Logistics doi: 10.3390/logistics10100235

Authors: Constantin Cornel Tuduriu Laurențiu Dan Milici

Background: Aircraft turnaround is a finite operational system in which aircraft, passengers, baggage, information, personnel, Ground Service Equipment, and temporal capacity interact under strict safety and time constraints. This study examines how local Operational Disturbances propagate through this architecture and develop into Systemic Instability before an Observable Delay occurs. Methods: The methodology combines structural observation of approximately 150 real turnarounds, Conceptual and Mathematical Modeling, an Operational Dependency Network, and discrete-event simulation. Constructal Flow Dynamics are used to represent disturbance access, propagation resistance, buffer consumption, absorption, and residual capacity. Results: The analysis shows that unlimited exponential propagation is incompatible with a finite turnaround system. Exponential growth provides only a local approximation, whereas logistic dynamics represent the transition from the Invasion Phase to the Consolidation Phase and eventual saturation. The model-generated scenarios reproduce complete absorption below the propagation threshold and increasing residual disturbance after available buffers are exceeded. The framework also identifies an Invisible Time Window in which a Pre-Critical State may be detected. Conclusions: Observable Delay may represent the externally visible manifestation of earlier internal degradation. The proposed framework supports anticipatory operational stabilization, subject to Safety, Security, and human oversight. Statistical calibration and out-of-sample predictive validation remain necessary.

Logistics doi: 10.3390/logistics10100234

Authors: Rytis Engelaitis Aldona Jarašūnienė

Background: Cannibalization, defined as the recovery of serviceable components from one vehicle for use in another, is an underexplored reverse logistics practice in public transport maintenance. This study aims to analyze the role of cannibalization in public transport systems and develop a framework for managing it as a controlled maintenance process. Methods: Scientific literature analysis was conducted to examine the theoretical foundations of cannibalization and reverse logistics. A quantitative case study was then performed using a complete fleet census of 628 buses and trolleybuses operated by JSC “Vilniaus viesasis transportas” (VVT) in Vilnius, Lithuania. Fleet data were systematized according to vehicle age, type, operational status, and End-of-Life/End-of-Use (EOL/EOU) status. Results: The analysis showed that 57.5% of the fleet consists of vehicles aged 6-15 years, while 15.9% are older than 20 years. A total of 73 vehicles were classified as EOL/EOU and identified as potential sources of recoverable components. Based on literature review and fleet analysis, a four-tier maintenance decision framework was developed. Conclusions: The proposed framework provides a structured approach for managing cannibalization within public transport maintenance and may support fleet availability under spare-part shortages. Future research should validate the framework using operational performance indicators.

Logistics doi: 10.3390/logistics10100233

Authors: Justin Neilson Bhaba R. Sarker

Background: Optimal ordering in purchasing garment products for international buying houses has become increasingly complex, particularly when companies manage a variety of products across geographically dispersed national and international locations. Existing studies focus on non-integer problems and do not address objectives that minimize the absolute value of a cost or profit function. Methods: This paper proposes a method to determine optimal order quantities for garment styles while satisfying box constraints and the required demand of the wholesale business. The approach minimizes over- and under-ordering costs by reducing total order quantities and fitting orders to the historical demand distribution of each size in international supply chain operations.Results: The model was applied to a garment company operating under cooperative purchasing agreements with international traders. The approach successfully identified optimal order quantities while accounting for operational constraints, minimum order requirements, and historical demand patterns.Conclusions: The findings demonstrate that the proposed method can effectively support purchasing decisions in international garment supply chains. By minimizing over- and under-ordering costs while meeting demand requirements, the model provides a practical framework for improving order allocation and inventory management. The results are encouraging and indicate the usefulness of the approach to international buying house operations.

Logistics doi: 10.3390/logistics10100232

Authors: Luay Jum’a

Background: Supply chain transparency (SCT) is increasingly important for sustainability, yet the organizational and contextual factors shaping SCT and its sustainability outcomes remain insufficiently understood, particularly in developing economies. This study examines five antecedents of SCT and the moderating role of environmental dynamism (ED) in its relationships with environmental, economic, and social sustainability. Methods: Data were collected through a cross-sectional survey of 327 managers and professionals in Jordanian industrial firms and analyzed using partial least squares structural equation modelling (PLS-SEM). The model examines disintermediation, country complexity, formalization, third-party integration, and supply chain communication as antecedents of SCT. Results: Country complexity and supply chain communication were positively associated with SCT, whereas disintermediation, formalization, and third-party integration were not statistically significant. SCT was positively associated with environmental, economic, and social sustainability, with the strongest relationship observed for social sustainability. ED significantly and negatively moderated all three SCT–sustainability relationships. Conclusions: The findings show that SCT is associated with multidimensional sustainability outcomes, but these relationships become weaker under greater environmental dynamism. The study highlights the importance of supply chain communication and adaptive information-management capabilities for realizing sustainability benefits from transparency in developing-economy industrial settings.

Logistics doi: 10.3390/logistics10100231

Authors: Prabhu Mannadhan

Background: Green supply chain management has become a key strategy for manufacturing firms that want to stay competitive while reducing their environmental footprint. Objectives: This study proposes a decision support system for evaluating and selecting green suppliers in automobile parts, cement, and electronics production. The framework has two hierarchical multi-level modules. Module I uses triangular fuzzy sets for qualitative supplier data, which is subjective. Module II combines qualitative assessments with quantitative production cost and lead time statistics. Methods: Both modules are analysed using recursive multi-level aggregation and the Center of Area defuzzification rule. Results: In Case I, two-level qualitative hierarchy, supplier S3 ranks highest (3.09), followed by S2 (2.95) and S1 (2.70). In Case II, with a three-level mixed-data hierarchy, S3 again ranks first (4.427), but S1 (4.308) and S2 (4.306) differ by only 0.002, so the two suppliers are virtually tied. Conclusions: Both scenarios show that entirely qualitative and mixed qualitative–quantitative supplier data can be processed through a multi-level hierarchy in one visible mathematical framework. Two related procurement settings, three suppliers, and five experts provide limited empirical evidence, therefore claims of applicability to cement, electronics, or other sectors must be substantiated by multi-sector validation and robustness testing.

Logistics doi: 10.3390/logistics10100230

Authors: SriHarisha Gudapati Jessica Olivares-Aguila Waguih ElMaraghy

Background: Supply chain (SC) ability to recover from disruption (i.e., resilience) is vital for thriving businesses, thus its relevance. This study investigates how resilience to disruption and disruption propagation (i.e., ripple effect (RE)) are influenced by product architecture (PA) and logistics strategies. Methods: Four SC configurations, derived from structural combinations of PA (integral and modular) with two logistics techniques (inventory storage and cross-docking), were generated using discrete-event simulation in FlexSim. Each SC configuration was subjected to five scenarios: no disruption; isolated disruptions at the distribution center (DC) and at the manufacturer; simultaneous disruptions; and sequential disruptions. Results: The results indicated a smoother recovery and lower post-disruption back-order rates for modular PA than for integral PA. Inventory buffering was higher in SC networks with DC storage than in those with cross-docking. The study found increased downstream and upstream disruption propagation under sequential disruptions, illustrating RE. Conclusions: The study suggests that integrating PA with logistics strategies early in supply chain design may improve recovery and overall supply chain performance.

Logistics doi: 10.3390/logistics10100229

Authors: Jurijs Tolujevs Irina Yatskiv (Jackiva) Lukas Eschment

Background: Hyperloop technology has emerged as a promising high-speed and energy-efficient transport concept capable of transforming future mobility systems. While existing research has primarily focused on system feasibility and corridor-scale modelling, limited attention has been paid to capsule dynamics in station environments, despite the significant impact of operational constraints and safety requirements on overall system performance. Methods: This study investigates the use of simulation to analyse hyperloop station configurations and their throughput capacity. The study combines different modelling approaches to analyse capsule movement within the station and assess station throughput capacity. Results: The results show how access arrangements, processing-point availability, and station dimensions affect throughput. In particular, parallel access to processing points provides higher throughput than sequential access when all other station parameters are identical. Conclusions: The developed models can be adapted to specific station layouts and access routes, and may form the analytical core of a future Simulation-as-a-Service framework for hyperloop station design and operational analysis.

Logistics doi: 10.3390/logistics10100228

Authors: Saša Aksentijević Matej Plenča Marija Jović Mihanović Edvard Tijan

Background: Peri-urban areas face mobility and logistics challenges, including car dependence, congestion, decarbonisation pressures, fragmented public transport, and growing demand for sustainable goods distribution, yet they remain less systematically addressed than dense urban cores. This paper examines how AI-enabled solutions can address these challenges in peri-urban systems. Methods: This study combines a structured literature review and a project-based systematic review of EU-funded initiatives. The literature review applies a Technology-Organisation-Environment lens to Web of Science and Scopus sources published between 2015 and 2026, while the project review screens initiatives from CIVITAS, EIT Urban Mobility, Interreg/KEEP, and CORDIS, retaining 124 relevant projects from 16,627 candidates. The synthesis focuses on three AI-enabled concepts: Green-Safe Routing Algorithms, Peri-Urban Mobility Hubs, and Smart and Collaborative Governance. Results: Key challenge is not the absence of individual technologies but an integration deficit involving data spaces, AI optimisation, digital twins, multimodal and freight-capable hubs, circular logistics, citizen participation, and governance capacity. The identified barriers are primarily institutional and social rather than technical. Conclusions: This paper provides an integrated conceptual framework, a drivers-barriers-integration-gaps matrix, and priorities for interoperable data governance, inclusive AI, scalable hub typologies, and policy-linked implementation pathways.

Logistics doi: 10.3390/logistics10100227

Authors: Olusola Olabanjo

Background: Intermittent retail sales create substantial uncertainty for inventory control, particularly across large portfolios of heterogeneous item–location systems. This study develops a scalable GPU-accelerated Fokker–Planck framework for probabilistic inventory modeling and safety-stock optimization. Methods: The framework is evaluated using 30,490 item–store sales series from the M5 dataset. Empirical sales characteristics are mapped to mean-reverting stochastic inventory dynamics, while a conservative finite-volume scheme and normalized formulation enable canonical policy densities to be solved on the GPU and mapped across the portfolio. Results: Numerical verification confirms analytical agreement, probability-mass preservation, grid convergence, and CPU–GPU consistency. More than 70% of the series exhibit intermittent sales characteristics. Across 35 economic scenarios, global and demand-class policies select no incremental safety-stock buffer beyond the baseline target. Item-specific optimization yields a 21.23% mean in-sample model-implied cost reduction under the original objective, whereas the mean locked-test personalization benefit is 2.46%. Conclusions: GPU-accelerated Fokker–Planck modeling provides a numerically stable and scalable framework for portfolio-level probabilistic inventory analysis, although the benefits of item-level personalization depend on the sales process, economic objective, and out-of-sample environment.

Logistics doi: 10.3390/logistics10100226

Authors: Yuanwei Sheng Suhaiza Zailani Sedigheh Moghavvemi

Background: Counterfeit goods realize illicit value only when moved, mainly by logistics intermediaries rather than counterfeiters, so how the law treats these intermediaries determines where enforcement can bite. This review traces the policies, laws, literature, and data relevant to China’s anti-counterfeiting landscape from 1979 to 2026. Methods: A narrative review combined a PRISMA 2020-guided search of Scopus and Web of Science (108 peer-reviewed publications) with 14 primary legal instruments and 4 types of institutional grey literature. Institutional theory was used to derive four expectations. Results: Four regulatory phases were identified, across which duties migrated toward logistics chokepoints: criminal accomplice liability (2004), civil facilitation liability, customs detention, platform liability, parcel-level identity, inspection and screening duties, franchisor network supervision (2024), and independent liability for assisting confusion (2025). Expectations of external origin, chokepoint migration, and ceremonial compliance were supported; capacity-calibrated decoupling awaits verification. Obligations were synthesized into an actor-by-actor matrix. Official data show that only about 3% of administrative cases reach criminal referral, with no breakdown by intermediary type. Conclusions: China has converted logistics intermediaries from neutral conduits into liability-bearing compliance nodes under a know-your-consignor regime calibrated to large integrated operators, but this regime still relies primarily on coercive measures.

Logistics doi: 10.3390/logistics10100225

Authors: Scott Joseph Warren Zoe A. Teel Ting Wang Ziang Donald Wang

Background: Large-scale one-to-one computing initiatives in K-12 education generate supply chain and environmental impacts that are rarely quantified before procurement decisions are made. Methods: This study applies a scenario-based environmental estimation approach, informed by supply chain management principles, to model manufacturing inputs, operational energy consumption, carbon dioxide (CO2) emissions, and end-of-life electronic waste for a representative U.S. school district deploying approximately 32,492 laptops across a standard 3-year replacement cycle, using publicly available lifecycle and energy data rather than proprietary manufacturer figures. Results: Manufacturing the device fleet is estimated to require approximately 48.7 million kg of water and 7.8 million kg of fossil fuels. In-service operation generates approximately 711,575 kWh of annual electricity demand and approximately 264 metric tons of CO2 emissions from device charging. One replacement cycle is estimated to generate approximately 55.3 metric tons of mixed-material e-waste, accumulating to approximately 165.8 metric tons across three cycles (9 years). Conclusions: Large-scale device procurement carries predictable environmental costs across the device lifecycle. The study contributes a replicable estimation framework that institutional decision-makers can use to incorporate these costs into procurement planning for similarly scaled K-12 public sector districts; further validation is needed before extending the findings to nonprofit or private-sector contexts.

