Daily activity space and exposure: A comparative study of Hong Kong's public and private housing residents' segregation in daily life

Wang, Donggen; Li, Fei

doi:10.1016/j.cities.2015.09.010

Cited by 88 publications

(84 citation statements)

References 33 publications

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“…In addition, one of the weakness of the CDR data used in this study is the dependency on call activities: data about people's spatial behaviour are received only when a person completes a call activity. Despite these limitations, mobile positioning data are being increasingly used in activity space based segregation studies (Farber, Páez, and Morency 2012;Silm and Ahas 2014a;Järv et al 2015;Wang and Li 2016;Tan, Kwan, and Chai 2017) because these data provide a more detailed picture of the activity spaces of people over a longer time period (e.g. a year), compared with questionnaires and travel diaries.…”

Section: Discussionmentioning

confidence: 99%

“…Nonetheless, the place-based approach ignores personal experience, geographical context, and spatial mobility (Kwan 2012). Therefore, we use the activity space approach also (Farber, Páez, and Morency 2012;Silm and Ahas 2014a;Järv et al 2015;Wang and Li 2016), where ethnic differences in space-time behaviour are assessed according to individual activity space measures.…”

Section: Methodsmentioning

confidence: 99%

“…These more complex patterns are related to growing spatial mobility and the use of ICT. Therefore, studies have increasingly adopted the activity space approach to segregation (Farber, Páez, and Morency 2012;Silm and Ahas 2014a;Järv et al 2015;van Ham and Tammaru 2016;Wang and Li 2016;Tan, Kwan, and Chai 2017).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Are younger age groups less segregated? Measuring ethnic segregation in activity spaces using mobile phone data

Silm

Ahas

Mooses

2017

Journal of Ethnic and Migration Studies

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Both assimilation theory and common sense suggest that the longer the immigrants reside in a host society, the more they become integrated. However, studies conducted in many countries show the opposite: younger generations of immigrants are more segregated than their parents. The aim of this study is to examine differences in ethnic segregation between age groups of the Estonian majority and Russian-speaking minority in Estonia. We use census data and passive mobile positioning data (CDR) to measure levels of segregation at the individual level for important activity locations and for the whole activity space. Results indicate that segregation in both places of residence and out-of-home nonemployment activity districts is higher in younger than in older age groups. Measures of activity space show that the activity spaces of Russian-speakers of all age groups are smaller and less diverse than those of Estonians, and are mainly bound to the places of residence of Russian-speakers. The differences between the activity space measures for Estonians and Russian-speakers generally reduce with age, which suggests higher ethnic segregation in younger age groups. The results thus show that, contrary to assimilation theory, the spatial behaviour of Russian-speakers has not become similar to that of Estonians over generations.

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Are younger age groups less segregated? Measuring ethnic segregation in activity spaces using mobile phone data

Silm

Ahas

Mooses

2017

Journal of Ethnic and Migration Studies

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“…In recent years, some literature indicates that people experience differentiation, not only in their residential neighborhoods, but also in their daily activities, physical mobility, or social networks [15,16]. For instance, spatial differentiation in shopping and leisure activity centers was analyzed in Seoul, South Korea [17]; segregation at workplaces for newly-arrived immigrant men and women was investigated in Sweden [18]; and activity differentiation, based on daily life experiences in terms of activity space, was studied in Hong Kong [19]. It greatly enriches the research content of differentiation.…”

Section: Introductionmentioning

confidence: 99%

Residential Spatial Differentiation Based on Urban Housing Types—An Empirical Study of Xiamen Island, China

et al. 2017

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Abstract:Residential spatial differentiation, also called residential segregation, is a representation of the differentiation of social stratum in economic income, social status, education degree, lifestyle, and other aspects, based on an urban geographical space. In this paper, Xiamen Island is taken as example to calculate the dissimilarity index and the multi-group dissimilarity index at three scales (districts, sub-districts, and communities) by using the land area, population size, and green space area of different housing types. The characteristics of residential differentiation are analyzed. It is found that both spatial differentiation and multi-group spatial differentiation have significant scale effects. The smaller the scale of the spatial statistics unit, the larger the spatial differentiation and multi-group spatial differentiation. Significant differences are found in residential differentiation among different housing types. The residential differentiation is, not only demonstrated in land area and population size, but also in the resources of green space. More importantly, a balanced allocation of green space will help to reduce the degree of residential differentiation. With urban expansion and social-economic development, residential spatial differentiation will likely change. An understanding of residential differentiation is a guide for urban master planning and detailed regulatory planning. It will help to promote social harmonious development and urban sustainable development by the reasonable configuration of land and resources.

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“…Furthermore, an instructive finding from numerous studies is that there seems to be a strong correlation between the characteristics of the residential neighbourhood and the areas visited during daily and other reoccurring activities (Wang et al 2012;Krivo et al 2013;Wang & Li 2016). In the study by Krivo et al (2013) on social isolation in the Los Angeles area, multi-level analysis revealed that the use of urban space during out of home-activities was strongly tied to the area of residence, indicating that most people spent their time in areas with characteristics akin to the home neighbourhood.…”

Section: Segregation Across Multiple Spatial Domainsmentioning

confidence: 99%

Spatial and temporal patterns of economic segregation in Sweden’s metropolitan areas: A mobility approach

Östh

Shuttleworth²,

Niedomysl

2018

Environ Plan A

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The statistical resources at hand for segregation research are usually almost exclusively confined to annual or decennial records where the only available spatial information is the individual’s place of residence. This coarse temporal periodicity and spatial resolution provides a very limited account of people’s diurnal lives. Incorporating mobility and temporal dimensions in segregation analysis is advocated within a growing body of research but there has rarely been sufficient data to make this possible. In this paper, we employ a fine-grained mobile phone dataset outlining the daily mobility of a substantial sample of the residents in Sweden’s metropolitan areas. Combining spatial trajectory data with detailed socio-economic residential statistics, we are able to study how everyday spatial mobility in cities shapes the segregation experiences of people and changes the segregation levels of places. Results indicate that while mobility alleviates segregation for some individuals, the population of a large number of areas remain highly segregated even when daily mobility is taken into account. Individuals residing or spending time in central urban areas are more exposed to individuals from other areas because of daily moves to these central places. Daytime movement to central areas also reduces segregation significantly for people from places remote from city centres but with high average levels of mobility whilst daytime segregation levels remain close to their original night-time levels in low-mobility areas in the outskirts of the cities.

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Daily activity space and exposure: A comparative study of Hong Kong's public and private housing residents' segregation in daily life

Cited by 88 publications

References 33 publications

Are younger age groups less segregated? Measuring ethnic segregation in activity spaces using mobile phone data

Are younger age groups less segregated? Measuring ethnic segregation in activity spaces using mobile phone data

Residential Spatial Differentiation Based on Urban Housing Types—An Empirical Study of Xiamen Island, China

Spatial and temporal patterns of economic segregation in Sweden’s metropolitan areas: A mobility approach

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