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Time allocation is closely related to life quality and is a potential indicator of urban space utilization and sociospatial differentiation. However, existing time allocation studies focus on how time is allocated to various activities but pay less attention to where individuals allocate their time. In the context of China's transformation, this study examines the differences in time allocation in different urban spaces between low- and non-low-income groups based on two methods, descriptive statistics and social area analysis. The results show that low-income participants' daily activities (especially work) are highly dependent on the central city area. However, they are at a disadvantage in accessing the central city area. Nevertheless, non-low-income individuals have diversified activity spaces and can better choose locations according to the purpose of activities and make fuller use of various types of urban areas. This study indicates that there are social differences in time allocation and urban space utilization among different income groups. The results obtained with regression models reveal that in addition to income, activity characteristics and built environment characteristics are significant factors affecting the differences. Social policies should support the equitable distribution of urban resources for different social groups, especially for vulnerable groups who live in affordable housing. [ABSTRACT FROM AUTHOR]

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The quality of urban settlement is an essential element of people's desire for a better life, which has been capitalized into housing prices of local cities. However, previous literature focuses overwhelmingly on the determinants of intracity housing prices. There is still a lack of research on the determinants of the spatial disparity in intercity housing prices, and there is even less research on the association between comprehensive urban settlement quality and housing prices. This paper uses principal component analysis to evaluate urban settlement quality for 294 cities in China and applies spatial econometric models to examine the impact of urban settlement quality on housing prices. The results show that urban settlement quality in China is composed of five principal components: social livelihood, service industry development, leisure-traffic, the ecological environment, and economic development. There is spatial correlation between urban settlement quality and housing prices in China, both of which show high values in eastern China and low values in western China. Spatial econometric modeling results indicate that social livelihood and the ecological environment have a significant positive impact on housing prices, while service industry development and the leisure-traffic factor have a significant impeding effect on housing prices. In addition, residential land prices and per capita real-estate development investment are significant factors affecting housing prices in China. [ABSTRACT FROM AUTHOR]

With rapid economic and urban development in recent decades, sociospatial inequalities in Chinese cities are exacerbating. In China, the sociospatial structure of cities has experienced tremendous changes during the economic transition. Based on a person‐based perspective, this study explores the relationship between urban spaces and individual behaviours of low‐income and non‐low‐income groups in general and at the community level. The results indicate that low‐income residents are more likely constrained to outer suburbs than non‐low‐income residents. However, differences in urban‐space use between income groups vary in different communities. The differences in inner‐city communities are the most moderate, while the differences are the most significant in affordable housing communities. The logistic regression models reveal that the income variable influences only the outer‐suburb individuals' use of urban space. [ABSTRACT FROM AUTHOR]

Abstract Examining the spatial distribution of the renewable energy industries (REIs) at the county-level and their driving factors is critical for appropriate future policy-making. However, there have been very few studies on this issue to date in China. From a geographical perspective, this study uses the data of the total number and generating capacity of renewable energy plants at the county-level to investigate the spatial distribution patterns of China's REIs, and analyzes their driving factors. The results show that the past decade has witnessed unprecedented development in renewable energy technologies in China, and REIs are constantly springing up in the southwestern and northwestern China, exhibiting a "double-core" spatial pattern. Furthermore, this distribution pattern significantly exhibits resource-dependent and policy-led characteristics, namely, environmental conditions, the abundance of renewable resources and supportive policies are the crucial factors in the clustering of the REIs in China. In addition, as a powerful stimulus to the development of renewable energy economy, the effect of governmental policy significantly varies among different REIs, and a spatial mismatch between the abundance of renewable resources and local governmental development policies is identified, especially for the wind and solar power industries. Highlights • The spatial distributions of the renewable energy industries in China at a county-level are investigated. • The renewable energy industries are concentrated in southwestern and northwestern China, with a "double-core" pattern. • The distribution of the renewable energy industries exhibits resource-dependent and policy-led characteristics. • A spatial mismatch between renewable resources and the local government's supportive policies is identified. [ABSTRACT FROM AUTHOR]

