Financial Policies for Single-Person Household Housing in South Korea

Abstract

We investigated the determinants of awareness, utilization, and satisfaction regarding financial aid programs for single-person households in South Korea and proposed policy enhancements. Our analysis employed logistic regression on microdata from the “2020 Housing Survey” by Statistics Korea, covering the nation and all age groups. We categorized single-person household traits affecting program awareness, utilization, and satisfaction into demographic, socio-economic, housing, and housing perception factors. The dependent variables included awareness, utilization status, and satisfaction levels of government-sponsored financial support programs, which were measured on a four-point Likert scale. The independent variables encompassed demographic, socio-economic, and housing characteristics, which were analyzed comprehensively. We identified factors that influenced awareness, utilization, and satisfaction and recommended tailored policy measures. The findings revealed lower awareness among elderly individuals, women, rural residents, and rental households. Moreover, older age, lower income, rental, and one-room dwelling households exhibited lower utilization rates, with decreased housing and residential environment satisfaction correlating with diminished program satisfaction. Due to the diverse characteristics of single-person households, strategic interventions are crucial. Measures to bridge information gaps, establish comprehensive long-term support systems, and develop differentiated policies tailored to single-person household traits are imperative for improving financial aid programs for this demographic.

1. Introduction

The proportion of single-person households is increasing rapidly, not only in South Korea but also in major cities around the world. According to the “2021 Social Indicators of Korea” by Statistics Korea, single-person households account for the largest share among all households, reaching 31.7% nationwide. The total population has been steadily decreasing since 2010, and the average number of household members has also declined from 3.12 in 2000 to 2.34 in 2020. In contrast, the proportion of households with two or fewer members is increasing annually. Particularly noteworthy is the surge in the ratio of single-person households, which rose from 15.5% in 2000 to 31.7% in 2020, becoming the predominant household type. This trend is projected to continue until 2047, with the single-person household ratio in 17 regions expected to rise to 37.3%. Furthermore, the willingness of single-person households to continue their current lifestyle, characterized by freedom and leisure time utilization, is high, indicating a sustained increase in the future [1]. This underscores the need for a transition in housing policies to align with the ongoing restructuring of the housing market, focusing on standalone and small-sized households.

Housing, due to its inherent characteristics, social attributes, and individual value, presents a complex array of issues. Consequently, many countries, including South Korea, actively adopt and manage major policies and systems related to housing [2]. Specifically, satisfaction with housing is referred to as “residential satisfaction”, which is defined as the emotional response of individuals to their housing environment and the subjective evaluation of housing needs [3]. Researching residential satisfaction is crucial for understanding housing, as it is influenced by various factors.

The residential environment generally affects residential satisfaction, and recent research by Lee [4] that explored the connection between the living environment and the well-being of the elderly demonstrated that the housing environment also influences their mental well-being. Similarly, a study by Shin and Chang [5] that focused on the growth and development of children, using the housing environment as a variable, indicates that the living environment affects the growth and development of children. Hence, the impact of the housing environment extends beyond mere residential satisfaction to various variables.

In a study conducted by Park, Kim, and Park [6] on the relationship between the housing environment and residential satisfaction, diverse housing environments were found to influence residential satisfaction positively, showing that improved housing environments lead to higher levels of residential satisfaction. Additionally, research suggests that as residential satisfaction and the housing environment improve, happiness increases [7]. This indicates that residential satisfaction and the housing environment also influence psychological well-being. Notably, in a study on the life satisfaction of single-person households conducted by So, the type of housing tenure was identified as one of the factors that affected life satisfaction, highlighting that the satisfaction of life varies based on housing for single-person households [8].

According to the 2020 Housing Survey [9], despite the sharp rise in single-person households, they still contend with substandard housing environments and the burden of housing costs. The proportion of single-person households finding housing expenses very burdensome is 17.7%, while those finding them somewhat burdensome constitute 51.2%, those finding them not very burdensome are 27.7%, and those finding them not burdensome at all make up 3.4%. Additionally, there exist non-residential single-person households at a rate 2.1 times that of households with occupants, with 50.5% of them residing in housing areas of 40 m² or less, and 68.9% experiencing housing cost burdens. Compared with multi-person households, single-person households face precarious employment stability, lower educational and income levels, and a risk of impoverishment when relying on a single income source [3]. These deteriorating housing conditions and housing cost burdens of single-person households can be attributed to various factors, particularly for those who have not secured stable employment and income sources, making it difficult to meet living expenses and accumulate savings for relocation to better housing environments.

The worsening housing conditions and financial burdens for single-person households can be attributed to various reasons. Particularly, for those who fail to secure stable employment and income sources, there are limitations in acquiring funds for living expenses and accumulating savings for upward mobility in housing. Compared with multi-person households, single-person households may face instability in employment, lower educational and income levels, and potential poverty when relying on a single income source. Moreover, single-person households are more susceptible to social issues, such as unemployment, illness, loneliness, and isolation, requiring specific social attention.

Despite these challenges, the current housing policies for single-person households in South Korea are insufficient, and they often do not receive priority consideration in policies compared with low-income multi-person households. According to the 2020 Housing Survey, 63.4% of single-person households are renters, and 82.2% belong to the low-income category. Among them, 59.9% express the most significant need for financial support for renting or purchasing a home. The demand for financial assistance among single-person households is high. However, satisfaction levels among current financial support program users are significantly lower than those of housing supply policies. Therefore, it is essential to re-evaluate and improve existing housing finance policies.

