Search Results (661)

Rail freight transport represents a key tool for the decarbonisation and greening of logistics chains within the European Union. However, in many Central and Eastern European countries, including the Slovak Republic, a vast network of industrial sidings (rail spurs) remains underutilized or neglected. This reduces the overall efficiency of transport infrastructure and represents a missed opportunity for sustainable transport development. This paper proposes a comprehensive public support model for rail sidings. It combines legislative analysis, a tax incentive mechanism, and analytical evaluation of transport and investment benefits. The methodology calculates the potential transport output of reactivated sidings. It also introduces three quantitative indexes: the Siding Efficiency Index (IEV), the Comprehensive Importance Index (ICV), and the Reactivation Value Index (RVI). These indicators allow for a structured, objective assessment of siding suitability for restoration and public funding. We applied the model to a sample of five sidings in Slovakia, deriving values from expert evaluations. The results show that objective indicators, performance estimates, and targeted public support can identify infrastructure with high revitalization potential. These tools help reintegrate such assets into sustainable transport flows. The analysis indicates that reactivating 5% of existing sidings could shift hundreds of thousands of tonnes of freight annually from road to rail. This change would reduce emissions and improve network efficiency. Full article

Implementing solutions consistent with the Industry 4.0 concept, including digitalization and process automation, plays a significant role in improving the efficiency and sustainable development of manufacturing companies. One of the key areas of this transformation is internal logistics, where simulation technologies and autonomous transport systems are gaining increasing importance. The aim of this article was to assess the potential of using computer simulation as a tool to support the process of reducing the electricity consumption of electric forklifts in logistics processes. The developed methodology can serve as a foundation for a wider use of digital tools in internal logistics planning, covering not only production goals but also improving energy efficiency and reducing emissions. Importantly, the proposed approach can be a starting point for decision makers in manufacturing and logistics companies, encouraging the use of simulation as a tool to support decisions. In the longer term, the results open the way for analyses focused on the implementation of green technology solutions and the integration of electric vehicles with renewable energy sources, in line with corporate sustainable development strategies. Full article

The betel palm is a critical economic crop on Hainan Island. Accurate and timely maps of betel palms are fundamental for the industry’s management and ecological environment evaluation. To date, mapping the spatial distribution of betel palms across a large regional scale remains a significant challenge. In this study, we propose an integrated framework that combines knowledge-based and machine learning approaches to produce a map of betel palms at 10 m spatial resolution based on Sentinel-1/2 data and Google Earth Engine (GEE) for 2023 on Hainan Island, which accounts for 95% of betel nut acreage in China. The forest map was initially delineated based on signature information and the Green Normalized Difference Vegetation Index (GNDVI) acquired from Sentinel-1 and Sentinel-2 data, respectively. Subsequently, patches of betel palms were extracted from the forest map using a random forest classifier and feature selection method via logistic regression (LR). The resultant 10 m betel palm map achieved user’s, producer’s, and overall accuracy of 86.89%, 88.81%, and 97.51%, respectively. According to the betel palm map in 2023, the total planted area was 189,805 hectares (ha), exhibiting high consistency with statistical data (R² = 0.74). The spatial distribution was primarily concentrated in eastern Hainan, reflecting favorable climatic and topographic conditions. The results demonstrate the significant potential of Sentinel-1/2 data for identifying betel palms in complex tropical regions characterized by diverse land cover types, fragmented cultivated land, and frequent cloud and rain interference. This study provides a reference framework for mapping tropical crops, and the findings are crucial for tropical agricultural management and optimization. Full article

