become increasingly complex, sourcing ingredients from multiple countries and intermediaries, creating opportunities for fraud, adulteration, and mislabeling that may compromise consumer safety and market confidence. Digital traceability technologies have been suggested as potential countermeasures, but there [...] Read more.

Background: Global food supply chains have become increasingly complex, sourcing ingredients from multiple countries and intermediaries, creating opportunities for fraud, adulteration, and mislabeling that may compromise consumer safety and market confidence. Digital traceability technologies have been suggested as potential countermeasures, but there is little concrete evidence of their impact in practice. This research presents an assessment of the maturity and effectiveness of these technologies, identifies implementation barriers and security/privacy concerns, and maps research gaps/future directions. Methods: A scoping review of 64 studies from 2023 to 2026 with data extracted from the Scopus and IEEE databases was carried out according to the PRISMA-ScR guidelines and a structured pre-specified data extraction framework. Results: The field is empirically immature, with none of the reviewed solutions offering a provably correct, adversarially tested solution to the oracle problem. There is a lack of alignment between on-chain immutability and GDPR right to erasure and an unequal burden of implementation costs imposed on smallholder producers. Conclusions: A gradual implementation of traceability regulations, along with cost-of-ownership models and harmonized certification measures that do not disadvantage smaller producers are proposed. Finally, field trials, adversarial testing and reporting results in a standardized format, capturing detection performance and implementation costs, are essential. Full article

(This article belongs to the Special Issue Digital Traceability in Agri-Food Supply Chains: Technologies, Challenges, and Future Directions)

► Show Figures

Figure 1

26 pages, 1402 KB

Open AccessArticle

Predictive Maintenance in Logistics Fleets: A Comparative Evaluation of Random Forest, XGBoost, and Logistic Regression Using Operational and Technical Indicators

by Małgorzata Grzelak, Daniela Voicu, Ramona-Monica Stoica and Radu Vilau

Logistics 2026, 10(8), 183; https://doi.org/10.3390/logistics10080183 - 6 Aug 2026

Abstract

Background: Predictive maintenance (PdM) is increasingly recognized as essential for reducing fleet downtime and maintenance costs, yet the existing literature on transport and logistics fleets relies predominantly on traditional or single-model approaches, with ensemble methods such as random forest and gradient boosting [...] Read more.

Background: Predictive maintenance (PdM) is increasingly recognized as essential for reducing fleet downtime and maintenance costs, yet the existing literature on transport and logistics fleets relies predominantly on traditional or single-model approaches, with ensemble methods such as random forest and gradient boosting remaining comparatively underexplored. Methods: This study develops and compares three classification algorithms—logistic regression, random forest and XGBoost—for predicting vehicle maintenance needs. Each classifier was first fitted once on a 70:30 train–test split (35,000/15,000 observations) to support interpretation of coefficients, predictor importance, and ROC curves, using precision, recall, and ROC-AUC. Performance and model ranking were then confirmed for robustness using 5-fold stratified cross-validation with formal significance testing. Results: Reported issues and service history emerged as the dominant predictors of maintenance needs. Random forest and XGBoost achieved comparable predictive performance under 5-fold cross-validation (mean AUC-ROC of 0.8546 and 0.8528, respectively), with the difference between them not statistically significant; both clearly outperformed logistic regression (AUC-ROC 0.8215). Conclusions: By integrating operational and technical data within a validated, comparative machine learning framework, the study provides a practical basis for decision-support systems enabling the reduction of unnecessary interventions, minimizing downtime, and improving fleet cost efficiency and reliability. Full article

► Show Figures

Figure 1

36 pages, 2372 KB

Open AccessArticle

A Hierarchical Two-Level Adaptive Allocation Framework for Multi-Location Inbound Logistics Under Operational Constraints

by Mohammad Hori and Bernd Noche

Logistics 2026, 10(8), 182; https://doi.org/10.3390/logistics10080182 - 6 Aug 2026

Abstract

Background: The allocation of non-divisible inbound deliveries across multiple warehouses requires the simultaneous consideration of capacity constraints, category-specific restrictions, workload balance, and long-term allocation consistency. Methods: This study proposes a hierarchical two-level allocation framework combining strategic category-rotation policies, normalized marginal scoring, [...] Read more.

