Search Results (57)

It is well known that there is a significant conflict of interest between high-speed rail (HSR) operators and logistics companies. This study proposes an HSR freight pricing strategy based on a multi-objective optimization framework and a freight mode splitting model based on the Logit model. A utility function was constructed to quantify the comprehensive utility of different modes of transportation by integrating five key influencing factors: economy, speed, convenience, stability, and environmental sustainability. A bi-objective optimization model was developed to balance the cost of the logistics with the benefits of high-speed rail operators to achieve a win–win situation. The model is solved by the TOPSIS method, and its effectiveness is verified by the freight case of the Zhengzhou–Chongqing high-speed railway in China. The results of this study showed that (1) HSR has advantages in medium-distance freight transportation; (2) increasing government subsidies can help improve the market competitiveness of high-speed rail in freight transportation. This research provides theoretical foundations and methodological support for optimizing HSR freight pricing mechanisms and improving multimodal transport efficiency. Full article

This study aims to explore the factors and mechanisms influencing the low-carbon development of Green Port Collection and Distribution Systems (GPCDSs) and to identify effective pathways and policy approaches to promote such development. Given the limited prior research integrating low-carbon policies, energy structure, and transportation systems, this study combines these three dimensions into a unified analytical framework. A scenario-based system dynamics model of GPCDS low-carbon development is established, incorporating factors such as low-carbon policies, energy structure, and transportation structure. The control variable method is employed to examine system behavior under 13 scenarios. The results indicate that freight subsidy policies and the internalization of carbon emission costs make the most substantial contributions to low-carbon development in GPCDS, yielding CO₂ emission reductions of 14.3% and 15.7%, respectively. Additionally, improvements in port railway infrastructure contribute to a 6.4% reduction in CO₂ emissions. In contrast, carbon taxes and energy structure adjustments have relatively limited effects, likely due to the delayed responsiveness of fossil fuel-dependent transportation sectors to pricing signals and the inherent inertia in transitioning energy systems. Full article

Against the backdrop of China’s “public-to-railway” freight policy that has led to railway yard congestion and imbalanced modal capacity utilization, this study develops a Dual-Channel Cargo-Transportation Service (DCTS) system model using queuing theory to optimize freight flow allocation and pricing strategies. Integrating the behavioral decisions of governments, carriers, and cargo owners, the research employs M/M/1 queuing models and the Logit choice framework to analyze the dynamic equilibrium between goods waiting times and carrier profits, exploring objectives of minimizing system-average waiting time and maximizing carrier profits. Key findings show that regulating highway pricing can effectively divert freight flows to reduce railway congestion and improve system efficiency, with optimal pricing intervals for highways identified based on service capacity to balance congestion relief and profitability. The model quantifies the trade-off between transportation costs and waiting times to guide cargo owners’ mode choices, and numerical simulations validate that strategic highway price adjustments alleviate bottlenecks and enhance modal synergy. This paper provides a theoretical basis for the government to formulate freight-transportation policies and optimize freight flow allocation. At the same time, it also provides a practical, theoretical basis and methodological reference for carrier pricing decisions, as well as for solving the problem of freight flow congestion and optimizing the pricing of transportation services. Full article

Amid intensified global climate mitigation efforts, integrating rail freight into carbon emissions trading schemes became critical under China’s “Dual-Carbon” strategy. Despite rail’s significantly lower emissions intensity compared to road transport, existing pricing frameworks inadequately internalized its environmental externalities, which limited its competitive advantage. To address this gap, this study systematically reviewed international and domestic practices of integrating transport into carbon trading systems and developed a novel “four-layer, three-dimensional” emissions trading scheme (ETS) framework tailored specifically for China’s rail freight sector. Employing a Stackelberg bilevel optimization model, this study analyzed how carbon quotas and pricing influenced rail operators’ pricing and investment decisions. The results showed that under optimized quotas and carbon prices, railway enterprises were able to generate surplus carbon credits, creating new revenue streams and enabling freight rate reductions. This “carbon revenue–freight rate feedback loop” not only delivered environmental benefits but also enhanced rail’s economic competitiveness. Overall, this study significantly advances the understanding of carbon-based pricing mechanisms in railway freight, providing robust theoretical insights and actionable policy guidance for achieving sustainable decarbonization in China’s transport sector. Full article