In Central Asian countries (CACs) Yes. we agree to remove Highlights part atmosphere pollution is increasing due to population growth, economic growth, agricultural development, energy consumption and climate change. The countries of the region developed climate change adaptation strategies—Nationally Determined Contributions (NDCs) under the UN Framework Convention on Climate Change (UNFCCC). At the same time, regional integration, which should be a necessary condition for achieving the Sustainable Development Goals (SDGs) in the solving of general environmental problems, is not involved. This article shows the importance of a comprehensive analysis of greenhouse gas (GHG) and non-greenhouse emissions into the atmosphere for the entire Central Asian region as a single ecosystem. The energy intensity of national economies structure was chosen as the main factor determining the level of pollution. The analysis shows that over the past 30 years, the main part of the commodity exports (73.6–81.4%) of Kazakhstan and Turkmenistan has been fossil natural resources. There is a strong economic dependence on coal and other types of fuel, which leads to atmospheric emissions. The analysis shows that limited financial resources, lack of effective systemic monitoring and control of air quality that meets modern international requirements and standards, leads to absence of tangible changes in practice yet. Over 30 years in CACs, the share of CO₂ emissions associated with fuel combustion has not decreased and amounts to 78%. The key mechanisms for reducing atmospheric emissions are significantly increase investments in the transformation of the economies in the context of regional development, interstate cooperation, the introduction of environmental norms, standards harmonized with world ones, green technologies based on alternative energy, sustainable transport and logistics infrastructure. Full article

Transportation Management Systems (TMSs) play a pivotal role in streamlining logistics operations, yet selecting the most suitable TMS software remains a complex, multi-criteria decision-making problem. This study introduces a hybrid evaluation framework combining the Bayesian Best–Worst Method (BBWM) and TOPSIS to identify, weigh, and rank software selection criteria tailored to the logistics business. Drawing on insights from 13 logistics experts, five main criteria—technological competence, service, functionality, cost, and software developer (vendor)—and 16 detailed sub-criteria are defined to reflect business-specific needs. The core novelty of this research lies in its systematic weighting of TMS software criteria using the BBWM, offering robust and expert-driven priority insights for decision makers. Results show that functionality (26.6%), particularly load tracking (35.8%) and cost (22.7%), mainly software license cost (39.8%), are the dominant decision factors. Beyond operational optimization, this study positions TMS software selection as a strategic entry point for sustainable digital transformation in logistics. The proposed framework empowers business to align digital infrastructure choices with sustainability goals such as emissions reduction, energy efficiency, and intelligent resource planning. Applying TOPSIS to a real-world case in Türkiye, this study ranks software alternatives, with “ABC” emerging as the most favorable solution (57.2%). This paper contributes a replicable and adaptable model for TMS software evaluation, grounded in business practice and advanced decision science. Full article

With the rapid growth of urban logistics demand, carbon emissions and the time-varying nature of vehicle speeds have become critical challenges in sustainable transportation planning. This paper addresses a Time-Dependent Green Vehicle Routing Problem (TDGVRP) that integrates time-varying speeds, carbon emissions, and cold chain logistics under a joint distribution framework involving multiple depots and homogeneous refrigerated vehicles. A Mixed-Integer Linear Programming (MILP) model is developed, explicitly considering carbon pricing, refrigeration energy consumption, and speed variations across different time periods. To efficiently solve large-scale instances, a Three-Phase Heuristic (TPH) algorithm is proposed, combining spatiotemporal path construction, local-improvement strategies, and an Adaptive Large Neighborhood Search (ALNS) mechanism. Computational experiments show that the proposed method outperforms traditional Genetic Algorithms (GAs) in both solution quality and computation time, and in some benchmark cases even achieves better results than the commercial solver Gurobi, demonstrating its robustness and scalability. Using real-world traffic speed data, comparative analysis reveals that the joint distribution strategy reduces total logistics costs by 14.40%, carbon emission costs by 23.12%, and fleet size by approximately 25% compared to single-entity distribution. The findings provide a practical and scalable solution framework for sustainable cold chain logistics routing in time-dependent urban road networks. Full article