The South Korean central government recognizes the importance of financial support in improving the housing conditions of single-person households. They have implemented the “Comprehensive Plan for Single-Person Households” and operate various programs, such as loans, housing supply, housing allowances, and home repair support. Despite various online promotions and media efforts, the awareness and utilization rates of housing support programs among single-person households remain low. This leads to inadequate government support perception [1]. Considering the socio-economic vulnerabilities of single-person households, the limitations of support policies, and the growing trend, there is a need for detailed housing support program operations to enhance the program effectiveness.

The current government is making efforts to improve and include single-person household financial support policies and secure various forms of housing. However, it is challenging to encompass the rapid increase in single-person households with a single support system. There are institutional difficulties, such as a shortage of housing supply. More importantly, single-person households exhibit diverse characteristics based on factors such as age, income level, and location, requiring a detailed classification and understanding of their specific situations.

Therefore, this study aimed to analyze the usage patterns of financial support programs for single-person households based on their housing demands by examining these patterns nationwide and across all age groups. This study also sought to identify factors influencing the recognition, usage, and satisfaction of financial support programs. This will provide a foundation for suggesting basic directions and responses for financial support in the housing of single-person households.

2. Review of Literature

The trend of single-person households is growing globally, especially in countries within the European Union and major cities. Research on foreign support systems for single-person households reveals that in the United States, policies mainly target low-income individuals, seniors, and persons with disabilities, with a focus on housing, community service programs, and taxation [5]. Similarly, major European countries, like France, Sweden, and the United Kingdom, emphasize citizenship protection and social integration through social welfare systems rather than single-person household-specific policies [4].

Thus, there are few specialized support systems exclusively for single-person households internationally, with a focus instead on stabilizing housing through social safety nets. As demographic shifts and the rise in single-person households continue, domestic research on single-person households is steadily increasing. Many studies now emphasize the need for tailored support policies that consider regional characteristics through age-specific financial policies and housing supply studies aimed at enhancing the housing satisfaction of single-person households [2,3,4,10,11,12,13,14].

First, when examining financial assistance programs for single-person households abroad, it was found that they are primarily operated through income tax deductions, housing allowances, and rental support vouchers [15]. In the United States, the low-income population is supported through income tax deductions for housing rent and interest payments on home loans via rental support vouchers [12]. France provides housing allowances to young single-person households residing in rental apartments, university dormitories, and privately operated dormitories [16,17,18].

Comparing Korean policies based on international support policies yields the following. In South Korea, the proportion of youth-headed households in the total household population accounts for 68.0% (ages 25–29), 43.4% (ages 30–34), and 26.0% (ages 35–39) based on the household head age, with a PIR (rent-to-income ratio) at 31.4% [3]. This indicates that youth often reside in rental rather than owned housing due to initial asset shortages, leading to difficulty in securing rental deposits, resulting in lower deposits and higher rents. The increasing number of single-person households, particularly among the youth, demands a systematic and comprehensive housing support program. Many individuals in this demographic are highly dependent on their parents, and there is a notable desire for housing support programs that can help them become independent [11]. While some policies for single-person households exist, most support programs target the youth, indicating a need for research focusing on the elderly, who also form a significant portion of single-person households [12].

Various housing support programs are being demanded for single-person households, but it is essential to assess their effectiveness. Housing expenses, such as key money and rent, significantly impact the life satisfaction of single-person households, playing a crucial role in determining their quality of life. Therefore, the necessity for housing welfare programs is high, and institutional responses for sustainability are imperative [13].

To address the issue, the government formed the 2020 Single-Person Household Policy Task Force to explore measures that support low-income individuals in vulnerable housing situations [8]. However, these efforts are mainly concentrated in Seoul and the metropolitan area, predominantly targeting the youth and posing limitations in encompassing the diverse characteristics of all single-person households. Despite the high demand for housing financial support among single-person households, the current central government’s housing support policy primarily focuses on the supply of rental housing for the youth and the elderly.

While overseas cases in Europe and the United States differ from the situation in South Korea, there is a need to explore institutions that can be applied in the short or long term. Establishing social consensus on the societal value of single-person households and implementing support measures in South Korea focusing on “community maintenance” and “social care” dimensions is necessary. Overseas countries focus on policy initiatives for the adaptation of single-person households to local communities, and minimizing trial and error and carefully assessing applicability upon domestic adoption is crucial. Considering changes in household structures, the increase in single-person households, and housing vulnerability across age groups, it is deemed necessary to tailor public housing support responses to different types of single-person households. The policy status of financial support for single-person households and preceding studies, both domestically and internationally, were analyzed, and the distinctiveness and implications of this study were derived.

2.1. Single-Person Household Housing Support Financial Programs in South Korea

The South Korean government has implemented various schemes to ensure housing stability for single-person households vulnerable to housing insecurity, considering the increasing trend of single-person households [11,12]. However, targeted support specifically for single-person households remains insufficient. Therefore, selecting programs targeting the entire age group that align with the support conditions of individual single-person households is unavoidable [16]. The financial programs supported in South Korea include the following.

Financial support programs in South Korea include Stable Housing Monthly Rent Loans, Housing Lease Fund Loans, and Housing Purchase Fund Loans (

Table 1. The characteristics of housing support programs in South Korea by type.