This paper analyses the evolution of the prices of intercity high-speed rail (HSR) services operated by the Spanish public company, Renfe, on the Madrid–Barcelona route between April 2019 and June 2022. This period marks one of the most important events in the recent history of railways in Spain: the end of Renfe’s monopoly and the opening of this and other corridors to private competitors. Our main objective is to study the impact of the entry of the first competitor, Ouigo, on the incumbent’s pricing strategy. Our analysis confirmed that Renfe perfectly anticipated Ouigo’s entry and adjusted its prices about four months before the market opened. Interestingly, the incumbent also modified its tariff structure in advance according to the target customer’s willingness to pay. These results may be of interest for the forthcoming liberalisation of other intercity corridors. Full article

Regional planning agencies increasingly rely on Spatial Economic Models (SEMs) to evaluate the impact of various policies. However, traditional SEMs often employ homogeneous technical coefficients (TCs) to represent technology patterns used by activities located in very different areas of a region, leading to misrepresentations of production and consumption behaviors, and consequently, inaccurate modeling results. To this end, we propose a Differential Spatial Economic Modeling (DSEM) framework that incorporates region-specific TCs for activities within Independent Planning Units (IPUs), such as provinces or cities, each characterized by unique economic, demographic, and technological features. The DSEM framework comprises three core components: (1) a regional economy model that forecasts activity totals for each IPU using economic and demographic forecasting model, supplemented by statistical analyses like the Gini index and K-means clustering to group activities from different IPUs into homogeneous ‘technology’ clusters based on their TCs; (2) a land use model that allocates IPU activity totals to corresponding traffic analysis zones (e.g., counties or districts) using the Differential Spatial Activity Allocation (DSAA) method. This determines the spatial distribution of commodities (such as goods, services, floor space, and labor) across exchange zones, balancing supply and demand to achieve spatial equilibrium in both quantity and price; and (3) a transport model that performs modal split and network assignment, distributing commodity trip origin–destination matrices across a multimodal transportation supernetwork (highways, railways, and waterways) using a probit-based stochastic user equilibrium assignment model. The proposed method is applied to a case study of the Yangtze River Economic Belt, China. The results demonstrate that the proposed DSEM yields better goodness-of-fit (R²) values between observed and estimated flows compared to the traditional aggregate SEM. This indicates a more precise and objective representation of spatial economic activities and technological patterns, thus resulting in improved estimates of freight flows for individual transportation modes and specific links. Full article

In the transportation organization optimization of high-speed railway (HSR), optimizations such as line planning, ticket pricing, and seat allocation are generally studied separately. However, in reality, when passengers choose trains, they need to consider multiple factors such as train routes, stop plans, seat prices, seat availability, and departure times. Therefore, there is an urgent need for an integrated optimization method to simultaneously make decisions regarding these multiple factors. This study constructs a nonlinear optimization model of line planning integrating differentiated pricing and seat allocation decisions for HSR under elastic demand. To efficiently solve the model, an improved heuristic algorithm based on the simulated annealing framework combined with a linear passenger flow allocation method is proposed. Finally, case analysis proves that the improved algorithm can effectively solve the model under the input conditions of an actual Y-shaped HSR network composed of 13 stations, with a potential for a 106.54% improvement from the initial solution to the final solution. The uniqueness of our study lies in the joint optimization of three critical HSR operations, which has not been comprehensively explored in prior studies and is of great significance for improving the level of HSR train operations and passenger services. Full article

This paper aims to analyze the influence mechanism of built environment factors on passenger flow by predicting the passenger flow of Shenzhen rail transit in the morning peak hour. Based on the classification of built environment factors into socio-economic variables, built environment variables, and station characteristics variables, eight lines and one hundred sixty-six stations in Shenzhen Railway Transportation are taken as research objects. Based on the automatic fare collection (AFC) system data and the POI data of AMAP, the multiple regression model (OLS) and the geographically weighted regression (GWR) model based on the least squares method are established, respectively. The results show that the average house price is significantly negatively correlated with passenger flow. The GWR model considering the house price factor has a high prediction accuracy, revealing the spatial characteristics of the built-up environment in the administrative districts of Shenzhen, which has shifted from the industrial structure in the east to the commercial and residential structure in the west. This paper provides a theoretical basis for the synergistic planning of house price regulation and rail transportation in Shenzhen, which helps to develop effective management and planning strategies. Full article

