High-speed Rail Services Research Articles

From Click to Buy: Enhancing User Experience on The Whoosh Mobile App for High-Speed Rail Booking

The Jakarta-Bandung High-Speed Railway has revolutionized transportation in Indonesia, offering a modern and efficient travel experience. To encourage the utilization of this service, enhancing the user experience (UX) of online ticket booking applications, such as Whoosh, is crucial. The scope of this study is limited to the core functionalities of account registration, login, and booking, up until the issuance of the electronic ticket. This study evaluates user satisfaction through qualitative analysis of user reviews from the Google Play Store and Apple App Store and quantitative analysis of user ratings and download numbers. Using the Customer Satisfaction Index (CSI) methodology, the study identifies a CSI score of 24.85%, which indicates significant dissatisfaction among users. The primary issues include failures during login and registration processes, unclear navigation during booking, the lack of an invoice or receipt printing feature, and the absence of a support center throughout the application. To address these pain points, textual recommendations are proposed, including the implementation of one-tap login, a Help Center feature, enhanced carriage selection visibility, and a “Send Receipt” button on the payment page. These improvements aim to simplify interactions, provide intuitive navigation, and enhance support systems, ultimately promoting greater user satisfaction and adoption of high-speed rail services. This research contributes actionable insights for improving digital ticketing solutions and highlights the importance of continuous user feedback to drive further enhancements.

The railway transport development in the new BRICS countries

With effect from January 1, 2024, Egypt, Ethiopia, Iran, Saudi Arabia and the United Arab Emirates have become new members of the BRICS. Today, BRICS is an association of 10 countries that account for about 42 % of the world’s total population (2.8 billion people) and 27 % of the global GDP.According to experts, a major focus is made on the association’s prospective economic potential and its expected share of the world’s economy. What seems interesting in the context of the continued economic growth is the research in the field of development of the transport industry in the BRICS countries.Earlier, the BRICS Transport journal (Issue No. 2 (4), 2023) presented an overview of the state and progress of high-speed railway transport in the five BRICS founding countries (Brazil, Russia, India, China, and the Republic of South Africa). In connection with the expansion of the transnational association, it is proposed that the research should be extended. The authors used both findings of scholarly works in the field of railway transport development, and BRICS summit reports and presentations available on Russian and foreign information platforms.The paper analyses the development of railway transport in the countries that have joined BRICS recently (Egypt, Iran, the United Arab Emirates, Ethiopia, and Saudi Arabia), in particular, the prospects of development of express and high-speed rail services.

High-speed rail passenger flow prediction based on crossformer and quantile regression: A deep learning approach assisted by internet search indices

Understanding potential fluctuations in passenger volume is crucial for the operation and management of high-speed rail, especially during peak times. The uncertainty caused by multiple factors is the main obstacle to accurate prediction. To quantify and mitigate the impact of these uncertainties, Internet search indices are utilized as insightful resources to grasp dynamic trends in passenger flow. Leveraging minimum redundancy maximum relevance, we identify the top search index features based on their predictive contribution to high-speed rail passenger flow. A two-level decomposition strategy is then established based on variational modal decomposition to extract significant influencing factors hidden in the Internet index and capture the dynamic uncertainty of passenger flow. By integrating Crossformer with quantile regression, we construct the upper and lower bounds of the prediction interval. Furthermore, the obtained upper and lower bounds are corrected by the error of point prediction, which allows for dynamic adjustment of the prediction intervals width based on fluctuations in uncertainty, thereby refining the precision of the prediction interval. Finally, the developed approaches effectiveness is validated through two real-world experiments, and the experimental results indicate that this method can more accurately capture variations in high-speed rail passenger flow, improving both management and service quality.