Logistics doi: 10.3390/logistics10100224

Authors: Sharaf Alkheder Abdulaziz Aldawish

Background: Authority-supplied daily port figures may be allocations of coarser records rather than measurements. Treating them as observed gate counts can produce spurious model accuracy. Methods: Using 365 daily container-discharge records for 2019 from the Kuwait Ports Authority (KPA), we apply four provenance diagnostics and a stochastic-count benchmark, formalize the allocation chain, distinguish discharge from pickup through a release-lag kernel, and explore assumed uncertainties by Monte Carlo simulation. Results: The daily series has a strong allocation signature (median within-month ratio coefficient of variation 2.1%; 141 of 308 operating days share repeated pairs). Under an assumed uniform pairing share, mean-preserving day-level noise, same-day pickup, and allocation of all modeled visits to six hourly slots from 11:00 to 17:00, peak-hour truck-visit medians are about 143, 185, and 259 for the three design levels. The maximum-day central 90% simulation interval reaches about 354 visits. Conclusions: The contribution is a provenance audit and conditional scenario framework for the import-discharge component. The intervals depend on uncalibrated assumptions and have no demonstrated coverage of observed gate traffic. Classified gate counts, container-to-truck linkage, and broader expert elicitation are required before operational use.

Logistics doi: 10.3390/logistics10100223

Authors: Khalid Alotaibi Idriss El-Thalji Abdelhakim Abdelhadi

Background: Aviation spare parts management faces unpredictable demand, long lead times, strict airworthiness requirements, and high inventory costs, which drive aircraft-on-ground events and operational disruption. Digital spare parts, enabled by digital warehousing and local on-demand manufacturing, offer a potential response, but no standardized framework exists for selecting items for digital warehousing in aviation. Methods: This study develops a modified Spare Parts Interchangeability Record framework incorporating digital readiness, manufacturability, and production-based lead times, coupled to a stochastic discrete-event simulation. Twenty candidate Airbus A320 components are screened, and three supply configurations are compared over a one-year horizon: physical warehousing with OEM procurement, fully digital warehousing with local production, and a hybrid strategy. Results: The hybrid configuration performs best. Relative to the baseline, total waiting time falls by 67.7%, demand-weighted aircraft-on-ground duration from 1089 to 316 h, operational cost by 19.7%, and transport-related emissions by 50%, while service level rises from 86.5% to 95.8%. A fully stockless configuration proves contingent on production capacity, leaving 32.3% of demand unserved at the capacity assumed; twenty simultaneous production slots are identified as the viability threshold. Conclusions: Technical suitability alone does not establish strategic viability. Results derive from simulation rather than field implementation.

Logistics doi: 10.3390/logistics10100222

Authors: Beatriz Martins Oscarina Conceição Joaquim Gonçalves António Rocha

Background: Indirect procurement in precision manufacturing remains under-digitised, generating high transaction volumes, limited spend visibility, and weak compliance enforcement. This study examines the selection and implementation of an e-Procurement platform for the indirect purchasing function of a high-precision optical components manufacturer. Methods: A qualitative action-research methodology, combining a narrative literature review, a weighted multi-criteria decision analysis (MCDA) across 16 candidate platforms, and participatory implementation across four data preparation workstreams. Results: The selected platform outperformed the competing finalist with a raw evaluation score of 82 vs. 81 (out of 90 scored criteria; 120 if the zero-weighted Sourcing criterion is included) and a weighted score of 23.3 vs. 22.9, with System Quality the decisive differentiator. Implementation outcomes include an 85.7% reduction in payment term codes (133 to 19), a 68.75% reduction in unit of measure codes (48 to 15), restructuring a 22-category taxonomy into 10-group and 56-subcategory, and a projected 75% reduction in purchase order lead time (a process-mapping estimate, pending post-go-live validation). 105 users were trained across six role categories before go-live. Conclusions: Data governance is a strategic prerequisite. The framework offers a replicable approach for precision manufacturing, with ERP integration, multi-level approval workflow design, and role-differentiated training as success factors.

Logistics doi: 10.3390/logistics10100221

Authors: Klysman Rezende Alves Vieira Marcela Castro Maria da Graça Costa Ana J. Mendes Tiago Pinho Nelson Carriço

Background: Accurate prediction of vessel time at berth is essential for smart berth planning, yet berth-allocation research typically treats processing time as a given input rather than a learned variable. This study develops a governed data lakehouse blueprint for port operational data and uses berth-time prediction at the Port of Sines, Portugal, to establish what routinely collected administrative records support. Methods: Following a design science research approach, a Bronze–Silver–Gold medallion pipeline was realised twice from one design, on a managed cloud platform and on single-node open-source components, demonstrating portability rather than vendor dependence. Four years of administrative data (October 2020 to September 2024) yielded 8148 berth visits. Results: Under rolling-origin temporal validation across five cut-offs, a Random Forest regressor attained a mean R2 of 0.260 and a mean absolute error of 10.1 h, against 13.5 h for the median-stay heuristic, predicting 52.6% of visits within six hours. SHapley Additive exPlanations identified the vessel’s own previous stay, the berth and vessel size as the strongest predictors. Pipeline measurement shows near-linear scaling and a hundredfold query speed-up over raw-source recomputation. Conclusions: Predictive accuracy remains bounded by the absence of exogenous operational variables; the contribution is the governed data foundation that berth planning requires.

Logistics doi: 10.3390/logistics10100220

Authors: Theofilos Mastos Apostolis Papavasileiou Christos Glykos George Michalos Angelos Papadopoulos Matina Vogiatzi Sotiris Makris

Background: In the pursuit of sustainable manufacturing logistics, the integration of human–robot collaboration (HRC) into shop floors with legacy systems remains a significant challenge due to dynamic environments that complicate task and action planning. To address this challenge, this study investigates a sustainable HRC workstation implemented within a real-world electrical panel assembly use case in the lift manufacturing sector. Methods: The article examines the role of an AI-enabled dynamic task and action planning tool that coordinates human and robotic resources. The proposed solution integrates collaborative robotics using a multi-criteria scheduling algorithm alongside real-time replanning capabilities. Furthermore, the study proposes an evaluation framework based on the triple bottom line (TBL) approach to assess the developed solution. Results: The findings suggest that executing assembly tasks through this collaborative method supports sustainable operations scheduling for all resources. Conclusions: Ultimately, the proposed HRC solution demonstrates the potential to simultaneously enhance environmental, financial and social performance within manufacturing logistics and operations.

Logistics doi: 10.3390/logistics10090219

Authors: Nadiia Shmygol Iryna Nechayeva Larisa Shytikova Sergiy Golovatenko

Background: Relocating logistics infrastructure under wartime conditions requires more than identifying a theoretically suitable location, as available facilities, costs, and emerging risks must also be considered. This study examines the relocation of an enterprise from the frontline Zaporizhzhia region of Ukraine and aims to develop and substantiate a Hybrid Adaptive Model for Relocating Logistics Infrastructure (HAMRLI). Methods: The methodology combines resilience assessment, spatial modelling, digital facility screening, and expert evaluation. The Normalized Resilience Index (NRI) was calculated using EWM and TOPSIS. HAMRLI integrates the Center of Gravity (COG) method, digital verification of available warehouses, and enterprise-specific multi-criteria assessment. Results: COG identified Zhytomyr as a potential relocation area. Seven warehouse offers were identified, and two were shortlisted for expert evaluation. Weighted assessment selected Offer 6. Sensitivity analysis showed that its preference remained stable across the tested scenarios but changed with substantial shifts in criterion weights. The results support the applicability of HAMRLI for relocation decisions under high uncertainty. Conclusions: This study provides an initial empirical application rather than statistical generalization. Further testing of HAMRLI under different enterprise operating conditions is required.

Logistics doi: 10.3390/logistics10090218

Authors: Jiarui Zhao Xiaoning Wang Zhimeng Li Zhengfeng He

Background: Power battery closed-loop supply chains face simultaneous competition for scarce materials, subsidies, market demand, and recyclable batteries, while strategic decisions remain coupled with production, recovery, transport, inventory, and carbon-control operations. Methods: We develop a Nash-type bi-level framework for two homogeneous competing chains, in which simultaneous upper-level strategies determine conditional lower-level operating responses. Shared resources make feasibility strategy-dependent; therefore, the computational target is a finite-candidate approximate equilibrium rather than an analytically solved continuous equilibrium. Public-information-adapted benchmarks are used for finite-grid validation, algorithm and model comparison, and sensitivity analysis. Results: The proposed framework approaches the discretized reference equilibrium in the small-instance validation. In the stylized homogeneous-duopoly benchmark, the Nash-type structure provides a more suitable joint representation of competitive stability and implementation conditions than the selected Stackelberg and centralized-cooperative alternatives, while this result does not identify the competitive structure of the real battery industry. Sensitivity analysis provides directional, benchmark-specific evidence that demand and scarce-material supply are the clearest drivers, whereas policy, preference, and isolated technical parameters mainly reshape equilibrium allocation and structure. Conclusions: These findings support the framework as a conditional analytical tool for competing closed-loop supply chain planning.

Logistics doi: 10.3390/logistics10090217

Authors: Juan Manuel Maqueira Beatriz Minguela-Rata Daniela Pereira de Oliveira

Background: Cloud computing has become a fundamental digital infrastructure to supply chain (SC) digitalization, supporting the implementation of Lean, Agile, Resilient and Green (LARG) strategies. Although previous studies have examined its contribution to individual SC strategies, the organizational capabilities through which cloud computing supports different strategic orientations remain fragmented. This study addresses this gap by systematically reviewing the literature and developing an integrative framework of cloud-enabled organizational capabilities. Methods: A systematic literature review was conducted following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) 2020 guidelines. Relevant studies were identified, screened and systematically coded. Reported capabilities were synthesized into five domains: Information, Integration, Operational, Decision, and Control. Results: The review identifies distinct capability configurations across LARG strategies. Lean SCs are supported by Operational, Integration, and Information capabilities; Agile SCs by Integration, Decision, and Information capabilities; Resilient SCs by Control, Decision, and Information capabilities; and Green SCs by Operational, Control, and Information capabilities. An integrative framework distinguishing primary and complementary capabilities is proposed. Conclusions: The study shifts the focus from cloud computing as a technological resource towards cloud-enabled organizational capability configurations that support SC strategies. The framework and theoretical propositions provide a foundation for future empirical research and managerial decision-making.

Logistics doi: 10.3390/logistics10090216

Authors: Hafiz Wasim Akram

Background: Research on the halal industry has expanded across food, logistics, tourism, finance, pharmaceuticals, cosmetics, digital technologies, and sustainability. Despite this growth, fragmented theoretical and operational perspectives limit an integrated understanding of sustainable halal industry development. Methods: This article employs a structured synthesis of 105 scholarly publications from 2005 to 2024 identified through Scopus and Web of Science. The literature was critically synthesized across certification and governance, market development, logistics and supply-chain integration, digital transformation, and sustainability. Four theoretical perspectives were applied to integrate the identified constructs and relationships. Results: The synthesis identifies persistent fragmentation in certification systems, institutional arrangements, cross-border logistics, technological interoperability, and stakeholder coordination. An integrated conceptual framework links infrastructure and institutional development, stakeholder collaboration and standardization, stakeholder concern and responsibility, halal economic advancement, stakeholder role fulfilment, and sustainable functioning. Eleven propositions define relationships for future empirical testing. Conclusions: Sustainable halal industry development depends on institutional coordination, integrated logistics and supply chains, stakeholder alignment, standardization, and interoperable governance. The proposed ecosystem perspective integrates fragmented research streams and provides a theory-grounded frame-work for explaining sustainable halal industry functioning and guiding future empirical research.

Logistics doi: 10.3390/logistics10090215

Authors: Federico Streithorst Garcia Jairo Núñez Rodríguez María Teresa Castañeda Galvis Ángel Ortiz Bas

Background: Administrative freight records can support repeated territorial analysis when their aggregation grain and measurement units are explicitly distinguished. This study analyzes Colombia’s National Registry of Road Freight Dispatches (RNDC) from January 2022 to December 2025. Methods: Territorial and functional concentration were measured separately by direction using represented trips and mass-recorded tonnes. Raw and normalized Herfindahl–Hirschman indices, effective numbers, supplementary Shannon measures, month-resampling and leave-one-month-out stability diagnostics, as well as directed interdepartmental density and reciprocity, were calculated. Results: Across the four years, 8,176,619 monthly aggregate source rows represented 46,969,693 trips. Represented trips increased from 10.28 million in 2022 to 13.24 million in 2025 (28.8%), whereas mass-recorded freight increased from 135.76 to 151.52 million tonnes (11.6%). Territorial concentration followed direction- and measure-specific, non-monotonic trajectories. Directed density was 0.827–0.841 and binary reciprocity was 0.939–0.954, compared with weighted reciprocity of 0.643–0.701. Trip-versus-tonne HHI rankings had Spearman correlations of 0.535–0.823 and a maximum departmental rank difference of 26. Fixed-versus-observed normalized-HHI rankings had correlations of 0.761–1.000 and a maximum rank shift of 30. Conclusions: Registered Colombian road freight combined broad binary connectivity with heterogeneous concentration. The framework supports comparative screening, while infrastructure or causal interpretation requires independent evidence.