Hymenopellis raphanipes is a high-value edible fungus with a short shelf life and high perishability, which poses significant challenges for quality control and safety assurance throughout its supply chain. Ensuring effective traceability is essential for improving production management, strengthening consumer trust, and supporting brand development. This study proposes a comprehensive traceability system tailored to the full lifecycle of Hymenopellis raphanipes, addressing the operational needs of producers and regulators alike. Through detailed analysis of the entire supply chain, from raw material intake, cultivation, and processing to logistics and sales, the system defines standardized traceability granularity and a unique hierarchical coding scheme. A multi-layered system architecture is designed, comprising a data acquisition layer, network transmission layer, storage management layer, service orchestration layer, business logic layer, and user interaction layer, ensuring modularity, scalability, and maintainability. To address performance bottlenecks in traditional systems, a multi-chain collaborative traceability model is introduced, integrating a mainchain–sidechain storage mechanism with an on-chain/off-chain hybrid management strategy. This approach effectively mitigates storage overhead and enhances response efficiency. Furthermore, data integrity is verified through hash-based validation, supporting high-throughput queries and reliable traceability. Experimental results from its real-world deployment demonstrate that the proposed system significantly outperforms traditional single-chain models in terms of query latency and throughput. The solution enhances data transparency and regulatory efficiency, promotes sustainable practices in green agricultural production, and offers a scalable reference model for the traceability of other high-value agricultural products. Full article

Supply chain resilience is a growing concern as risk becomes increasingly challenging to interpret and anticipate due to sudden global events that disrupt the core of global supply chains. This paper discusses the use of advanced technologies to enhance supply chain resilience, proposing a two-step hybrid fuzzy analytic hierarchy process (FAHP) and the technique for order of preference by similarity to ideal solution (TOPSIS) approach that evaluates a set of different supply chain KPIs or criteria that trigger possible supply chain risks, with a focus on transportation disruptions. Using FAHP, the highest potential risks from disasters are identified, and TOPSIS is used to rank alternative solutions that enhance supply chain resilience. The approach is tested on real-world applications across multiple supply chain systems involving various companies and experts to demonstrate its validity, feasibility, and applicability. Based on five criteria and six alternatives per case study, the findings showed that for manufacturing supply chains, the highest risk was attributed to travel time (46%), and the most effective solution to mitigate it was found to be strengthening highway networks (0.72). For transportation, delivery time (56%) was the primary risk, addressed by green logistics and sustainability (0.89). Full article

The purpose of this study was to establish the relationship between the chilling resistance of rubber trees and the bark-bleeding characteristics caused by chilling stress, considering physiological indicators in rubber tree bark, cell wall chemical components, fiber morphologies, and tensile properties. This offered a unique perspective for examining the underlying mechanisms of latex bleeding and chilling stress in Hevea brasiliensis. One-year-old seedlings and two-year-old twig segments in five- and twenty-one-year-old rubber trees (5YB and 21YB) were used to compare the age-mediation differences in their various parameters. Meanwhile, the LT₅₀ values were calculated with Logistic regression analysis of relative electrical conductivity (REC) data under gradient low temperatures. Subsequently, changes in corresponding parameters of 1-year-old seedling stem bark at different ages were determined, and the bark-bleeding characteristics of seedlings and twig segments were analyzed under artificially simulated chilling stress, respectively. A correlation analysis between semi-lethal temperature (LT₅₀) values, relative water content (RWC) values, bark-bleeding characteristics, cell-wall chemical component contents, fiber dimensions, and tensile property parameters was implemented to estimate interrelationships among them. The LT₅₀ values ranged from −2.0387 °C to −0.8695 °C. The results showed that the chilling resistance order of rubber trees at different ages was as follows: 21YB (2-year-old twig bark from 21-year-old rubber trees) > 5YB (2-year-old twig bark from 5-year-old rubber trees) > SLB (semi-lignification bark in 1-year-old seedlings) > GB (green bark in 1-year-old seedlings). The chilling resistance of seedlings and twig segments in rubber trees was highly positively (p < 0.001) related to fiber morphologies. Chilling-induced bark-bleeding characteristics were significantly correlated (p < 0.001) with fiber morphologies, bark tensile properties, and cell-wall components. The analysis data in this study contribute towards building a comprehensive understanding of the mechanisms of chilling-induced bark bleeding needed not only in rubber tree cultivation but also in sustainable rubber production. Full article