Research on an Algorithm for High-Speed Train Positioning and Speed Measurement Based on Orthogonal Time Frequency Space Modulation and Integrated Sensing and Communication

The Doppler effect caused by the rapid movement of high-speed rail services has a great impact on the accuracy of train positioning and speed measurement. Existing train positioning algorithms require a large number of trackside equipment and sensors, resulting in high construction and maintenance costs. Aiming to solve the above two problems, this article proposes a train positioning algorithm based on orthogonal time–frequency space (OTFS) modulation and integrated sensing and communication (ISAC). Firstly, based on the OTFS, the positioning and speed measurement architecture of communication awareness integration is constructed. Secondly, a two-stage estimation (TSE) algorithm is proposed to estimate the delay Doppler parameters of HST. In the first stage, a low-complexity coarse grid search is used, and in the second stage, a refined off-grid search is used to obtain the delay Doppler parameters. Then, the time difference of arrival/frequency difference of arrival (TDOA/FDOA) algorithm based on multiple base stations is used to locate the target, the weighted least square method is used to calculate the location, and the Cramér–Rao lower bound (CRLB) for positioning and speed measurement is derived. The simulation results demonstrate that, compared to GNSS/INS and OFDM radars, the algorithm exhibits enhanced positioning and speed measurement accuracy.

Connect to green: High-speed rail network and firms’ environmental performance

High-speed rail (HSR) has completely revolutionized intercity travel, significantly impacting economic activities. Recent studies have increasingly focused on how HSR affects environmental pollution. Given China’s extensive HSR policy in recent years, we extend this discussion in the context of China, introducing several new dimensions. Firstly, by manually collecting the daily operating routes of each HSR line in China, we construct a dynamic, directed, and weighted HSR network and provide a detailed description of the topological evolution of Chinese HSR from 2007 to 2014. Secondly, by employing network theory algorithms, we develop a city-level HSR strength index. This approach diverges from the commonly used multi-period difference-in-differences (DID) specification, allowing us to better address heterogeneity and discontinuity issues in identifying HSR effects. Thirdly, by leveraging the specific structure of the HSR network, we analyze how cities are interconnected and, for the first time, discuss the impact of “HSR-catalyzed supervision pressure” on firms’ pollution performance. Our findings show that firms exposed to higher HSR service intensity are more likely to reduce their SO2 emissions, a result that remains robust across various checks and other pollutants. We propose an intercity interaction story, predicting that HSR facilitates spillovers among city groups, thereby increasing environmental supervision pressure from neighboring cities in the HSR network. In further empirical analysis, we identify three specific sources of supervision pressure: peer pressure, vertical pressure, and public pressure.

Promotion Effects of High-Speed Rail on Urban Development: Evidence from Three Lines in China

Amid the vigorous development of the high-speed rail (HSR) network, local governments in China generally consider the construction of HSR as a crucial task in their regional development strategies. Currently, most provincial capitals and prefecture-level cities in the eastern and central regions of China already have operational HSR services. This study aims to examine a key question: has the objective of local governments to promote urban development through the construction of HSR been effective? The research selects cities along the Beijing–Shanghai, Beijing–Guangzhou, and Harbin–Dalian HSR lines as the study subjects. Based on the principles of proximity and similarity, cities with operational HSR and those without are chosen as the experimental group and the control group, respectively. Following the double difference (difference-in-differences) approach, an advantage index is proposed to systematically evaluate the impact of HSR operation on urban development from three dimensions: population aggregation, economic development, and expansion of construction land. Furthermore, the evaluation results are systematically clustered to identify city types that exhibit different promotional effects in various dimensions. The research findings indicate the following: (1) The promotion effect of HSR on the development of small to medium-sized cities is more reflected in economic growth and construction land growth. (2) The promotion effect of HSR on the development of large cities is more reflected in the growth of the employment population. (3) For smaller or economically less-developed cities, HSR may be detrimental to the aggregation of resident and employment populations. (4) Cities with moderate size and good economic development have the opportunity to use HSR to promote population aggregation. On this basis, combined with the findings above, strategies to promote the coordinated development of high-speed rail construction and urban systems are discussed.

