Modelling locational choices of older adults in China, 2010–2015

Huang, Cui‐Ying; Liu, Ye; Pan, Zehan; Wu, Rongwei

doi:10.1016/j.apgeog.2023.102954

Cited by 3 publications

(3 citation statements)

References 49 publications

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“…In terms of accessibility, proximity to market, family, school, and health institute positively influence the selection of location with a high density of these services. It is consistent with Gonz alez-Espejo et al (2022), Huang et al (2023), Salihoglu and Turkoglu (2019), Schirmer et al (2014), Stokenberga (2019) and Zhan (2015), who suggest nearness to school, family, market, and health positively influence location choice behavior of household.…”

Section: Discussion and Policy Recommendationssupporting

confidence: 90%

“…It is consistent with González-Espejo et al . (2022), Huang et al . (2023), Salihoglu and Turkoglu (2019), Schirmer et al .…”

Section: Discussion and Policy Recommendationsmentioning

confidence: 99%

“…Proximity to retail service, subway, and public transportation was found to have a positive influence (Salihoglu and Turkoglu, 2019; Schirmer et al ., 2014). Huang et al . (2023) and (Stokenberga, 2019) found that households prefer to reside in locations that are near to their extended family.…”

Section: Literature Reviewmentioning

confidence: 99%

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Factors influencing residential location choice: learnings from the Indian context

Saini,

Pandit

2023

OHI

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PurposeThe purpose of the present study is to explore the factors that influence the residential location choice of households in the Indian context.Design/methodology/approachTwo sub-urban towns of Kolkata, i.e. Biddhanagar Municipal Corporation and Rajarhat Newtown, are taken as case studies. In total, 34 variables are considered related to the household's socioeconomic background (10), dwelling (3), travel (2) and level of importance of neighborhood characteristics (19). A revealed preference household survey is conducted, which resulted in the collection of 390 samples. Firstly, 19 level of importance variables are deduced to 3 latent factors using exploratory and confirmatory factor analysis. After that, a utility function is estimated using a multinomial logit regression to identify significant factors.FindingsThe results indicate the significance of car ownership, work travel time, work mode, monthly income, proximity to work, proximity to family/relative/friends, proximity to quality schools, quality of physical infrastructure such as water availability, power availability and housing typology among others in the residential location choice of households.Research limitations/implicationsKolkata, a major metropolitan area in eastern India, has been experiencing space constraints to cater to the housing demand of the ever-increasing population. Although satellite towns are being developed, the infrastructure landscape in such towns is uneven, resulting in more housing demand in one area than another. The study furnishes significant findings to develop more informed policies to attract households in low-demand areas and manage high-demand areas to achieve sustainable planning.Originality/valueConsidering the importance of geographical context, it is the first study on residential location choice, providing a perspective of household behavior from eastern India. It also shows the importance of physical infrastructure attributes in residential location choice for developing countries, which is seldom employed in the current practice. Moreover, previous studies (although few) done in India consider the objective value of location characteristics. The present study focuses on subjective value or the level of importance perceived by respondents.

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Section: Discussion and Policy Recommendationssupporting

confidence: 90%

“…It is consistent with González-Espejo et al . (2022), Huang et al . (2023), Salihoglu and Turkoglu (2019), Schirmer et al .…”

Section: Discussion and Policy Recommendationsmentioning

confidence: 99%

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Factors influencing residential location choice: learnings from the Indian context

Saini,

Pandit

2023

OHI

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Stay, leave late, leave early, return, or move onward? Interprovincial migration decisions of older adults in China, 2000–2005 and 2010–2015

Huang,

Liu,

Pan

2024

Population Space and Place

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Existing studies on the migration of older adults in China have tended to treat older migration as a one‐off activity and have failed to investigate the multiple processes involved. Based on the microdata samples of the 1% national population sample surveys in 2005 and 2015, this study examines the effect of regional and personal attributes on older adults' two‐phase migration decisions. In the first phase, older adults decide whether to leave the province of household registration, while in the second phase, they decide to stay in the same province, return to the province of household registration, or move onward to a new province. In the first phase of migration, older adults' decisions were affected by several regional amenities, including medical services, public green areas, air pollution, and temperature differences. In the second phase of migration, older adults who had decided to remain in the first phase tended to leave provinces with a lower cost of living, fewer public green areas, and more extreme temperature differences. Older adults who, in the first phase, had moved to a new province with fewer medical services, more severe air pollution, and larger temperature differences were more likely to return to their province of household registration in the second phase in 2000‐2005, while those residing in provinces with more extreme temperature differences tended to move onward to a new province in 2010‐2015. This study enhances our understanding of the heterogeneity of older migration in China by disentangling the complexity of multiple migration processes.

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Who can access what? Uncovering urban inequality in access to service for senior citizens

Sulis,

Proietti

2024

Environment and Planning B: Urban Analytics and City Science

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The scarcity or lack of access to essential services at the local and neighbourhood levels in cities can result in significant spatial inequalities, as some areas and their residents can deal with disadvantages and a lower quality of daily life. In particular, the spatial distribution and the variety of amenities at the local scale represent an important feature of the liveliness of places. The local availability and access to essential services are particularly relevant for some demographic groups experiencing limited mobility or mobility poverty, such as older adults living in cities, and spatial disparities have been further exacerbated by the COVID-19 pandemic, which highlighted severe difficulties in accessing essential services. This work explores the issue focussing on the following question: who can access what depending on where they live in cities? Using Machine Learning and Spatial Autocorrelation applied to different data sources for spatial information on the location of urban amenities and Internet access, this work aims to identify the most underserved places in terms of the variety of available amenities and access to quality broadband in three European capital cities. A comparison to urban areas where high percentages of older adults reside makes it possible to identify where residents can locally access several essential services (green spaces, health care, and local shopping) and where this need cannot be satisfied because of a lack in the amenity variety available at walking distance to their home. The combination of underserved areas with a high concentration of senior residents identifies left-behind areas in these cities, where interventions on inequalities are most needed. Results can inform policies aiming at favouring fair access to services at the local scale, possibly including slow and active mobility modes, and in general to develop comprehensive and sustainable planning strategies for cities, leaving no place and no person behind.

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Modelling locational choices of older adults in China, 2010–2015

Cited by 3 publications

References 49 publications

Factors influencing residential location choice: learnings from the Indian context

Factors influencing residential location choice: learnings from the Indian context

Stay, leave late, leave early, return, or move onward? Interprovincial migration decisions of older adults in China, 2000–2005 and 2010–2015

Who can access what? Uncovering urban inequality in access to service for senior citizens

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