Background: The allocation of non-divisible inbound deliveries across multiple warehouses requires the simultaneous consideration of capacity constraints, category-specific restrictions, workload balance, and long-term allocation consistency. Methods: This study proposes a hierarchical two-level allocation framework combining strategic category-rotation policies, normalized marginal scoring, and signed historical feedback. The algorithm is executed once per day to generate warehouse assignments for the following operational day. Historical correction is based on a rolling window covering the preceding 30 daily planning periods. Results: The framework was evaluated using daily simulation instances ranging from 100 to 1500 pallets, with an average of approximately 130 lots per pallet. Across all evaluated instances, the complete allocation procedure was completed in less than 5 s on the specified test system. The results indicate balanced warehouse utilization, progressive reductions in category–location imbalance, stable historical correction, and preservation of hard operational constraints. Conclusions: The framework provides an interpretable and computationally efficient approach for next-day inbound allocation. By combining explicit feasibility filtering, strategic policy signals, and a 30-day historical correction mechanism, it supports both short-term operational decisions and longer-term allocation balance. Full article

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

► Show Figures

Figure 1

32 pages, 2177 KB

Open AccessSystematic Review

Theorizing Blockchain Technology for Supply Chain Management Practices: A Systematic Literature Review

by Adeeb Alshakhs and Dawn Gregg

Logistics 2026, 10(8), 181; https://doi.org/10.3390/logistics10080181 - 6 Aug 2026

Abstract

Background: Blockchain adoption in supply chain management has attracted growing academic and practitioner attention; yet the impact varies significantly by implementation context, and the knowledge of the conditions driving this variation remain limited. Methods: This study conducts a systematic review of [...] Read more.

Background: Blockchain adoption in supply chain management has attracted growing academic and practitioner attention; yet the impact varies significantly by implementation context, and the knowledge of the conditions driving this variation remain limited. Methods: This study conducts a systematic review of 112 papers to systematically synthesize how blockchain integration affects supply chain management practices (SCMPs), including upstream practices (e.g., supplier partnerships), downstream practices (e.g., customer relationships), and practices spanning both sides of the supply chain (e.g., information sharing and information quality). Results: The review finds that the benefit of blockchain adoption depends on a firm’s supply chain position, cost structures, and market conditions. Two theoretical perspectives are used to interpret these findings: the resource-based view, which viewed blockchain as a capability for integrating processes and transactions across organizations, and the practice-based view, which viewed blockchain as an imitable activity requiring context-specific deployment conditions. Fourteen propositions are developed to guide future research. Conclusions: This review provides practitioner guidance for evaluating when and how blockchain is likely to generate values across different SCMPs. Also, it provides researchers with a theory-grounding agenda for testing the proposed propositions empirically. Full article

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

► Show Figures

Figure 1

23 pages, 986 KB

Open AccessReview

Factors Influencing Consumer Adoption of Smart Parcel Lockers: A Scoping Review

by Lujain Hussein Alamoudi and Mohammad Asif Salam

Logistics 2026, 10(8), 180; https://doi.org/10.3390/logistics10080180 - 6 Aug 2026

Abstract

Background: Smart Parcel Lockers (SPLs) have emerged as an important solution for improving last-mile delivery (LMD) efficiency in response to the rapid growth in e-commerce and increasing consumer demand for flexible delivery options. Despite growing research interest, the factors influencing consumer adoption [...] Read more.

Background: Smart Parcel Lockers (SPLs) have emerged as an important solution for improving last-mile delivery (LMD) efficiency in response to the rapid growth in e-commerce and increasing consumer demand for flexible delivery options. Despite growing research interest, the factors influencing consumer adoption of SPLs remain fragmented across different theoretical and geographical contexts. This scoping review aims to synthesize the existing literature and identify the key factors influencing consumer adoption of SPLs. Methods: A structured literature search using PRISMA Extension for Scoping Reviews (PRISMA-ScR) guidelines was conducted to identify peer-reviewed studies published between 2014 and 2024. Following the screening and selection process, 38 studies were included in the scoping synthesis. Results: The findings show that convenience, security, service reliability, and perceived value are the most frequently reported factors shaping SPL adoption. The review also shows that the TAM, DOI, and UTAUT are the most commonly applied theoretical frameworks. The studies were also methodologically dominated by quantitative survey-based studies and geographically concentrated mainly in Asian markets. Conclusions: Overall, the review identifies the main drivers and barriers of SPL adoption and provides guidance for future research and practical implementation. Full article