Passenger Service Satisfaction Evaluation of Jakarta-Bandung High-Speed Railway

As competition in the passenger transportation industry intensifies, high-speed railway must continuously improve service quality to win passenger satisfaction and secure a place in the competitive market. The Jakarta- Bandung High-Speed Railway (JBHSR), Indonesia’s and Southeast Asia’s first high-speed rail, commenced operation in October 2023. This study aims to identify areas for service improvement by measuring and evaluating passenger satisfaction and proposing optimization suggestions. Combining domestic and international service quality evaluation schemes and customer satisfaction models, this study employs the Analytic Hierarchy Process (AHP) to construct a passenger satisfaction evaluation system for high-speed rail services from three dimensions: perceived quality, expected value, and perceived value. A passenger satisfaction survey was conducted, and the results were analyzed using AHP and Fuzzy Comprehensive Evaluation (FCE) methods to calculate satisfaction scores. The Importance-Performance Analysis (IPA) revealed that aspects such as ease of ticket purchasing, accuracy of train operation information, and punctuality scored highly in terms of satisfaction. However, items categorized under ‘Concentrate Here’ and ‘Low Priority’ quadrants require further optimization. This study benchmarks successful practices from other countries’ HSR systems and proposes specific improvement measures, including installing free Wi-Fi at stations and on trains, expanding parking capacity with an online reservation system, increasing the number of escalators and elevators at Padalarang Station, and installing electronic displays and enhancing ground signage for better visibility of carriage positions. These measures aim to improve the quality of HSR services and enhance passenger satisfaction.

Short-term high-speed rail passenger flow prediction by integrating ensemble empirical mode decomposition with multivariate grey support vector machine

Short-term prediction of high-speed rail (HSR) passenger flow provides a daily ridership estimation for the near future, which is critical to HSR planning and operational decision making. This paper proposes a new methodology that integrates ensemble empirical mode decomposition with multivariate support vector machines (EEMD-MSVM). There are four steps in this hybrid forecasting approach: (i) explore the correlation of multivariate HSR passenger flows at various stations based on archived data; (ii) decompose empirical modes of historical passenger flows for each HSR station, using EEMD to generate a number of intrinsic mode functions (IMFs) and a trend term; (iii) predict the IMF for each correlated station pair using MSVM; and (iv) reconstruct the refined IMF components to predict daily multivariate HSR passenger flows. The proposed EEMD-MSVM approach is demonstrated with multiple OD pairs along the Wuhan-Guangzhou HSR in China. Results from various origin-destination pairs, show that the EEMD-MSVM approach outperforms the existing ensemble empirical mode decomposition with grey support vector machine approach (EEMD-GSVM). With the multivariate approach, the mean absolute percentage error in demand prediction is reduced by 13.9%, 1.2%, 1.0%, 2.0%, and 2.7% and the mean absolute deviation is reduced by 78.8, 38.0, 4.4, 4.6, and 3.9, between these OD pairs respectively. Such increase in short-term demand prediction accuracy can significantly improve HSR service planning, operations, and revenue management in the real world.

Competition in cargo and passenger between high-speed rail and airlines—considering the vertical structure of transportation

High-speed rail (HSR) services are experiencing rapid global expansion, posing competition not only in the traditional passenger sector but also challenging air cargo with their attributes of speed and punctuality. In this study, we establish a straightforward model for air-HSR competition in both passenger and cargo markets, taking into account the vertical structure of transportation supply chain. We explore various market equilibria based on the combination of three factors: 1) HSR's provision of cargo services, 2) the integration or separation of HSR's ownership and operation, and 3) uniform or differentiated airport administrative fees for passenger and cargo airlines. The analytical results of our model indicate that the entry of HSR into the cargo market consistently enhances social welfare and may even improve the profit of cargo airlines. However, if airports adopt uniform pricing or there is vertical separation in HSR sector, this could potentially weaken the positive impact on welfare enhancement. These findings have important implications for transportation policy, highlighting how strategic management of infrastructure can significantly influence the effectiveness and societal benefits of HSR's expansion into cargo services.

