Economic transition, urbanization and population redistribution in China

He, Canfei; Chen, YangQuan; Mao, Xiyan; Zhou, Yi

doi:10.1016/j.habitatint.2015.10.006

Cited by 139 publications

(84 citation statements)

References 20 publications

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“…Hence, large-scale rural surplus labor migrates to the eastern coastal developed provinces and urbanization area because of economic interests. However, the incompleteness of institutional, economic, and social factors, such as hukou, housing, and social insurance, and the constraint of population-carrying capacity of large cities impede the settlement of migrants [33][34][35]. Hence, an abnormal travel rush occurs around Spring Festival holiday and brings various kinds of social problems.…”

Section: Discussionmentioning

confidence: 99%

Spatial-Temporal Analysis on Spring Festival Travel Rush in China Based on Multisource Big Data

Deng

et al. 2016

Sustainability

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Spring Festival travel rush is a phenomenon in China that population travel intensively surges in a short time around Chinese Spring Festival. This phenomenon, which is a special one in the urbanization process of China, brings a large traffic burden and various kinds of social problems, thereby causing widespread public concern. This study investigates the spatial-temporal characteristics of Spring Festival travel rush in 2015 through time series analysis and complex network analysis based on multisource big travel data derived from Baidu, Tencent, and Qihoo. The main results are as follows: First, big travel data of Baidu and Tencent obtained from location-based services might be more accurate and scientific than that of Qihoo. Second, two travel peaks appeared at five days before and six days after the Spring Festival, respectively, and the travel valley appeared on the Spring Festival. The Spring Festival travel network at the provincial scale did not have small-world and scale-free characteristics. Instead, the travel network showed a multicenter characteristic and a significant geographic clustering characteristic. Moreover, some travel path chains played a leading role in the network. Third, economic and social factors had more influence on the travel network than geographical location factors. The problem of Spring Festival travel rush will not be effectively improved in a short time because of the unbalanced urban-rural development and the unbalanced regional development. However, the development of the modern high-speed transport system and the modern information and communication technology can alleviate problems brought by Spring Festival travel rush. We suggest that a unified real-time traffic platform for Spring Festival travel rush should be established through the government's integration of mobile big data and the official authority data of the transportation department.

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Section: Discussionmentioning

confidence: 99%

Spatial-Temporal Analysis on Spring Festival Travel Rush in China Based on Multisource Big Data

Deng

et al. 2016

Sustainability

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“…Empirical tests with diverse variables can accurately reflect how the major factors influence environmental performance [14,[20][21][22][23][24][25][26]. From the existing literature, one can learn that the combination of spatial econometrics and the EKC theory is growing increasingly popular for analyzing the dynamic relationship between the regional economy and environmental performance.…”

Section: Environmental Kuznets Curve With Spatial Econometricsmentioning

confidence: 99%

Spatial Spillover Effects of Environmental Pollution in China’s Central Plains Urban Agglomeration

et al. 2018

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Promoting the rise of Central China is one of the most important national strategies regarding the promotion of China's economic development. However, the environmental issues in the central regions have become remarkably severe. It is therefore worthwhile exploring how economic development and environmental protection can be coordinated. Focusing on the 29 prefecture-level cities in the Central Plains Urban Agglomeration, the authors empirically analyze the relationship between the economy and the environment from 2004 to 2014. The combined methods of the spatial autocorrelation model, the environmental Kuznets curve, and the global spatial correlation test are systematically employed. The results show that: (1) a strong spatial correlation exists between industrial wastewater discharge, industrial sulfur dioxide, and dust emissions in the Central Plains Urban Agglomeration; (2) the relationship between the economy and the environment of this urban agglomeration reveals an inverted "U" curve, which confirms the classical environmental Kuznets curve hypothesis. Industrial dust emissions have surpassed the inflection point of the Kuznets curve, but its spatial spillover effect still remains strong. This is caused by an accumulation effect and a lag effect; (3) the proportion of the secondary industry and population has a strong positive effect on pollution discharge; investments in science and technology have a certain inhibitory effect on industrial sulfur dioxide emission. Moreover, an increase in the number of industrial enterprises has a negative effect on industrial wastewater emission. At the end, the authors put forward policy recommendations regarding the establishment of a joint supervisory department and unified environmental standards at the regional level to deal with the spillover effects of pollution.

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“…Since China's Reform and Opening up, Chinese cities have been experiencing an unprecedented rapid urbanization process [1,2], with the country's urbanization rate increasing from 17.9% in 1978 to 56.1% in 2016. That has led to a major human migration from the countryside to cities, especially to Beijing, Shanghai and other large cities [3].…”

Section: Introductionmentioning

confidence: 99%

Decentralization and Polycentricity: Spatial Changes of Employment in Beijing Metropolitan Area, China

Zheng

Zhou

et al. 2017

Sustainability

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Decentralization and polycentric spatial structure strategies are important ways to alleviate urban disease in China. However, whether the urban spatial structure is meeting expectations is still unknown. Taking the Beijing Metropolitan Area as a case, the author adopted a non-parametric method to identify the subcenters, then an employment density model was used to analyze the spatial changes of employment and the employment centers' impacts on the urban spatial structure. The results show that the Beijing Metropolitan Area was undergoing processes of employment decentralization, the monocentric structure was obvious throughout this time, but the polycentric model prevailed. The spatial structure of the Beijing Metropolitan Area was characterized as depicting "all centers aggregation" and the spatial structure of the central district of Beijing can be described as "subcenter agglomeration" between 2004 and 2013. The spatial structure became increasingly polycentric in the Beijing Metropolitan Area, but became more scattered in the central district.

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Economic transition, urbanization and population redistribution in China

Cited by 139 publications

References 20 publications

Spatial-Temporal Analysis on Spring Festival Travel Rush in China Based on Multisource Big Data

Spatial-Temporal Analysis on Spring Festival Travel Rush in China Based on Multisource Big Data

Spatial Spillover Effects of Environmental Pollution in China’s Central Plains Urban Agglomeration

Decentralization and Polycentricity: Spatial Changes of Employment in Beijing Metropolitan Area, China

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