(This article belongs to the Section Last Mile, E-Commerce and Sales Logistics)

► Show Figures

Figure 1

16 pages, 2649 KB

Open AccessArticle

A Spatially Constrained PCA–MST-Based Clustering Model for Railway Freight Management in Kazakhstan

by Aizhan Mukhametzhanova, Marat Baiseitov, Aliya Izbairova, Dariga Kushtayeva and Gabit Bakyt

Logistics 2026, 10(8), 179; https://doi.org/10.3390/logistics10080179 - 5 Aug 2026

Abstract

Background: Kazakhstan’s railway network exhibits substantial spatial heterogeneity, limiting the effectiveness of uniform freight management strategies and necessitating differentiated analytical approaches to regional transport planning. This study aims to develop a spatially constrained clustering model for railway freight management based on the [...] Read more.

Background: Kazakhstan’s railway network exhibits substantial spatial heterogeneity, limiting the effectiveness of uniform freight management strategies and necessitating differentiated analytical approaches to regional transport planning. This study aims to develop a spatially constrained clustering model for railway freight management based on the economic, infrastructural, and operational characteristics of the regions served by KTZh—Freight Transportation LLP. Methods: The proposed methodology integrates principal component analysis (PCA) with a minimum spanning tree (MST) algorithm under railway connectivity constraints. A dataset comprising 20 standardized indicators for 17 regions of Kazakhstan was analyzed. Results: PCA reduced the original variable space to five principal components, explaining 77.9% of the cumulative variance. Cluster validity was confirmed using the Elbow, Silhouette, and Calinski–Harabasz indices, resulting in the identification of six spatially connected transport clusters with distinct functional profiles. The clusters revealed significant regional differences in freight generation, logistics infrastructure, transit potential, and investment characteristics. Conclusions: The proposed framework provides an evidence-based analytical tool for railway freight management, infrastructure planning, and the prioritization of regional development strategies while accounting for spatial connectivity constraints. Full article

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

► Show Figures

Figure 1

23 pages, 2462 KB

Open AccessArticle

A Hybrid Linear Programming and Heuristic Approach for Production Scheduling—A Case Study in Automotive Part Manufacturing

by Peter Kačmáry and Martin Straka

Logistics 2026, 10(8), 178; https://doi.org/10.3390/logistics10080178 - 5 Aug 2026

Abstract

Background: Reducing production time while making efficient use of resources is a key challenge in modern manufacturing, particularly in environments with high variability in specific components for the automotive industry. Methods: This paper presents a hybrid approach to production scheduling that combines linear [...] Read more.

Background: Reducing production time while making efficient use of resources is a key challenge in modern manufacturing, particularly in environments with high variability in specific components for the automotive industry. Methods: This paper presents a hybrid approach to production scheduling that combines linear programming (LP) principles with heuristic decision-making. A structured literature review is conducted to compare exact methods, heuristics, and metaheuristics in terms of their applicability and limitations. Based on this analysis, a hybrid scheduling method is proposed, where LP defines the objective function and constraints, while heuristic rules enable efficient assignment of operations to workstations under capacity limitations. The approach is validated through a case study involving over 900 product variants in an automotive part production system characterized by interchangeable workstations. The proposed heuristic algorithm was tested in terms of real company daily scheduling performance and compared with former scheduling performance. Results: The results show that the proposed approach achieves better solution quality with significantly lower computational effort, while also improving time utilization and production efficiency. Conclusions: The hybrid LP-heuristic approach provides a computationally efficient and practical tool for real-time production scheduling in high-variability manufacturing environments, effectively balancing solution quality and sub-minute execution speed under strict capacity constraints. Full article

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

► Show Figures

Figure 1

30 pages, 1023 KB

Open AccessArticle

A DLT- and ZKP-Enabled Framework for Privacy-Preserving Digital Product Passports in Maritime Container Logistics

by Samiullah Khairy and Mariano Falcitelli

Logistics 2026, 10(8), 177; https://doi.org/10.3390/logistics10080177 - 5 Aug 2026

Abstract

Background: Maritime container shipping carries over 80% of global trade, yet compliance verification creates a confidentiality–verifiability conflict: carriers treat telemetry as commercially sensitive, while regulators, insurers, and port authorities require verifiable proof that cargo remained within specification. The EU Ecodesign for Sustainable Products [...] Read more.