Agent-based modelling of high-speed railway interdependent critical infrastructures facing physical and cyber threats

Globally, high-speed rail systems serve nearly 2 billion passenger-km daily. By virtue, they are a critical infrastructure like telecommunication and power networks. Accordingly, they become a catalyst for societal and economic growth stemming from the mobility business. The highspeed rail operations are very complex and interdependent, owing to the escalated demands for long-distance interconnected transportation. In recent years, there have been unreasonable delays for passengers as a new norm due to unfortunate train cancellations and relaxation of mobility performance requirements. Therefore, accurate measurements, monitoring and prediction of disruptive impacts and service performance metrices are indispensable. Within the scope of high-speed rail services, this paper examines how agent-based and multi-agent-based models are utilized to address such the challenges. Our findings reveal that the current use of agents or multi-agent models has some limitations for practical applications. Previous studies showed that mathematical methods to assess the resilience of critical infrastructures, railway scheduling, and vehicle dispatching can yield more satisfactory outcomes, although the approaches can be relatively time-consuming. In contrast, agent-based and multi-agent-based models can shorten processing time and uncover disruptive events more promptly. The paper thus showcases several emerging concepts, including i) the utilization of big data for crisis management, ii) interconnectivity analysis of high-speed rail infrastructures, and iii) enhancement of transport resilience. In addition, our findings identify the most influential agents and their possible applications to enhance systems resilience of highspeed rail networks when dealing with unforeseen physical and cyber threats.

A Study of the Impact of the Use of Real-Time Crowding Information on the Perceived Service Quality of High-Speed Rail by Passengers with Unfixed-Seat Tickets

Unfixed-seat tickets are one of the supplementary forms of tickets used when the transport capacity of high-speed rail is insufficient; however, the needs of passengers with unfixed-seat tickets are often neglected. To understand the influence of unfixed-seat tickets on passengers’ perception of the quality of high-speed rail service, including their satisfaction, this study takes the provision of real-time crowding information (RTCI) as the independent variable and the satisfaction of passengers with unfixed-seat tickets with the quality of the high-speed rail service as the dependent variable, and adds social anxiety as a moderating variable, to construct a model. We conducted experiments and gathered data through questionnaires. The results showed that the implementation of RTCI has a significant impact on the satisfaction levels about high-speed railway service quality. In comparison to scenarios without RTCI or with RTCI failure, successful RTCI implementation can significantly enhance user satisfaction. Additionally, the moderating effect of social anxiety is significant. Perceived satisfaction did not significantly differ for individuals with low social anxiety in the absence of RTCI or in cases where RTCI failed; however, for individuals with high social anxiety, perceived satisfaction was significantly lower when RTCI failed compared to the No-RTCI condition. The potential practical implications of these findings are discussed.

Geographic proximity and trade credit: Evidence from a quasi-natural experiment

This paper examines the impact of geographic proximity on suppliers' decisions to provide trade credit to their customers. To establish a causal relationship, we utilize the implementation of high-speed rail (HSR) services in China as a quasi-natural experiment. Our findings reveal a significant increase in trade credit received by firms after introducing HSR services. We propose and test three mechanisms to elucidate the influence of proximity on trade credit provision: the enhanced convenience for acquiring soft information, heightened competition among suppliers, and the potential development of social trust. Empirical evidence strongly supports the first two mechanisms, underscoring their importance in shaping trade credit decisions. However, limited evidence is found regarding the role of social trust. These findings contribute to understanding the complex interplay between geographic proximity, trade credit, and supplier decision-making processes.

Competitive integrated airline schedule design and fleet assignment

Airline profits are significantly influenced by competitive timetables that match passenger demand to fleet resources. In this research, we develop an integrated, mixed-integer optimization model to derive a comprehensive flight schedule, fleet assignment, and average airfares jointly. Passenger choice behavior is incorporated through a prospect theory-adjusted, nested, multinomial logit model which estimates market share. The competitive fleet assignment and schedule design (CFSD) formulation is embedded in a differentiated Bertrand game, such that each transport operator optimizes their best response function connected through the market share model. To solve the integrated optimization problem efficiently, a hybrid algorithm is developed that combines stabilized column generation with a large neighborhood search algorithm.The game-theoretic framework is applied to a case study in China involving legacy airlines, a low-cost carrier, and a high-speed rail (HSR) operator. The equilibrium outcomes suggest that the low-cost carrier is likely to stimulate demand and improve the level of service through secondary airports. The further development of high-speed rail service is expected to intensify competition among airlines and reduce the overall fare level. The low-cost carriers and HSR are able to significantly increase overall consumer surplus, providing insights into the potential for low-cost service in the Chinese aviation markets and the entrance of the public service obligation program at minimum cost.

