scholarly journals The Impact of High-Speed Railways on Unequal Accessibility Based on Ticket Prices in Korea

2020 ◽  
Vol 12 (16) ◽  
pp. 6302
Author(s):  
Kyungtaek Kim ◽  
Junghoon Kim
Keyword(s):  
Urban Population ◽  
High Speed ◽  
National Level ◽  
High Speed Railway ◽  
Large Cities ◽  
South Korean ◽  
Time Value ◽  
Population Sizes ◽  
Ticket Prices ◽  
The Impact

The high-speed railway (HSR) has affected accessibility at diverse spatial levels. Although previous studies have examined HSR impacts on accessibility and inequality, the price attribute in estimating accessibility is less noted. This study evaluates the effects of HSR on unequal accessibility at the South Korean national level, capital and non-capital regions and according to urban population sizes by comparing ticket prices to time values. There are two major conclusions of this study. First, an increase in time value through national growth or other exogenous conditions maximizes HSR impact and, thus, increases accessibility. For example, when the time value is 9.98 USD/h, the national HSR access inequality is reduced by 0.56%. However, when the time value is 6.02 USD/h, the reduction in the national inequality by the HSR is 0.19%. Second, if considering generalized travel time, HSR impact is maximized in medium cities rather than in large cities. When the time value is 6.02 USD/h (or 9.98 USD/h), the change in inequality between cities is −0.4% (−1.29%) in medium cities, while large cities show a −0.08% (−0.9%) reduction in access inequality.

The Impact of High-Speed Rail on the Spatial Structure of Chinese Urban Agglomerations

2020 ◽  
Vol 46 (3) ◽  
pp. 379-397
Author(s):  
Chunyang Wang
Keyword(s):  
High Speed ◽  
River Delta ◽  
City Size ◽  
High Speed Rail ◽  
Local Conditions ◽  
Urban Agglomerations ◽  
Large Cities ◽  
Spatial Systems ◽  
Economic Concentration ◽  
The Impact

This paper measures the spatial evolution of urban agglomerations to understand be er the impact of high-speed rail (HSR) construction, based on panel data from fi ve major urban agglomerations in China for the period 2004–2015. It is found that there are signi ficant regional diff erences of HSR impacts. The construction of HSR has promoted population and economic diff usion in two advanced urban agglomerations, namely the Yang e River Delta and Pearl River Delta, while promoting population and economic concentration in two relatively less advanced urban agglomerations, e.g. the middle reaches of the Yang e River and Chengdu–Chongqing. In terms of city size, HSR promotes the economic proliferation of large cities and the economic concentration of small and medium-sized cities along its routes. HSR networking has provided a new impetus for restructuring urban spatial systems. Every region should optimize the industrial division with strategic functions of urban agglomeration according to local conditions and accelerate the construction of inter-city intra-regional transport network to maximize the eff ects of high-speed rail across a large regional territory.

scholarly journals Does the Opening of High-Speed Railway Lines Reduce the Carbon Intensity of China’s Resource-Based Cities?

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4648
Author(s):  
Zhipeng Tang ◽  
Ziao Mei ◽  
Jialing Zou
Keyword(s):  
High Speed ◽  
National Average ◽  
Carbon Intensity ◽  
Time Varying ◽  
Low Carbon ◽  
High Speed Railway ◽  
Different Types ◽  
Endogenous Selection ◽  
Mode Of Development ◽  
The Impact

The carbon intensity of China’s resource-based cities (RBCs) is much higher than the national average due to their relatively intensive mode of development. Low carbon transformation of RBCs is an important way to achieve the goal of reaching the carbon emissions peak in 2030. Based on the panel data from 116 RBCs in China from 2003 to 2018, this study takes the opening of high-speed railway (HSR) lines as a quasi-experiment, using a time-varying difference-in-difference (DID) model to empirically evaluate the impact of an HSR line on reducing the carbon intensity of RBCs. The results show that the opening of an HSR line can reduce the carbon intensity of RBCs, and this was still true after considering the possibility of problems with endogenous selection bias and after applying the relevant robustness tests. The opening of an HSR line is found to have a significant reducing effect on the carbon intensity of different types of RBC, and the decline in the carbon intensity of coal-based cities is found to be the greatest. Promoting migration of RBCs with HSR lines is found to be an effective intermediary way of reducing their carbon intensity.