This paper examines the contrasting effects of local agglomeration in innovation activities and the interregional networks derived from innovation collaboration on R&D productivity. Based on a two-stage R&D process, this study enriches the existing research and highlights the significance of interregional networks and local agglomeration in understanding spillover effects and productivity improvement. This study employs the network slacks-based measure model to quantify the R&D productivity of two successive stages of research and technology transfer using panel data from 2009 to 2017 for 30 Chinese provinces. It employs the spatial Durbin model to explore and compare the effects of interregional networks and local agglomeration on R&D productivity at each stage. The findings show that interregional networks play an important role in improving research productivity, while local agglomeration is more important in technology transfer research. The significant spatial spillover effect of technology transfer productivity in adjacent provinces indicates a large likelihood of convergences in R&D productivity. The results confirm that interregional networks and local agglomeration operate at distinct parts of the R&D process. • Productive R&D contributes to innovation, driving sustainable economic development. • R&D productivity is measured at each stage using network DEA. • The contrasting effects reported by the spatial econometric model. • Interregional network has a significant effect on improving the knowledge productivity. • Local agglomeration is more important in technology transfer research. • There is a significant spatial spillover effects of technology transfer productivity across neighbouring regions [ABSTRACT FROM AUTHOR]

Building livable cities has been an important goal for new urbanization in China. Thus, understanding residents' satisfaction with urban livability in China and its determinants is beneficial for urban planning and policy making regarding livable cities construction. However, scientific evidence on satisfaction with urban livability towards Chinese cities is still lacking. Drawing on large-scale questionnaire surveys conducted in 2015 in 40 major cities in China, this paper aims to explore the characteristics of satisfaction with urban livability and the effect magnitude of its determinants using the geographical detector model. The results show that the respondents are just moderately satisfied with urban livability in China (2.996). With respect to the dimensions of urban livability, the respondents are relatively satisfied with the convenience of public facilities (3.118), the natural environment (3.057) and the sociocultural environment (3.056), while slightly dissatisfied with urban security (2.788), environmental health (2.912) and convenient transportation (2.929). The result of the geographical detector model further reveals that all the six dimensions of urban livability have significant and positive impacts upon overall satisfaction with urban livability, of which the natural environment, convenient transportation, environmental health are the greatest contributing factors. Moreover, individual socioeconomic attributes such as geographical location, type of housing, education, family size, age, hukou status, also exert significant effects on overall satisfaction with urban livability in descending order, but the magnitude of their effects is far less than that of the dimensions of urban livability. [ABSTRACT FROM AUTHOR]

Recent studies on racial or ethnic differences have moved beyond the residential neighborhood to understand segregation in terms of people's space-time behavior. In China, where the spatial distribution of ethnic minorities is quite different from Western countries, research on ethnic issues based on this new perspective to date has received far less attention than other social issues such as poverty. This study seeks to examine the effects of ethnicity on people's space-time behavior in the Chinese context. Focusing on the Hui minorities and the Han majorities in Xining, a multi-ethnic city in the western region of China, we examined the space-time patterns of daily activities of these two ethnic groups. We use geovisualization tools and statistical measures to explore the extent to which ethnicity accounts for the differences in space-time behavior between the two ethnic groups. The paper concludes that ethnic characteristics of the Hui minorities, such as gender division of domestic labor and the participation in spatially and temporally fixed daily religious activities, have led to an independent and significant influence of ethnicity on space-time behavior when compared with the Han majorities in Xining. [ABSTRACT FROM AUTHOR]

Housing pressure is one of the most important factors affecting urban residents' quality of life and subjective well-being (SWB). However, few studies have examined the impact of housing pressure on people's SWB and whether housing pressure has heterogeneous effects on SWB in cities of different sizes and for different social groups is still under-researched. Using data from a large-scale social satisfaction survey of 115,000 respondents across 36 cities in China, this paper employs a multiple linear regression model to explore the combined impacts of both subjective and objective housing pressure on urban residents' SWB. It also examines the heterogeneity effects of housing pressure for different city sizes and housing tenure groups. The results show that individuals' subjective housing pressure is significantly and negatively associated with SWB, and its impact intensity is greater than most perceived living environment factors. As for objective housing pressure, only the housing rent-to-income ratio has a significant negative correlation with SWB. Dimensions of individuals' perceived quality of the living environment are also significant positive predictors for the SWB level of urban residents except for the urbanscape and portrait dimension. Housing pressure has heterogeneous effects on SWB in different city sizes and housing tenure groups. • Both the impact of subjective and objective housing pressure on SWB are examined. • The heterogeneity effects of housing pressure for different city sizes and housing tenure groups are considered. • Perceived housing affordability is positively related to SWB. • Perceived quality of the living environment are positive predictors of SWB. [ABSTRACT FROM AUTHOR]

