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The configurations of Chinese national urban systems in both high-speed railway and airline networks

5. Conclusions and discussions

This paper contributes to the current state of research, as it clearly reveals differential
China's spatial structures of urban systems connected by its two high-speed transportation
networks (HSR and airlines). To the best of our knowledge, this paper is the first study to
use the actual O/D passenger flow data and compares the resulting configuration of the
Chinese urban systems in tow type of high-speed transportation networks at the national
scale. These urban systems are likely those of upper socialoccupational groups given the
social filter that shapes the use of fast, long-distance transportation modes.

First, in terms of city strength, HSR dominant cities are mainly centralized in the middle
and eastern parts of China, whereas airline dominant cities are evenly distributed over the
whole China. This difference can be partly explained by the Chinese physical geography
of the country: many cities are located far away from each other in the non-densely
populated mountain areas of the west region that cannot be easily reached by surface HSR
transportation, in contrast to the cities located in the densely populated plain areas of the
east region. Movover, that difference can be further explained by that although both HSR
and air passenger flows are constrained by the socio-economic performance of cities, the
city strength in HSR networks tends to be more sensitive to socio-economic performance
but less sensitive to administrative level of cities compared to air networks. This is largely
a consequence of the relatively expensive investments in HSR networks that are socially
and economically justifiable in high-density passenger volume areas compared to airline
networks. In other words, not only HSR networks are not suitable for long-distance travel
at the national scale, but also not viable for low-density passenger volume corridors, even
though central governments can decide differently due to political reasons (de Rus and
Nombela, 2007; Dobruszkes et al., 2017). Typically, in this case, remoter but higher ranked
cities in the west part of China in 2013 are usually served by airline instead of HSR at the
national scale, at least for the needs of the public authority’s interactions between them
and other dominant cities in the east from an administrative and governance perspective.
Therefore, cities with high GDP and populations in the east are normally the core cities in
both transportation networks, reflecting the inequitable development of urban systems.
For instance, Beijing, Shanghai and Guangzhou as the top three cities in both HSR and
airline networks reflect their national socio-economic importance in China’s urban systems,
which is similar to the finding of scheduled data in airline networks (Lin, 2012; Ma and
Timberlake, 2008) but different from that in HSR networks (Jiao et al., 2017) where Nanjing
instead of Guangzhou is in the top three. Regarding a much better socio-economic position
of Guangzhou than Nanjing in China, logically Guangzhou should be more dominant than
Nanjing at least in HSR networks from the perspective of demand side.

Second, in line with the former observation and explanation, the findings from the perspective
of link strength further confirm that the regional connections between the middle and the
east part have been largely facilitated by the HSR travel, but the interregional connections
between the west and the east part still largely rely on the airline travel, consolidating
a typical “flyover” effect in China as mentioned by (Jin et al., 2004). This is partly a
reason that HSR travel is competitive for short and medium distance travel but airline
travel competitive for medium and long distance travel, which is similar to the finding from
World Bank (Zheng and Kahn, 2013). Moreover, although city nodes of links with better
socioeconomic performance still induce a certain level of travel demand between both HSR
and airline networks, the link strength in HSR networks is compared to airline networks
highly sensitive to the geographical distance due to a severe distance decay effect, but less

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