Impacts of high-speed railway on the industrial pollution emissions in China

Kybernetes ◽  
2020 ◽  
Vol 49 (11) ◽  
pp. 2713-2735 ◽  
Author(s):  
Xiaomin Fan ◽  
Yingzhi Xu ◽  
Yongqing Nan ◽  
Baoli Li ◽  
Haiya Cai
Keyword(s):  
Environmental Effects ◽  
Industrial Pollution ◽  
High Speed ◽  
Assessment Method ◽  
Economic Effects ◽  
High Speed Railway ◽  
Central Cities ◽  
Content Type ◽  
Pollution Emissions ◽  
The Impact

Purpose The purpose of this paper is to analyse the impact of high-speed railway (HSR) on industrial pollution emissions using the data for 285 prefecture-level cities in China from 2004 to 2016. Design/methodology/approach The research method used in this paper is the multi-period difference-in-differences (DID) model, which is an effective policy effect assessment method. To further address the issue of endogeneity, the DID integrated with the propensity score matching (PSM-DID) approach is employed to eliminate the potential self-selection bias. Findings The results show that the HSR has significantly reduced industrial pollution emissions, which is validated by several robustness tests. Compared with peripheral cities, HSR exerts a greater impact on industrial pollution emissions in central cities. In addition, the mechanism test reveals that the optimised allocation of inter-city industries is an important channel for HSR to mitigate industrial pollution emissions, and this is closely related to the location of HSR stations. Originality/value Previous studies have paid more attention to evaluating the economic effects of HSR, however, most of these studies overlook its environmental effects. Consequently, the impact of HSR on industrial pollution emissions is led by using multi-period DID models in this paper, in which the environmental effects are measured. The results of this paper can provide a reference for the pollution reduction policies and also the coordinated development of economic growth and environmental quality.

Notch-based speed trajectory optimisation for high-speed railway automatic train operation

2021 ◽  
pp. 095440972110421
Author(s):  
Minling Feng ◽  
Chaoxian Wu ◽  
Shaofeng Lu ◽  
Yihui Wang
Keyword(s):  
High Speed ◽  
Applied Force ◽  
Mixed Integer ◽  
High Speed Railway ◽  
Train Operation ◽  
Train Speed ◽  
Automatic Train Operation ◽  
The Impact ◽  
Trajectory Optimisation

Automatic train operation (ATO) systems are fast becoming one of the key components of the intelligent high-speed railway (HSR). Designing an effective optimal speed trajectory for ATO is critical to guide the high-speed train (HST) to operate with high service quality in a more energy-efficient way. In many advanced HSR systems, the traction/braking systems would provide multiple notches to satisfy the traction/braking demands. This paper modelled the applied force as a controlled variable based on the selection of notch to realise a notch-based train speed trajectory optimisation model to be solved by mixed integer linear programming (MILP). A notch selection model with flexible vertical relaxation was proposed to allow the traction/braking efforts to change dynamically along with the selected notch by introducing a series of binary variables. Two case studies were proposed in this paper where Case study 1 was conducted to investigate the impact of the dynamic notch selection on train operations, and the optimal result indicates that the applied force can be flexibly adjusted corresponding to different notches following a similar operation sequence determined by optimal train control theory. Moreover, in addition to the maximum traction/braking notches and coasting, medium notches with appropriate vertical relaxation would be applied in accordance with the specific traction/braking demands to make the model feasible. In Case study 2, a comprehensive numerical example with the parameters of CRH380AL HST demonstrates the robustness of the model to deal with the varying speed limit and gradient in a real-world scenario. The notch-based model is able to obtain a more realistic optimal strategy containing dynamic notch selection and speed trajectory with an increase (1.622%) in energy consumption by comparing the results of the proposed model and the non-notch model.

scholarly journals Examining partial proportional odds model in analyzing severity of high-speed railway accident

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jing Wang ◽  
Yinghan Wang ◽  
Yichuan Peng ◽  
Jian John Lu
Keyword(s):  
High Speed ◽  
Proportional Odds Model ◽  
Impact Factors ◽  
Proportional Odds ◽  
High Speed Railway ◽  
Severity Level ◽  
Content Type ◽  
Factors Affecting ◽  
Partial Proportional Odds Model ◽  
The Impact

Purpose The operation safety of the high-speed railway has been widely concerned. Due to the joint influence of the environment, equipment, personnel and other factors, accidents are inevitable in the operation process. However, few studies focused on identifying contributing factors affecting the severity of high-speed railway accidents because of the difficulty in obtaining field data. This study aims to investigate the impact factors affecting the severity of the general high-speed railway. Design/methodology/approach A total of 14 potential factors were examined from 475 data. The severity level is categorized into four levels by delay time and the number of subsequent trains that are affected by the accident. The partial proportional odds model was constructed to relax the constraint of the parallel line assumption. Findings The results show that 10 factors are found to significantly affect accident severity. Moreover, the factors including automation train protection (ATP) system fault, platform screen door and train door fault, traction converter fault and railway clearance intrusion by objects have an effect on reducing the severity level. On the contrary, the accidents caused by objects hanging on the catenary, pantograph fault, passenger misconducting or sudden illness, personnel intrusion of railway clearance, driving on heavy rain or snow and train collision against objects tend to be more severe. Originality/value The research results are very useful for mitigating the consequences of high-speed rail accidents.