Background: This systematic review explores the integration of green practices into humanitarian supply chains to mitigate environmental impacts and contribute to global decarbonization efforts. Methods: This review focused on peer-reviewed articles published between 2011 and 2024 that addressed the environmental dimension of humanitarian logistics. Studies were included if they examined environmental practices within humanitarian supply chains and excluded if they lacked focus on environmental impact or logistics. A comprehensive search of the Scopus database in April 2024 yielded 291 records, of which 51 studies met the inclusion criteria. A thematic synthesis was conducted; due to the qualitative nature of the data, no formal risk-of-bias assessment was conducted. Results: The analysis revealed increasing adoption of environmentally focused practices, such as emissions monitoring, waste reduction, and resource-efficient transportation. Key barriers included operational complexity, inadequate digital infrastructure, and the absence of standardized environmental frameworks. The review identified digital innovation, inter-organizational collaboration, and integrated environmental performance metrics as promising pathways for improvement. Despite growing awareness, significant gaps remain in the standardization and measurement of environmental performance across humanitarian supply chains. Conclusions: The findings highlight the need for further research and coordinated efforts to develop consistent, scalable green practices in the humanitarian context. Full article

The increasing environmental concerns of plastic waste have encouraged more interest in environmentally friendly packaging, but consumer willingness to pay (WTP) for green alternatives in emerging markets such as Saudi Arabia is not fully explored. This research explores the relationship between awareness of sustainability and price sensitivity in determining WTP for green packaging in the Saudi retail market. The study utilizing a mixed method included both a Contingent Valuation Method (CVM) and a Discrete Choice Modeling (DCM). In it, data was gathered and analyzed using a sample of 424 urban consumers in Saudi Arabia’s major cities. The findings of OLS regression indicated awareness of sustainability had a significant, positive effect on WTP, whereas price sensitivity had a negative effect. There was a marginal interaction effect indicating that awareness could overcome price aversion. Logistic regression supported awareness as a dominant factor in binary product choice, although price sensitivity was not significant in the said model. The multinomial logit model also showed that the type of package, environmental labels (more so the “100% recyclable” type), and price had significant effects on consumer preferences. These results indicate that there is acceptance of sustainable packaging by consumers in Saudi Arabia if the product is communicated effectively and priced competitively. Full article

Background: The growing demand for fresh food leads to extensive use of cold chain logistics (CCL) that significantly contributes to greenhouse gas (GHG) emissions due to its dependence on energy-intensive transport refrigeration units (TRUs). Understanding the need to balance food preservation with environmental sustainability, this paper explores practical strategies for reducing GHG emissions in CCL, focusing on fresh food products. Methods: The quantitative and qualitative analyses are applied to analyse data from Transport for London and Transport Scotland. Emission data were assessed to evaluate the impact of alternative TRU technologies and route optimisation practices. Results: The findings reveal that electric and cryogenic TRUs, along with improved route planning and operational practices, can significantly reduce the emissions of carbon dioxide, nitrogen oxides and particulate matter. These results highlight the potential strategy for industry-led emission reductions without compromising food quality. Conclusions: This paper recommends the coordination of government policy and industry to support technological adaptation and infrastructure upgrades and to research into real-time monitoring and renewable energy integration in CCL systems. Full article

