The middle class in metropolitan Chinese cities has become an important social group. With the rapid development of urbanization and constant advancement of suburbanization, the middle class has increasingly come to i...The middle class in metropolitan Chinese cities has become an important social group. With the rapid development of urbanization and constant advancement of suburbanization, the middle class has increasingly come to influence city traffic. Research into middle-class commuting activities thus has practical significance for improving traffic congestion and reducing the commuting burden in metropolitan cities. Based on a dataset formed by 816 completed surveys, this paper analyzes the commuting mode, time and distance of middle-class residents in Guangzhou City using the descriptive statistical method. The results indicate that private cars are the main commuting mode, followed by public transport. Meanwhile, middle-class residents mainly undertake medium-short time and medium-short distance commuting. The study subsequently uses multilevel logistic regression and multiple linear regression models to analyze the factors that influence commuting mode choice, time and distance. The gender, age, number of family cars, housing source and jobs-housing balance are the most important factors influencing commuting mode choice; housing, population density, jobs-housing balance and commuting mode significantly affect commuting time; and transport accessibility, jobs-housing balance and commuting mode are the notable factors affecting commuting distance. Finally, this paper analyzes what is affecting the commuting activities of middle-class residents and determines the differences in commuting activity characteristics and influence factors between middle-class and ordinary residents. Policy suggestions to improve urban planning and urban management are also proposed.展开更多
Urban agglomeration(UA)is an advanced spatial economic form formed and developed in the process of rapid industrialization and urbanization,and an important carrier of urbanization and economic development.The economy...Urban agglomeration(UA)is an advanced spatial economic form formed and developed in the process of rapid industrialization and urbanization,and an important carrier of urbanization and economic development.The economy has developed rapidly in the recent decades of China,and the UAs have also developed rapidly.However,as a large population country,the population distribution and changes of UAs in China has unique characteristics.Using the fifth,sixth and seventh population census data,spatial auto-correlation and spatial econometric models,we analyzed the spatial-temporal evolution characteristics and influencing factors of population agglomeration in China’s UAs.Results revealed that:1)from 2000 to 2020,the population gradually converged into UAs,and the characteristics of population agglomeration in different development degree of UAs differ.The higher the development degree of UA,the higher the population agglomeration degree.Besides,UAs are the main area with the most significant population agglomeration degree,and the spatial autocorrelation show that the cities with similar degree tend to be concentrated in space.The urban population gathering in UAs has a certain positive spillover effect on population size of neighboring cities.2)Economic development and social conditions factors are important factors affecting population agglomeration degree in UAs.The main factors of population gather into UAs are similar with the outside UAs,but the positive promotion of urbanization rate and proportion of tertiary industry in GDP on population agglomeration of UAs in China are enhancing from 2000 to 2020.Meanwhile,the other factors,such as high-quality public services,good urban living environment conditions,high-quality medical and educational resources,are also important factors to promote urban population gather into UAs.This study provides a basis for formulating the development planning of UAs in China,and enriches the relevant theoretical research of population evolution and influencing factors of UAs.展开更多
The vigorous development of information and communications technology has accelerated reshaping of the financial industry. The COVID-19 pandemic has further catalyzed the demand for digital financial services. Digital...The vigorous development of information and communications technology has accelerated reshaping of the financial industry. The COVID-19 pandemic has further catalyzed the demand for digital financial services. Digital financial inclusion relies on information technology to overcome spatial limitations. In this case, the research question is whether it adheres to the spatial laws governing conventional financial activities. This study uses exploratory spatial data analysis and a geographical detector to elucidate the spatiotemporal characteristics and factors influencing digital financial inclusion at the county level in China(Data don’t include that of Hong Kong, Macao and Taiwan of China) from 2014 to 2020. The research findings indicate: first, China’s county-level digital financial inclusion is generally increasing and exhibits significant spatial autocorrelation. Second, population density, level of traditional financial development, government regulation, and education level are key determinants of China’s county-level digital financial inclusion. Third,policies should be differentiated by region to narrow the spatial gap in digital financial inclusion. The results provide a reference for other developing countries on using digital technology to develop financial inclusion.展开更多