An Agent-Based Simulation Model of Knowledge Spillover Under the Influence of High-Speed Railway

2019 ◽  
Vol 7 (2) ◽  
pp. 99-114 ◽  
Author(s):  
Yun Zhao ◽  
Chongren Bi
Keyword(s):  
Simulation Model ◽  
Labor Migration ◽  
Migration Rate ◽  
High Speed ◽  
Innovation System ◽  
Knowledge Spillover ◽  
Regional Innovation ◽  
High Speed Railway ◽  
Knowledge Innovation ◽  
The Impact

Abstract The calculation for the influence of high-speed railway on knowledge spillover is based on the results of global instantaneous equilibrium in the mechanism explanation of knowledge spillover. In real production, the interaction between the high-speed railway and the regional innovation system is dynamic and local. In order to simulate the impact of high-speed railway on innovation activities in the time dimension, it is necessary to simulate scenarios under appropriate parameter assumptions. Based on the interaction of economic participants, a discrete evolutionary simulation model is established, which is helpful to predict and estimate the evolution of spatial effect of high-speed railway according to the theory of cellular automata. It is concluded that high-speed railway accelerates the formation of knowledge innovation industry cluster in the region in the process of regional knowledge innovation and evolution. Under the influence of high-speed railway, the node city will gradually evolve into a regional innovation center. By comparing the production evolution of knowledge innovation system with and without high-speed railway, the results show that high-speed railway has a more significant impact on knowledge spillover in higher knowledge privatization environment. Under the background of low labor migration rate, high-speed railway has increased the potential of regional innovation to external knowledge spillover. In the case of higher labor migration rate, the convergence rate of influence of high-speed railway on the concentration of innovation is faster.

Does opening high-speed railways affect the cost of debt financing? A quasi-natural experiment

2020 ◽  
Vol 10 (4) ◽  
pp. 473-496
Author(s):  
Hongling Guo ◽  
Keping Wu
Keyword(s):  
High Speed ◽  
Geographical Location ◽  
Debt Financing ◽  
Cost Of Debt ◽  
High Speed Railway ◽  
Content Type ◽  
Financing Cost ◽  
Debt Market ◽  
The Cost ◽  
The Impact

PurposeThis study aims to investigate how opening high-speed railways affects the cost of debt financing based on China's background.Design/methodology/approachUsing panel data on Chinese listed firms from 2008 to 2017, this study constructs a quasi-natural experiment and adopts a difference-in-difference model with multiple time periods to empirically examine the relation between the high-speed railway openings and debt financing cost.FindingsOur results show that opening high-speed railways reduces the cost of debt financing, and this negative correlation is more significant in non-state firms, firms with weaker internal control, and firms that hire non-Big Four auditors. Besides, we explore the impact mechanisms and find that opening high-speed railways improves analyst attention, institutional investor participation, and information disclosure quality, which in turn lowers the cost of debt financing.Research limitations/implicationsThe results imply that the opening of high-speed railways helps to alleviate the information asymmetry and adverse selection between firms and creditors and ultimately reduces the cost of corporate debt financing.Practical implicationsThis paper can inform firms and stakeholders about the impact of opening high-speed railways on debt financing cost: it improves the information environment, reduces the geographical location restrictions of debt financing, ensures the reasonable pricing of corporate debt, and thus promotes the healthy and sound development of the debt market.Originality/valueThis paper provides theoretical support and empirical evidence for the impact of infrastructure construction on the information environment of the debt market in China, which enriches the research on the “high-speed railway economy.” In addition, as an exogenous event, the opening of high-speed railways instantly shortens the time distance between firms and external stakeholders, which gives us a natural environment to conduct empirical research, thus providing a new perspective for financial research on firms' geographical location.

scholarly journals Evaluation of Dynamic Load Factors for a High-Speed Railway Truss Arch Bridge

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Ding Youliang ◽  
Wang Gaoxin
Keyword(s):  
Finite Element ◽  
Dynamic Load ◽  
High Speed ◽  
Field Monitoring ◽  
Generalized Extreme Value Distribution ◽  
Monitoring Data ◽  
Load Factor ◽  
High Speed Railway ◽  
Arch Bridge ◽  
The Impact

Studies on dynamic impact of high-speed trains on long-span bridges are important for the design and evaluation of high-speed railway bridges. The use of the dynamic load factor (DLF) to account for the impact effect has been widely accepted in bridge engineering. Although the field monitoring studies are the most dependable way to study the actual DLF of the bridge, according to previous studies there are few field monitoring data on high-speed railway truss arch bridges. This paper presents an evaluation of DLF based on field monitoring and finite element simulation of Nanjing DaShengGuan Bridge, which is a high-speed railway truss arch bridge with the longest span throughout the world. The DLFs in different members of steel truss arch are measured using monitoring data and simulated using finite element model, respectively. The effects of lane position, number of train carriages, and speed of trains on DLF are further investigated. By using the accumulative probability function of the Generalized Extreme Value Distribution, the probability distribution model of DLF is proposed, based on which the standard value of DLF within 50-year return period is evaluated and compared with different bridge design codes.

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