Large-scale High-speed Rail Research Articles

The unintended economic impact of high-speed rail on China's non-core cities: A spatial-difference-in-differences analysis

China's large-scale high-speed rail (HSR) construction has raised heated debates worldwide. Differing from previous research on metropolitan areas, this study examines on the economic impacts on periphery cities connected by HSR lines. Using a unique panel dataset of 237 Chinese non-core cities at the prefecture level spanning from 2002 to 2016, this study adopts a spatial difference-in-differences model to investigate the impact of HSR on service industry output. The estimation results suggest that the operation of HSR has a significant negative impact on service industry output of non-core cities, confirming the existence of a siphoning effect of HSR. Such negative impact varies with the profile of the non-core cities. HSR-connected non-core cities in the relatively well-developed coastal region, medium-sized and located within half-an-hour's travel time to mega cities tended to be associated with the most pronounced reductions. These findings provide important implications to the Chinese government and could be cogent for those planning or constructing HSR lines in other countries, given the numerous ongoing HSR initiatives around the globe.

Analysis of Vehicle-Induced Vibration Response and Comfort in Large-Scale High-Speed Rail Station Buildings with Integrated Bridges

Analysis of Vehicle-Induced Vibration Response and Comfort in Large-Scale High-Speed Rail Station Buildings with Integrated Bridges

The Spatial Structure Evolution of China's High-Speed Rail Network and Its Impacts on Real Estate Investment

The construction of China's large-scale high-speed rail (HSR) could exert a significant impact on the connectivity of urban networks in the long run. Through the dominance index of city nodes and the strength index of city links, the evolution of Chinese HSR networks has been explored based on frequency flow data from 2007 to 2017. Meanwhile, this paper uses a spatial econometric model to test the impact of the evolution of HSR networks on real estate investment agglomeration. Our examination shows that, as China's HSR network expands spatially, connectivity between cities improves, and the spatial structure of China's urban systems tends to be less hierarchical and polycentric. HSR networks promote the spatial agglomeration of real estate investment in cities connected by HSR. Although the influence of population scale, manufacturing scale, per capita GDP, and the degree of openness on real estate investment is greater than that of HSR network connection, the impact of the proportion of residential (commercial service) land and per capita GDP on real estate investment is less than that of HSR network connection. China's HSR network connection can expand the spatial agglomeration effect of site cities' real estate investment. The urban land use structure, such as the proportion of residential (commercial) land and the degree of openness, can promote a spatial spillover effect of real estate investment.

How to Optimize Train Stops under Diverse Passenger Demand: a New Line Planning Method for Large-Scale High-Speed Rail Networks

Optimizing stop plans of train lines greatly contributes to improving the quality of rail passenger service. Traditionally, stop plans are pre-specified according to the classification of stations in the line planning process. However, with the expansion of railway networks and the great changes of travel demand among different origin–destination pairs (ODs), it becomes more difficult to generate stops using this simple method. To meet the new challenges of line planning in railway management, a linear integer programming model based on a new definition of lines is presented in this paper. In the proposed model, proper lines with reasonable train ODs and frequencies can be selected from a series of potential lines in the given line pool. The stops of selected lines can be chosen from candidate stop sets that are generated based on both station classification and types of trains. More practical considerations of stop planning are integrally considered, i.e., the balance of the stop distribution and restrictions on the stop numbers. In experiments involving small-scale cases, the stop numbers decrease under different types of demand scenarios when using the proposed method compared to the traditional methods. We also conduct a series of sensitivity analyses using large-scale random cases to reveal the impact of different stopping rules on the quality of passenger services. Finally, two real-world case studies based on the Beijing-Shanghai high-speed rail network are utilized to demonstrate the applicability of the proposed method.

Stochastic Risk Assessment with a Lagrangian Solution for the Optimal Cost Allocation in High-Speed Rail Networks

In large-scale high-speed rail networks (HSRNs), the occurrence of occasional malfunctions or accidents is unavoidable. The key issue considered in this study is the optimal allocation of the maintenance costs, based on the stochastic risk assessment for HSRNs. Inspired by the theoretical risk evaluation methods in the complex network, three major factors, including the local effects, global effects, and component self-effects are considered in the process of assessing the impact on the network components (nodes or lines). By introducing the component failure occurrence probability, which is considered to be an exponential function changing with the component maintenance costs, a feasible stochastic risk assessment model of the HSRNs together with the component impact assessment is proposed that can better unify the impact assessment of both the high-speed rail stations and railways. An optimal allocation algorithm based on a Lagrangian relaxation approach is designed. Correspondingly, the optimal cost allocation scheme can be determined using the algorithm to eliminate the various HSRN risks under the given costs. Furthermore, a real-world case study of the HSRNs in eastern China is illustrated. Compared with the genetic algorithm, the simulation shows that the approach can solve the optimal cost allocation problem to more effectively reduce the risks of large-scale HSRNs in practice.

