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Buildings
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Study on Real Estate and Housing Management—2nd Edition
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Study on Real Estate and Housing Management—2nd Edition

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Architectural Design, Urban Science, and Real Estate".

Deadline for manuscript submissions: 31 August 2025 | Viewed by 2940

Special Issue Editors

Dr. Jian Liang

E-Mail Website
Guest Editor
Faculty of Business & Law, School of Economics & Finance, Queensland University of Technology, Brisbane, QLD 4001, Australia
Interests: housing economics; REITs; real estate finance and investment
Special Issues, Collections and Topics in MDPI journals
Dr. Song Shi

E-Mail Website
Guest Editor
School of Built Environment, Faculty of Design, Architecture and Building, University of Technology Sydney, Ultimo, NSW 2007, Australia
Interests: regional and urban land use; real estate asset pricing; sustainable real estate development and finance; natural disaster and housing market; monetary policy and macroprudential tools on housing
Special Issues, Collections and Topics in MDPI journals
Dr. Han-Suck Song

E-Mail Website
Guest Editor
Department of Real Estate and Construction Management, KTH Royal Institute of Technology, 114 28 Stockholm, Sweden
Interests: housing economics and finance; commercial real estate economics and finance; land valuation; macro economics and real estate; listed real estate; REITs
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue aims to report research regarding the latest developments in real estate and housing management strategy. Recent years have evidenced how the COVID-19 pandemic changed our work–life style and reconfigured the value system, which further influenced the housing behavior of individuals and reshaped the regional structure of real estate and the housing market. Furthermore, most governments' recent unprecedented, aggressive monetary policies further aggregate the risk of real estate and housing markets. Consequently, the existing theories and practicing guidelines of real estate and housing management need a refresh to enhance the real estate industry's productivity and the housing market's efficiency. Some related research papers have been published in the previous edition of this Special Issue, which can be accessed using the following link: https://www.mdpi.com/journal/buildings/special_issues/G6WW309U6M.

In this regard, submissions of research reporting the latest developments in the following fields related to real estate and housing are welcome:

  • Real estate management;
  • Corporate real estate;
  • Housing policy;
  • Housing economics;
  • Real estate finance;
  • Real estate valuation.

Dr. Jian Liang
Dr. Song Shi
Dr. Han-Suck Song
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • real estate management
  • corporate real estate
  • housing policy
  • housing economics
  • real estate finance
  • real estate valuation

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Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Published Papers (4 papers)