The socio-spatial segregation experienced by migrants has attracted considerable attention and an increasing number of studies have examined segregation in migrants' daily activity space recently. However, research on activity diversity and spatial contact between local residents and migrants has been limited. This paper fills this knowledge gap by investigating the differences in the extensity, intensity, diversity and exclusivity of activity spaces among local residents, urban migrants and rural migrants based on their routine activities in suburban Shanghai, China. It finds that rural migrants have low daily mobility and are physically constrained, and there is spatial sorting of activity locations among different social groups. Neighborhood environment significantly influences activity space-based segregation: People who live in neighborhoods with higher POI density and better access to commercial establishments and public spaces have small activity spaces, while those who live in neighborhoods with mixed land use, better access to public transit, and higher street connectivity have more diverse activity participation. Neighborhoods with better public spaces and a lower land use mix promote shared activity spaces. This study uncovers the segregation suffered by migrants by examining the usage of urban space and spatial interactions among social groups, enhancing our understanding of activity space-based segregation in developing countries. • We analyze the activity space-based segregation emphasizing diverse locations visited in residents' daily lives. • There is significant activity space-based segregation among hukou groups. • Rural migrants have limited daily mobility and are physically constrained in activity space. • Local residents tend not to share activity spaces with migrants. • Residential neighborhood attributes significantly influence activity space-based segregation. [ABSTRACT FROM AUTHOR]

Accessibility is closely related to human health and life quality and is a potential indicator of social exclusion. With an activity-space measure and by weighting the importance of facilities, this study examines the differences in access to facilities between low- and non-low-income groups at both the individual and community levels using Nanjing as a case study. The results show that low-income individuals' access to public transit and commercial facilities is lower than that of individuals in the non-low-income group at the individual level. However, the differences in facility accessibility vary by community type. Participants living in danwei communities and traditional dilapidated communities have better access to facilities and services. However, low-income individuals who live in affordable housing have the lowest accessibility levels among the residents in the three different types of neighborhoods, resulting in their highest risk of social exclusion and isolation in disadvantaged spaces. The regression models reveal that individuals' socioeconomic attributes and characteristics of activities and built-environment attributes have different impacts on facility accessibility of participants of different communities. Social policies should support the equitable distribution of urban resources for different social groups, especially for vulnerable groups who live in affordable housing. • A weighted activity-space approach is used to examine individuals' facility accessibility. • Facility access among participants of low- and non-low-income groups is compared. • Low-income residents have a lower level of access to public transit and commercial facilities. • Facility access among residents of affordable housing is the lowest. • Different variables have different impacts on the facility accessibility of the participants of different communities. [ABSTRACT FROM AUTHOR]

Abstract Given the ongoing "mobility turn" in social science research, a more comprehensive understanding of segregation is needed. Activity-space-based segregation studies have aroused renewed interests in geography and urban planning research. Most of the existing studies utilized the differences in spatial characteristics of people's actual activity space to identify the segregation among social groups. However, few studies have examined activity-space-based segregation in terms of individuals' potential activity space and the temporal variations in their segregation experiences. This paper aims to help fill these two research gaps by implementing an empirical study in Beijing. We examine the activity-space-based segregation of the residents of different types of housing in a Beijing suburb in terms of both actual activity space and potential activity space. We further investigate the temporal variations of the residents' segregation experiences during a week. A 7-day individual GPS tracking dataset, combined with the activity diary data and the socioeconomic attributes data of 422 participants is used for the study. The major finding is that residents of different types of housing in Beijing do experience activity-space-based segregation, while the characteristics of segregation vary with respect to actual activity space and potential activity space. Also, participants' segregation experiences varies between different days of the week. This paper offers some empirical evidence on enriching the understanding of activity-space-based segregation research as well as improving the understanding about social segregation among the residents of different types of housing in Chinese cities. It also generates some nuanced knowledge for future policy recommendations in a broad context. Highlights • Residents of different housing types in Beijing do experience activity-space-based segregation, while the characters of segregation varies in AAS and PAS. • The residents of affordable housing have both the smallest AAS and PAS on weekdays, which makes them the most isolated group. • With respect to the residents of market housing and institutional housing, they have relatively large AAS on weekdays while having relatively moderate PAS. • As for the residents of resettlement housing, their PAS are relatively large, although their AAS are small. • Significant differences in the extensity of both the AAS and PAS of the residents in different housing types can only be identified on weekdays. In weekends, differences in the extensity of the activity spaces are not significant. [ABSTRACT FROM AUTHOR]