Classification		Characteristics
Housing fund loan support	Residential Stability Monthly Rent Loan	A monthly rent loan for non-homeowners, targeting job seekers, Hope Savings Account subscribers, and recipients of employment encouragement subsidies, with a focus on household heads and early career individuals among those not owning a home
	Housing Lump-Sum Rental Deposit Loan	Loans for securing lump-sum rental payments, including Mortgage Support Loans, Worker and Low-Income Tenant Deposit Loans, and Low-Income Household Tenant Deposit Loans
	Housing Purchase Fund Loan	Loans for securing home purchase funds, including First Home Loans, Worker and Low-Income Purchase Loans, and Lifetime First Purchase Loan

). The usage of Stable Housing Monthly Rent Loans has been increasing annually, but the actual usage remains minimal for vulnerable populations [17]. The Housing Lease Fund Loan support provides loans for housing stability to non-homeowners based on the income level of lessees and the size of the deposit. This system reinforces support for low-income individuals and vulnerable households. Housing Purchase Fund Loans include various programs aimed at alleviating housing financial burdens and expanding opportunities for non-homeowners, such as Home Acquisition Savings Loans, loans for purchasing office-tels (provide integrated office and hotel amenities within a residential environment), and profit-sharing mortgages.

The Housing Stability Monthly Rent Loan is a program that provides financial support for monthly rent to those without homes based on Article 9 of the Housing and Urban Fund Law. The program prioritizes vulnerable groups, such as job seekers, early career individuals, and recipients of basic living allowances, and does not feature any lump sum or prepayment fees [13]. Importantly, there are no restrictions on the type of residence, including studio apartments, at the time of application. Although the eligibility criteria have expanded to include recipients of housing benefits, the utilization remains minimal, considering the housing cost burden faced by single-person households in vulnerable situations. Despite government efforts to support young individuals, many are unaware of the specific programs available, as highlighted by Lee Hyo-jung in her article “Financial Support Suitable for Single Youth”, published in Dailypop on 1 September 2021 [18].

The Support for Security Deposits for a Lump-sum Rental Payment program is implemented under Article 9, Paragraph 1, Clause 1 of the Housing and Urban Fund Law, targeting non-homeowners with low incomes [19]. The eligibility criteria include all household members being non-homeowners, with the head of the household being legally an adult on the loan application date. Since 2018, the government has been improving or introducing new programs to support youth with a short employment history, including the Youth-Exclusive Rental Security Deposit Loan (introduced in January 2018), Small- and Medium-Sized Enterprise Employment Youth Lump-Sum Rental Deposit Loan (introduced in June 2018), and Tailored Youth Rental Deposit Loan (introduced in May 2019).

Home purchase loans are available for single-person households without homes through programs such as the Housing Fund’s Dream Home Loan, Housing Stability Home Purchase Loan, Profit-and-Loss-Sharing Mortgage, and Office-Tel Purchase Loan. The Dream Home Loan integrates various fund products for homebuyers and housing stability loans. Due to its status as a government policy product, it enjoys a top priority for low-interest rates and additional interest rate incentives, making it the preferred loan for low-income home purchases. However, there are limited types of home purchase loans available for single-person households. The Dream Home Loan, in particular, gives priority to households without homes, primarily favoring newlyweds or married households without homes, making it difficult for single individuals to access. Furthermore, the increasing trend in home purchase loans among youth can be attributed to government support enhancements and the expansion of online credit loans for youth. Establishing interest rate levels to prevent housing purchases by young individuals from becoming a credit risk and setting criteria based on life cycle characteristics are essential.

Many of South Korea’s financial support programs have eligibility criteria that are based on factors like being in the early stages of one’s career, being married, and having multiple dependents. This often limits the options available to single-person households. Additionally, improvements made to these programs tend to focus on young people, such as job seekers, those employed in small- and medium-sized enterprises, and those who are starting their careers, which leaves middle-aged and elderly individuals with few options to address their own unique challenges. It is important to develop improvement plans that cater to the needs of a diverse range of age groups, rather than focusing solely on the youth.

2.2. Previous Studies on Financial Programs for Single-Person Household Housing Support

It is apparent from multiple studies that housing support policies for single-person households, with their distinct characteristics compared with traditional household types, are based on an understanding of demographic, socio-economic, and housing features (Table 2). Therefore, there is a need for the micro-level analysis of factors influencing satisfaction with housing support programs to identify areas for maintaining, improving, and strengthening the current operational framework.

Upon analyzing the results of previous studies, the following findings emerged. First, many studies presented policy proposals by primarily understanding the characteristics, distribution variations, residential characteristics, and residential perceptions of single-person households [15,16,17,20]. Second, a significant number of research works focused on the average characteristics of specific age groups, such as the elderly and youth [21,22,23]. Third, domestic studies mainly proposed policies centered around housing supply and loan support, while international research [24,25] indicates the implementation of welfare systems aiming at protecting the citizenship rights and social integration of single-person households [26].

Policies for single-person households in the United States and Canada are primarily focused on supporting low-income individuals, seniors, and people with disabilities, with an emphasis on housing, community service programs, and tax regulations [27,28]. In major European countries, such as France, Sweden, and the United Kingdom, the focus is on protecting citizenship rights and promoting social integration through social welfare systems rather than specific support policies for single-person households. Thus, overseas, there are not many special support systems exclusively for single-person households, and it can be observed that the focus is on stabilizing housing for single-person households through the concept of social safety nets.

Table 2. Previous studies on housing support for single-person households.