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Research

34 pages, 7121 KiB  
Article
A Novel Prediction Model for the Sales Cycle of Second-Hand Houses Based on the Hybrid Kernel Extreme Learning Machine Optimized Using the Improved Crested Porcupine Optimizer
by Bo Yu, Deng Yan, Han Wu, Junwu Wang and Siyu Chen
Buildings 2025, 15(7), 1200; https://doi.org/10.3390/buildings15071200 - 6 Apr 2025
Viewed by 263
Abstract
Second-hand housing transactions are an important part of the housing market. Due to the dual influence of location and price, the sales cycle of second-hand housing has shown significant diversity. As a result, when residents sell or buy second-hand houses, they often cannot [...] Read more.
Second-hand housing transactions are an important part of the housing market. Due to the dual influence of location and price, the sales cycle of second-hand housing has shown significant diversity. As a result, when residents sell or buy second-hand houses, they often cannot accurately and quickly evaluate the cycle of the second-hand house; thus, the transaction fails. For this reason, this paper develops a prediction model of the second-hand housing sales cycle based on the hybrid kernel extreme learning machine (HKELM) optimized using the Improved Crested Porcupine Optimizer (CPO), which has achieved rapid and accurate prediction. Firstly, this paper uses a Stimulus–Organism–Response model to identify 33 factors that affect the second-hand housing sales cycle from three aspects: policy factors, economic factors, and market supply and demand. Then, in order to solve the problems of slow convergence, easy-to-fall-into local optimum, and insufficient optimization performance of the traditional CPO, this paper proposes an improved optimization algorithm for crowned porcupines (Cubic Chaos Mapping Crested Porcupine Optimizer, CMTCPO). Subsequently, this paper puts forward a prediction model of the second-hand housing sales cycle based on an improved CPO-HKELM. The model has the advantages of a simple structure, easy implementation, and fast calculation speed. Finally, this paper selects 400 second-hand houses in eight cities in China as case studies. The case study shows that the maximum relative error based on the model proposed in this paper is only 0.0001784. A ten-fold cross-test proves that the model does not have an over-fitting phenomenon and has high reliability. In addition, this paper discusses the performances of different chaotic maps to improve the CPO and proves that the algorithm including chaotic maps, mixed mutation, and tangent flight has the best performance. Compared with the classical meta-heuristic optimization algorithm, the improved CPO proposed in this paper has the smallest calculation error and the fastest convergence speed. Compared with a BPNN, LSSVM, RF, XGBoost, and LightGBM, the HKELM has advantages in prediction performance, being able to handle high-dimensional complex data sets more effectively and significantly reduce the consumption of computing resources. The relevant research results of this paper are helpful to predict the second-hand housing sales cycle more quickly and accurately. Full article
(This article belongs to the Special Issue Study on Real Estate and Housing Management—2nd Edition)
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23 pages, 1234 KiB  
Article
Housing Behaviors for Older Households in South Korea: The Role of Intergenerational Networks
by Jinyhup Kim
Buildings 2025, 15(5), 740; https://doi.org/10.3390/buildings15050740 - 25 Feb 2025
Viewed by 700
Abstract
This study assesses the predictions of future mobility rates and tenure choice behaviors by characterizing older households by age and place, focusing on the role of intergenerational networks. This study employed mixed effects logistic regression along with longitudinal household data acquired from the [...] Read more.
This study assesses the predictions of future mobility rates and tenure choice behaviors by characterizing older households by age and place, focusing on the role of intergenerational networks. This study employed mixed effects logistic regression along with longitudinal household data acquired from the 2008–2020 Korea Longitudinal Study of Aging. The findings are as follows. First, co-residence with children encouraged older people to remain in their current places of residence. In contrast, those within 30 min of a child’s house by public transportation tended to experience residential mobility and dissave their accumulated housing wealth. Second, the effects of intergenerational networks on housing behaviors—independent living, residential mobility, and tenure transition—seemed greater and statistically significant for the oldest cohort, aged 75 years and above, and in non-metropolitan areas. Finally, intergenerational networks might help vulnerable households—being single or having poor health—stay in their current independent living situations, but they did not appear to be major factors influencing housing decisions, such as residential mobility or housing adjustments, in older households. In conclusion, intergenerational networks seem to have a partial direct impact on aging in place (AIP) in Korea. Instead, older Koreans tend to relocate closer to their children and seem to age in those areas. Understanding the reasons why older households choose to stay or leave their current homes is crucial, as it relates to aging in place (AIP), a widely used term in aging-related matters and a goal of elderly housing policies. This study provides seminal insights into this issue. Full article
(This article belongs to the Special Issue Study on Real Estate and Housing Management—2nd Edition)
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24 pages, 1133 KiB  
Article
Latent Class Analysis of Discrimination and Social Capital in Korean Public Rental Housing Communities
by Sungeun Kim and Seran Jeon
Buildings 2025, 15(3), 337; https://doi.org/10.3390/buildings15030337 - 23 Jan 2025
Viewed by 690
Abstract
This study explored typologies among residents of South Korean public rental housing, focusing on their experiences of discrimination and social capital. Latent class analysis (LCA) was applied to data from 4683 individuals in the 2021 Seoul Public Rental Housing Panel Survey. Four distinct [...] Read more.
This study explored typologies among residents of South Korean public rental housing, focusing on their experiences of discrimination and social capital. Latent class analysis (LCA) was applied to data from 4683 individuals in the 2021 Seoul Public Rental Housing Panel Survey. Four distinct groups were identified: ‘Group Seeking Friendly Neighbor Relationships’, ‘Group Accepting Losses’, ‘Group with High Social Capital’, and ‘Group Indifferent to Neighbors’. The findings revealed that while discrimination was widespread, certain groups exhibited strong social capital. Notably, the ‘Group Accepting Losses’ showed the highest willingness to help neighbors despite facing significant discrimination, while the ‘Group with High Social Capital’ displayed high levels of neighbor trust and mutual support. These results challenge traditional views by showing that social capital can thrive even in the presence of discrimination. This study suggests that policies aimed at addressing discrimination in public rental housing should focus not only on physical integration but also on fostering social connections to enhance community cohesion and reduce mental health issues among residents. Full article
(This article belongs to the Special Issue Study on Real Estate and Housing Management—2nd Edition)
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21 pages, 1231 KiB  
Article
The Impact of Housing Vulnerability on the Relationship Between Social Capital, Residential Satisfaction, and Attitudes Toward Disadvantaged Groups in South Korea
by Sungeun Kim and Seran Jeon
Buildings 2025, 15(1), 36; https://doi.org/10.3390/buildings15010036 - 26 Dec 2024
Cited by 1 | Viewed by 709
Abstract
This study examines the relationships among social capital, residential satisfaction, and attitudes toward disadvantaged groups in South Korea, with a focus on the moderating effects of educational and employment vulnerability. Using data from the 2022 Seoul Survey, which included a sample of 39,340 [...] Read more.
This study examines the relationships among social capital, residential satisfaction, and attitudes toward disadvantaged groups in South Korea, with a focus on the moderating effects of educational and employment vulnerability. Using data from the 2022 Seoul Survey, which included a sample of 39,340 individuals, the analysis employed Hayes’ Process Macro to assess both mediation and moderated mediation effects. The findings show that social capital significantly enhances residential satisfaction (β = 0.557, p < 0.001), which, in turn, positively influences attitudes toward disadvantaged groups (β = 0.411, p < 0.001). Notably, the impact of residential satisfaction on attitudes was stronger for individuals who were educationally and employment-vulnerable, underscoring the amplified role of housing conditions in shaping social attitudes for these groups. These results highlight the importance of strengthening social capital and implementing targeted housing policies to improve the well-being of vulnerable populations. Policy recommendations include integrating social capital-building initiatives with urban planning strategies and addressing the specific needs of vulnerable groups through tailored housing interventions to foster social cohesion and inclusivity. Future research should explore other dimensions of vulnerability and utilize longitudinal data to assess long-term impacts. Full article
(This article belongs to the Special Issue Study on Real Estate and Housing Management—2nd Edition)
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