Logistics doi: 10.3390/logistics10090214

Authors: Muhammad Zaka Shaheryar Monzer Alharairi Saman Hassanzadeh Amin Saeed Zolfaghari

Background: Accurate sales forecasting supports inventory planning, resource allocation, revenue management, and operational decision-making. However, the incremental predictive value of external factors such as weather, beyond historical sales information, remains important to assess. This study evaluates an interpretable forecasting framework for daily-location sales revenue and examines the relative contributions of historical and weather information. Methods: Daily sales data were integrated with weather observations and temporal lag features. Random Forest, Extreme Gradient Boosting, CatBoost, and Stacked Long Short-Term Memory (LSTM) models were used for forecasting. Performance was assessed using mean absolute error, root mean squared error, symmetric mean absolute percentage error, and R2. Results: Stacked LSTM achieved the strongest overall test performance (MAE = 28.50, RMSE = 57.04, sMAPE = 5.82%, R2 = 0.972). Feature-importance analysis indicated that historical sales, particularly one-day sales lag, provided a stronger predictive signal than individual weather variables. Conclusions: Historical sales information was the primary predictive signal, while weather provided supplementary information. From a practical perspective, the framework can support revenue-oriented forecasting and help assess the additional value of incorporating weather information. This study also contributes to forecasting research by distinguishing the predictive role of historical sales patterns from the incremental contribution of external contextual variables.

Logistics doi: 10.3390/logistics10090213

Authors: Rafi Garo Melkonyan Svetoslav Hristosov Enkov Vanya Nachkova Melkonyan

Background: Despite the widespread adoption of IoT and LTE technologies in logistics, empirical research quantifying the economic impact of preventing operational errors remains scarce. Methods: This paper presents a case study of a Bulgarian transport company with over 800 tractors and 650 trailers, awarded “Transport Company of the Year 2025” at the Plovdiv Business Awards. An architecture combining BLE sensors, LTE trackers, and two-way integration between the TMS and the Kitin GPS platform was deployed. Using a mixed-methods approach (quantitative KPIs and qualitative process analysis), we measured the effect on annual excess mileage, trailer swap registration time, and error frequency. Results: The results show a 90% reduction in excess mileage (from 10,000 km to 1000 km), a 99.9% faster swap registration time, and a 90% reduction in errors. Annual savings amount to €19,750, with an investment payback period of 13–14 months (334% ROI over 5 years). Conclusions: The scientific contribution is the empirical demonstration that error prevention (correct trailer attachment) dominates asset tracking as a source of value. Theoretical and practical recommendations for fleet managers are presented.

Logistics doi: 10.3390/logistics10090212

Authors: Juan Carlos Muyulema-Allaica Luis Cuautle-Gutiérrez Patricia Cano-Olivos

Background: Integrating additive manufacturing (AM) into manufacturing small and medium-sized enterprises (SMEs) requires addressing technological, economic, organizational, environmental, and institutional conditions whose interrelationships remain insufficiently understood. Methods: This study proposes a conceptual framework for the sustainable integration of AM by combining Systematic Literature Mapping (SLM) with Fuzzy DEMATEL. The SLM covered publications indexed in Scopus, Web of Science Core Collection, and EI Compendex from January 2015 to May 2026. Among 1123 identified records, 72 studies met the inclusion criteria, leading to eight critical factors across political, economic, social, and environmental dimensions. These factors were subsequently evaluated by a panel of 15 experts to determine their interdependencies and cause–effect structure. Results: Government incentives (F1; D − R = 0.928) and digital infrastructure (F2; D − R = 0.469) emerged as the main causal drivers, while implementation costs (F4; D + R = 22.690) showed the highest prominence. The resulting framework comprises four levels: strategic activation, implementation enablement, operational integration and feasibility, and sustainable outcomes. Conclusions: Sustainable AM integration follows a hierarchical causal structure in which institutional and digital conditions initiate adoption, financial and regulatory mechanisms support implementation, and organizational and environmental benefits emerge as subsequent outcomes, providing SMEs with a structured basis for implementation decisions.

Logistics doi: 10.3390/logistics10090211

Authors: Bechir Ben-Daya Jean-François Audy

Background: Port access traffic combines pronounced calendar structure with substantial day-to-day variability, raising the question of whether temporal heterogeneity should condition a common forecasting configuration or support model specialization. Methods: Daily car and freight-truck arrivals at an urban non-containerized port were forecast at 1-, 7-, and 14-day horizons using statistical, machine-learning, and composite models under a leakage-free rolling-origin protocol. A unified calendar-conditioned ensemble was compared with a prespecified regime-based model assignment, with development, test, and temporal stress-test periods kept distinct. Results: The unified ensemble achieved next-day R2 values of 0.75 for trucks and 0.80 for cars on the held-out 2018 test period and 0.73 and 0.75, respectively, under the 2019 temporal stress-test. Model preference varied jointly with temporal regime, forecast horizon, and evaluation period. Although fixed assignment improved car accuracy on the 2018 test period, the model–regime dominance required to justify it was not sufficiently stable across horizons and evaluation periods. Conclusions: Calendar conditioning provides a robust strategy for the present forecasting problem. More generally, fixed regime-based specialization should be supported by sufficiently stable model–regime dominance rather than inferred from identifiable temporal heterogeneity alone.

Logistics doi: 10.3390/logistics10090210

Authors: Chang-Bong Kim Hye-Jeong Yang

Background: This study examines the relationships among resource reduction awareness (RRA), AIoT-enabled Cold Chain System (CCS) implementation, supply–demand control (SDC), perceived operational performance (OPF), and ISO certification from a Lean Logistics perspective. Method: Data were collected from 250 Korean agricultural and marine product firms. PLS-SEM was used to examine the hypothesized relationships and indirect associations, while MICOM and multi-group analysis assessed differences between firms holding both ISO 9001 and ISO 14001 certifications and other firms. Result: RRA was positively associated with ACI and OPF. ACI was positively associated with SDC and OPF, and SDC was positively related to OPF. The indirect association between ACI and OPF through SDC was also significant. The ACI–OPF relationship differed significantly across ISO certification groups and was stronger in the high-certification group. Conclusions: The findings suggest that AIoT-enabled cold chain implementation is associated with perceived operational performance directly and through supply–demand control, while standardized management practices may be relevant to the ACI–OPF relationship. This study therefore clarifies organizational and operational conditions associated with digital cold chain practices and provides implications for research.

Logistics doi: 10.3390/logistics10090208

Authors: Roman Chinoracky Rebecca Neumannova Natalia Stalmasekova Tatiana Corejova

Background: The transformation of businesses resulting from the implementation of artificial intelligence (AI) is currently underway. A research gap lies in the absence of research examining the impact of AI on logistics companies from the perspective of its effect on their business models. Methods: Logistics companies are described, using PRISMA methodology, through an analysis of 151 open-access scientific studies indexed in the Web of Science and Scopus databases, using the Business Model Canvas (BMC) framework and its nine blocks. This research focuses on identifying how AI might influence individual BMC blocks. The research follows the PRISMA methodology and is based on an analysis of 108 open-access scientific studies indexed in the Web of Science and Scopus databases. Results: The findings suggest that AI is transforming the business models of logistics companies across all nine of its blocks. This transformation is taking the form of AI-supported, data-driven ecosystems. Across all BMC blocks, the importance of data analytics, automation, predictive management, service personalization, and digital interoperability is growing. Conclusions: The competitive advantage of logistics companies is increasingly based on the ability to process data, coordinate processes in real time, and create adaptive logistics systems, thereby broadening the interpretation of how logistics companies operate.

Logistics doi: 10.3390/logistics10090209

Authors: Anila Duka Houxiang Zhang Pero Vidan Guoyuan Li

Background: Cruise and passenger vessel traffic is an important component of coastal transportation, but increasing activity can intensify logistical complexity, traffic interactions, and environmental pressure. Understanding vessel behavior across ports and sailing corridors is therefore necessary to support safer and more efficient transport planning. Methods: A reproducible AIS-based framework is proposed to integrate port- and route-level analysis. Port calls are detected using predefined port geofences and minimum dwell time criteria; operational states are classified from vessel location and speed; AIS-valid study-network voyages are reconstructed between consecutive qualifying calls; and modeled CO2 is estimated separately for hoteling and transit using representative engine power assumptions and speed-dependent load factors. The framework is applied to 2023–2024 AIS data from ten Norwegian ports. Results: The analysis identified 5546 port calls and 3323 AIS-valid voyages in 2023 and 5768 calls and 3794 voyages in 2024. Modeled hoteling CO2 decreased from 124,350 to 114,406 tons, while modeled transit CO2 increased from 1.027 to 1.076 million tons; transit CO2 per voyage decreased from 309.1 to 283.7 tons. Conclusions: Traffic frequency alone does not determine modeled emissions; integrated AIS analysis can support differentiated port- and corridor-level transportation planning and emissions mitigation.

Logistics doi: 10.3390/logistics10090207

Authors: Renato Bruni Alberto Geri Marco Maccioni Ludovico Nati

Background: Planning power distribution networks is crucial in contemporary infrastructure development. Current distribution paradigms require not only cost minimization but also reliability and fault tolerance. However, designing meshed network topologies is a computationally demanding combinatorial optimization problem, especially for large instances. Methods: We reframe this problem as a multi-depot vehicle routing problem in which electrical substations act as depots and power lines represent routes. We develop a four-phase Large Neighborhood Search (LNS) that combines geographically-based destroy operators with a topology-specific MILP repair operator. Each repair subproblem is solved to optimality under the adopted topological, flow conservation, and line capacity constraints. Results: Experiments on realistic medium-voltage distribution network instances with up to 1150 nodes show that the proposed method handles cases that are beyond the reach of exact global optimization. Compared with a greedy constructive heuristic, the best LNS solution achieves an average cost reduction of 28.5%. Ablation and sensitivity analyses support the algorithmic design and show stable behavior under reasonable parameter variations. AC power flow analyses on the largest instance confirm electrical consistency under the tested single-branch outage scenarios, with a maximum voltage deviation of 5.1%. Conclusions: The proposed optimal-repair LNS provides a scalable approach for planning large fault-tolerant distribution networks under topology and line capacity constraints.

Logistics doi: 10.3390/logistics10090206

Authors: Darar E. Apiri Ifije Ohiomah

Background: Counterfeit alcoholic beverages pose a major public health threat in Nigeria, yet their infiltration of legitimate supply chains remains poorly understood, especially in Sub-Saharan African markets where informality and weak regulation create conditions overlooked by mainstream counterfeiting models. Methods: This study utilised a qualitative multiple case design, drawing on eight enforcement cases and fourteen semi-structured interviews with retailers, distributors, regulatory officers and police. Results: The findings revealed a contradiction to global models built on the model of upstream adulteration or transnational smuggling. The findings revealed that counterfeiting in Nigeria operates domestically, whereby the supply chain is vertically compressed network in which manufacturing, warehousing, distribution and retail are operated as whole within residential and commercial premises. Three operational clusters are identified: vertically integrated illicit hubs (Cluster A), covert urban micro-production sites (Cluster B), and peripheral component and distribution nodes (Cluster C). Conclusions: Theoretically, the study extends Transaction Cost Economics by showing illicit actors invert conventional governance logic to minimise detection rather than transaction costs; enriches Principal–Agent Theory by demonstrating dual-agency equilibria in which downstream intermediaries serve legitimate and illicit principals simultaneously; and integrates institutional voids theory to explain why this infiltration regime self-reinforces under fragmented licensing and sporadic enforcement.

Logistics doi: 10.3390/logistics10090205

Authors: Ladislav Rigó Jana Fabianová Jakub Kovalčík

Background: Digital twins (DTs) are a key technology of Industry 4.0 and play a crucial role in the digital transformation of industry. The education of experts for the needs of Industry 4.0 and the emerging 5.0 must align with the requirements of practice. However, the availability of these technologies for educational institutions is problematic due to their complexity and limited resources. Methods: This study develops and implements DT and a virtual monitoring system for a specialised 6-DOF laboratory robotic manipulator. The architecture uses a multi-layered communication via middleware KEPServerEX. AI-assisted “Vibe Coding” supports development of a custom Python control application and integration with multiple APIs. Next, the application of a virtual monitoring system enables tracking of selected metrics via a web interface. Results: Our work provides three primary contributions: (1) consolidation of multiple devices through middleware (KEPServerEX) to link robots and PLCs; (2) accelerated development through AI-assisted “Vibe Coding”; and (3) remote accessibility through a custom web-based monitoring platform. Conclusions: The study demonstrates that a fully functional digital twin, integrated with a virtual monitoring system, can be implemented in a university laboratory environment using a combination of cost-effective technologies.

Logistics doi: 10.3390/logistics10090204

Authors: Hagazi Abrha Heniey Alessandro Di Pretoro Guillaume Revenu Hailekiros Sibhato Gebremichael Ludovic Montastruc

Background: Following industrial energy consumption, freight transportation represents the second-largest source of greenhouse gas emissions nowadays. However, although several metrics for the supply chain’s profitability already exist, indicators for its environmental performance are currently lacking. Methods: Hence, a preliminary review of metrics for green logistics was carried out in order to select a comprehensive indicator for more detailed studies. The effectiveness of the proposed metrics was tested on a real industrial case concerning the Messebo cement factory in Ethiopia to explore potential advances in developing countries, where the availability of renewable energy sources is extremely high but infrastructures for their exploitation are absent. Then, the constrained route optimization problem was solved to investigate the implementation of potential improvements. Results: The outcome of this study shows that delivery route optimization improves transportation environmental performance, on average, by 15%, while the replacement of conventional freight trucks with electric vehicles can abate up to 90% of the overall carbon footprint. In both cases, all constraints were satisfied within the required time window. Conclusions: In conclusion, this work proves the effectiveness of green logistics indicators and represents a first step towards supply chain optimization for carbon-intensive sectors in developing countries.

