Search Results (187)

This study examines the spatio-temporal evolution and restricting mechanisms of agricultural supply chain resilience in the Yangtze River Basin from a gradient perspective. An evaluation index system encompassing the dimensions of the supply side, demand side, circulation side, and support side was developed. The Entropy-Weighted TOPSIS method, kernel density estimation, and obstacle degree model were comprehensively applied to measure and dynamically analyze supply chain resilience across 11 provinces from 2013 to 2023. The findings reveal distinct spatio-temporal evolution patterns: while the overall resilience shows an upward trend, significant gradient disparities exist, with downstream areas exhibiting markedly higher resilience than the mid- and upstream regions. Regarding the restricting mechanisms, the circulation and support sides exhibit higher levels of obstacles, representing key constraints to resilience enhancement. Among these, express delivery volume, freight turnover, and local R&D personnel full-time equivalents are the core obstacle factors affecting resilience. Based on these findings, this study proposes targeted recommendations, including optimizing rural last-mile logistics, upgrading inter-provincial freight hubs, improving rail–water intermodal transport, and strengthening cold-chain infrastructure, as well as implementing differentiated regional strategies and establishing cross-regional coordination mechanisms. These recommendations aim to provide decision-making guidance for enhancing the risk-response capabilities of agricultural supply chains in the Yangtze River Basin and to promote balanced regional development. Full article

Globally, the transport sector accounts for almost a quarter of CO₂ emissions from fuel combustion and generates large amounts of pollutants, placing significant pressure on the environment and human health. By 2050, the European Green Deal requires a 90% reduction in transport-related emissions, making sustainability necessary across all modes of transport. Based on the relevant literature, this study examines the role and potential of railways in decarbonising the EU transport sector. Railway is highly efficient, consuming just 1.9% of transport sector energy while handling 16.9% of freight and 5.1% of passenger transport in the EU, yet is responsible for only 0.4% of total emissions. According to studies, greenhouse gas emissions can be reduced by improving energy efficiency, using low-carbon or renewable energy, and expanding train electrification. The greatest potential for decarbonisation lies in a modal shift to rail. However, this requires significant infrastructure investment: raising line speeds to at least 160 km/h, expanding networks, building terminals, digitalisation, and alignment with TEN-T standards. Although the EU supports the modal shift with funding programmes, the transition is not progressing as expected—the share of road freight transport increased from 74% in 2013 to 78% in 2023. Stronger investment is needed in Member States’ national policies for the development and modernisation of railways. The authors developed a Path Evaluation Matrix (PEM), a quantitative decision framework integrating the fields of energy, transport, politics, and economics. The PEM results indicate that BEMU (battery electric multiple units) is optimal for 68% of secondary lines in south-eastern Europe. Full article

This article examines the impact of intermodal wagon technical specifications and railway infrastructure parameters on electricity consumption in rail freight transport. For this purpose, a three-stage analytical model was developed. The first stage defines the core assumptions, including train length, rolling stock types, container configurations, infrastructure constraints, and the characteristics of the energy consumption model. The second stage identifies the technical constraints of specific wagons, determines representative train compositions, and performs loading simulations. The third stage evaluates energy efficiency across different loading scenarios. The case study shows that specific energy consumption varies significantly with wagon type, train mass, and route characteristics. This findings challenge the use of static energy consumption values commonly applied in the literature. The results indicate that 40-foot wagons incur high energy penalties due to their tare weight and axle count, despite offering high loading capacity. While 60-foot wagons consume less energy, they lead to a high share of empty slots under a 20 t/axle limit. In contrast, 80-foot wagons are the most energy-efficient, particularly at a 22.5 t/axle limit. Mixed consists provide a balance between operational flexibility and competitive performance. Extending train length from 600 m to 730 m increases volume but does not automatically reduce unit energy consumption. These findings highlight the need to align wagon fleet selection with infrastructure capabilities and cargo characteristics. This study therefore provides practical recommendations for planning energy-efficient intermodal operations. Full article

Background: Railways worldwide are increasingly adopting digital technologies to improve operational performance and reliability. However, digital transformation in rail freight remains challenging, particularly in developing countries where organizational, technological, and institutional barriers persist. This study aims to identify key barriers to rail freight digital transformation and propose strategies to address these challenges in Thailand’s rail freight sector. Methods: An integrated analytical approach combining Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Importance–Performance Analysis (IPA) was applied. DEMATEL was used to analyze causal relationships among seven factors influencing digital transformation barriers, while IPA evaluated their importance and performance based on a case study of the State Railway of Thailand. Results: The findings show that management has the highest causal prominence, while quality and efficiency emerge as the primary effect factor. IPA results indicate that people, collaboration, and infrastructure require priority improvement. Conclusions: The study proposes four strategic directions to support rail freight digital transformation and provides a structured framework for identifying and prioritizing digital transformation barriers in rail freight systems. The study contributes by providing a structured framework for identifying, prioritizing, and addressing digital transformation barriers in rail freight systems. Full article