Background: Maritime container shipping carries over 80% of global trade, yet compliance verification creates a confidentiality–verifiability conflict: carriers treat telemetry as commercially sensitive, while regulators, insurers, and port authorities require verifiable proof that cargo remained within specification. The EU Ecodesign for Sustainable Products Regulation (ESPR) mandates Digital Product Passports (DPPs), but no standardised DPP architecture exists for the multi-stakeholder maritime domain. Methods: We present Ocean DPP, a blockchain-anchored platform combining GS1 EPCIS 2.0, oneM2M, IOTA, and Groth16 zero-knowledge proofs (ZKPs), letting stakeholders verify compliance predicates without revealing raw sensor values; Merkle-tree batching reduces anchoring costs. We evaluate it in 16 experiments on a single-host testbed using synthetic workloads and a local IOTA network. Results: The platform achieved 95th-percentile latency of 48 ms without ZKP and 500 ms with proof generation, throughput of 7 events/s per host, 304 ms mean proof generation and 9.8 ms verification, 100% EPCIS 2.0 compliance, and zero permanent message loss across four failure-injection scenarios; horizontal scaling reduced the median latency by 37%. Conclusions: To the best of our knowledge, Ocean DPP is the first implemented, quantitatively evaluated platform integrating EPCIS 2.0, oneM2M, IOTA, and Groth16 ZKPs for privacy-preserving maritime DPPs; broader multi-host and public-network validation remains for future work. Full article

(This article belongs to the Section Maritime and Transport Logistics)

► Show Figures

Figure 1

16 pages, 17134 KB

Open AccessArticle

An Agent-Based Simulation of Truck Fleet Operations to Supply a Biorefinery Year-Round

by Jonathan P. Resop and John S. Cundiff

Logistics 2026, 10(8), 176; https://doi.org/10.3390/logistics10080176 - 3 Aug 2026

Abstract

Background: The cost to operate a truck fleet to haul feedstock from satellite storage locations (SSLs) to a biorefinery is typically more than 30% of the logistics cost. The use of central control can minimize truck wait times and maximize truck productivity (Mg [...] Read more.

Background: The cost to operate a truck fleet to haul feedstock from satellite storage locations (SSLs) to a biorefinery is typically more than 30% of the logistics cost. The use of central control can minimize truck wait times and maximize truck productivity (Mg hauled per day). Methods: An agent-based model, developed in Python 3.12.7, simulated truck hauling operations and SSL loading operations at a 1 min time step for each day in a six-day workweek over a 48-week hauling season for a theoretical biorefinery centered in Gretna, VA, USA. Several truck and SSL operational parameters included stochastic components to allow for random variability (e.g., drive speed and loading rate). Results: The theoretical minimum fleet, assuming no unproductive time, was 6 trucks. Assuming realistic delays, a fleet of 13 trucks could supply the biorefinery with one unloading operation, but unproductive time was over 50% of the hauling day. Conclusions: By adding a second unloading operation at the biorefinery, average truck idle time was reduced, and a fleet of 8 trucks could achieve the same average truck productivity with total unproductive time reduced to about 20% of the total truck fleet operating time. Full article

► Show Figures

Figure 1

26 pages, 309 KB

Open AccessFeature PaperArticle

Sustainable and Resilient Production–Distribution Planning Under Stochastic Demand: A Carbon-Aware MILP Framework with Lost Sales and Rolling Horizon Replanning

by Mohammed Machkour, Abdellah El Barkany and Bilal Harras

Logistics 2026, 10(8), 175; https://doi.org/10.3390/logistics10080175 - 3 Aug 2026

Abstract

Background: Manufacturing supply chains must increasingly coordinate cost, environmental impact, and service continuity under demand uncertainty and limited capacity. Methods: This study develops a stochastic mixed-integer linear programming framework for carbon-aware production–distribution planning in an automotive supply chain. The model jointly [...] Read more.