The integration of railway stations into urban environments necessitates a detailed examination of their vitality and influencing factors. This study assesses urban vitality around four major railway stations in Beijing utilizing a variety of analytical models including Ordinary Least Squares, Geographically Weighted Regression, Multi-Scale Geographically Weighted Regression, and machine learning approaches such as XGBoost 2.0.3, Random Forest 1.4.1.post1, and LightGBM 4.3.0. These analyses are grounded in Baidu heatmaps and examine relationships with spatial form, functional distribution, and spatial configuration. The results indicate significant associations between urban vitality and variables such as commercial density, average number of floors, integration, residential density, and housing prices, particularly in predicting weekday vitality. The MGWR model demonstrates enhanced fit and robustness, explaining 84.8% of the variability in vitality, while the Random Forest model displays the highest stability among the machine learning options, accounting for 76.9% of vitality variation. The integration of SHAP values with MGWR coefficients identifies commercial density as the most critical predictor, with the average number of floors and residential density also being key. These findings offer important insights for spatial planning in areas surrounding railway stations. Full article

Recreation and nature-based tourism targeting forests are important cultural services provided by forests, and are also considered non-productive social functions of forests. Many factors influence the demand for forest recreation and tourism that are worth exploring for each forest area. The main aim of our study was to compare the results of visitor surveys related to two mountainous forested areas (Börzsöny and Cserhát) that are both located near to the capital city of Budapest but have different characteristics regarding the forests, accessibility, and the level of tourism infrastructure and services. The questionnaires focused on the characteristics of the visits, perceptions of visitors regarding the values of the areas, and the development needs besides the characteristics of the respondents. In addition to basic statistics, Chi² and Fisher’s exact tests were used to detect the differences between the two sites. Despite the different characteristics of the study areas, the main results were quite similar at both sites. Most respondents came from Budapest or within a 60 km distance of the sites by car with family and friends, mainly for hiking and nature walks, and spent less than a day in the areas. The state of forests was perceived as good in both areas. Landscape and fresh air were the most attracting factors for visiting both sites. There was a demand for more guided tours, and regarding tourism infrastructure development needs, benches and toilets ranked high at both sites. However, there were also some slight differences between the sites. For example, Börzsöny was visited more frequently, and railway and bicycle were more often used to access this site. Pleasant climate, easy access and fresh air were more important reasons to visit Börzsöny, and it was more associated with wilderness. In Cserhát, low prices and cultural values seemed more important reasons to visit; Hollókő as a world heritage site was highlighted, and more nature-related and other tourism development needs were mentioned regarding this site. These differences were probably due to the different characteristics of the forests (more mosaic forests in Cserhát), the level of the public transportation network, tourist infrastructure and services (higher in Börzsöny), and cultural heritage (more important in Cserhát). Based on our results, Cserhát needs more development in tourism infrastructure and services, while in Börzsöny, the development of a visitor management plan would be useful to harmonize the different uses of the forest. Full article

The railway infrastructure projects in Thailand aim to shift transportation from roads to railways. This is crucial for transporting goods in emerging economies and increasing the demand for rail freight transport. However, several dynamic uncertainties hinder sustainable rail freight transport in Thailand. This study aims to identify the key factors and validate their effects on the success of the modal shift from roads to railways in Thailand. A total of 200 participants filled out a questionnaire delivered online and via postal service. The key factors were categorized into the following categories: the rail freight transport system, demand, and development factors in Thailand. The inter-relationship and connection of these factors were analyzed using SEM (structural equation modeling). The SEM results showed that all causal factors in the model had a positive influence on rail freight development in Thailand, which explained 98.3% of the variance in the factors influencing development. This study’s findings underscore the influential significance of rail performance, rail infrastructure, the legal framework, pricing, mode choice, and technology on the expansion of rail freight transport in Thailand. The rail freight transport system, rail performance, rail infrastructure, and Thailand’s rail infrastructure development strategy were significant direct predictors of rail freight expansion. An expansion of the rail freight transport system also leads to rail freight demand. The results of this study have positive implications for the government, railway practitioners, and policymakers to prioritize their focus on achieving rail freight transport as the national target. Full article