Classification		Objectives	Methods	Results
Research report	1 [11]	Analysis of limitations in public sector policies for single-person households Analysis of economic, social, and housing characteristics of single-person households and proposal of policy measures for housing improvement	Literature and institutional review Policy comparison Statistical analysis	Revision of central government regulations is necessary Tailored support policies for single-person households based on their characteristics are needed Expansion of housing supply to reduce the burden of living expenses Proper housing standards and support are required for upward movement of housing
	2 [16]	Proposal of measures to address housing vulnerability based on changes in the patterns of single-person households and their characteristics by age, region, and housing vulnerability traits	Literature and institutional review Statistical analysis In-depth interviews	Improvement of policies considering the demands and vulnerabilities of single-person households across different age groups and regions
	3 [17]	Investigation of the social, cultural, and economic characteristics of single-person households residing in shared housing in Japan	Literature and institutional review Case studies In-depth interviews	Introduction of individual tenant housing subsidies Activation of affordable shared housing for single-person households
	4 [18]	Analysis of the relationship between demographic, socio-economic, and housing characteristics and well-being indicators of single-person households in Canada	Statistical analysis	Pricing of housing demand and costs considering the financial difficulties of single-person households Housing policies reflecting the preferences and needs of single-person households
Academic (degree) research paper	5 [19]	Analysis of the impact of single-person households’ characteristics on housing preferences and satisfaction Proposal of differentiated housing policies for single-person households by subgroups	Stratified sampling method Face-to-face survey Structural equation modeling (SEM) analysis	Differentiated housing policies reflecting household characteristics, housing preferences, and satisfaction levels
	6 [15]	Analysis of the impact of young adult single-person households in Helsinki, Finland, on apartment prices	Literature review Statistical analysis	The 1% increase in single-person households among young people caused a 0.51% increase in apartment prices (the 10% increase in the proportion of young people increased housing costs by EUR 10,061)
	7 [20]	Proposal of measures through longitudinal analysis of life satisfaction by age group among single-person households	Literature review Latent growth model	Application of linear change and non-change models for life satisfaction No influence on life satisfaction and change rate by generation, and differences were equally maintained
	8 [21]	Analysis of housing characteristics and factors influencing housing satisfaction among single-person households by age group	Literature and institutional review Statistical analysis	Enhancement of housing policies for elderly single-person households Supply-oriented housing policies and regulations are needed
	9 [22]	Analysis of living conditions of elderly single-person households in the Czech Republic and Slovakia	Literature review Statistical analysis	40% of elderly single-person households are poor, requiring multidimensional policies in the fields of public and social policies
	10 [23]	Surveying the social, cultural, and economic characteristics of single-person households residing in shared housing in Japan	Literature and policy review Case studies In-depth interviews	Introduction of individual tenant housing allowances needed Activation of affordable shared housing for single-person households necessary
	11 [24]	Analysis of demographic, socio-economic, and housing characteristics and well-being indicators of Canadian single-person households	Statistical analysis	Analysis of demographic, socio-economic, and housing characteristics and well-being indicators of Canadian single-person households
	12 [25]	Analysis of the current status and policy trends of single-person households in the United States	Review of literature and regulations Case studies	Implementation focusing on housing, community programs, and tax regulations Housing policies for single-person households in the United States primarily target low-income, elderly, and disabled households
	13 [27]	Analysis of the impact of young single-person households on apartment prices in Helsinki, Finland	Literature review Statistical analysis	A 1% increase in young single-person households leads to a 0.51% rise in apartment prices

Table 2. Previous studies on housing support for single-person households.

Classification		Objectives	Methods	Results
Research report	1 [11]	Analysis of limitations in public sector policies for single-person households Analysis of economic, social, and housing characteristics of single-person households and proposal of policy measures for housing improvement	Literature and institutional review Policy comparison Statistical analysis	Revision of central government regulations is necessary Tailored support policies for single-person households based on their characteristics are needed Expansion of housing supply to reduce the burden of living expenses Proper housing standards and support are required for upward movement of housing
	2 [16]	Proposal of measures to address housing vulnerability based on changes in the patterns of single-person households and their characteristics by age, region, and housing vulnerability traits	Literature and institutional review Statistical analysis In-depth interviews	Improvement of policies considering the demands and vulnerabilities of single-person households across different age groups and regions
	3 [17]	Investigation of the social, cultural, and economic characteristics of single-person households residing in shared housing in Japan	Literature and institutional review Case studies In-depth interviews	Introduction of individual tenant housing subsidies Activation of affordable shared housing for single-person households
	4 [18]	Analysis of the relationship between demographic, socio-economic, and housing characteristics and well-being indicators of single-person households in Canada	Statistical analysis	Pricing of housing demand and costs considering the financial difficulties of single-person households Housing policies reflecting the preferences and needs of single-person households
Academic (degree) research paper	5 [19]	Analysis of the impact of single-person households’ characteristics on housing preferences and satisfaction Proposal of differentiated housing policies for single-person households by subgroups	Stratified sampling method Face-to-face survey Structural equation modeling (SEM) analysis	Differentiated housing policies reflecting household characteristics, housing preferences, and satisfaction levels
	6 [15]	Analysis of the impact of young adult single-person households in Helsinki, Finland, on apartment prices	Literature review Statistical analysis	The 1% increase in single-person households among young people caused a 0.51% increase in apartment prices (the 10% increase in the proportion of young people increased housing costs by EUR 10,061)
	7 [20]	Proposal of measures through longitudinal analysis of life satisfaction by age group among single-person households	Literature review Latent growth model	Application of linear change and non-change models for life satisfaction No influence on life satisfaction and change rate by generation, and differences were equally maintained
	8 [21]	Analysis of housing characteristics and factors influencing housing satisfaction among single-person households by age group	Literature and institutional review Statistical analysis	Enhancement of housing policies for elderly single-person households Supply-oriented housing policies and regulations are needed
	9 [22]	Analysis of living conditions of elderly single-person households in the Czech Republic and Slovakia	Literature review Statistical analysis	40% of elderly single-person households are poor, requiring multidimensional policies in the fields of public and social policies
	10 [23]	Surveying the social, cultural, and economic characteristics of single-person households residing in shared housing in Japan	Literature and policy review Case studies In-depth interviews	Introduction of individual tenant housing allowances needed Activation of affordable shared housing for single-person households necessary
	11 [24]	Analysis of demographic, socio-economic, and housing characteristics and well-being indicators of Canadian single-person households	Statistical analysis	Analysis of demographic, socio-economic, and housing characteristics and well-being indicators of Canadian single-person households
	12 [25]	Analysis of the current status and policy trends of single-person households in the United States	Review of literature and regulations Case studies	Implementation focusing on housing, community programs, and tax regulations Housing policies for single-person households in the United States primarily target low-income, elderly, and disabled households
	13 [27]	Analysis of the impact of young single-person households on apartment prices in Helsinki, Finland	Literature review Statistical analysis	A 1% increase in young single-person households leads to a 0.51% rise in apartment prices