Logistics doi: 10.3390/logistics10090203

Authors: Viktoriia Koilo-Gabillaud

Background: Global maritime supply chains increasingly face overlapping disruptions, yet existing studies often analyse individual crises rather than comparing how stress regimes evolve across system states, channel-specific conditions, and recovery duration. Methods: This study develops a diagnostic Stress–Activation–Recovery (SAR) framework to analyse container-shipping freight-market resilience during the January 2007–June 2026 period. Layer 1 classifies monthly system states using the Global Supply Chain Pressure Index. Layer 2 identifies supply-related, demand-related, logistics/freight-market-related, concurrent, and diffuse system state conditions using six standardized monthly indicators, while crude oil price parameters are recorded separately as energy-state indicators. Layer 3 measures freight-market recovery duration using HARPEX time-to-baseline. Results: Stress regimes unfold as evolving sequences rather than isolated events. The 2008–2009 financial crisis combines system contraction with concurrent supply–demand–logistics/freight-market conditions, while the COVID-19/post-pandemic period shifts from demand- and supply-related abnormal conditions through diffuse system state to logistics/freight-market dominance condition. Recovery duration varies substantially, from 3 months after the early COVID-19 freight collapse to 42 months after the financial crisis. The 2024–2026 high-freight deviation remains right-censored. Conclusions: The SAR framework provides a transparent diagnostic tool for comparing stress regimes and restorative freight-market recovery.

Logistics doi: 10.3390/logistics10090202

Authors: Nasser M. Al Jurf Kadir Ertogral

Background: The demand for natural gas and advancements in LNG technologies have made it easier and more cost-effective to transport large quantities of natural gas over long distances by cooling it and then delivering it to customers according to an annual delivery plan (ADP). This plan is crucial for the LNG supply chain to minimize operational costs and meet contractual obligations; however, there are random factors that deviate from the ADP’s initial plan, such as production rate interruptions, weather conditions, and a reduction in the number of berths. Methods: Available optimization methods for ADPs in the literature were reviewed using a systematic literature review (SLR) and validated with the PRISMA 2020 Statement checklist and flow diagram, which showed that many existing studies use simplified deterministic models to optimize ADPs within reasonable time and effort. This research suggests establishing a simulation-based optimization (sim-heuristics) framework to develop ADPs with an objective function that minimizes expected total costs while capturing real-life uncertainties. This approach will provide tactical insights to decision-makers and is adaptable for various operational policy evaluations. Conclusions: This simulation-based optimization approach could offer the LNG industry a powerful analytical engine for robust, real-world decision-making, bridging the gap between theoretical planning and operational complexity.

Logistics doi: 10.3390/logistics10090201

Authors: Çelepçıkay Ömer Tuzkaya Gulfem

Background/Objectives: Selecting candidate cross-docking locations is a critical strategic decision in early-stage logistics network design. Conventional approaches often aggregate all demand data into a single planning snapshot, hiding the difference between consistently important locations and those attractive only under average conditions. This study proposes a demand-weighted spatial clustering framework for identifying temporally stable candidate cross-docking locations. Methods: The framework applies clustering to each monthly period independently and evaluates candidate centers through a cross-month stability analysis. K-Means++ is the main method, K-Medoids provides cross-validation, and DBSCAN serves as a density-based reference. Cluster counts are selected using a composite metric based on the Silhouette score, Davies–Bouldin index, and Calinski–Harabasz score. A stability score ranks candidate zones by combining frequency of appearance and demand weight. Results: On a real Turkish logistics dataset of 375,259 orders from 563 customers over 16 months, the framework produced 12 consensus candidate locations, eight appearing in all 16 months. A single-period baseline gave only nine candidates and missed four moderate-demand zones. A paired t-test showed the K-Means++ and K-Medoids difference was significant (p < 0.001). Conclusions: The framework offers a repeatable, data-driven approach to candidate-location screening as a structured input to subsequent sustainability-oriented network optimization models.

Logistics doi: 10.3390/logistics10090200

Authors: Botagoz Kaldybayeva Alisher Khussanov Oleksandr Prokhorov Zhakhongir Khussanov Aizhan Kamysbayeva Saule Bekzhanova Baurzhan Korganbayev Doskhan Kenzhebekov

Background: The development of international transport corridors and growing freight flows require decision-support tools that jointly consider transport infrastructure, economic performance, and risks. This study develops a simulation-based decision-support system for strategic development of multimodal transport logistics in Kazakhstan. Methods: The system is based on an agent-based model representing producers, consumers, logistics centers, border checkpoints, container terminals, transport hubs, road and rail vehicles, and freight orders. AnyLogic simulation, geospatial transport-network data, optimization mechanisms, economic assessment, and risk-oriented indicators are integrated within a unified environment. Results: The model enables assessment of freight flows, transportation costs, infrastructure performance, profitability, integrated risk, and system resilience. Scenario experiments representing border modernization, rail corridor development, multimodal hub expansion, digital logistics, and integrated modernization demonstrate how infrastructure and operational changes affect transport, economic, and risk-related indicators. The integrated framework supports identification of bottlenecks and comparison of alternative development strategies under common model assumptions. Conclusions: The proposed system provides a unified simulation environment for scenario-based evaluation of Kazakhstan’s multimodal transport logistics development. It supports comparative assessment of infrastructure and operational interventions and provides quantitative information for strategic transport planning.

Logistics doi: 10.3390/logistics10090199

Authors: Verry Surya Hendrawan Taufik Djatna Yandra Arkeman Khaswar Syamsu

Background: Imported halal meat supply chains face substantial challenges caused by fragmented certification systems, information gaps, and uncertainties. These factors challenge procurement management and hinder the assurance of halal compliance. Conventional Enterprise Resource Planning (ERP) systems are mainly designed for transaction processing and offer limited support for flexible decision-making. Methods: An Adaptive Bayesian-Feedback Framework was developed that integrates Digital Halal Authentication, Evidence-Based Decision Support, Bayesian inference, adaptive feedback learning, and the Markov Decision Process (MDP) within the ERP Purchasing Module. The framework was evaluated using 30 imported meat shipment cases, expanded into 300 procurement transaction records. Results: Implementation of the framework reduced halal authentication processing time from 2509 s to 290 s, representing an 88.44% decrease and an approximately 8.65-fold improvement in processing speed. The framework also enabled continuous revisions to evidence on vendors and procurement risks and improved the consistency of decision-making amid uncertain supply chain circumstances. Conclusions: The framework develops a unified decision-support system comprising adaptive halal authentication, evidence-based decision support, and intelligent ERP. This integration improves procurement governance, traceability, transparency, and uncertainty management in imported halal meat supply chains.

Logistics doi: 10.3390/logistics10090198

Authors: Israt Hridi Mikiharu Arimura Chawis Boonmee

Background: Agile humanitarian logistics (HL) has emerged as an imperative approach for improving preparedness, response, and recovery in flood disasters. However, achieving agility in HL depends on identifying and implementing critical strategies that enhance logistics performance. Using the 2024 Bangladesh flash flood as an empirical case, this study provides an early investigation into the critical success factors (CSFs) required to strengthen agile HL performance. Methods: First, a PRISMA-guided review was conducted to systematically identify the most relevant CSFs and their associated dimensions from prior studies. Next, the Content Validity Index (CVI) method was applied to evaluate and refine the CSFs through expert consensus, ensuring strong content validity. Results: The results indicate that 12 CSFs, organized across five dimensions—collaboration, managerial, operational, strategic, and technological—collectively contribute to improving HL performance and supporting long-term agility. Conclusions: This study offers a structured set of validated factors that can guide policymakers and humanitarian organizations in prioritizing interventions, strengthening coordination, improving decision-making and resource utilization during flood emergencies. These insights extend agile HL knowledge by linking validated CSFs to performance enhancement in a real-world, high-impact disaster context.

Logistics doi: 10.3390/logistics10090197

Authors: Reza Eshtehadi Ying Xie Dong-Ping Song

Background/Objectives: UK ports are central to maritime decarbonisation, but comparable evidence on implementation remains limited. This study examines documented practices at 16 major UK ports represented by 17 analytical cases. Methods: A documentary multiple-case design classified 408 case indicator assessments across six dimensions and 24 indicators. Five ordered categories described documented implementation maturity, and results were compared using category frequencies and distributions. Results: Solar generation, efficient infrastructure, equipment electrification, rail connectivity, and industry partnerships were more extensively documented. Wind, hydrogen, green corridors, and just-in-time operations were largely absent from the public record or at planning and pilot stages. Patterns also varied by port type and ownership. Conclusions: The study identifies transferable implementation patterns while distinguishing documented activity from verified emissions effectiveness. Greater disclosure, coordinated infrastructure planning, and sustained cross-sector partnerships are needed to support wider implementation.

Logistics doi: 10.3390/logistics10090196

Authors: Beáta Furmannová Dávid Hanzlovič Martin Krajčovič

Background: High-mix manufacturing environments are characterized by increasing product variety, dynamic material flows, and growing operational complexity, creating significant challenges for intralogistics layout redesign. Existing research addresses manufacturing complexity, facility layout planning, simulation, and multi-criteria decision-making; however, these approaches are typically applied independently and provide limited guidance for systematically translating manufacturing complexity into layout redesign decisions. Methods: This study proposes the Complexity-Driven Intralogistics Layout Redesign Framework (CDILRF), which integrates manufacturing complexity assessment, Complexity Translation, layout design, digital layout evaluation, and structured decision support into a unified redesign methodology. The framework was demonstrated through an industrial case study in a high-mix automotive manufacturing environment. Results: The framework transformed manufacturing complexity into structured layout redesign requirements, supported the evaluation of five layout alternatives, and identified the preferred redesign solution digital material-flow analysis and multi-criteria assessment. The selected layout reduced logistics effort by approximately 37% while increasing available warehouse space. Conclusions: CDILRF establishes an explicit link between manufacturing complexity assessment and intralogistics layout redesign through a structured, transparent decision-support process. The framework contributes to manufacturing logistics research and provides a practical methodology for data-driven intralogistics layout redesign in high-mix manufacturing environments.

Logistics doi: 10.3390/logistics10090195

Authors: Milos Poliak Adela Poliakova Jakub Malik

Background: Transport remains one of the hardest sectors to decarbonize in the European Union, and the effectiveness of environmental taxation as a “polluter pays” instrument remains contested for the institutionally distinct Visegrad Four (V4) countries. Methods: Using a balanced panel of four V4 countries over 2000–2024 (n = 100 observations) from Eurostat, we estimate fixed-effects models with Driscoll–Kraay standard errors, complemented by two-way fixed effects, lag, interaction, and robustness specifications, including a sensitivity test for mechanical endogeneity. Results: GDP per capita and freight transport volume are positively associated with emissions (elasticities 0.244 and 0.230, both p < 0.001), while renewable energy share is negatively associated (−2.93%, p < 0.001). Environmental taxes show no significant association at any lag, and their positive association is strongest where highway infrastructure is least developed, disappearing where it is most developed. Freight transport remains the only robust driver once year effects are controlled for; a tax-to-freight intensity indicator reveals a significant three-year lag effect. Conclusions: Environmental taxation alone is not robustly associated with lower transport emissions in the V4; its association is conditional on infrastructure development and best complemented by renewable-energy investment. Findings should be read as descriptive associations rather than causal effects.

Logistics doi: 10.3390/logistics10090194

Authors: Raphael Lissillour

Background: Regenerative supply chain research seeks to move beyond minimal-harm sustainability toward forms of organizing that preserve, restore, and enhance social–ecological systems. However, existing work often explains regeneration through principles, capabilities, and governance arrangements while giving less attention to the uneven socioecological conditions and appropriative dependencies that shape supply-chain activity. Methods: This conceptual study uses an abductive close reading of Anna Lowenhaupt Tsing’s The Mushroom at the End of the World as a sole-source textual dataset. The analysis combines an immanent reading of the complete monograph with a theory-informed reading that places Tsing’s concepts in dialogue with regenerative supply-chain scholarship. Results: The study develops two linked theoretical shifts. First, it conceptualizes supply chains as patchy socioecological assemblages composed of firms, livelihoods, infrastructures, ecological processes, and disturbance histories that only partially cohere under managerial control. Second, it defines regenerative attunement as the ongoing, place-sensitive reconfiguration of supply-chain scale, timing, governance, and value distribution so that economic activity helps reproduce rather than merely appropriate socioecological capacities. Conclusions: These concepts extend regenerative supply-chain theory by clarifying the relationships among supply-chain structure, value appropriation, temporal plurality, and distributed governance, while providing directions for managerial diagnosis and future empirical research.