Should China further expand its high-speed rail network? Consider the low-cost carrier factor

This paper examines China’s large-scale high-speed rail (HSR) expansion, announced in July 2016, and the associated benefits assessment of the expansion program from the perspective of HSR-LCC (low-cost carriers) interactions. Our analysis suggests that in the highly populated and developed corridors the HSR expansion is likely to leave LCCs with little survival room, which is also shown by our case study on Spring Airlines. On the other hand, in the low-density corridors especially in the central and western China, LCCs might leave HSR with little survival room in the long run. By conducting a “propensity score matching” to pair HSR-linked city pairs in China to the counterfactual US airline routes, we find that most of these Chinese routes would be viable markets for LCCs to operate. The benefits of HSR expansion may thus be overestimated if not recognizing the LCCs’ role as an alternative mode to serve these markets. In particular, for the routes to the central and western China with very small travel demand and high HSR construction cost, LCC service could be more cost efficient and operationally flexible than HSR. Our analysis calls for a more careful evaluation of the program and, more generally, a balanced and coordinated HSR and LCC development in China.

Benefits Assessment of Large Scale High-Speed Rail Network in China: The Effect on Low-Cost Carriers

This paper examines the impact of China’s large-scale high-speed rail (HSR) expansion, announced in June 2016, on low-cost carriers (LCCs) and the associated benefits assessment of the expansion program. Our analysis suggests that HSR imposes a greater threat to LCCs than to full service carriers, and the HSR expansion that is intended to reach a great number of small cities has left Chinese LCCs with little survival room, even with full airline market liberalization and sufficient airport capacity. By conducting a “propensity score matching” to pair HSR-linked city pairs in China to the counterfactual US airline routes, we find that most of these Chinese routes would be viable markets for LCCs to operate. The benefits of HSR expansion may thus be overestimated if not recognizing the LCCs’ role as an alternative mode to serve these markets. In particular, for the routes to the central and western China with very small travel demand and high HSR construction cost, LCC service could be more cost efficient and operationally flexible than HSR. Our analysis calls for a more careful evaluation of the program and, more generally, a balanced and coordinated HSR and LCC development in China.

The variation in the value of travel-time savings and the dilemma of high-speed rail in China

This paper examines the variation in the value of travel-time savings (VTTS), a fundamental element determining the market demand for high-speed rail. Following a review of time allocation theories, a time allocation model for general travel behavior is proposed as a further elaboration of Evans’ (1972) activities analysis. There are relationships among activities that can be expressed using a linear inequality to show the constraints on the arrangement of activities. This model indicates that two or more activities can be simultaneously rearranged to improve time management, which may be a source of variation in VTTS. This time allocation model can explain why large-scale high-speed rail construction in China faces significant market risks and a high likelihood of economic loss. Data from a new ticket sales and booking system for railway passengers indicate that passengers prefer conventional overnight sleeper trains, rather than high-speed trains, for long-distance travel, which supports the analysis of the time allocation model.

High-Speed Rail and Urban Decentralization in China

The construction of a large-scale high-speed rail (HSR) network in China is altering the time–space relationships between cities. As a result, HSR is changing the traditional hierarchical urban system in China, and regions with large-scale networks of cities are forming. At the city level, the construction of HSR new towns could contribute to urban decentralization. The focus in this study is on the impact of HSR at the city level and how HSR is transforming cities in China through urban spatial restructuring. Case studies on two cities located on the Beijing–Shanghai HSR corridor were conducted, and the impact of the planned HSR new towns on the decentralization patterns of these two cities as well as the potential effects on their economic development are discussed. For large cities, the decentralization is actively driven by HSR because these cities are able to carefully choose the locations of their HSR stations. An HSR new town (i.e., a new district built around an HSR station) serves as an opportunity for well-planned spatial restructuring and as a catalyst for sustainable economic growth. For medium-sized to small cities, decentralization is often passively driven by HSR because the site selections of HSR stations are beyond the cities' control. The long distance between the HSR new town and the urban center weakens the economic strength of the existing urban core. The HSR new town presumably functions as a distraction rather than an attraction to the economic growth of the city as a whole. The leapfrog type of development also induces a wasteful use of land and other resources and further increases the living costs of the city's people and the operation costs of its firms.