2.3. Research Scope and Objectives

Previous research suggested financial and housing policies aimed at specific age groups, such as youth and the elderly, as well as women, based on general characteristics and residential features of single-person households [11,16,19,20,21]. However, policies specifically designed for single-person households are presently inadequate, and there is a lack of studies analyzing the factors that directly influence the satisfaction of single-person households with housing support programs. Given the changing household structure and the increasing trend of single-person households, there is a need for in-depth root cause analysis and preventive measures to ensure the housing stability of single-person households.

Furthermore, the current situation requires the establishment of a comprehensive support system that takes into account housing, societal, and welfare aspects when formulating policies to support single-person households. This system should address issues such as housing stability and social isolation. Therefore, this study aimed to examine how various factors of single-person households influence actual financial support programs, utilizing cognitive status, usage patterns, and satisfaction levels as variables.

To differentiate from previous studies, we expanded the scope of our investigation nationwide and targeted single-person households across all age groups. It further categorizes demographic, socio-economic, and housing characteristics and residential perceptions, providing policy alternatives for the future housing stability of single-person households categorized by type.

3. Materials and Methods

This study focused on one-person households in South Korea. The research material utilized microdata from the “2020 Housing Situation Survey” provided by Statistics Korea. The Housing Situation Survey has been conducted since 2006 to gather basic data for housing policy formulation by comprehensively investigating various aspects of residential life to formulate housing policies that meet the diverse characteristics of the population. The survey is conducted through face-to-face interviews by trained interviewers based on structured questionnaires prepared by the Ministry of Land, Infrastructure and Transport; the Korea Research Institute for Human Settlements; and specialized research agencies. The continuous accumulation of statistical data aims to derive new policy directions through the analysis of longitudinal changes in key indicators. The 2020 Housing Situation Survey, conducted as the 10th survey, took place over approximately five months from 13 July to 23 December 2020. This study, with the purpose of analyzing the characteristics of one-person households, selected 13,826 individuals as the analysis target by extracting only households designated as “one-person households” out of a total of 51,421 households. Therefore, the dependent variables for this study were awareness, utilization status, and satisfaction of financial support programs provided by the South Korean government. The independent variables include demographic, socio-economic, and housing characteristics and housing perception. Statistical analyses were conducted using SPSS 25.0 (IBM Corp., Armonk, NY, USA) and AMOS 25.0 programs, and the statistical significance was determined at a significance level of 5%. The research method was as follows.

First, through a literature review, domestic and international research trends were examined, and an analysis of the characteristics and application status of one-person households based on an examination of the central government’s housing support program system was conducted. In this study, three programs with survey results obtained through the Housing Situation Survey among the currently implemented housing support programs were targeted. The programs were the “Residential Stability Monthly Rent Loan”, “Housing Lump-Sum Rental Deposit Loan”, and “Housing Purchase Fund Loan”.

Second, we established the analytical framework by integrating previous studies and statistical data. We segmented the characteristics of single-person households into demographic, socio-economic, housing, and perception aspects.

Third, we conducted logistic regression analysis to examine the impact of awareness, utilization, and satisfaction with financial support programs. We used a binomial logistic regression for our statistical analysis. Logistic regression analysis was developed to alleviate the challenges of calculation, which is a disadvantage of the probit model. Logistic regression is a model of selected probability that assumes the probabilistic utility is an independent distribution with a Weibull distribution. The purpose and procedure of the analysis are similar to linear regression analysis but differ in that ostensible-typed variables are applied as dependent variables. Logistic regression analysis utilizes odds, which is a ratio between the probability of occurrence and the probability of non-occurrence. The corresponding formula is expressed as

$$Odds=\frac{p}{1-p}=\exp \left[\alpha +B_1{X}_1+B_2{X}_2+\cdots +B_P{X}_P\right]$$

The concept of odds cannot be used for general regression analysis with values between 0 and 1. Odds have 2 problems: the first is that they do not have negative (-) values, and the second is that the relationship between probabilities reveals an asymmetry around 1. To solve these problems, natural logs are assigned to the values of odds, which is called logit. On the condition of a given explanatory variable, if the S-shape of a logistic function with a maximum value of 1 and a minimum value of 0, which represents the probabilities that a particular choice occurs or not, is converted to logit, it appears linearly. The formula is expressed as follows:

$$ln\left(\frac{p}{1-p}\right)=\alpha +B_1{X}_1+B_2{X}_2+\cdots +B_P{X}_P$$

The odds ratio concept is utilized to analyze the logistic regression results. The odds ratio represents the change in the dependent variable when the explanatory variable increases by one unit, while holding all other variables constant. The formula is expressed as follows:

$$Odds Ratio=\frac{\exp \left(\alpha +B_1{X}_1+\cdots +B_i(X_i+1\right)+\cdots +B_P{X}_P)}{\exp \left(\alpha +B_1{X}_1+\cdots +B_i{X}_i+\cdots +B_P{X}_P\right)}=\exp \left(B_i\right)$$

When the odds ratio is less than 1, it indicates a negative impact of the explanatory variable on the dependent variable. Conversely, if the odds ratio is greater than 1, it indicates a positive influence. After conducting statistical analyses using SPSS 25.0 (IBM Corp., Armonk, NY, USA) and AMOS 25.0 programs, this study synthesized the literature review and all statistical analyses to propose policy recommendations for improving the efficacy of housing finance support programs. The statistical analyses were determined to be statistically significant at a 5% significance level.