Railway traffic monitoring requires robust detection technologies capable of operating reliably under real-world vibration and environmental conditions. In this work, we present the design and validation of an optical vibration sensor based on a Single-mode–Multimode–Single-mode (SMS) fiber structure for Light Rail Vehicle (LRV) detection. The sensing mechanism relies on multimodal interference in the multimode fiber (MMF), where rail-induced vibrations modify the guided mode distribution and, consequently, the transmitted optical intensity. The optical signal is converted to voltage and processed through an embedded acquisition system. Additionally, we conducted tests with freight trains and maintenance trains in order to evaluate the applicability of the sensor in other types of trains besides the LRV. We conducted laboratory experiments to assess mechanical stability, sensibility, and packaging strategies, followed by supervised field tests on an operational LRV line. The recorded time-domain signal exhibited clear modulation during train passage, and first-derivative and sliding-window variance analyses were applied to reliably identify vibration events, even in the presence of slow baseline drift. In addition, frequency-domain analysis was performed by applying the Fast Fourier Transform (FFT) to the measured signal, enabling the identification of characteristic low-frequency spectral components induced by train passage. A quantitative sensitivity assessment was further carried out by correlating the integrated spectral energy (0–12 Hz) with vehicle weight, yielding a linear response with a sensitivity of 0.0017 a.u./t and coefficient of determination $R^2=0.933$. The proposed solution demonstrated stable operation using commercially available low-cost components, confirming the feasibility of SMS-based optical sensing for railway monitoring. These results indicate strong potential for future deployment in traffic safety systems and distributed sensing networks. Full article

Modern urban transport systems face the critical challenge of fully integrating regional and international hubs into local mobility strategies. This article addresses the role of airports in shaping sustainable urban mobility, with a specific focus on their inclusion in Sustainable Urban Mobility Plans (SUMPs). Despite airports being major generators of passenger and freight traffic, they are often treated as isolated “transport islands” in spatial planning. The primary objective of this research is to develop and validate an original method for assessing the integration and transport accessibility of airports using the AirportSustainIndex. The methodology is based on a mathematical Weighted Sum Model (WSM), integrating twelve technical, economic, and environmental criteria, including travel times and costs for public vs. private transport, frequency of rail and bus connections, availability of electric vehicle infrastructure, and tariff integration. The analysis is supported by Geographic Information Systems (GIS) tools and OpenStreetMap data, allowing for a precise reflection of real-world network accessibility. The study covers two significant aviation hubs in Poland: Katowice Airport in Pyrzowice and Poznań-Ławica Airport. The results reveal a paradox: Katowice Airport, despite its significant distance from the agglomeration center (approx. 36 km), achieved a markedly higher sustainability index (0.554) than Poznań-Ławica Airport (0.301), which is located close to the city center (approx. 7 km). Key factors determining this outcome include the high frequency of metropolitan bus lines (“M” lines), the implementation of new rail infrastructure, and a coherent parking policy for low-emission vehicles. The article demonstrates that physical distance from the center is not the primary barrier to building sustainable mobility, provided that high intermodality and integration within the SUMP framework are ensured. The presented research tool is universal and can be applied by policymakers and urban planners to optimize airport-city connectivity, a necessary condition for achieving EU climate goals in the transport sector. Full article

With rising customer demands for the timeliness and quality of refrigerated goods, the efficiency and fluidity of cold chain logistics remain inadequate, resulting in a notable imbalance between supply and demand in the cold chain market. To reduce the damage of fresh produce and lower logistics costs, this paper introduces multimodal transportation into the cold chain market and performs an analysis of optimizing multimodal transportation routes for refrigerated goods. This study constructs a mixed-integer programming model for cold chain multimodal transportation, aiming to minimize total costs while considering carbon emissions and uncertain demand. An improved adaptive large neighborhood search (ALNS) algorithm is developed to solve the mathematical model, featuring improved adaptive scoring and operator selection mechanisms. The algorithm’s performance is validated through a real-world multimodal transportation network in China. Furthermore, a sensitivity analysis is performed on rail freight rates, confidence levels, and ambient temperature, from which we derive managerial insights with practical significance. Full article

