Railway is one of the most important components of the integrated transportation system. A functional and efficient railway system can be conducive to sustainable development of society and economy, thus highlighting the importance of studies on rail efficiency. In this paper, we study the spatio-temporal evolution of China's railway transportation efficiency during 2005-2013 using the ultra-efficient SBM model and Malmquist index method. Hence, the characteristics and influencing mechanism of railway efficiency in China are also analyzed. The results are as follows: (1) the SBM model analysis of 18 Chinese rail bureaus indicates that rail efficiency increased from 0.724 to 0.778 due to a series of measures taken by the governments in recent years, such as reorganization, deregulation, and innovation. Scale efficiency increased by 1.93% per year and technical efficiency by 0.27% per year, indicating scale efficiency's major influence. We also find that the gap between 18 bureaus' efficiency narrowed in 2005-2013, standard deviation dropped from 0.287 in 2005 to 0.23 in 2013, and the coefficient of variation dropped from 0.396 to 0.295. (2) The spatial distribution pattern of railway transportation efficiency suggests that the railway system in the eastern region is more efficient than that of the central region, which, in turn, is more efficient than that of the western region. In addition, there are differences in the spatial distribution of the internal transport efficiency in the high-, medium-, and low-value areas, while the types of rail efficiency are also different. According to the characteristics of the railway bureaus' efficiency change, the 18 railway bureaus can be divided into three types: equilibrium, fluctuation, and growth. (3) Through the analysis of railway evolution, we find that the construction of large-scale high-speed railways in recent years has not caused significant changes in transport efficiency and productivity. (4) From the perspective of transportation geography, the location conditions, resource potential difference, topography, and urbanization pattern affect the spatial pattern of transport efficiency and its evolution.
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SU Qin et al
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2018, 37(3): 512-526.
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