3.1. Research Hypotheses

This study aimed to examine the effects of financial support programs on housing conditions and to analyze the differences in awareness, utilization, and satisfaction with financial support programs based on the demographic, socio-economic, and housing characteristics and housing perception of single-person households. This study also aimed to derive policy implications of financial support programs by understanding the relationship between housing conditions and satisfaction with the residential environment. To achieve these research objectives, this study formulated research hypotheses as presented in

Table 3. Research hypotheses for financial support program analysis.

Category		Hypotheses
Awareness Utilization Satisfaction	Null hypothesis 1 (H0-1)	There will be no difference in the awareness of financial support programs among single-person households based on their demographic, social, residential characteristics, and housing perception.
	Null hypothesis 2 (H0-2)	There will be no difference in the utilization of financial support programs among single-person households based on their demographic, social, residential characteristics, and housing perception.
	Null hypothesis 3 (H0-3)	There will be no difference in the satisfaction level with financial support program utilization among single-person households based on their demographic, social, residential characteristics, and housing perception.

.

First, this study expected that factors influencing the awareness of financial support programs will vary depending on the various characteristics of single-person households. Therefore, the null hypothesis (H₀-1) was formulated as “There is no difference in factors influencing awareness of financial support programs according to demographic, socio-economic, housing characteristics, and housing perception of single-person households”.

Second, this study categorized the various characteristics of single-person households, such as gender, age, income, and residential area, into demographic, socio-economic, and housing characteristics and housing perception to identify the factors that influenced the utilization of financial support programs. Thus, the null hypothesis (H₀-2) was formulated as ”There is no difference in factors influencing the utilization of financial support programs according to demographic, socio-economic, housing characteristics, and housing perception of single-person households”.

Third, based on previous research, this study established that the diverse characteristics of single-person households have a positive impact on satisfaction with financial support programs. Therefore, the null hypothesis (H₀-3) was formulated as “There is no difference in factors influencing satisfaction with financial support programs according to demographic, socio-economic, housing characteristics, and housing perception of single-person households”.

3.2. Data Source and Sample

This study utilized data from the 2020 Housing Situation Survey. The survey aims to investigate various aspects of residential life and provide foundational data for housing policy formulation that aligns with the diverse characteristics of the population. The survey was carried out by the Ministry of Land, Infrastructure and Transport; the Korea Land and Housing Corporation; and specialized research institutions, and involves structured questionnaires administered through trained interviewers in face-to-face interviews.

The purpose of this study was to derive characteristics of single-person households. To achieve this, a sample of 13,826 individuals from single-person households was extracted from the total respondents of 51,421 in the 2020 Housing Situation Survey. The analysis focused on demographic and socio-economic characteristics, as well as the housing environment and perceptions.

This study examined the awareness, utilization, and satisfaction with government-provided financial support programs as the dependent variables. Awareness and utilization refer to whether participants were aware of and used each program, respectively. Satisfaction was measured on a 4-point Likert scale, where higher scores indicate higher satisfaction levels.

The independent variables were categorized into four aspects: demographic, socioeconomic, and housing characteristics and housing perception. The demographic characteristics included gender, age, and residential area. The socioeconomic characteristics encompassed income level. The housing characteristics included type of housing, occupancy status, and housing structure. The housing perception covered willingness to live in public rental housing, homeownership awareness, housing satisfaction, and satisfaction with the residential environment.

3.3. Variables and Measurements

This study examined four types of independent variables: demographic, socio-economic, and housing characteristics and housing perception. These variables were analyzed in detail, including gender, age, and residential area as demographic characteristics; socio-economic features, such as income strata; and housing characteristics that encompassed housing type, occupancy type, and housing structure. Housing perception was assessed based on inclinations toward public rental housing occupancy, homeownership awareness, housing satisfaction, and satisfaction with the living environment.

The dependent variable was satisfaction with the utilization of housing support programs among individuals who had experience with such programs. This variable was measured on a 4-point Likert scale ranging from “very dissatisfied” to “very satisfied”. A higher score indicated higher satisfaction with the utilization of housing support programs.

Housing support programs were categorized into three types: financial support programs (housing stability rental loans, housing lease deposit loans, housing purchase loans), housing supply support programs (public rental housing, public pre-sale housing, private pre-sale special supply), and other housing support programs (rental subsidies, maintenance subsidies, housing improvement/renovation, housing welfare counseling, and information usage) (

Table 4. Variable classification and measurement.