Background: Manufacturing supply chains must increasingly coordinate cost, environmental impact, and service continuity under demand uncertainty and limited capacity. Methods: This study develops a stochastic mixed-integer linear programming framework for carbon-aware production–distribution planning in an automotive supply chain. The model jointly optimizes production quantities, inventory levels, shipments, truck usage, and lost sales over a multi-period horizon. Demand uncertainty is represented through scenarios, while production- and transportation-related emissions are monetized using an internal carbon price. Lost-sales penalties capture service degradation when demand cannot be fulfilled by the focal plant, and a rolling-horizon analysis evaluates planning responsiveness as demand information is updated. The framework is applied to an industrially inspired, capacity-constrained automotive case with multiple products, production lines, destinations, and demand scenarios. Computational experiments assess carbon pricing, lost-sales penalties, demand volatility, deterministic versus stochastic planning, and rolling-horizon replanning. Results: Results show that carbon pricing mainly acts as an economic valuation mechanism under the studied fixed-structure configuration, whereas lost-sales penalties strongly influence service performance. Demand volatility increases unmet demand, and lower emissions may reflect lower fulfilled demand rather than improved efficiency. Conclusions: The study provides a decision-support framework for evaluating cost–carbon–service trade-offs under stochastic demand while acknowledging single-plant and fixed-routing limitations. Full article

28 pages, 2784 KB

Open AccessArticle

Unlocking Lean Potential in SME Logistics and Supply Chains: A Study on Commitment, Tools, and Outcomes Through a Systematic Review and Survey Analysis

by Abishae Noel, László Buics and Eszter Sós

Logistics 2026, 10(8), 174; https://doi.org/10.3390/logistics10080174 - 3 Aug 2026

Abstract

Background: Lean management is widely recognized as an effective approach to process optimization. However, its implementation in Small and Medium Enterprises (SMEs), particularly in logistics and supply chain contexts, remains challenging. Resource constraints and inconsistent organizational commitment often hinder effective implementation. This [...] Read more.

Background: Lean management is widely recognized as an effective approach to process optimization. However, its implementation in Small and Medium Enterprises (SMEs), particularly in logistics and supply chain contexts, remains challenging. Resource constraints and inconsistent organizational commitment often hinder effective implementation. This study examines Lean adoption, leadership commitment, and implementation outcomes in SME logistics and supply chains. Methods: A mixed-methods design was used, combining a systematic literature review guided by PRISMA and PEO frameworks, followed by a structured survey. A total of 780 valid responses from SME professionals were analyzed using descriptive statistics, correlation, regression, and reliability assessment. Results: Top and middle management commitment was identified as a significant predictor of perceived Lean implementation success. A measurable gap was observed between respondents’ knowledge of Lean methods and their practical application, emphasizing the importance of strategic alignment, organizational culture, and employee engagement. Conclusions: The findings provide practical implications for strengthening Lean implementation in SMEs through enhanced managerial commitment and employee involvement. The study is limited by its focus on SMEs from a single country and the literature retrieved from one bibliographic database. Future research should include broader geographical coverage, multiple databases, and objective organizational performance indicators. Full article

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

► Show Figures

Figure 1

28 pages, 592 KB

Open AccessArticle

Optimizing Last-Mile Delivery Solutions: An Investigation into User Behavioral Intention to Use Smart Parcel Lockers in Saudi Arabia

by Lujain Hussein Alamoudi and Mohammad Asif Salam

Logistics 2026, 10(8), 173; https://doi.org/10.3390/logistics10080173 - 1 Aug 2026

Abstract

Background: The growth of e-commerce has intensified last-mile delivery challenges, including failed deliveries, delivery-time uncertainty, and pressure on urban logistics. Smart parcel lockers (SPLs) offer a technology-enabled out-of-home delivery solution, yet limited evidence explains consumer adoption in Saudi Arabia. This study examines [...] Read more.

Background: The growth of e-commerce has intensified last-mile delivery challenges, including failed deliveries, delivery-time uncertainty, and pressure on urban logistics. Smart parcel lockers (SPLs) offer a technology-enabled out-of-home delivery solution, yet limited evidence explains consumer adoption in Saudi Arabia. This study examines which factors motivate Saudi consumers to adopt SPLs, how trust shapes adoption intention, and whether perceived risk affects intention, using an extended UTAUT2 framework. Methods: Data were collected through an online self-administered questionnaire from 415 residents in Saudi Arabia, and the model was analyzed using partial least squares structural equation modelling (PLS-SEM). Results: Performance expectancy was the strongest determinant of behavioral intention. Effort expectancy, social influence, trust, facilitating conditions, and hedonic motivation also had significant positive effects, whereas price value and perceived risk did not directly influence intention. Conclusions: The study contributes to SPL adoption literature by validating an extended UTAUT2 model in an underexamined Saudi context and highlighting the role of trust in technology-enabled LMD acceptance. Full article

