Understanding Spatial Distribution of Retirement Villages: An Analysis of the Greater Brisbane Region

Bo Xia; Jiaxuan E; Qing Chen; Laurie Buys; Tan Yigitcanlar; Connie Susilawati

doi:10.3390/urbansci5040089

Urban Science (Nov 2021)

Understanding Spatial Distribution of Retirement Villages: An Analysis of the Greater Brisbane Region

Bo Xia,
Jiaxuan E,
Qing Chen,
Laurie Buys,
Tan Yigitcanlar,
Connie Susilawati

Affiliations

Bo Xia: School of Architecture and Built Environment, Faculty of Engineering, Queensland University of Technology, 2 George Street, Brisbane, QLD 4000, Australia
Jiaxuan E: School of Architecture and Built Environment, Faculty of Engineering, Queensland University of Technology, 2 George Street, Brisbane, QLD 4000, Australia
Qing Chen: School of Architecture and Built Environment, Faculty of Engineering, Queensland University of Technology, 2 George Street, Brisbane, QLD 4000, Australia
Laurie Buys: Faculty of Health and Behavioural Sciences, The University of Queensland, St. Lucia, QLD 4072, Australia
Tan Yigitcanlar: School of Architecture and Built Environment, Faculty of Engineering, Queensland University of Technology, 2 George Street, Brisbane, QLD 4000, Australia
Connie Susilawati: School of Economics and Finance, Faculty of Business and Law, Queensland University of Technology, 2 George Street, Brisbane, QLD 4120, Australia

DOI: https://doi.org/10.3390/urbansci5040089
Journal volume & issue: Vol. 5, no. 4
p. 89

Abstract

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The nature of the increasingly ageing populations of developed countries places residential issues of these populations at the heart of urban policy. Retirement villages as housing options for older adults in Australia has been growing steadily in recent years; however, there have been a dearth of geographical studies looking into the distribution of existing retirement villages at the regional level. This study aims to reveal the geographical distributions and cluster patterns of retirement villages in the Greater Brisbane Region of Australia to better understand and serve the living requirements of current and potential retirement village residents. The geovisualization method was adopted to visually explore the distribution patterns of retirement villages. The Global Moran’s I and Local Moran’s I measures were employed to analyze the spatial correlation and the clusters of retirement villages in the study region. The study revealed that distribution of retirement villages was not random (z-score = 7.11; p < 0.001), but clustered in nature and included hotspot patterns, especially along the coastline and Brisbane River areas. Moreover, for-profit and not-for-profit retirement villages have different distribution patterns and adopted significantly different tenure agreements. In the study region, the spatial distribution of retirement villages aligns with the aggregation trend of older residents. The findings of this study disclosed the spatial distribution patterns of retirement villages and will provide developers and policymakers with geographically referenced data for the choice of new development sites to meet the market demand of potential customers, forming aged-friendly development strategies, and eventually leading to improved quality of life for older Australians.

Published in Urban Science

ISSN: 2413-8851 (Online)
Publisher: MDPI AG
Country of publisher: Switzerland
LCC subjects: Geography. Anthropology. Recreation; Social Sciences
Website: http://www.mdpi.com/journal/urbansci

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