Logistics doi: 10.3390/logistics10090193

Authors: Mohammadjavad Zeinali Joshua D’Alton Soroush Veisee Navid Kousheshi Pezhman Ghadimi

Background: Emergency aeromedical services, including helicopter emergency medical service (HEMS) and medical emergency evacuation (MEDEVAC), are critical to time-sensitive care. Dispatch decisions are complex and consequential, determining whether, which, and under what conditions to deploy aeromedical resources. This study reviews modelling approaches for emergency aeromedical dispatch. Methods: Following PRISMA, studies between 2003 and 2026 (June) were screened, yielding 42 studies. Models were classified as predictive and learning-based, sequential decision, and prescriptive optimisation-based, with solution techniques, operational applications, and policy contexts analysed. Results: Markov decision process and approximate dynamic programming models dominate the sequential decision literature, particularly in military MEDEVAC. Prescriptive models support resource allocation, base location, coverage planning, and dispatch optimisation, while predictive and AI/ML-based approaches remain limited but emerging. Key challenges include computational complexity, data uncertainty, policy fragmentation, and ethical concerns. Sequential models reflect dispatch’s dynamic, stochastic nature, where current deployments constrain future resource availability. Priority-aware policies outperform closest-unit rules, but limited real-world validation hinders adoption. Conclusions: This review maps methods and provides evidence-based guidance for researchers and dispatch organisations selecting decision support models. Future opportunities include AI-assisted dispatch, hybrid predictive–prescriptive modelling, real-time adaptive algorithms, sustainability-oriented optimisation, improved helicopter landing zone identification, and standardised ethical and regulatory frameworks.

Logistics doi: 10.3390/logistics10090192

Authors: Vadim Mavrin Irina Makarova Gennadiy Mavrin

Background: Transport costs in industrial waste management can account for up to 60% of total expenditures, yet existing optimization models often rely on simplified distance metrics and treat facility location and routing separately. This paper addresses these gaps. Methods: A simulation model is developed integrating real OpenStreetMap road networks, differentiated environmental risk coefficients by waste hazard class, and joint optimization of the number, location, and capacity of sorting stations and recycling plants. A nearest-available-facility heuristic is applied for routing. The model is implemented as an agent-based simulation in AnyLogic and validated on real data from the Republic of Tatarstan. Results: The optimized configuration (five sorting stations and two new recycling plants) increased the recycling rate from 29.8% to 69.1%, reduced waste sent to storage from 59.3% to 21.5%, and achieved a positive net present value. Transport costs became the dominant cost item (47% of total costs). Conclusions: The model provides a practical decision-support tool for transport planners and logisticians, enabling an assessment of infrastructure decisions on transport work, mileage, and emissions. Integrating real road networks and environmental risk coefficients significantly improves the accuracy of logistics optimization in waste management systems.

Logistics doi: 10.3390/logistics10080191

Authors: Vuk Mirčetić Tijana Đukić Aleksandar Ignjatović Pertini Stefan Milojević Aleksandra Vujko

Background: Algorithmic Operational Control increasingly shapes logistics operations through AI-enabled decision systems, yet its relationships with Human Operational Agency and innovation remain insufficiently understood. This study examines relationships among Algorithmic Operational Control, Leadership Mediation Capacity, Human Operational Agency, and perceived Logistics Innovation Quality. Methods: Survey data were collected from 3613 logistics employees across six Western Balkan countries. A split-sample design combined exploratory and confirmatory factor analyses with structural equation modeling, supplemented by organizational clustering diagnostics, multi-group CFA, and a reduced-overlap sensitivity analysis. Results: Algorithmic Operational Control was negatively associated with Human Operational Agency and Logistics Innovation Quality, whereas Leadership Mediation Capacity was positively associated with Human Operational Agency. Human Operational Agency partially mediated the association between Algorithmic Operational Control and Logistics Innovation Quality and fully mediated the association between Leadership Mediation Capacity and Logistics Innovation Quality. Organizational clustering was negligible, the measurement structure was stable across countries, and sensitivity analysis preserved all principal relationships and mediation effects. Conclusions: The findings indicate that preserving human judgment and adaptive decision-making is associated with more exploratory and long-term-oriented innovation and position leadership as an interpretive mechanism reconciling algorithmic recommendations with human judgment.

Logistics doi: 10.3390/logistics10080190

Authors: Amlan Baruah Mohammad Moshref-Javadi

Background: Generative artificial intelligence (GenAI) has attracted significant attention in supply chain management (SCM) due to its potential to improve data-driven decision-making and operational performance. However, existing studies mainly focus on individual GenAI models or specific supply chain applications, lacking a comprehensive understanding of how different GenAI architectures support decision-making across the supply chain. Methods: This study conducts a systematic literature review using the PRISMA framework to examine the applications of Generative Adversarial Networks (GANs), Transformers, Variational Autoencoders (VAEs), and flow-based models within a six-level supply chain decision-making framework. A total of 692 peer-reviewed publications were analyzed using bibliometric methods, including keyword co-occurrence, temporal and density analyses, and Supervised Embedding Visualization. Results: Current research is concentrated on Transformer and GAN applications, particularly in data analytics, optimization, forecasting, manufacturing, transportation, logistics, and quality management. The analyses also reveal major research themes, the evolution of GenAI in SCM, and limited attention to sustainability, cybersecurity, resilience, and reverse logistics. Conclusions: This study provides a comprehensive overview of GenAI applications in SCM, identifies key research gaps, and offers a foundation for future research while helping practitioners evaluate opportunities and limitations of GenAI for supply chain decision-making.

Logistics doi: 10.3390/logistics10080189

Authors: Aisha Mussabekova Vladislav Galyandin Saltanat Massakova Gulnara Ayazbayeva

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.

Logistics doi: 10.3390/logistics10080188

Authors: Yue Zhao Jingfeng Dong

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.

Logistics doi: 10.3390/logistics10080187

Authors: Joash Mageto Makgosi Tlholwe Hugo van den Berg

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.

Logistics doi: 10.3390/logistics10080186

Authors: Jugendra Singh Amit Kumar Gupta Imlak Shaikh

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.

Logistics doi: 10.3390/logistics10080185

Authors: Ruaa BinSaddig Abdulla Subhi Ruzieh Bahaa Subhi Razia Reem Khamis Bahaa Subhi Awwad

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.

Logistics doi: 10.3390/logistics10080184

Authors: Evripidis P. Kechagias Nikolaos A. Panayiotou Sotiris P. Gayialis Georgios A. Papadopoulos

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.

Logistics doi: 10.3390/logistics10080183

Authors: Małgorzata Grzelak Daniela Voicu Ramona-Monica Stoica Radu Vilau

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.

Logistics doi: 10.3390/logistics10080182

Authors: Mohammad Hori Bernd Noche

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.

Logistics doi: 10.3390/logistics10080181

Authors: Adeeb Alshakhs Dawn Gregg

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.

Logistics doi: 10.3390/logistics10080180

Authors: Lujain Hussein Alamoudi Mohammad Asif Salam

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.

Logistics doi: 10.3390/logistics10080179

Authors: Aizhan Mukhametzhanova Marat Baiseitov Aliya Izbairova Dariga Kushtayeva Gabit Bakyt

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.

Logistics doi: 10.3390/logistics10080178

Authors: Peter Kačmáry Martin Straka

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.

Logistics doi: 10.3390/logistics10080177

Authors: Samiullah Khairy Mariano Falcitelli

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.

Logistics doi: 10.3390/logistics10080176

Authors: Jonathan P. Resop John S. Cundiff

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.

Logistics doi: 10.3390/logistics10080175

Authors: Mohammed Machkour Abdellah El Barkany Bilal Harras

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.

Logistics doi: 10.3390/logistics10080174

Authors: Abishae Noel László Buics Eszter Sós

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.

Logistics doi: 10.3390/logistics10080173

Authors: Lujain Hussein Alamoudi Mohammad Asif Salam

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.

Logistics doi: 10.3390/logistics10080172

Authors: Mahmoud Abdulhadi Alabdali Mohammad Asif Salam Mohammed Abu Jahed Ummee Kulsum

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.

Logistics doi: 10.3390/logistics10080171

Authors: Pablo Emilio Mora Lozano Jairo R. Montoya-Torres

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.

Logistics doi: 10.3390/logistics10080170

Authors: Rebecca Fussone Rachele Fussone Enrico Favazza Azar Mahmoum Gonbadi Paz Perez Gonzalez Jose Manuel Framinan Salvatore Cannella

Background: Circular economy transitions challenge conventional supply chain design and require decision-support tools that remain valid across multiple plausible futures. However, futures thinking in circular supply chain research is still used mainly as a narrative device, with limited guidance on how to translate scenario insights into model-ready assumptions. Methods: This paper proposes a four-step framework that converts qualitative circular-futures narratives into modelling factors and parameterised assumptions for waste electrical and electronic equipment supply chain simulation and optimisation. Four plausible circular futures, defined along economic-orientation and governance axes, are translated into operational and circularity factors and then into numerical parameters or structural modelling choices. The framework is illustrated through three applications: circular Supply Chain Resilience, electric-vehicle battery remanufacturing, and regional collection and treatment optimisation. Results: Circular strategies create value only when reverse flows, capacity and allocation choices are coherently aligned. Higher return rates improve resilience and material recovery but can destabilise upstream inventories when remanufacturing capacity and return shares are unbalanced. Different scenario priorities lead to distinct trade-offs across cost, emissions, resilience and circularity. Conclusions: This paper offers a replicable pathway for embedding plausible futures into quantitative circular supply chain models and supports more transparent decision-making under uncertainty.

Logistics doi: 10.3390/logistics10080169

Authors: Daniela Ambrosino Veronica Asta Khawar Bashir Costanza Chiesa

Background: Rail operations form a critical interface between maritime container terminals and their hinterlands, yet their operational planning remains underexplored; this paper introduces the Train Unloading Planning Problem (TUPP), which jointly determines the container unloading sequence, gantry crane movements, reach stacker routing, and the assignment of containers to compatible export yard bay-locations. Methods: We propose a mixed-integer linear programming (MILP) formulation that captures the tightly coupled interactions among these decisions, strengthened by valid inequalities that reduce CPU time; because exact optimization becomes intractable at operationally realistic sizes, we develop an Iterated Local Search (ILS) heuristic that refines an MILP warm-start using two complementary neighborhood operators, each embedding a greedy reach stacker re-routing procedure, together with a controlled perturbation mechanism. Results: On 16 groups of benchmark instances reflecting Italian terminal operations, the MILP proves optimality only for the smallest instances, with optimality gaps high on medium sized instances. Averaged across all groups, the ILS improves solution quality by 16.62% over the time-limited MILP while requiring about 360 s of total solution time, roughly a ten-fold reduction, with gains reaching 36.56% on the largest instances. Conclusions: The framework provides an effective decision support tool for operational planning in non-automated maritime container terminals.

Logistics doi: 10.3390/logistics10080168

Authors: Salma Tallaki Mourad Abouelala Abderahmane Kebe Sekoun Faycal Mimouni Mario Di Nardo

Background: The confluence of the Internet of Things (IoT) and the Physical Internet (PI) is a major accelerant of Logistics 4.0, which can provide significant upsides to supply chain performance. While prior reviews mainly concentrated on technological advancement and applications, limited consideration has been given to the mechanisms through which the PI-IoT system integration generates benefits, namely operational, economic, and environmental benefits. Methods: To fill this gap, this study undertakes a systematic literature review of 43 peer-reviewed studies guided by PRISMA. This study uses the Context, Intervention, Mechanism, Outcome (CIMO) framework to automatically conduct a mechanism-based synthesis of PI-IoT integration, unlike previous reviews. Results: The results show that enhanced operational and economic efficiency, as well as environmentally sustainable performance, can be achieved by using real-time visibility, predictive decision-making, collaborative resource optimization, intelligent automation, and adaptive system responsiveness. Conclusions: This review also proposes a conceptual framework, linking contextual conditions, technological interventions, mechanisms, and outcomes, while also identifying important research gaps and future research directions. This study offers essential findings that offer practical insights for researchers, logistics managers, and policymakers intending to implement collaborative, data-driven, and sustainable PI-IoT-enabled logistics systems.

Logistics doi: 10.3390/logistics10070167

Authors: Stefan Ugrinov Sanja Stanisavljev Dragan Ćoćkalo Mihalj Bakator Edit Terek Stojanović Mića Đurđev

Background: Technological innovation in logistics (TIL), logistics capability (LC), and lean logistics (LL) are receiving wider attention in logistics and supply chain research. They are often examined in separate models and less often in relation to both business performance (BP) and market performance (MP). Their joint effects on organizational performance remain insufficiently examined in previous research. Methods: This study examined the effects of TIL, LC, and LL on BP and MP through a quantitative survey conducted among enterprises in Serbia, a transition economy with limited empirical evidence on these relationships. Data from 129 valid responses were analyzed through descriptive statistics, correlation analysis, linear regression analysis, and multicollinearity diagnostics. Results: The findings show that LC has a positive and significant effect on both BP and MP. LL has a positive and significant effect on BP, while TIL has a positive and significant effect on MP. The model explains a larger share of variance in BP than in MP. Conclusions: The results support a differentiated view of logistics transformation and indicate that BP and MP should be examined as related but distinct outcome dimensions. The study integrates TIL, LC, and LL within a unified performance framework.

