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undergraduate thesis: Determinants of pricing premiums in elderly housing : a multi-factor analysis of continuing care retirement communities (CCRCs) in Hong Kong

TitleDeterminants of pricing premiums in elderly housing : a multi-factor analysis of continuing care retirement communities (CCRCs) in Hong Kong
Authors
Issue Date2025
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Citation
Li, W. T. [李穎潼]. (2025). Determinants of pricing premiums in elderly housing : a multi-factor analysis of continuing care retirement communities (CCRCs) in Hong Kong. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR.
AbstractThis paper studies the pricing dynamics of Continuing Care Retirement Communities (CCRCs) in the elderly housing market of Hong Kong. The econometric model of the research analyzes care service levels, nursing care needs, and property characteristics and their impact on rental prices. The elderly housing provision in Hong Kong is facing a severe challenge, as it is projected that the aged population will account for 30 % of the total population by 2041. Current accommodation does not cater to the needs of middle-income elderly residents who require integrated care services. There have been no comprehensive studies of housing pricing dynamics among the elderly in Hong Kong’s specific high-density context. Based on this research, this quantitative framework is provided for market analysis, from both an academic perspective and a practical perspective of improving elderly living conditions. The results indicate that elderly housing developments with medium-level CCRC implementation also have substantial price premiums over basic elderly housing (as a comparison), which implies strong market acceptance of integrated care services. And properties providing high nursing care needs particularly excel, implying recognition of these properties' value. This pricing pattern indicates a market segmentation based on the capabilities for a higher level of care at significant premiums if compliance with nursing home regulatory requirements is not compromised. Findings support that developers and investors should be more involved in medium-level CCRC service implementation while developing specialty capabilities for high-level nursing care needs. It recommends designing such a service-oriented development strategy that pays more attention to care quality and nursing support, whilst guaranteeing operational flexibility for sustained viability. This evidence-based approach offers a framework for optimizing investment returns while meeting the growing demand for comprehensive care services for the elderly in Hong Kong's elderly housing market.
DegreeBachelor of Science in Surveying
SubjectOlder people - Housing - China - Hong Kong
Housing - Prices - China - Hong Kong
Life care communities - China - Hong Kong
Persistent Identifierhttp://hdl.handle.net/10722/366147

 

DC FieldValueLanguage
dc.contributor.authorLi, Wing Tung-
dc.contributor.author李穎潼-
dc.date.accessioned2025-11-18T03:46:15Z-
dc.date.available2025-11-18T03:46:15Z-
dc.date.issued2025-
dc.identifier.citationLi, W. T. [李穎潼]. (2025). Determinants of pricing premiums in elderly housing : a multi-factor analysis of continuing care retirement communities (CCRCs) in Hong Kong. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR.-
dc.identifier.urihttp://hdl.handle.net/10722/366147-
dc.description.abstractThis paper studies the pricing dynamics of Continuing Care Retirement Communities (CCRCs) in the elderly housing market of Hong Kong. The econometric model of the research analyzes care service levels, nursing care needs, and property characteristics and their impact on rental prices. The elderly housing provision in Hong Kong is facing a severe challenge, as it is projected that the aged population will account for 30 % of the total population by 2041. Current accommodation does not cater to the needs of middle-income elderly residents who require integrated care services. There have been no comprehensive studies of housing pricing dynamics among the elderly in Hong Kong’s specific high-density context. Based on this research, this quantitative framework is provided for market analysis, from both an academic perspective and a practical perspective of improving elderly living conditions. The results indicate that elderly housing developments with medium-level CCRC implementation also have substantial price premiums over basic elderly housing (as a comparison), which implies strong market acceptance of integrated care services. And properties providing high nursing care needs particularly excel, implying recognition of these properties' value. This pricing pattern indicates a market segmentation based on the capabilities for a higher level of care at significant premiums if compliance with nursing home regulatory requirements is not compromised. Findings support that developers and investors should be more involved in medium-level CCRC service implementation while developing specialty capabilities for high-level nursing care needs. It recommends designing such a service-oriented development strategy that pays more attention to care quality and nursing support, whilst guaranteeing operational flexibility for sustained viability. This evidence-based approach offers a framework for optimizing investment returns while meeting the growing demand for comprehensive care services for the elderly in Hong Kong's elderly housing market. -
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subject.lcshOlder people - Housing - China - Hong Kong-
dc.subject.lcshHousing - Prices - China - Hong Kong-
dc.subject.lcshLife care communities - China - Hong Kong-
dc.titleDeterminants of pricing premiums in elderly housing : a multi-factor analysis of continuing care retirement communities (CCRCs) in Hong Kong-
dc.typeUG_Thesis-
dc.description.thesisnameBachelor of Science in Surveying-
dc.description.thesislevelBachelor-
dc.description.naturepublished_or_final_version-
dc.date.hkucongregation2025-
dc.identifier.mmsid991045130480803414-

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