A multi-ride ticket with a certain period of validity and maximum number of uses has been introduced into railway transport. The key to pricing the railway multi-ride ticket is determining the uncertain demand within an agreed time limit. Unfortunately, limited studies have focused on this pricing issue. Therefore, we focused on railway multi-ride ticket pricing optimization in two different scenarios: a single train with multiple stops and multiple trains with multiple stops. First, the expected coefficient and incentive coefficient were introduced to describe the decision-making process for multi-ride tickets and simulate the change in passengers’ travel behavior after purchasing multi-ride tickets. Then, passenger demand functions based on a normal distribution were developed to establish the pricing models with maximized revenue. Finally, we adopted improved particle swarm optimization (PSO) to solve the models. Two numerical cases were used to verify the models separately for two application scenarios. The results revealed that the multi-ride ticket pricing problem is not a simple summation of pricing for one-time travel of passengers. In the situation of a single train with multiple stops, the expected coefficient is positively related to the total income, whereas the incentive coefficient has limited influence on the optimal price and total revenue. Furthermore, a multi-ride ticket should allow the passenger to take trains eight times at most in 8 days at the price of CNY 4922 (abbreviated as 4922 (8, 8)) rather than 3785 (8, 6). Railway enterprises should cautiously limit the scope of trains available for multi-ride tickets in the case of multiple trains with multiple stops. Full article

High-cost abatement measures to mitigate greenhouse gas emissions in the basic commodity industry is known to result in substantial increases in the production costs. Consequently, investments in such measures are lagging behind what is required to make deep emission cuts in line with the Paris Agreement. As high-cost abatement measures (such as Carbon Capture and Storage; CCS) are perceived as expensive for the basic commodity producer, this study investigates the impacts down-stream of the product value chain when assuming full cost pass-through (i.e., the cost increase related to basic commodity production is fully passed on down-stream of the product chain to the end-consumer). We investigate the effects on both costs, by means of a techno-economic assessment, and carbon footprints, using a Life Cycle Assessment (LCA), along the product value chain for the case of post-combustion CCS applied to the cement, pulp, Waste-to-Energy (WtE), and refinery industries, towards abating fossil- and process-related emissions and generating negative emissions. Here, we analyse the product value chains that involve cement to a high-speed railway, pulp to a disposable baby diaper, WtE in connection with housing and plastic products, and refineries to different transportation solutions (truck transport and air-freight). The results show that even though the costs for producing basic commodities can increase significantly (200% for cement, 75% for pulp, 230% for heat, and 6–37% for refinery products) when implementing CCS, the increases in prices for end-users are marginal (1% for the railway, 3% for the disposable baby diaper, 1% for the housing, 0.4% for truck transport and 2% for air-freight). Simultaneously, the carbon footprint associated with the end-use may be reduced by up to 36% for the railway, 31% for the diaper, 80% for the housing, and 3–23% for the refinery cases. Full article

The Belt and Road Initiative (BRI) has become a household name for developing countries, especially in Africa. The BRI proposal by Chinese President Xi Jinping was positively received by many countries, including policymakers in China. In response, the Chinese Government committed to investing USD 1 trillion over ten years from 2013 to 2023. As a result, 152 countries signed a cooperation agreement with China to work under the BRI framework. The BRI has played a vital role in addressing the global infrastructures gap through the construction of modern highways, airports, high-speed railways, bridges, power generation (hydropower), and industrial parks. As a result, this has enhanced connectivity and economic growth between Asia, Europe, and Africa. Despite the BRI’s significant role in strengthening trade, infrastructure and investment links between China and other countries, there is limited literature on specific countries’ experience with the initiative. This study, therefore, will advance our understanding of the BRI, especially on the conceptualization of the term; comparative analysis of Africa–China relationships before and after the BRI; the benefits in relation to the “Five Connectivities” and the challenges the BRI is facing in Africa. The article is based on a literature review and case study as research methodologies mainly used the Policies, Projects, Initiatives, and Strategies (PPIS) as a data source. The study focuses on five African countries; Uganda, Kenya, Egypt, Djibouti, and Mozambique. These countries were selected purposefully for analysis because of their experience, long-term relationships with China, and strategic locations. The findings revealed that the BRI lacked a clear description and that it was difficult to distinguish between BRI projects and other regular economic or diplomatic relations. The study also identified four differences between Africa–China relationships before and after the BRI. Furthermore, the findings revealed that the BRI has positively contributed to all five connectivity pillars. However, the major challenges reported concerning the initiative from the various countries were: procurement corruption, low/lack of involvement of stakeholders, high compensation prices, labor violations, increasing debts, and environmental hazards. In conclusion, while the BRI has brought about significant infrastructure development and economic benefits, the project has also experienced some challenges. This study, therefore, contributes to the body of knowledge on China’s Belt and Road Initiative and its impact on African countries, specifically in Uganda, Kenya, Djibouti, Mozambique, and Egypt. The paper then provides conclusions and policy implications as well as future research opportunities in the current body of the literature. Full article