Logistics doi: 10.3390/logistics10070166

Authors: Gelmar García-Vidal Laritza Guzmán-Vilar Alexander Sánchez-Rodríguez Rodobaldo Martínez-Vivar Reyner Pérez-Campdesuñer

Background: Logistics and supply chain resilience research typically assumes access to formal infrastructure, including contracted fleets, warehouses, inventory systems, and institutionalized contingency mechanisms. Yet many micro and small enterprises (MSEs) in emerging economies operate without these resources, leaving their logistics practices underexplored. This study examines how informal MSEs sustain operational continuity and recover from disruptions through tacit relational support. Methods: Fuzzy-set Qualitative Comparative Analysis (fsQCA) was applied to 400 informal MSEs in Ecuador’s manufacturing, services, and commerce sectors. Tacit network structure was measured using four function-specific name generators covering transport, storage, contingency management, and informal financing. Operational resilience was assessed through order fulfillment rate and recovery time after disruption. Results: No relational-support domain was individually necessary for resilience. Six sufficient configurations were identified, with consistency values from 0.817 to 0.978 and solution coverage of 0.433. One configuration combined contingency-management and informal-financing ties despite low membership in transport and storage networks, indicating a compensatory relational pathway. Conclusions: Tacit personal networks are better understood as context-dependent relational logistics support systems than as substitutes for formal infrastructure. The findings offer bounded, exploratory configurational evidence on selected pathways associated with operational resilience in informal MSEs.

Logistics doi: 10.3390/logistics10070165

Authors: Lydie Beassemda Alim Hamadou Henri Thaddée Mba Gilbert Roméo Hubert Ngock Marius Tony Kibong Marcel Rodrigue Ewodo-Amougou Jean Marie Stevy Sama Jean Gaston Tamba

Background: This study analyses the predictive causal relationships between sesame supply chain performance, participatory governance, and domestic credit to the private sector in Chad. In Sahelian economies, agricultural value chains continue to be subject to structural constraints relating to limited access to finance and substandard institutions. Therefore, understanding the interactions between local governance, productive finance and agricultural performance is essential for guiding public policy. Methods: This analysis uses annual data from 2002 to 2021. Sesame production serves as an indicator of supply chain performance, while participatory governance is assessed using a composite index based on citizen participation, government effectiveness, and regulatory quality. The study applies the Granger causality test in the Toda–Yamamoto sense. Results: The findings reveal unidirectional causality from participatory governance to sesame production. The findings also reveal bidirectional causality between domestic credit to the private sector and sesame production. No direct causality was observed between participatory governance and private credit. Impulse response functions confirm that institutional and financial effects on production manifest themselves gradually over time. Conclusions: These results imply that sustainable development of the sesame sector in Chad necessitates an integrated strategy combining stronger local governance, improved access to private finance, and agricultural value chain modernisation.

Logistics doi: 10.3390/logistics10070164

Authors: Eduardo Molina

Background: Last-mile delivery is the most operationally complex and consumer-visible segment of E-commerce fulfillment, and direct-from-store (DFS) operations account for a growing share of online orders; yet packaging has been studied largely as a materials or sustainability problem rather than as a consumer-facing logistics decision. This study characterizes consumer packaging expectations across fulfillment channels and compares them with observed DFS practice. Methods: We integrate two empirical efforts: an online survey of general E-commerce packaging perceptions (n = 1947 U.S. consumers) and a DFS investigation comprising an exploratory international field audit of 51 orders across four countries and an online DFS consumer survey (314 participants). Analyses include professional–consumer comparisons, internal-consistency and exploratory factor analyses, and a mixed-effects model of the repeated scenario ratings. Results: Consumers consistently prioritize functional protection, content concealment, and practical sustainability over experiential and branding attributes; packaging professionals rate experiential attributes more highly than consumers do (medium-to-large effects); and observed DFS practices frequently misalign with consumer-prioritized functions. Conclusions: The findings support treating packaging as a managed, consumer-centric logistics variable and identify packaging choice at checkout as a feasible lever for DFS providers.

Logistics doi: 10.3390/logistics10070163

Authors: Leonardo G. Hernández Landa Carolina Solís Peña Juan M. Hernández Ramos Jania A. Saucedo Martínez

Background: Traditional value-based ABC inventory classification allocates protection according to economic value, overlooking operational risk factors such as demand variability, lead time, and assembly criticality, and it couples safety-stock and replenishment-cycle decisions. Methods: We propose a Hybrid Risk-Value framework that decouples these two decisions: stock-keeping units (SKUs) are segmented by multivariate K-means clustering on operational risk variables to set safety-stock factors (Z), while ABC economic value sets replenishment cycle coverages (d). The framework is validated through stochastic discrete-event simulation on an anonymized dataset of 200 SKUs from an automotive supplier, under base, high-demand-variability, and extended-lead-time scenarios (20 replications each), and is benchmarked against both classic ABC and a coupled ABC-XYZ policy. Results: Across all scenarios, the Hybrid framework reduces average inventory investment and total logistical cost by approximately 26–28% relative to ABC (p<0.001) while maintaining the service level; stockout days remain statistically unchanged except under extended lead times. The coupled ABC-XYZ benchmark performs almost identically to ABC, indicating that the gains arise from decoupling rather than from variability-based segmentation alone. Conclusions: Decoupling safety-stock and replenishment decisions offers a capital-efficient, data-driven alternative to static financial segmentation for resilient industrial inventories.

Logistics doi: 10.3390/logistics10070162

Authors: Wei Yang Jiaxin Liu

Background: Within the fresh food e-commerce supply chain, government effort-contingent subsidies and logistics partnerships critically impact order pricing, preservation, and profitability. This study aims to investigate how different logistics cooperation modes interact with effort-contingent subsidies to optimize supply chain performance under preservation effort and random demand. Methods: We developed three Stackelberg game models: an independent logistics model, a logistics-supplier cooperation model without subsidies and a logistics-supplier cooperative model with government effort-contingent subsidies. Equilibrium strategies were derived theoretically and analyzed through numerical simulations to examine preservation efforts and pricing. Results: The findings show that logistics cooperation combined with effort-contingent subsidies not only optimizes the decision-making behaviors, but also effectively shares preservation costs and mitigates double marginalization. This synergy incentivizes higher preservation efforts and lowers wholesale prices, ultimately reducing retail prices and expanding market demand. Furthermore, the analysis reveals that excessively optimistic demand forecasts (over-ordering) sharply increase systemic costs, causing a reverse drop in actual demand. Conclusions: Government subsidies are an effective macro-policy tool for alleviating cold-chain costs when integrated with logistics cooperation. To build a sustainable supply chain, e-commerce platforms must adopt prudent ordering strategies, while policymakers should structurally design subsidies to incentivize preservation investments rather than purely subsidizing profits.

Logistics doi: 10.3390/logistics10070161

Authors: Saeed Sadeghi Darvazeh Farzaneh Mansoori Mooseloo Andres Acero Yasel Costa Abdoulmohammad Gholamzadeh Chofreh

Background: Supply chains are becoming increasingly complex, interconnected, and stakeholder-intensive, making effective problem formulation as important as identifying optimal solutions. Although problem structuring methods (PSMs) have been widely applied in logistics and supply chain management (LSCM), the literature remains fragmented, providing limited guidance on selecting appropriate methodologies for different problem contexts. Methods: Following the PRISMA guidelines, this review analyzes 187 journal articles published between 1997 and 2026. Bibliometric analysis and qualitative synthesis were combined to examine the evolution of the field, compare the characteristics and applications of different PSMs, and identify emerging methodological trends. Results: PSM research has grown substantially since 2015, with System Dynamics, Cognitive Mapping, and Scenario Planning emerging as the dominant methodologies. The review also identifies a clear shift toward mixed-methodology approaches that integrate PSMs with optimization, simulation, and multi-criteria decision-making techniques. Stakeholder complexity, uncertainty, and system dynamics were identified as the primary factors influencing methodology selection. Conclusions: This study advances theory and practice by developing an integrated decision-support framework and methodological guidance for selecting appropriate PSMs in complex logistics and supply chain environments. The proposed framework provides a practical roadmap for diagnosing ill-structured problems and choosing suitable problem structuring approaches across diverse supply chain contexts.

Logistics doi: 10.3390/logistics10070160

Authors: Kristína Kováčiková Andrej Novák Martina Kováčiková Alena Novák Sedláčková

Background: The air cargo sector is undergoing significant digital transformation driven by increasing demands for operational efficiency, transparency, and real-time information exchange. Despite the growing importance of digitalization, substantial differences remain in the level of technological implementation and system integration among air cargo carriers, while sector-specific evaluation frameworks remain limited. Methods: This study develops an evaluation framework for measuring digitalization in air cargo logistics. The framework is based on five evaluation pillars and a structured set of indicators covering electronic documentation, real-time shipment tracking, automation, digital communication, technological capabilities, and system integration. A scoring-based assessment methodology was applied to three international air cargo carriers to enable comparative evaluation of their digital maturity. Results: The assessment revealed substantial differences in digitalization among the evaluated carriers, indicating that higher levels of system integration, automation, and real-time data utilization revealed substantial differences in digital maturity among the evaluated carriers. Conclusions: The proposed framework provides a structured, sector-specific approach for assessing digitalization in air cargo logistics. It contributes to existing research by enabling systematic comparison of digital maturity among air cargo carriers while providing a practical benchmarking and decision-support tool for digital transformation initiatives.

Logistics doi: 10.3390/logistics10070159

Authors: Rick Acosta-Vega Nathalia Chaparro-Hernandez Enrique Delahoz-Domínguez

Background: Perishable agri-food supply chains require logistics networks that remain economically viable despite fluctuations in demand, transportation costs, and market prices. This study develops and evaluates a two-echelon logistics network for the banana supply chain in Magdalena, Colombia. Methods: A mixed-integer linear programming model was formulated to maximise daily profit by jointly determining collection-centre activation and product flows among 14 producers, five candidate collection centres, and two commercial buyers. The deterministic solution was complemented by sensitivity analysis and 1000 Monte Carlo optimisation scenarios incorporating variability in demand, transportation costs, and selling prices. Results: Under nominal conditions, all five collection centres were activated, the full demand of 42,000 kg/day was served, and the optimal profit was USD 3093/day. Centres C1–C4 operated at full capacity, whereas C5 reached 42.9% utilization. Under uncertainty, the mean profit decreased to USD 1955.70/day, the mean unmet demand was 954.03 kg/day, and shortages occurred in 72.3% of scenarios. C1–C4 remained the network core, while C5 acted as a flexible contingency facility. Conclusions: The proposed framework reveals an efficiency–resilience trade-off overlooked by deterministic optimisation. Demand growth and capacity reductions are the principal operational risks, supporting investment in collection capacity and proactive demand management.

Logistics doi: 10.3390/logistics10070158

Authors: Zahra Abdalla Sajwani Hamdi Bashir Ridvan Aydin

Background: As supply chains undergo rapid transformation, the concept of supply chain viability (SCV) has gained increasing attention among scholars and industry practitioners. Despite this growing interest, the existing literature lacks a comprehensive and integrated understanding of readiness factors across SCV dimensions. Methods: To address this gap, this study conducted a systematic review of the literature. A total of 86 peer-reviewed articles published between 2015 and 2025 were included, synthesizing evidence across four SCV dimensions: agility, resilience, sustainability, and digitalization. Two-mode network representation was used to analyze cross-dimensional connections between readiness factors and SCV dimensions via degree centrality. Results: The analysis identified 36 readiness factors, 9 of which are cross-dimensional and connected to all four SCV dimensions: leadership and decision-making, stakeholder integration, customer relationship and engagement, partner collaboration and readiness, advanced analytics, technological/digital capabilities, real-time data visibility, information and communication technology infrastructure availability, and digital transformation/smart technologies in supply chain management. Conclusions: Readiness factors vary across SCV dimensions, with some spanning multiple dimensions and others remaining specific. SCV strategies should account for these differences rather than treating factors as uniform.

Logistics doi: 10.3390/logistics10070157

Authors: Leon Döhler Alexander Grahle Michael Görges Marius Held Volkmar Lüthen Diego Fadranski Dietmar Göhlich

Background: Road transport accounts for 73% of transport-related greenhouse gas emissions within the EU, 27% of which are attributable to heavy-duty vehicles. In order to reduce emissions in the area of heavy-duty commercial vehicles, electrifying the fleet offers a perspective. As part of a cooperation between TU Berlin, Siemens and BLG Logistics within the Mobility2Grid research campus, an analysis was carried out to determine how an exemplary BLG depot for regional logistics transport with six diesel trucks can be converted to battery–electric trucks. Methods: This analysis was conducted under a fixed depot schedule with defined dwell times and charging opportunities, with the aim of developing practical recommendations for the acquisition of suitable vehicles and infrastructure. To this end, simulations were carried out using the eFlips consumption and depot simulation software developed at TU Berlin. Results and Conclusions The results show that electrification for regional logistics transport can already be fully implemented with the current state of the art technology and that neither very large batteries nor very high charging powers are required for technically feasible and economically balanced operation. Notably, the cost-optimal battery capacities identified (approximately 200–230 kWh) are currently smaller than those of commercially available 40 t electric trucks, revealing a gap between the model-optimal configuration and present market offerings. Based on the identified optimal configuration, a life cycle assessment (LCA) is conducted to evaluate the environmental impact of fleet electrification. Over a 10-year lifetime, the battery–electric fleet reduces cumulative greenhouse gas emissions by approximately 53% compared to the diesel baseline, with operational-phase savings clearly outweighing higher production-related emissions. The combined techno-economic and environmental assessment provides a structured decision basis for depot-centered fleet electrification.

