Pavlína Hejduková, Lucie Kureková
Population migration continues to be a current topic linked to a wide spectrum of various external and internal factors on both international and regional levels. In contemporary literature, there is a whole score of empirical studies that deal with international migration, its determinants and impacts on the economy. However, there are only few empirical studies that deal primarily with solely regional (i.e. internal) migration in comparison to the large number of studies analyzing international migration, which is one of the main reasons for the selection of the topic of this study and its focus on internal migration and thus on movements that take place within one geopolitical entity, usually a nationstate (for more on the definition of internal migration, see, e.g., Fendel, 2014; Royuela & Ordóñez, 2016). So-called “gravity models” stemming from an analogy to Newton’s law of gravity and Ravenstein’s laws of migration are often used for modelling internal migration and the study of it, or for the analysis of the main determinates that impact these internal fluctuations of citizens; however, these gravity models of migration are often criticized for their insufficient theoretical foundation.
Lei Fang, Xuewei Zhang, Zihua Feng, Ce Cao
The economy of China has been maintaining a middle and high growth rates in the past 40 years since reform and opening-up. Railway is an important infrastructure and a major factor of economic development. It is also a witness and beneficiary of reform and opening-up. Railway in China has undergone transformation and development. Given the continuous expansion of traffic network and innovative reform of technologies, high-speed rail construction has achieved outstanding progresses. During the “12th Five-Year Plan,” the total investment of China to high-speed rail system has exceeded 1,800 billion RMB. Moreover, 3,500 billion RMB of investment is expected under railway plan in the “13th Five-Year Plan.” Currently, China owns a high-speed
rail network with the longest operation miles, the highest transportation density, and the most complicated network operation scenario in the world (Karolys et al., 2019).