Coupling development of high-speed rail network and innovative cooperation based on travel behavior of depressed passengers

Background Depression is a common mental illness. Patients with depression show somatization symptoms such as loss of appetite, insomnia and low mood. The etiology and pathogenesis of depression are still unclear, and the pathogenesis is related to biochemical, neuroendocrine, sleep and brain electrophysiological abnormalities. This study takes depressed passengers as the research object to explore the intervention and influence of innovative high-speed rail services on patients with depressive episodes when they travel, so as to provide ideas for the coupling development of high-speed rail network and innovative cooperation.Subjects and Methods38 cases of high-speed rail passengers with depression were randomly divided into the experimental group and the control group. The experimental group was treated with innovative psychological services of high-speed rail. Hamilton Depression Scale (HAMD) was used to evaluate the degree of depression before and after treatment, and Hamilton Anxiety Scale (HAMA) was used to evaluate the degree of anxiety.ResultsThe scores of HAMD and HAMA in the experimental group after innovative psychological intervention services were lower than those before participation (P<0.05), and the difference was statistically significant.ConclusionsThe innovative high-speed rail depression psychological intervention service has a positive impact on depressed passengers. After the intervention, depressed passengers’ depressed mood and pessimistic thoughts are improved, they no longer resist others, and their discomfort symptoms are significantly reduced. At the same time, this intervention mode opens new ideas for the coupling development of high-speed rail network and innovative cooperationAcknowledgementFoundation: National Natural Science Foundation of China (No. 41301104); Foundation: National Natural Science Foundation of China (No. 41871108).

Transportation infrastructure and eco-environmental quality: Evidence from China's high-speed rail.

Ecological civilization construction is China's national development strategy, and improving the urban eco-environmental quality is the key to accelerating this strategy, while the high-speed rail (HSR) opening is an important factor affecting the urban eco-environmental quality. Using panel data of 290 cities in China from 2004 to 2020, this study explores the impact of HSR opening on urban eco-environmental quality and its heterogeneity from the perspective of direct impact and interaction between HSR connected cities. Compared with cities without HSR service, the eco-environmental quality of cities with HSR service has significantly increased by 0.023 standard deviations, which is about 4.11% of the total change in urban eco-environmental quality in the same period. Second, there is an inverted U-shaped relationship between eco-environmental quality and urban space expansion. Third, the impact of HSR on eco-environmental quality is heterogeneous, mainly manifested in different cities and urban agglomerations. It means that the government should focus on the differences in the economic foundation and development characteristics of various regions, steadily push forward the construction and operation of the HSR, and speed up the renovation of existing lines to help the green development of cities. The research results provide a policy basis for the government to handle the relationship between infrastructure construction and eco-environmental quality, and effectively promote green sustainable development.

Diverted and induced demand: Evidence from the London-Paris passenger market

The paper investigates passengers' preferences and demand induction (or reduction) patterns for the London-Paris passenger market. By leveraging an integrated model calibrated on an extensive dataset about passenger flows between London and Paris during the period 2009–2019, we investigate key dimensions by which travelers evaluate transport modes and how both socio-economic characteristics and supply-attribute variations contribute to stimulating or reducing the overall demand. The research confirms the importance of attributes, such as travel times, fares, and frequencies on passenger modal choice, providing some sketches about passengers' propensity toward air or high-speed rail (HSR) mode. Based on data in this study, we find that ceteris paribus a one-trip increase in the daily frequency of Eurostar would stimulate demand for more than 94,500 passengers per year (2.3% of current ridership), while a reduction of HSR travel time by 10 min would increase current flows by at least 1.3%. Analyzing the demand implications of a possible policy of ending air routes for environmental purposes, we prove that the cancellation of air connections would result in a reduction of current demand higher than 6%. HSR service providers could offset the reduction in service levels resulting from air routes closure mainly by leveraging service frequency.