Logistics doi: 10.3390/logistics10070156

Authors: Amina Meskaoui Hakim Nasaoui Rania Rejjaoui Adil El Amri Abdelhak Sahib Eddine

Background: Global logistics generates 16–25% of greenhouse gas emissions, yet small and medium-sized enterprises (SMEs) in developing economies lack the digital infrastructure to measure and improve their sustainability performance. Business intelligence (BI) systems can support data-driven sustainability decisions, but their application in SME logistics remains poorly understood, and no prior review has examined this intersection with a developing-economy focus. Methods: We conducted a systematic literature review following PRISMA 2020 guidelines, searching Scopus, Web of Science, and IEEE Xplore for peer-reviewed articles published between 2015 and April 2026. Two reviewers independently screened 412 records; 67 studies met inclusion criteria. Results: Five thematic clusters emerged: BI tools for logistics, sustainability KPI frameworks (triple bottom line [TBL], environmental–social–governance [ESG], Sustainable Development Goals [SDGs]), ERP integration, SME-specific barriers, and geographic gaps. Of the studies, 92% originate from developed economies; Africa and MENA remain almost entirely absent. No study combines open-source ERP with a validated TBL KPI framework for logistics SMEs. Conclusions: We propose a six-priority research agenda targeting empirical validation in developing economies and open-source BI solutions for SME logistics sustainability.

Logistics doi: 10.3390/logistics10070155

Authors: Giacomo Lupi Andrea L’Afflitto Riccardo Manzini Gabriele Sirri

Background: Four-way shuttle-based storage and retrieval systems (FSS/RSs) have recently emerged as flexible and scalable solutions for high-density warehousing, enabling shuttle movement in four directions and supporting multi-deep dual-access storage configurations. However, these features increase the complexity of vehicle coordination and collision management. This study proposes a multi-agent path-planning methodology for FSS/RSs with multi-deep dual-access lanes hosting homogeneous items. Methods: An A*-based path-planning framework was developed and integrated with a dynamic collision-management strategy comprising collision detection, priority assignment, and collision avoidance. The methodology was evaluated through a multi-scenario analysis considering different fleet sizes, priority-assignment strategies, safety-area extensions, transaction-entry patterns, and collision-management policies. Results: The results show that fleet size is the most influential operational parameter, significantly affecting throughput, waiting times, and collision frequency. Increasing the number of vehicles improves system productivity but also increases traffic interactions and congestion. The analyses further highlight the effects of safety-area size, priority rules, and transaction-entry patterns on operational performance and system robustness. Conclusions: The proposed methodology effectively combines path planning and collision management in four-way shuttle systems, providing a decision-support tool for evaluating operational trade-offs among throughput, congestion control, and system stability in multi-deep dual-access warehouse environments.

Logistics doi: 10.3390/logistics10070154

Authors: Chanikarn Kamonsook Vatcharapol Sukhotu

Background: Digital Supply Chain Adoption (DSCA) has emerged as a critical strategic imperative associated with Operational Performance (OP); however, empirical evidence within Thailand’s food and beverage manufacturing industry remains limited. Methods: A structured survey of 200 supply chain professionals was analysed using Partial Least Squares Structural Equation Modeling (PLS-SEM) via SmartPLS 4. To ensure analytical rigor and mitigate potential method bias, a retrospective comparison design was employed. Furthermore, DSCA was operationalized as a Type II reflective-formative higher-order construct, and Digital Dynamic Capabilities (DDC) as a Type I higher-order construct. Results: DSCA was positively associated with all perceived performance dimensions, with cost reduction exhibiting the strongest direct association (β = 0.510, p < 0.001). DDC significantly moderated the statistical relationships for quality and productivity performance. However, the moderating role of DDC on cost reduction was not statistically significant. Conclusions: Within the investigated sample, DSCA was more closely associated with perceived cost efficiencies, whereas DDC showed a supplementary moderating role specific to quality and productivity outcomes. The findings are also consistent with the integrated Dynamic Capabilities View and Technology, Organization, and Environment (DCV-TOE) perspective, suggesting that statistical associations between digital transformation and operational outcomes may vary across performance dimensions rather than follow a uniform pattern.

Logistics doi: 10.3390/logistics10070153

Authors: José M. Pérez-Canosa M. Natividad López-López Will van’t Hek Lidia Pérez-López

Background: Current international regulations for cargo securing rely on simplified assumptions that may not accurately represent the behavior of oversized cargo, particularly regarding rotational inertia and ship motion effects, which are critical under tipping conditions. Methods: This study presents a methodology for the evaluation, modeling and optimization of lashing systems for large cargo units. A comparative analysis between the CSS Code and DNV guidelines is performed to assess differences in the estimation of ship-induced accelerations and the resulting tipping moments. Simulations are performed considering different stowage positions, environmental conditions, and lashing configurations. Predictive mathematical models are developed using Design of Experiments (DOE) and Response Surface Methodology (RSM). Results: The results reveal that the CSS Code systematically leads to more conservative requirements, significantly increasing the number of required lashing devices compared to DNV guidelines. The influence of lashing angles is quantified, identifying optimal configurations that minimize securing effort while ensuring tipping equilibrium. The developed models accurately estimate the number of lashing devices required for both longitudinal and transverse tipping. Conclusions: The methodology is validated through a real case study involving heavy offshore cargo and provides practical decision-support tools. The proposed approach enables more efficient and reliable securing design in maritime cargo transport.

Logistics doi: 10.3390/logistics10070152

Authors: Vangelis Malamas Georgios Lagoumitzis Panayiotis Kotzanikolaou Theodore G. Voutsinas Thomas K. Dasaklis

Background: Traceability has gained significant importance in supply chain (SC) networks, especially driven by the growing need for transparency, regulatory compliance and consumer assurance. Although blockchain technology addresses several traditional traceability challenges, granularity, interoperability and integration with existing Enterprise Resource Planning (ERP) systems remain open problems. Methods: In this paper, we propose an integrated blockchain-enabled framework aimed at granular traceability in SC networks. The proposed framework supports the tokenization of the Bill of Materials (BoM) and introduces append-only versioned tokens that capture state evolution across SC stages. Security and privacy are managed through a baseline Role-Based Access Control (RBAC) policy, while EPCIS GS1 event modeling supports standardized data exchange between ERP middleware and the blockchain layer. To examine its applicability, we implement a proof-of-concept prototype and apply the framework to an illustrative wheat SC scenario. Results: Finally, we provide a controlled performance and feasibility analysis based on a private Ethereum/Ganache environment. Conclusions: The results should be interpreted as proof-of-concept evidence of technical feasibility rather than as production-grade validation.

Logistics doi: 10.3390/logistics10070151

Authors: Qian Huang Yao Hu Shunichi Ohmori

Background: The Physical Internet (PI) promotes resource sharing among independent firms. This can improve logistics efficiency, but shared route capacity and limited compensation may also create unequal outcomes among firms. Methods: This study develops a framework for coordinated logistics planning under shared route capacity constraints. The framework includes two coordination rules. Model 3.3 is an efficiency-oriented participation-guaranteeing rule with individual rationality constraints. Model 3.4 is a fairness-oriented rule that minimizes the maximum firm-level disadvantage under a limited compensation budget. Numerical experiments are conducted using a stylized Japanese domestic consumer goods distribution network. Results: Coordinated planning reduces total logistics cost compared with decentralized sequential allocation. Model 3.3 achieves the lowest system cost but gives benefits unevenly. Model 3.4 gives more balanced firm-level outcomes and improves the worst-off firm in the tested scenarios. The results also show that substantial fairness improvements can be obtained through small route-allocation changes. Conclusions: The study shows how two coordination rules can be used in PI-oriented logistics coordination. Model 3.3 is useful when firms need a no-loss guarantee, especially in an early stage. Model 3.4 is useful in a mature or repeated coordination stage, where the platform needs to avoid excessive disadvantage.

Logistics doi: 10.3390/logistics10070150

Authors: James Byrne Paul Liston

Background: Humanitarian logistics decisions extend beyond immediate relief delivery to include preparedness, recovery, service continuity and the development of durable local capabilities. Simulation can support these decisions under uncertainty, yet the evidence remains fragmented across logistics domains, modelling approaches and phases of the relief–development continuum. This review synthesises how simulation has been used in humanitarian logistics and identifies where the evidence is concentrated and where important gaps remain. Methods: A systematic scoping review was conducted in accordance with PRISMA-ScR and PRISMA-S, using multi-disciplinary and specialist database searches supplemented by backward and forward citation searching. Included studies were coded by logistics decision problem, continuum phase, decision level, performance outcome, simulation approach and operational grounding. Results: The literature is concentrated in preparedness and response, particularly around coordination, network design, inventory, allocation, transport and capacity. System dynamics, agent-based modelling and discrete-event simulation are well established, whereas hybrid simulation and digital twin applications remain limited. Early recovery, reconstruction, development-oriented transition and practice-embedded modelling are comparatively underdeveloped. Conclusions: Simulation-supported humanitarian logistics is strongest for structured preparedness and response problems. Future research should connect decisions across phases and strengthen beneficiary-sensitive, operationally grounded modelling of recovery, localisation, service continuity and longer-term logistics capability.

Logistics doi: 10.3390/logistics10070149

Authors: Mohammad Hori Bernd Noche Abbas Horri

Background: Retail product recognition is difficult in practice because products often look similar, class distributions are unbalanced, and annotations usually contain only one observed product label, even though products belong to broader category structures. This study addresses this setting as classification under incomplete supervision rather than as a fully annotated multi-label problem. Methods: We evaluate a lightweight hierarchy-aware recognition framework on a laboratory-based retail dataset containing real supermarket products. Visual features are extracted with a pretrained ResNet-50, reduced by truncated singular value decomposition (TSVD), and classified using class-conditional kernel density estimation (KDE). A coarse-to-fine refinement step first assigns each sample to one of seven product groups and then applies a group-specific classifier. Results: The hierarchical TSVD-KDE model achieved 83.7% Top-1 accuracy, 95.8% Top-5 accuracy, and 71.8% macro-averaged F1-score, improving over the flat TSVD-KDE variant and the convolutional neural network (CNN) linear baseline. For rare classes, the model reached 62.4% Top-1 accuracy while maintaining an average inference time of 6.1 ms per sample. Conclusions: The results suggest that combining compact visual representations with probabilistic classification and a simple product hierarchy can improve balanced recognition performance without relying on a large end-to-end architecture.

Logistics doi: 10.3390/logistics10070148

Authors: Slim Belaid Houssein Ballouk

Background: Artificial intelligence (AI) is increasingly discussed as a means of improving procurement efficiency and supply chain agility, yet its role in supplier evaluation remains insufficiently understood, particularly when decisions depend on fragmented information, cross-functional coordination, explainability, and managerial accountability. This study examines how AI may augment decision-making agility in supplier evaluation. Methods: An exploratory qualitative single-case study was conducted in a large multinational manufacturing company. Data were collected through 18 semi-structured interviews with procurement, logistics, quality, operations, and ERP/process actors, and analyzed through a Gioia-inspired thematic analysis, complemented by a descriptive assessment of theme recurrence. Results: The findings show that supplier evaluation is constrained by informational fragmentation, weak organizational memory, limited explainability, and the need to preserve contextual human judgement. AI was not perceived as a substitute for procurement professionals but as a decision-support infrastructure that may reconnect dispersed supplier knowledge, detect recurring problems earlier, and support transparent recommendations. Conclusions: The study develops a preliminary conceptualization of AI-augmented procurement agility as a bounded, process-level capability composed of AI-enabled supplier sensing, AI-supported interpretive integration, explainable decision support, and human-supervised responsiveness. The findings remain context-dependent and require further validation through comparative and longitudinal research.

Logistics doi: 10.3390/logistics10070147

Authors: Najat Toufah Alaa Eddine El Moussaoui Taoufiq El Moussaoui Marc Ardizio Aymen Benkhouili

Background: This study examines how humanitarian supply chain cooperation in Morocco may evolve toward 2030, focusing on the roles of donors, volunteers, and digital technologies in strengthening coordination, operational performance, and resilience in crisis environments. Methods: A mixed-methods approach was adopted, combining qualitative data collected through interviews and focus groups with 57 humanitarian actors and quantitative data obtained from 1183 logistics professionals. Regression analysis, analysis of variance (ANOVA), and qualitative foresight techniques were employed to explore current cooperation patterns and future humanitarian supply chain dynamics. Results: The findings indicate that donors are increasingly expected to support digital coordination, predictive planning, and capacity-building initiatives rather than acting solely as financial contributors, while volunteers continue to play a critical role in adaptive and decentralized operations, particularly in rural areas. The results further suggest that digital technologies may enhance visibility, responsiveness, and collaboration when integrated into human-centered governance systems. Conclusions: The study proposes an integrated socio-technical framework for understanding humanitarian supply chain cooperation toward 2030 and provides practical insights for developing resilient, collaborative, and future-ready humanitarian logistics systems in emerging economies.