Although numerous studies have examined the impact of high-speed rail (HSR) on regional economic development, few have explored this relationship from a network perspective—a research gap this paper seeks to fill. Specifically, this paper aims to clarify the theoretical mechanism through which the HSR network affects the spatial evolution of regional industries, focusing on the new industry entry. We improve the local spread model by incorporating the HSR network as a key component and perform empirical analyses using the Spatial Durbin Model (SDM) and spatial mediation effect model, drawing on data from Chinese A-share-listed companies. The findings indicate that China’s regional industries underwent spatial evolution characterized by “diffusive agglomeration”. In terms of direct effects, connectivity ranks as the most influential HSR network indicator; however, when both direct and spillover effects are taken into account, accessibility becomes the primary factor, underscoring its vital role in reshaping the spatial distribution of industries. Additionally, the HSR network exerts a slightly stronger impact on industrial spatial diffusion (fueled by knowledge spillovers) than on industrial agglomeration (driven by market size), and its attraction to new industry entry is notably greater in peripheral regions than in core regions. These results demonstrate that HSR, characterized by “transporting people rather than goods”, mainly facilitates the exchange of knowledge, technology and information instead of reducing freight costs, offering valuable insights for optimizing regional industrial layouts. Full article

Combining with the wheel–rail rolling contact models and extended finite element method (XFEM), this study systematically analyses the influence of wheel thermal expansion induced by braking thermal load on the tread cracking behavior of railway freight trains during the emergency braking process. Unlike the well-documented effect of material softening at elevated temperatures, the key contribution of this work lies in identifying and elucidating the dominant role of thermally induced geometrical changes in the contact conditions. The results demonstrate that wheel thermal expansion significantly alters the shape of the contact spot and the stress distribution, thereby reconstructing the mechanical driving force at the crack tip. Specifically, thermal expansion effectively suppresses Mode I cracking. Although it slightly reduces the magnitude of ΔK_II, the primary and critical outcome is a distinct shift in the location of the maximum ΔK_II from the deep interior of the crack to its superficial outer tip, driven by the altered contact geometry. This shift intensifies the crack propagation trend along the length direction near the surface. Therefore, although the nominal contact stress decreases when considering braking heat, the risk of surface-initiated damage increases, which needs to be paid attention to during operations and maintenance. Full article

The development of the railway system has emerged as an imperative in strengthening the freight transportation system, particularly considering the inherent restrictions of road transport. Road congestion, limited carrying capacity, cost inefficiencies, speed constraints, and numerous socio-environmental concerns are common limitations. Nevertheless, the effectiveness of railway development initiatives varies across nations owing to distinct macro-scale influences. Accordingly, developing rail freight requires a systematic evaluation of both its constraining elements and strategic imperatives, tailored to a country’s specific context and competencies in rail freight operations. In response to this necessity, a comprehensive model assessing rail freight performance has been formulated in this research by employing a unique methodology targeting the underlying causal factors. The model consists of an initial phase of problem analysis, identification of rail freight performance drivers, followed by a study of rail freight performance in 64 countries and a subsequent non-linear multiple regression analysis. Key findings from the model emphasize the importance of evaluating controllable and uncontrollable variables, strategic considerations, and factors leading towards degradation of rail freight performance in formulating strategies to enhance rail freight system in a country. Full article

This study develops a compact elasticity-based framework for assessing how autonomous truck adoption influences corridor-level performance, freight demand, modal competition, and CO₂ emissions in multimodal freight Intelligent Transportation Systems. The model specifies the constant elastic (log-linear) responses of traffic performance and generalized costs to adoption, enabling the closed-form characterization of system-level rebound and road–rail reallocation effects. The analytical results show that an internal adoption threshold $P^{*}$ emerges, defined by $d\widehat{E}/dP=0$, which separates a beneficial regime (efficiency gains dominate) from an adverse regime (rebound and modal shift dominate). Comparative statics indicate that $P^{*}$ decreases with stronger ITS capability A and increases with rebound intensity R and the road–rail carbon intensity contrast K. Numerical experiments across representative corridor contexts illustrate induced demand effects exceeding 25% under high-rebound conditions and threshold ranges around $P^{*}\approx 0.3$–0.4 for plausible parameters. The results provide interpretable guidance for coordinating autonomous truck deployment with intermodal logistics design and decarbonization strategies. Full article

To assess the market competitiveness of high-speed rail (HSR) express and forecast its freight volume, this paper develops an integrated framework combining strategic analysis, market forecasting, and competition assessment. A hybrid SWOT-AHP model identifies and quantifies key strategic factors, clarifying HSR express positioning. Considering macroeconomic and consumption factors, a GM(1,N) model forecasts intercity express volume. Based on a generalized cost function covering timeliness, economy, safety, and stability, an improved Logit model calculates HSR’s mode share against road and air express, deriving future HSR freight volume. Using China as a case study, results show: (1) A proactive strategy leveraging intrinsic strengths is recommended, supported by rapid intercity express growth; (2) HSR can capture over 20% mode share initially, showing strong competitiveness in medium-long distance transport; (3) Transport cost is the most sensitive factor, a 20% reduction raises mode share by 10%, while rising timeliness demands enhance long distance advantages. This study offers a quantitative basis for HSR express strategic planning. Full article