Variable Type		Variable Name			Measurement
Dependent variables		Awareness	Loan products	Yes	The awareness of the financial support program was measured: yes = 1, no = 2
				No
			Housing supply scheme	Yes
				No
			Other housing assistance programs	Yes
				No
		Utilization	Loan products	Yes	The utilization of the financial support program was measured: yes = 1, no = 2
				No
			Housing supply scheme	Yes
				No
			Other housing assistance programs	Yes
				No
		Satisfaction	Loan products	Likert 4-point scale	The overall satisfaction with the financial support program was measured on a Likert 4-point scale: 1 = very dissatisfied, 2 = somewhat dissatisfied, 3 = generally satisfied, 4 = very satisfied
			Housing supply scheme
			Other housing assistance programs
Independent variables	Demo graphics	Gender		Male	Male = 1, female = 2
				Female
		Age (years)	Young (18 to 34 years)		Age groups were divided into 5 categories: young = 1, middle-aged = 2, older middle-aged = 3, early elderly = 4, late elderly = 5
			Middle-aged (35 to 49 years)
			Older middle-aged (50 to 64 years)
			Early elderly (65 to 74 years)
			Late elderly (75 years⁺)
		Residential region	Capital area		Residential areas were categorized into 3 levels: capital area = 1, metropolitan city = 2, provincial area = 3
			Metropolitan city
			Provincial area
	Socio economics	Income level	Lower (1–4 deciles)		Income brackets were divided into 3 categories: low-income = 1, middle-income = 2, upper-income = 3
			Middle (5–8 deciles)
			Upper (9–10 deciles)
	Housing character istics	Housing type	Detached house		Types of housing residence: detached house = 1, apartment = 2, etc. = 3
			Apartment
			Etc.
		Housing situation	Ownership status		Housing situation was divided into 2 categories: ownership status = 1, residential type = 2
			Residential type
		Housing structure	A one-bedroom type		Housing structure was divided into 2 categories: one-bedroom type = 1, not a one-bedroom type = 2
			Not a one-bedroom type
	Housing perception	Intention to move into public rental housing		Yes	The intention to relocate to public rental housing and the intention to purchase a home were measured: yes = 1, no = 2
				No
		Intention of home purchase		Yes
				No

).

This study had a nationwide geographical scope and was divided into metropolitan areas (Seoul, Incheon, Gyeonggi), provincial areas (Gangwon, Chungbuk, Chungnam, Jeonbuk, Jeonnam, Gyeongbuk, Gyeongnam, Jeju), and metropolitan cities (Busan, Daegu, Gwangju, Daejeon, Ulsan, Sejong) to reflect diverse regional characteristics.

To analyze the detailed influencing factors by age group, individuals were categorized into five groups: youth, middle-aged, older middle-aged, early elderly, and late elderly. The age groups were set according to the criteria of the Youth Basic Act, the Enforcement Decree of the Act on the Promotion of Youth Employment, and the Seoul Metropolitan Government’s Basic Ordinance on Youth Housing, in line with the specific criteria for each law.

Income strata were categorized as lower (1st to 4th deciles), middle (5th to 8th deciles), and upper (9th to 10th deciles), providing a detailed analysis of the characteristics for each income group. The housing characteristics were assessed based on the housing type (single-family house, apartment, other), occupancy type (self-owned, rented), and whether the residence was a one-room unit. The housing perception was investigated by examining factors related to the inclination toward public rental housing, intention for homeownership, housing satisfaction, and satisfaction with the living environment.

To verify the impact of the demographic, socio-economic, and housing characteristics and housing perception of single-person households on the perception, utilization, and satisfaction of financial support programs, a multiple regression analysis was conducted. The suitability and explanatory power of the regression model were confirmed through validation. After verifying the Durbin–Watson statistic, the independence of residuals was assessed. Through significance testing of the regression coefficients, factors that significantly influenced perception, utilization, and satisfaction were identified.

4. Results

This study examined the variables of utilization and satisfaction in housing support programs. These were categorized into housing finance support, housing supply support, and other types of housing support programs. The highest utilization rate was observed in other housing support programs (74.3%), while the rates for housing finance support and housing supply support were 16.6% and 21.7%, respectively.

This study also looked at independent variables, such as gender, age, and socio-economic characteristics. The gender distribution was 41% male and 59% female. The age distribution showed that 30% were late seniors, 20.2% were middle-aged, 19.5% were early seniors, 16.9% were youth, and 13.4% were in their middle age. The majority of respondents lived in rural areas (40.1%), followed by the metropolitan area (32.6%) and urban areas (27.3%).

In terms of socio-economic characteristics, the lower-income group accounted for 82.2%, while the middle- and upper-income groups constituted 15.0% and 2.8%, respectively. In regard to housing types, 49.3% lived in detached houses, 27.4% in apartments, and 23.3% in other types. The ratio of homeowners to renters was 36.6% to 63.4%.

This study found that 25.1% of respondents lived in one-room accommodations, and 43.7% expressed a willingness to move into public rental housing. Additionally, 79.5% of respondents had the intention of owning a home (

Table 5. General characteristics of survey subjects.

Category		Classification	Frequency	Ratio
Demographic	Gender	Male	5667	41.0
		Female	8159	59.0
	Age	Youth (18–34 years old)	2332	16.9
		Middle-aged (35–49 years old)	1854	13.4
		Older middle-aged (50–64 years old)	2797	20.2
		Early elderly (65–74 years old)	2693	19.5
		Late elderly (75 years of age or older)	4150	30.0
	Residential region	Capital area	4505	32.6
		Metropolitan city	3779	27.3
		Provincial area	5542	40.1
Socioeconomic	Income level	Lower	11,370	82.2
		Middle	2073	15.0
		Upper	383	2.8
Residential characteristics	Housing type	Detached house	6817	49.3
		Apartment	3793	27.4
		Etc.	3216	23.3
	Housing situation	Ownership status	5057	36.6
		Residential type	8769	63.4
	Housing structure	A one-bedroom type	3475	25.1
		Not a one-bedroom type	10,351	74.9
Residential awareness	Intention to move into public rental housing	Yes	6043	43.7
		No	7783	56.3
	Thoughts on owning my own house	Yes	10,987	79.5
		No	2839	20.5
Sum			13,826	100.0

). This study indicates the need for policy measures that are suitable for the current characteristics of the elderly population, especially single-person households. Given the predominance of low-income households among single-person households, nationwide policy support is warranted.