Logistics doi: 10.3390/logistics10070146

Authors: Klavdij Logožar

Background: High-technology supply chains are interdependent logistics infrastructures in which digital, energy, manufacturing, cloud and orbital layers are tightly coupled. This paper examines how such layering changes supply chain resilience and systemic vulnerability. Methods: The paper develops an analytical–conceptual framework linking supply chain resilience, interdependent infrastructure theory and network topology. It introduces Topological Phase Vulnerability (TPV), capturing proximity to structural fragility thresholds, and the Shock Amplification Coefficient (SAC), conceptualizing disruption amplification as a function of centrality concentration, cross-layer coupling and reconfiguration capacity. The framework is supported by a fuzzy-inspired diagnostic scorecard and stylized assessment of alternative infrastructure configurations. Orbital computing is an extreme illustrative context because it combines dependence on advanced semiconductor fabrication, hyperscale cloud orchestration, energy systems, launch capacity and logistics coordination. Results: Highly centralized configurations are more likely to transform local disruptions into cross-layer cascades, whereas modular and distributed configurations are more likely to contain disruption through redundancy, substitutability and rerouting. Conclusions: Resilience in next-generation logistics infrastructure depends not only on capacity or component reliability, but also on topology. Centrality dispersion, modularity and reconfiguration capacity are critical design principles for reducing shock amplification in high-technology supply chains.

Logistics doi: 10.3390/logistics10070145

Authors: Tawinan Simajaruk Jirapan Liangrokapart

Background: Strengthening, coordinating, and sustaining rail freight services is one of the most pressing yet neglected challenges for transport planners in developing economies. Focusing on the institutional context of Thai freight transport, we assess, contextualise, and rank the collaboration factors shaping rail freight competitiveness. Methods: MICMAC analysis was selected because it does not require a pre-defined hierarchical structure and it is computationally straightforward for small variable sets. A qualitative study comprising semi-structured interviews was conducted with participants from government transport agencies, the State Railway of Thailand (SRT), private logistics operators, and freight customers. Results: The analysis extracted six key factors: government policy, finance, infrastructure readiness, technology and innovation, information sharing, and human resource capacity. Government policy alone occupies the driving quadrant, exerting the strongest systemic influence. Finance and infrastructure readiness emerge as linkage factors, simultaneously shaping and being shaped by the wider network, whereas technology, information sharing, and human resources sit in the dependent quadrant and respond to change. Conclusions: This classification allows us to derive seven collaboration strategies matched with appropriate policy levers; the three highest-ranked are policy collaboration, economic instruments, and multimodal integration.

Logistics doi: 10.3390/logistics10070144

Authors: Alaa Eddine El Moussaoui Taoufiq El Moussaoui Najat Toufah Marc Ardizio

Background: The rapid digitalization of warehouse logistics has accelerated the adoption of smart industrial robots, AI-driven autonomous vehicles, and drones to enhance operational coordination and supply chain performance. However, empirical evidence regarding the combined operational implications of these autonomous technologies within emerging-market logistics environments remains limited. This study examines the relationships between autonomous warehouse technologies and perceived warehouse operational performance in Morocco. Methods: A quantitative cross-sectional research design was employed using survey data collected from 1753 logistics professionals operating in warehouses connected to the SoftLogistics platform. Exploratory Factor Analysis (EFA), Confirmatory Factor Analysis (CFA), and Structural Equation Modeling (SEM) were conducted to evaluate the proposed relationships and interaction effects among the study constructs. Results: The findings indicate that smart industrial robots, AI-driven autonomous vehicles, and drones are positively associated with perceived warehouse operational efficiency, operational accuracy, and warehouse resilience. The results further suggest that technological interoperability, workforce readiness, organizational adaptation, and AI-enabled coordination mechanisms may enhance the operational contribution of autonomous warehouse systems. Conclusions: Autonomous logistics technologies are associated with smart warehouse transformation and improved operational performance within emerging logistics environments. The findings also highlight the importance of organizational and socio-technical readiness for the implementation of autonomous warehouse technologies.

Logistics doi: 10.3390/logistics10070143

Authors: Aizhan Kamysbayeva Alisher Khussanov Botagoz Kaldybayeva Oleksandr Prokhorov Zhakhongir Khussanov Saule Bekzhanova Marat Sabyrkhanov Aikerim Issayeva

Background: Agricultural logistics in Kazakhstan is critical for export-oriented supply chains, but its resilience is limited by infrastructure constraints, fluctuating export demand, and insufficient coordination between market and logistics processes. Methods: This study develops a conceptual multi-level model of the agricultural logistics system and a hybrid simulation model combining system dynamics and discrete-event simulation to analyze intermodal transportation under demand and capacity constraints. The model integrates demand formation, storage, transport, and export operations, as well as feedback mechanisms between fulfilled demand, repeat orders, and logistics performance. The model is implemented in AnyLogic 8.9. Results: The conceptual model structures the interaction of key participants, logistics facilities, and infrastructure levels within Kazakhstan’s agricultural logistics system. Simulation experiments reproduce cyclic logistics behavior and show that reduced logistics capacity increases the demand gap and system pressure, while stronger market signals intensify demand and infrastructure load. The results confirm that resilience depends on the balance between demand activation, logistics capacity, and replenishment policy. Conclusions: The proposed approach provides a tool for analyzing the resilience of agricultural intermodal logistics in Kazakhstan and supports scenario-based evaluation of infrastructure and market factors. The novelty lies in combining a conceptual multi-level logistics model with hybrid simulation of demand and logistics flows.

Logistics doi: 10.3390/logistics10070142

Authors: Nicoletta González-Cancelas Beatriz Molina-Serrano Francisco Soler-Flores Javier Vaca-Cabrero

Background: Sustainable and smart logistics transition requires tools that connect environmental, energy, social and digital performance with transport structure. This study proposes an exploratory classification framework for European maritime–port logistics systems using Eurostat-based country-year observations. Methods: A composite transition profile was constructed from environmental, energy, social and digital indicators using min–max normalization, equal weighting and tercile classification into low, medium and high profiles. A shallow decision tree classifier was applied to identify transport, modal structure and maritime–port activity variables that discriminate between profiles. Results: Road freight transport intensity was the main discriminator, followed by inland passenger modal structure variables. Maritime–port activity variables were included in the initial predictor set but were not retained by the final tree, indicating that transition profiles are more strongly differentiated by inland logistics and modal configuration at the country-year level. The model showed moderate performance, with a five-fold cross-validated accuracy of 0.561, above the majority-class baseline. Conclusions: The framework provides an interpretable diagnostic tool for identifying logistics-related transition patterns and supporting sustainable logistics planning. Its exploratory scope and data limitations are explicitly acknowledged.

Logistics doi: 10.3390/logistics10060141

Authors: Nidal Mansouri Aziz Soulhi

Background: Evaluating centralized purchasing performance is a complex multi-criteria decision-making problem involving uncertainty, linguistic assessments, and subjective judgments from internal clients. Existing approaches provide limited support for handling these characteristics simultaneously. Methods: This study proposes a Mamdani fuzzy inference model integrating four criteria: Service Quality, Responsiveness, Compliance, and Collaboration. The fuzzy rule base was developed using expert knowledge and organizational evaluation practices. The model was applied to a real industrial case study based on an annual evaluation conducted collaboratively by four internal evaluators. Results: The model transformed qualitative assessments into an interpretable performance score while capturing interactions among evaluation criteria and handling uncertainty in the evaluation process. Conclusions: The proposed approach provides a structured decision-support framework for evaluating centralized purchasing performance. It enables the integration of linguistic assessments and expert knowledge, offering a flexible and coherent evaluation tool for industrial environments.

Logistics doi: 10.3390/logistics10060140

Authors: Neyfe Sablón Cossío Giselle Rodríguez Rudi Daniel Coq-Huelva Alexander Pulido-Rojano

Background: Given the disruption of the global market, technological factors are impacting food supply chains (FSCs). As a result, traceability is emerging as a potential solution for faster and more secure decision-making within FSCs. Methods: This research aims to define a traceability model for a shrimp food supply chain (FSC) in Ecuador using structural equation modelling which insists not only on the main factors that explain its overall performance but also on the effects of the changes in agents’ behaviours. The research was conducted between March and December 2025. A 41-item questionnaire was used for data collection and was administered to 73 stakeholders. The information was reduced and assembled in five main factors. A structural equation model was applied to explore the impact of agents’ coordination, digital transformations, and customer satisfaction on the traceability of the shrimp FSC. Results: The results show that customer satisfaction is broadly affected by the improvements in chain traceability. Furthermore, the results demonstrate the relevance of coordination, digitalization, and traceability as key factors for strengthening the FSC’s performance. Conclusions: The results could contribute to Sustainable Development Goals 12 and 17 and be applicable to other agri-food chains.

Logistics doi: 10.3390/logistics10060139

Authors: Mai S. Abdelaziz Tamer F. Abdelmaguid

Background: Egypt is one of the top steel producers in the Middle East and Africa, yet it faces acute water scarcity and rising energy costs, making it a critical context for studying trade-offs among carbon emissions, water ecological effects, and operational cost in steel supply chain. Methods: Using a multi-objective optimization model based on real data from a major Egyptian steel manufacturer, this study evaluates trade-offs among cost, tardiness, and environmental impact measured by carbon emissions and water ecological effects. Unlike prior studies, this study demonstrates that dedicated warehousing enables batch-level traceability of returned scrap while reducing material handling travel time and carbon emissions. The AUGMECON method generates Pareto-optimal solutions, and sensitivity analysis is conducted on six parameters: scrap take-back rate, demand variability, raw material price, energy cost, production capacity, and carbon tax. Results: Demand and raw material prices dominate performance: a 5% demand increase raises cost by 8.6%, and a 15% raw material price increase raises cost by 32.7%. The knee-point solution achieves 58.18 billion EGP, 0.99 months tardiness, and 2096 million kg CO2 over nine months. Conclusions: This study quantifies the impact of the circular economy and operational parameters on steel supply chain performance under a dedicated warehousing policy.

Logistics doi: 10.3390/logistics10060138

Authors: Patrik Eszes László Buics

Background: This study seeks to explore the link between smart city development and demand-responsive transport, analyze the ways of integrating demand-responsive transport into smart mobility concepts, estimate public perceptions about those phenomena, and review any international efforts aimed at promoting sustainable environmentally friendly transport options for cities in the EU. Methods: A systematic literature review was used as a basis for the current study; it is grounded in the analysis of scientific sources available in Scopus with the application of both PEO and PRISMA models. Survey analysis was also applied in order to examine public perception towards smart cities and DRT. Results: The results show that, even though the topics of smart cities and smart mobility have received significant attention in scholarly research, their links to demand-responsive transport still need more exploration. This paper describes the main features of smart mobility, urban mobility, and demand-responsive transport as well as the implications associated with each concept from an environmental, social, and operational perspective. In addition, the current international activities and examples of sustainable and flexible mobility systems are discussed. Conclusions: This paper presents a thorough examination of the relationships among smart mobility, urban mobility, and demand-responsive transportation.

Logistics doi: 10.3390/logistics10060137

Authors: Lei Jiang Anan Pongtornkulpanich Namphone Chaidee

Background: Although green supply chain management (GSCM) has been widely examined, prior studies have often treated it as a homogeneous construct and have paid limited attention to how different types of GSCM practices operate in logistics firms. This study addresses this gap by distinguishing between technical GSCM practices and behavioral GSCM practices and examining how both dimensions influence organizational performance through green innovation culture (GIC). Methods: Drawing on data from a cross-sectional survey of 426 logistics practitioners involved in supply chain, operations, and sustainability-related functions in Guangzhou, China, the study tested the proposed model using structural equation modeling (SEM). Results: Both technical and behavioral GSCM practices positively influence GIC, with behavioral practices having a stronger effect. GIC significantly improves organizational performance. Technical and behavioral GSCM practices also directly enhance organizational performance, indicating partial mediation. The indirect effect of behavioral GSCM practices through GIC is stronger, suggesting that behavioral governance is especially important for developing an innovation-oriented green culture. Conclusions: The study advances GSCM and green innovation literature and suggests logistics firms can achieve more sustainable performance improvements by combining technological upgrading with leadership support, employee involvement, stakeholder collaboration, and an innovation-oriented green culture.

Logistics doi: 10.3390/logistics10060136

Authors: Amal Belmabrouk Arij Lahmar Houssam Chouikhi Hatem Bentaher

Background: The Vehicle Routing Problem (VRP) is foundational to logistics optimization, yet its alignment with the Triple Bottom Line (TBL) and UN Sustainable Development Goals (SDGs) remains fragmented. This study conducts a strategic bibliometric audit of 301 peer–reviewed publications (1992–2025) to quantify the evolutionary progression and thematic maturity of sustainable routing research. Methods: A four–stage scientometric framework was employed, utilizing Scopus–based data retrieval, longitudinal mapping, and Python 3.14–driven text mining to visualize keyword co–occurrence networks, author collaborations, and regional research clusters. Results: Findings reveal a pronounced “Sustainability Asymmetry,” where 51.5% of studies prioritize economic efficiency, while only 2.6% address the social pillar. Additionally, social sustainability remains an “isolated island” with minimal cross–citation to the research core. Geographic analysis identifies a heavy concentration in China, the USA, and Western Europe, uncovering a critical North–South—collaboration gap. Conclusions: The study proves that while environmental themes reached maturity between 2018 and 2022, social indicators exhibit a significant maturity lag. This quantified social deficit, centered on the neglect of SDG 3 and SDG 10, mandates a fundamental paradigm shift toward a geographically inclusive and socially conscious research agenda to ensure global logistical equity.