基金Under the auspices of National Natural Science Foundation of China(No.41271182)
文摘The middle class in metropolitan Chinese cities has become an important social group. With the rapid development of urbanization and constant advancement of suburbanization, the middle class has increasingly come to influence city traffic. Research into middle-class commuting activities thus has practical significance for improving traffic congestion and reducing the commuting burden in metropolitan cities. Based on a dataset formed by 816 completed surveys, this paper analyzes the commuting mode, time and distance of middle-class residents in Guangzhou City using the descriptive statistical method. The results indicate that private cars are the main commuting mode, followed by public transport. Meanwhile, middle-class residents mainly undertake medium-short time and medium-short distance commuting. The study subsequently uses multilevel logistic regression and multiple linear regression models to analyze the factors that influence commuting mode choice, time and distance. The gender, age, number of family cars, housing source and jobs-housing balance are the most important factors influencing commuting mode choice; housing, population density, jobs-housing balance and commuting mode significantly affect commuting time; and transport accessibility, jobs-housing balance and commuting mode are the notable factors affecting commuting distance. Finally, this paper analyzes what is affecting the commuting activities of middle-class residents and determines the differences in commuting activity characteristics and influence factors between middle-class and ordinary residents. Policy suggestions to improve urban planning and urban management are also proposed.
基金Under the auspices of National Planning Office of Philosophy and Social Science(No.17BRK010)。
文摘Urban agglomeration(UA)is an advanced spatial economic form formed and developed in the process of rapid industrialization and urbanization,and an important carrier of urbanization and economic development.The economy has developed rapidly in the recent decades of China,and the UAs have also developed rapidly.However,as a large population country,the population distribution and changes of UAs in China has unique characteristics.Using the fifth,sixth and seventh population census data,spatial auto-correlation and spatial econometric models,we analyzed the spatial-temporal evolution characteristics and influencing factors of population agglomeration in China’s UAs.Results revealed that:1)from 2000 to 2020,the population gradually converged into UAs,and the characteristics of population agglomeration in different development degree of UAs differ.The higher the development degree of UA,the higher the population agglomeration degree.Besides,UAs are the main area with the most significant population agglomeration degree,and the spatial autocorrelation show that the cities with similar degree tend to be concentrated in space.The urban population gathering in UAs has a certain positive spillover effect on population size of neighboring cities.2)Economic development and social conditions factors are important factors affecting population agglomeration degree in UAs.The main factors of population gather into UAs are similar with the outside UAs,but the positive promotion of urbanization rate and proportion of tertiary industry in GDP on population agglomeration of UAs in China are enhancing from 2000 to 2020.Meanwhile,the other factors,such as high-quality public services,good urban living environment conditions,high-quality medical and educational resources,are also important factors to promote urban population gather into UAs.This study provides a basis for formulating the development planning of UAs in China,and enriches the relevant theoretical research of population evolution and influencing factors of UAs.
基金Under the auspices of National Natural Science Foundation of China (No.42171188)Natural Science Foundation of Guangdong Province (No.2022A1515010992)。
文摘The vigorous development of information and communications technology has accelerated reshaping of the financial industry. The COVID-19 pandemic has further catalyzed the demand for digital financial services. Digital financial inclusion relies on information technology to overcome spatial limitations. In this case, the research question is whether it adheres to the spatial laws governing conventional financial activities. This study uses exploratory spatial data analysis and a geographical detector to elucidate the spatiotemporal characteristics and factors influencing digital financial inclusion at the county level in China(Data don’t include that of Hong Kong, Macao and Taiwan of China) from 2014 to 2020. The research findings indicate: first, China’s county-level digital financial inclusion is generally increasing and exhibits significant spatial autocorrelation. Second, population density, level of traditional financial development, government regulation, and education level are key determinants of China’s county-level digital financial inclusion. Third,policies should be differentiated by region to narrow the spatial gap in digital financial inclusion. The results provide a reference for other developing countries on using digital technology to develop financial inclusion.