The present paper investigates the adoption of green manufacturing approaches among industrial enterprises in Slovakia, emphasizing the interplay between institutional pressures and enterprise-level resources. Based on a survey of 88 enterprises from energy- and material-intensive sectors, the study evaluates how regional context and enterprise size influence the adoption of green practices. Using logistic regression and the chi-squared test, the findings reveal minimal regional variation, suggesting strong isomorphic effects of harmonised European Union environmental regulations. In contrast, enterprise size significantly correlates with the adoption of complex green practices, confirming the relevance of the resource-based view. These results highlight the dominance of internal capabilities over regional factors in green transition pathways within small post-transition economies. The study contributes to cross-national theorising by showing how resource asymmetries, rather than institutional diversity, shape environmental behaviour in uniform regulatory environments. Specifically, the paper examines how institutional pressures, enterprise-level resources, stakeholders, and legitimacy influence the adoption of green manufacturing practices in Slovak industrial enterprises. The study draws on institutional theory, the resource-based view, stakeholder theory, and legitimacy theory to explore the relationship between enterprise size, regional location, and the adoption levels of green manufacturing. Full article

This paper proposes the Open Competency Optimization (OCO) approach, based on adaptive combinatorial operators, to solve the Dynamic Green Traveling Salesman Problem (DG-TSP), which extends the classical TSP by incorporating dynamic travel conditions, realistic road gradients, and energy consumption considerations. The objective is to minimize fuel consumption and emissions by reducing the total tour length under varying conditions. Unlike conventional metaheuristics based on real-coded representations, our method directly operates on combinatorial structures, ensuring efficient adaptation without costly transformations. Embedded within a dynamic metaheuristic framework, our operators continuously refine the routing decisions in response to environmental and demand changes. Experimental assessments conducted in practical contexts reveal that our algorithm attains a tour length of 21,059, which is indicative of a 36.16% reduction in fuel consumption relative to Ant Colony Optimization (ACO) (32,994), a 4.06% decrease when compared to Grey Wolf Optimizer (GWO) (21,949), a 2.95% reduction in relation to Particle Swarm Optimization (PSO) (21,701), and a 0.90% decline when juxtaposed with Genetic Algorithm (GA) (21,251). In terms of overall offline performance, our approach achieves the best score (21,290.9), significantly outperforming ACO (36,957.6), GWO (122,881.04), GA (59,296.5), and PSO (36,744.29), confirming both solution quality and stability over time. These findings underscore the resilience and scalability of the proposed approach for sustainable logistics, presenting a pragmatic resolution to enhance transportation operations within dynamic and ecologically sensitive environments. Full article

Chickpea is a highly weed-prone crop with limited herbicide options and high labor demands, raising the following question: Can fall-planted legume–cereal cover crops (CCs) improve soil properties while reducing herbicide use and manual weeding pressure? To explore this, we evaluated the effect of fall-planted winter rye (WR) alone in 2021 and mixed with hairy vetch (HV) in 2022 and 2023 at Randolph farm in Petersburg, Virginia. The objectives were two-fold: (a) to examine the effect of CCs on soil properties using monthly growth dynamics and biomass harvested from fifteen 0.25 m²-quadrants and (b) to evaluate the efficiency of five termination methods: (1) green manure (GM); (2) GM plus pre-emergence herbicide (GMH); (3) burn (BOH); (4) crimp mulch (CRM); and (5) mow-mulch (MW) in suppressing weeds in chickpea fields. Weed distribution, particularly nutsedge, was patchy and dominant on the eastern side. Growth dynamics followed an exponential growth rate in fall 2022 (R² ≥ 0.994, p < 0.0002) and a three-parameter sigmoidal curve in 2023 (R² ≥ 0.972, p < 0.0047). Biomass averaged 55.8 and 96.9 t/ha for 2022 and 2023, respectively. GMH consistently outperformed GM in weed suppression, though GM was not significantly different from no-till systems by the season’s end. Kabuli-type chickpeas under GMH had significantly higher yields than desi types. Pooled data fitted well to a three-parametric logistic curve, predicting half-time to 50% weed coverage at 35 (MM), 38 (CRM), 40 (BOH), 46 (GM), and 53 (GMH) days. Relapses of CCs were consistent in no-till systems, especially BOH and MW. Although soil properties improved, CCs alone did not significantly suppress weed. Full article