Accompanying rapid urbanization and economic transformation, the reconstruction of inner city in urban China has been taking place during recent decades. However, the social and geographic inequality resulted from such reconstruction and experienced by minority groups has received less attention to date. To address this, a case study using individual-level data based on a survey of a relocated state-owned enterprise (SOE) in Guangzhou was conducted. The study shows that similar to other cities in the world, the spatial mismatch that results in long and time-consuming commuting as well as lower quality of life exists. It has considerable adverse impact on the low- and middle-income employees of the relocated enterprise. However, it was not social or racial segregation but institutional transformation that brought about the spatial mismatch in China. Based on the dual economic system in China, both the planned and market systems played important roles in the enterprise's relocation and their employees' daily lives. Institutional barriers associated with the welfare system had a great impact on the geographic immobility of its employees. These include the retirement and medical insurance systems inherited from the planned economy and the supply of work unit buses, which rendered employees more attached to and dependent on their enterprise. However, these provisions were big burdens to the enterprise which reduced their profit and led to lower spatial mobility of its lower-income employees. [ABSTRACT FROM AUTHOR]

The social and spatial patterns of ageing population in urban China illuminate the influence of the socioeconomic transformation associated with the dual economic system. Guangzhou, one of China's megacities, is used as a case study in this paper. Data from the 2010 National Census were used to examine the spatial differentiation and the related factors of ageing communities in Guangzhou. Using social area analysis, the study identified six categories of ageing communities: traditional inner-city communities, traditional danwei residential communities, commercial housing ageing communities, danwei compound ageing communities, immigrant ageing communities, and rural ageing communities. The paper analyses the reasons and processes leading to the clustering of the elderly population in each category of areas associated with distinctive spatial patterns of ageing differentiation. These patterns suggest that the socio-spatial differentiation of ageing communities is a joint outcome of urban development, housing policies, personal status and family relationships. The dynamics of both ageing in place and ageing with migration had a dual impact on the spatial, social and ecological patterns of ageing communities. The spatial differentiation of ageing communities in the study area should be taken into account when formulating urban planning and public policies. In addition, a dynamic public facility and service allocation system is also necessary to meet the needs associated with evolving socio-spatial urban restructuring. [ABSTRACT FROM AUTHOR]

With China’s rapid urbanisation driving its growing economy, the enlarging socio-spatial inequalities in the cities have received wide attention. Rather than following the largely studied residential spaces, this paper focuses on socio-spatial differentiation based on the spaces of one’s out-of-home activities. Using data of 1006 individuals collected by door to door questionnaires, this paper sets up the spatial and temporal autocorrelation GT coefficient to examine the spatial heterogeneity characteristics of high- and low income groups’ out-of-home activities in a continuous spatiotemporal framework. The factors and different mechanisms influencing the clustering of the activities are discussed to better understand social diversity in post-reform urban China. The results suggest that there is obvious spatial and temporal variation in high- and low income groups’ out-of-home activities, indicating that differing social spaces are not just limited to the macro-static residence-based living space, but also exist in the individual’s daily-activities space. Both high- and low income people have drastically different activity spaces and they may not interact much with each other. This is socially very significant because it means that there is considerable social isolation or segregation for both groups. The results also show that within the same income group there exists a divisive cluster with different formation mechanisms, including the job–housing relationship, the correlation of activity opportunities with those surrounding residential areas and the individual’s ability to access activities (that is, space–time accessibility). Structural transition can also impact on activities choices of various social groups. [ABSTRACT FROM AUTHOR]