To identify the emission reduction potential and policy synergies of Tokyo’s road passenger and urban road freight transport under the “carbon neutrality target,” this paper constructs an assessment framework for megacities. First, based on macroeconomic socioeconomic variables (population, GDP, road length, and employment), regression equations are used to predict traffic turnover for different modes of transport from 2021 to 2050. Then, the prediction results are imported into the LEAP (Long-range Energy Alternatives Planning) model. By adjusting three policy levers—vehicle technology substitution (ZEV: EV/FCEV), energy intensity improvement, and upstream electricity and hydrogen supply decarbonization—a “single-factor vs. multi-factor (policy synergy)” scenario matrix is designed for comparison. The results show that the emission reduction potential of a single measure is limited; upstream decarbonization yields the greatest independent emission reduction effect, while the emission reduction effect of deploying zero-emission vehicles and improving energy efficiency alone is small. In the most ambitious composite scenario, emissions will decrease by approximately 83% by 2050 compared to the baseline scenario, with cumulative emissions decreasing by over 35%. Emissions from rail and taxis will approach zero, while buses and freight will remain the primary residual sources. This indicates that achieving net zero emissions in the transportation sector requires not only accelerated ZEV penetration but also the simultaneous decarbonization of electricity and hydrogen, as well as policy timing design oriented towards fleet replacement cycles. The integrated modeling and scenario analysis presented in this paper provide quantifiable evidence for the formulation of a medium- to long-term emissions reduction roadmap and the optimization of policy mix in Tokyo’s transportation sector. Full article

To address the insufficient multi-layer optimization of fastener and cushion stiffness in ballastless tracks for mixed passenger and freight railways, a vehicle–track coupled dynamic model is developed, and the effects of individual and combined stiffness parameters on track and vehicle dynamics are systematically analyzed. Based on this model, a multi-dimensional stiffness matching approach is proposed to determine appropriate stiffness ranges for mixed-use railways. Results indicate that fastener stiffness primarily affects the local dynamic response of the rail, whereas cushion stiffness has a stronger influence on overall track performance. When the damping pad stiffness exceeds 600 MPa/m, the fastener force increases sharply, posing a risk of accelerated structural deterioration. Differences in axle load and speed between passenger and freight trains induce distinct excitation patterns, leading to nonlinear variations in interlayer forces. The optimal stiffness combination is 50 kN/mm for fasteners and 600 MPa/m for damping pads under passenger conditions, and 40 kN/mm and 600 MPa/m, respectively, under freight conditions. Considering the operational requirements of mixed lines, a fastener stiffness of 40–50 kN/mm and a damping pad stiffness of 600 MPa/m are recommended. This study provides theoretical support for stiffness design and parameter optimization in ballastless tracks for mixed-use railways. Full article

This paper is dedicated to analysing sustainability and digitalisation in the transport systems of the European Union (EU) and Ukraine, with a particular focus on three representative subsectors: freight rail, urban public transport and last-mile postal logistics. It explores how technological innovation, operational efficiency and environmental responsibility interact within these sectors under distinct institutional and economic conditions: mature, market-based systems in the EU and resilience-driven systems in wartime Ukraine. This study applies a comparative, descriptive–analytical methodology using secondary data drawn from corporate sustainability reports, official statistics and sectoral databases for 2022. Quantitative KPls were complemented with a qualitative assessment of digitalisation maturity to ensure cross-country comparability. Through a comparative analysis of KPIs, such as freight volumes, emissions intensity, revenue efficiency and digital maturity, this study identifies structural and policy gaps that hinder progress toward sustainable mobility. This study develops a multi-dimensional framework combining operational, financial, environmental and digital indicators. In this paper, digital integration refers to the degree to which transport operators embed digital tools such as tracking, data management and automation into their core processes, while environmental efficiency denotes the ability to deliver transport services with minimal resource consumption and carbon emissions per operational unit. Institutional resilience is understood here as the capacity of transport organisations and governing institutions to maintain functionality, adapt and recover under crisis or systemic stress, which is particularly relevant for Ukraine’s wartime context. The findings demonstrate that while EU operators lead in transparency, digital integration and environmental performance, Ukrainian actors exhibit rapid adaptive innovation and significant potential for technological leapfrogging during reconstruction. This paper concludes that the EU must overcome regulatory inertia and infrastructure fatigue, while Ukraine should institutionalise resilience and transparency. Full article