Investigation of the Policy Effect of High-Speed Metropolitan Rail Service in Seoul Through Latent Class Modeling Analysis of Stated Preference Survey

The sprawl of megacities is increasing the need to improve public transit services to cover longer distances in shorter times than current services. High-speed metropolitan rail services have been introduced to satisfy the needs of passengers and are expected to alleviate the transportation problems caused by urban sprawl. However, the effectiveness of public transit demand inducement policies, which have been employed in various ways in South Korea, has been questioned. Thus, agencies responsible for high-speed metropolitan rail services should also evaluate whether such policies will work properly. The achievement of the policy can be evaluated as sufficiently inducing the demand of the target group, and investigated through the residence information and the current travel behavior. This study investigates the current travel behavior of users to be replaced when a new high-speed metropolitan rail service is introduced and directly analyzes the travel mode shifting effect. While previous studies focused on increasing the applicability to general services by classifying groups based on personal attributes, this study focuses on evaluating detailed policy achievements for specific services. We apply a latent class modeling approach using stated preference survey data for group classification. In particular, by employing the user’s current travel behavior as a class membership attribute, the characteristics of potential passengers of the high-speed metropolitan rail service are analyzed. The estimation results suggest that current travel behavior significantly classifies high-speed rail passengers. In addition, the policy achievement was investigated in detail by region and operation time, and several additional policy directions are presented to satisfy the policy goals.

Mobility-as-a-Service (MaaS) and High-Speed Rail Operators: Do Not Let the Train Pass!

Rail operators are developing their own Mobility-as-a-Service (MaaS) applications for mobility management, integrating all the transport links for door-to-door intermodal journeys. In this context, this paper analyses the main challenges railway operators face when implementing their new MaaS applications on a national scale, analysing and evaluating the factors influencing the successful implementation of MaaS in cities with high-speed rail services. These factors are related directly to the adaptation of MaaS services to different geographies, from large metropolitan areas to small cities located in rural environments. The differences among all the HSR cities in Spain are related to both socioeconomic and transport systems’ variables. Smaller cities are generally in a more rural/suburban environment, with higher percentages of aged and illiterate inhabitants, who are much more vulnerable to the digital divide. In addition, these areas present very few and/or inefficient public transport options, and practically non-existent shared mobility services, largely limiting the possibility of competing for private car mobility. Our paper’s analysis of all these factors fills a gap in the literature and opens the debate about different approaches and transport policies that rail operators could adopt when entering the MaaS environment.

Service on the rise, agriculture and manufacturing in decline: The labor market effects of high-speed rail services in Spain

Service on the rise, agriculture and manufacturing in decline: The labor market effects of high-speed rail services in Spain

Stimulus Perception in Long-Distance Railway Mode Choice

In the context of countries in the so-called Global South, where passenger railway services are either nonexistent or poorly performed, discrete choice models are useful to identify the attributes that affect users’ choices and provide insights on their behaviour in regional long-distance trips. Several theories and models have been proposed to understand travel behaviour for effective strategical decision in the transport field. The well-knownRandom Utility Maximization (RUM) approach has been widely used for such purposes, while the Random Regret Minimization (RRM) approach has been recently explored in the literature. However, the magnitude in the difference of levels of the attributes, or the stimulus perception, may affect the results of such models and biases the estimations. Therefore, this paper aims to assess the stimulus perception in mode choice to compare conventional rail (CR) and high-speed rail (HSR) services for passenger transport in intercity trips in Brazil. Estimations of RUM and RRM models were performed with a dataset from a stated preference survey comparing two railway technologies (CR and HSR) with other modes of transport (car, bus, and airplanes) for long-distance trips in the Southeast region of Brazil. Findings provide useful insights about the impacts of travel costs, travel times, and frequency of services, as well as sociodemographic characteristics of users. From the modelling outputs, it was found that users are affected by the magnitude of travel costs, time, and frequency only in business trips by HSR in the Brazilian context.