• Activity satisfaction and air and noise pollution vary in space and time. • Geographic contexts matter in activity satisfaction. • Perceived environmental exposures are significant covariates of wellbeing. • Perceived air pollution has a greater effect than noise on activity satisfaction. Understanding how mobility-based real-time exposures to environmental pollution influence activity satisfaction has great potential for improving subjective wellbeing. Using real-time data from Global Positioning System trajectories and portable sensors collected in Beijing, this study investigates whether and how individual's real-time and perceived exposures to air and noise pollution at a fine spatio-temporal resolution influence activity satisfaction while controlling for geographic contexts, activity characteristics, socio-demographic attributes, health and life circumstances. The results show that activity satisfaction and air and noise pollution vary greatly in various microenvironments. Perceived air and noise pollution are more significant covariates of activity satisfaction than objectively measured pollution, and air pollution has a greater effect than noise pollution on activity satisfaction. These findings indicate that more granular data should be collected to further examine the relationships among geographic microenvironment, personal exposure and wellbeing, and compact city design is of great potential for improving subjective wellbeing. [ABSTRACT FROM AUTHOR]

Rapid industrialization in China has brought forward serious and harmful atmospheric pollution. In this study, spatial econometric analysis was used to analyze the spatial change and the driving forces behind the industrial sulfur dioxide (SO 2 ) discharge in China from 2001 to 2014. The study found that the amount of industrial SO 2 discharge (ISOD) increased first and then decreased during this period. ISOD intensity witnessed a fluctuating drop. There were large differences among intercity ISOD amount and intensity, which had various spatial patterns. Global Moran's I of ISOD amount and intensity had a tendency to increase on the whole, showed positive spatial autocorrelation, and revealed a more and more remarkable clustered spatial pattern. Local spatial autocorrelation analysis found that the spatial patterns of ISOD amount and intensity changed considerably over space and time. The spatial patterns of ISOD were significantly influenced by the regional differences in land use and environmental policy. The study also found that the driving forces of ISOD in China changed significantly from 2001 to 2014. [ABSTRACT FROM AUTHOR]

• Inequality in urban greenspace exposure is assessed for 303 cities in China. • Dynamic inequality is characterized using multi-source geospatial data. • Severe inequality in greenspace exposure is pervasive in Chinese cities. • Dry cold climate and urban densification contribute to high inequality. Given the important role of green environments playing in healthy cities, the inequality in urban greenspace exposure has aroused growing attentions. However, few comparative studies are available to quantify this phenomenon for cities with different population sizes across a country, especially for those in the developing world. Besides, commonly used inequality measures are always hindered by the conceptual simplification without accounting for human mobility in greenspace exposure assessments. To fill this knowledge gap, we leverage multi-source geospatial big data and a modified assessment framework to evaluate the inequality in urban greenspace exposure for 303 cities in China. Our findings reveal that the majority of Chinese cities are facing high inequality in greenspace exposure, with 207 cities having a Gini index larger than 0.6. Driven by the spatiotemporal variability of human distribution, the magnitude of inequality varies over different times of the day. We also find that exposure inequality is correlated with low greenspace provision with a statistical significance (p-value < 0.05). The inadequate provision may result from various factors, such as dry cold climate and urbanization patterns. Our study provides evidence and insights for central and local governments in China to implement more effective and sustainable greening programs adjusted to different local circumstances and incorporate the public participatory engagement to achieve a real balance between greenspace supply and demand for developing healthy cities. [ABSTRACT FROM AUTHOR]

Environmental justice is a crucial environmental and social problem. Previous research in the cities of developed countries has found that ethnic minorities and low-income people were disproportionately exposed to the residential environment with more serious environmental risks. This study proposed a transition from the residence-based perspective to a mobility-based and context-aware approach to reinterpret environmental justice with a focus on the air pollution issue in urban China. A novel research protocol combining geographic ecological momentary assessment and portable air pollutant sensors was developed to collect and analyze real-time data of air pollution exposure and psychological stress for residents living in the same residential neighborhood of Beijing, China. The results show that residents of different types of housing were exposed to varying PM 2.5 concentrations although they experienced similar levels of air pollution in their residential neighborhoods. Residents of public low-rent housing were the disadvantaged group because of their limited mobility, exposure to serious air pollution at home, and insensitive stress responses to air pollution. These findings not only uncover the mobility-based environmental justice issue in the context of government-led and egalitarianism-pursuing urban China, but also provide references for the residential mix policy on how to narrow the disparity in environmental pollution exposure from the perspective of human mobility. • Go beyond the neighborhood effect to examine mobility-based environmental justice. • Use housing as a lens to understand disparities in air pollution exposure in China. • Employ a novel protocol combining air sensors and ecological momentary assessment. • Residents of public low-rent housing are the disadvantaged social group. • Residential mix policy fails to address mobility-based environmental injustice. [ABSTRACT FROM AUTHOR]