| Author: | Chan, Wing Yee |
| Title: | Analysis of the distribution patterns of rental housing tenants in Hong Kong |
| Advisors: | Liu, Xintao (LSGI) |
| Degree: | M.Sc. |
| Year: | 2019 |
| Subject: | Synthetic aperture radar -- Changbai Shan (China and Korea) Volcanoes -- Changbai Mountains (China and Korea) Hong Kong Polytechnic University -- Dissertations |
| Department: | Faculty of Construction and Environment Department of Land Surveying and Geo-Informatics |
| Pages: | vii, 70 pages : color illustrations |
| Language: | English |
| Abstract: | Under the situation of high land price and limited supply of new public and new private housing, the price of private housing is prohibitively expensive that only can be afforded by middle-income class or above. Coupled with the waiting time for public rental housing is getting longer and longer, there is clearly a growing demand for private rental housing. This paper attempts to analyse where most people rent through exploring the spatial patterns of rental housing tenants in Hong Kong, and to understand why most people rent in that place through finding out which factors will affect people's choice of renting and which factor is the most influential one. The data analytical results show that the distribution of total rental housing tenants, public residential tenants and co-tenants of private rental housing demonstrated a positive spatial autocorrelation. By contrary, the distribution of private residential tenants and sole-tenants of private rental housing do not has any spatial autocorrelation. The regression analysis shows that the school network, the MTR network, the work place of working population, and the house rent would affect people's choice of where to rent a house. Noticeably, among of these factors, people's work place is the most influential one. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 991022385340803411.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 2.56 MB | Adobe PDF | View/Open |
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