(This article belongs to the Section Last Mile, E-Commerce and Sales Logistics)

► Show Figures

Figure 1

30 pages, 2034 KB

Open AccessArticle

Financial and Market Performance-Driven TQM: The Mediating Roles of Supply Chain Resilience and Corporate Social Performance

by Mahmoud Abdulhadi Alabdali, Mohammad Asif Salam, Mohammed Abu Jahed and Ummee Kulsum

Logistics 2026, 10(8), 172; https://doi.org/10.3390/logistics10080172 - 31 Jul 2026

Abstract

Total quality management (TQM) is widely regarded as a critical approach for improving firm performance, yet evidence on the mechanisms linking TQM practices to financial and market outcomes remains fragmented, with most prior studies testing only direct effects. This study examines whether supply [...] Read more.

Total quality management (TQM) is widely regarded as a critical approach for improving firm performance, yet evidence on the mechanisms linking TQM practices to financial and market outcomes remains fragmented, with most prior studies testing only direct effects. This study examines whether supply chain resilience (SCR) and corporate social performance (CSP) mediate the relationship between TQM practices and firms’ financial and market performance (FMP). Drawing on the resource-based view and stakeholder theory, a conceptual model was tested using partial least squares structural equation modeling (PLS-SEM) complemented by necessary condition analysis (NCA), based on survey data from 330 firms operating in Saudi Arabia. The results show that TQM practices do not have a significant direct effect on FMP but have strong positive effects on SCR and CSP. SCR and CSP, in turn, significantly predict FMP, and both fully mediate the TQM–FMP relationship (indirect effects: 0.381 via SCR; 0.252 via CSP). The NCA further identifies SCR and CSP as necessary conditions for achieving higher FMP. The findings indicate that the financial and market benefits of TQM are realized through building resilient supply chains and stronger social performance, rather than directly. These results offer managers and policymakers a clearer roadmap for translating TQM investments into sustainable performance outcomes. Full article

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

► Show Figures

Figure 1

40 pages, 2160 KB

Open AccessArticle

Maturity Model for Authorized Supply Chains

by Pablo Emilio Mora Lozano and Jairo R. Montoya-Torres

Logistics 2026, 10(8), 171; https://doi.org/10.3390/logistics10080171 - 29 Jul 2026

Abstract

Background: The Authorized Economic Operator (AEO) status has become the “gold standard” for supply chain security and trade facilitation under the WCO SAFE Framework. Nevertheless, contemporary certification remain largely limited to binary compliance with minimum requirements, restricting deeper strategic evaluation of security [...] Read more.

Background: The Authorized Economic Operator (AEO) status has become the “gold standard” for supply chain security and trade facilitation under the WCO SAFE Framework. Nevertheless, contemporary certification remain largely limited to binary compliance with minimum requirements, restricting deeper strategic evaluation of security management; Methods: This article develops a Maturity Model for Authorized Supply Chains (MMASC), categorizing operators into five evolutionary levels across eight critical dimensions—Leadership, Risk Management, Collaboration and External Partnership, Access Control and Physical Security, Supply Chain Visibility and Protection, Cybersecurity, Personnel Security, and Security Culture. The model was validated through a two-round modified Delphi process and a post-Delphi consensus workshop with ten regional experts (Cronbach’s

α = 0.935),

operationalized through a diagnostic engine grounded in Mamdani-type fuzzy logic to reduce subjectivity in qualitative assessments; Results: The framework converts qualitative self-assessment into a crisp 0–100 maturity index, enabling customs administrations and private enterprises to move beyond regulatory compliance while aligning with the 2025 SAFE Framework updates—environmental sustainability, MSME inclusion, and ethical conduct codes; Conclusions: The MMASC provides a basis for a proportional allocation of trade facilitation benefits, such as expedited release, according to an operator’s maturity level, promoting a more resilient, transparent, and sustainable global trade ecosystem. Full article

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

► Show Figures

Figure 1

Journal Description

Logistics

Latest Articles

Journal Menu

Journal Browser

Highly Accessed Articles

Latest Books

E-Mail Alert

News

Topics

Conferences

Special Issues

Further Information

Guidelines

MDPI Initiatives

Follow MDPI