scholarly journals Optimal Project Planning for Public Rental Housing in South Korea

2020 ◽  
Vol 12 (2) ◽  
pp. 600 ◽  
Author(s):  
Jae Ho Park ◽  
Jung-Suk Yu ◽  
Zong Woo Geem
Keyword(s):  
Public Housing ◽  
Rental Housing ◽  
Land Development ◽  
Optimal Investment ◽  
Project Planning ◽  
Optimization Techniques ◽  
Korean Society ◽  
Housing Investment ◽  
Public Rental Housing ◽  
Gyeonggi Province

Although Korea has made notable progress in the availability of public rental housing, Korea’s public rental housing representing 6.3% of the country’s total housing is still below the 8% OECD average from 2016. The Seoul Metropolitan Area (composed of Seoul City, Incheon City, and Gyeonggi Province) has nearly 50% of the country’s population, but 11% of the nation’s territory, meaning the area suffers from an acute shortage of public rental housing. This is a serious problem which is hampering the sustainability of Korean society in general. We will examine the possibility of improving this public housing problem using certain algorithms to optimize decision making and resource allocation. This study reviews two pioneering studies on optimal investment portfolio for land development projects and optimal project combination for urban regeneration projects, and then optimizes a public housing investment combination to maximize the amount of public rental houses in Gyeonggi province using optimization techniques. Through the optimal investment combination, public rental houses were found to be more efficiently and sustainably planned for the community.

scholarly journals Public Housing Allocation Model in the Guangdong-Hong Kong-Macao Greater Bay Area under Clustering Algorithm

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Lei Zhang ◽  
Xueqing Hu
Keyword(s):  
Hong Kong ◽  
Public Housing ◽  
Clustering Algorithm ◽  
Rental Housing ◽  
Data Set ◽  
Allocation Model ◽  
Housing Security ◽  
Bay Area ◽  
Public Rental Housing ◽  
Housing Allocation

In the Guangdong-Hong Kong-Macao Greater Bay Area (Bay Area), the allocation methods of public rental housing are analyzed to achieve scientific and fair housing allocation as much as possible, so as to protect the housing demand of low-income and middle-income families. The housing model in the Bay Area is analyzed firstly, and the key points of public rental housing and allocation management models are discussed comprehensively. Furthermore, a method based on rough-based fuzzy clustering (RFC) is proposed to analyze the housing demands of security groups, and a public housing allocation model is constructed based on actual demand of residents. The housing allocation plan is given and decided by the decision-making department based on the demand of the security objects and the characteristics of public housing. The simulation experiments are performed on the clustering algorithm optimized based on rough set feature selection. On the Chess data set, the optimized clustering algorithm shows an obvious improvement in clustering accuracy and recall rate compared with the traditional clustering algorithms, which are 0.76 and 0.95, respectively. The bilateral matching method based on fuzzy axiom design can fully consider the actual needs of both the supply and demand of the housing security, which is beneficial to improve the rationality and correctness of public housing allocation. The allocation method of public housing based on demand clustering analysis focuses on improving the housing security level and strives to meet the higher-level housing improvement needs of housing security objects, so as to provide security objects with more expected living conditions and improve housing allocation effect.

scholarly journals Investment Valuation Model of Public Rental Housing PPP Project for Private Sector: A Real Option Perspective

2019 ◽  
Vol 11 (7) ◽  
pp. 1857 ◽  
Author(s):  
Jiangang Shi ◽  
Kaifeng Duan ◽  
Shiping Wen ◽  
Rui Zhang
Keyword(s):  
Private Sector ◽  
Real Option ◽  
Rental Housing ◽  
Tree Model ◽  
Binomial Tree ◽  
Housing Investment ◽  
Valuation Model ◽  
Public Rental Housing ◽  
Investment Valuation ◽  
The Government

Public rental housing (PRH) in China is mainly invested by the government at present. The huge capital demand brings it great pressure and a series of problems appear meanwhile. Public–private partnership (PPP) has been regarded as a way to solve the funding dilemma of PRH. However, the PRH project is not attractive for the private sector since the expected profit seems unsatisfactory based on traditional valuation methods. To improve this situation, this paper proposed an investment valuation model from a real option perspective. For the private sector, three types of options, including deferral option, abandonment option, and expansion option, were identified during the concession period of a PRH PPP project. On this basis, a two-stage binomial tree model was constructed for estimating the investment value. Then, the proposed model was tested in a hypothetical example of a typical PRH PPP project in Chongqing, China. The result shows that great potential value can be excavated through flexible strategies and adaption to uncertainties. This paper provides a deep analysis on the gaps of the real option application in public housing investment assessment, which is meaningful for improving the supply efficiency and financial sustainability of PRH.

A Study on the Improvement of the Public Rental Housing Policy in Korea

2009 ◽  
Vol 39 (3) ◽  
pp. 727-744
Author(s):  
Sang-Bong KIM ◽  
Ki-Sik HWANG ◽  
Rok RYU
Keyword(s):  
Housing Policy ◽  
Rental Housing ◽  
The Public ◽  
Public Rental Housing
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