4.1. Factors Influencing Awareness of Financial Support Programs for Single-Person Households

Logistic regression analysis was conducted to determine the effects of demographic, socio-economic, and housing characteristics and housing perceptions of single-person households on the awareness of financial support programs (

Table 6. Characteristics of single-person households influencing awareness of financial support programs.

Independent Variable	p	OR	95% CI
			Lower Bound	Upper Bound
Gender (ref: female)
male	<0.001	1.284 ***	1.167	1.413
Age (ref: late elderly (75 years of age or older))
Youth (18–34 years old)	<0.001	2.739 ***	2.335	3.213
Middle-aged (35–49 years old)	<0.001	3.450 ***	2.869	4.149
Older middle-aged (50–64 years old)	<0.001	2.453 ***	2.155	2.791
Early elderly (65–74 years old)	<0.001	1.735 ***	1.552	1.940
Residential region (ref: provincial area)
Capital area	<0.001	2.079 ***	1.858	2.327
Metropolitan city	<0.001	1.346 ***	1.218	1.488
Income level (ref: upper)
Lower	0.029	1.338 *	1.031	1.738
Middle	<0.001	2.486 ***	1.852	3.339
Housing type (ref: etc.)
Detached house	0.070	0.896	0.796	1.009
Apartment	0.052	1.144	0.999	1.310
Housing situation (ref: residential type)
Ownership status	<0.001	1.242 ***	1.116	1.383
Housing structure (ref: not a one-bedroom type)
A one-bedroom type	0.093	0.895	0.787	1.019
Intention to move into public rental housing (Ref: no)
Yes	<0.001	1.601 ***	1.449	1.769
Thoughts on owning my own house (ref: no)
Yes	0.648	0.975	0.872	1.089
Overall satisfaction with residential housing	0.389	1.038	0.953	1.131
Overall satisfaction with residential environment	0.439	1.036	0.947	1.134

Hosmer and Lemeshow test: chi-square = 13.450 (p > 0.05). Cox and Snell’s R² = 0.099, Nagelkerke R² = 0.148. Dummy variables: gender (female = 0), age (late elderly, 75 years and older = 0), region (non-metropolitan area = 0), income bracket (upper = 0), housing type (other = 0), tenure type (rental = 0), housing structure (not a studio apartment = 0), intention to occupy public rental housing (no = 0), thoughts on homeownership (no = 0). * p < 0.05, *** p < 0.001.

). The results of the Hosmer and Lemeshow test indicate that the regression model was suitable (χ² = 13.450, p > 0.05), and the explanatory power of the independent variables for the awareness of financial support programs was found to be 14.8% (Nagelkerke R² = 0.148).

The significance testing of regression coefficients revealed that gender, age, region, income bracket, occupancy type, and intention to move into public rental housing had significant impacts on the awareness of financial support programs. Males were found to be approximately 1.284 times more likely to be aware of financial support programs than females (OR = 1.284, p < 0.001). In terms of age, young adults (18–34 years) were 2.739 times, middle-aged individuals (35–49 years) were 3.450 times, older adults (50–64 years) were 2.453 times, and early seniors (65–74 years) were 1.735 times more likely to be aware of financial support programs than late seniors (75 years and above) (all p < 0.001).

Regarding regions, metropolitan areas were found to be 2.079 times more likely and urban areas were 1.346 times more likely to have awareness of financial support programs than rural areas (both p < 0.001). In terms of income bracket, compared with the upper bracket, the likelihood of awareness for the lower bracket was 1.338 times higher, and for the middle bracket, this was 2.486 times higher (p < 0.05 and p < 0.001, respectively). Homeowners were found to be 1.242 times more likely to have awareness of financial support programs than renters (OR = 1.242, p < 0.001). Those who intended to move into public rental housing were approximately 1.601 times more likely to be aware of financial support programs than those who did not have such an intention (OR = 1.601, p < 0.001).

4.2. Factors Influencing Utilization of Financial Support Programs for Single-Person Households

A logistic regression analysis was conducted to investigate the impact of demographic, socio-economic, and housing characteristics and housing perceptions on the utilization of financial support programs by single-person households (

Table 7. Characteristics of single-person households influencing utilization of financial support programs.

Independent Variable	p	OR	95% CI
			Lower Bound	Upper Bound
Age (ref: late elderly (75 years of age or older))
Youth (18–34 years old)	<0.001	8.191 ***	5.395	12.438
Middle-aged (35–49 years old)	<0.0001	4.931 ***	3.224	7.542
Older middle-aged (50–64 years old)	<0.001	2.814 ***	1.856	4.268
Early elderly (65–74 years old)	<0.001	2.318 ***	1.504	3.573
Residential region (ref: provincial area)
Capital area	<0.001	1.685 ***	1.318	2.154
Metropolitan city	0.289	1.156	0.884	1.512
Income level (ref: upper)
Lower	0.003	0.455 **	0.272	0.759
Middle	0.061	0.608	0.361	1.024
Housing type (ref: etc.)
Detached house	0.011	0.722 *	0.561	0.929
Apartment	0.005	1.445 **	1.118	1.866
Housing structure (ref: not a one-bedroom type)
A one-bedroom type	<0.001	0.281 ***	0.216	0.365
Overall satisfaction with residential housing	<0.001	1.667 ***	1.327	2.095
Overall satisfaction with residential environment	0.242	0.879	0.708	1.091

Hosmer and Lemeshow test: chi-square = 9.919 (p > 0.05). Cox and Snell’s R² = 0.100, Nagelkerke R² = 0.168. Dummy variables: age (late elderly, 75 years and older = 0), region (non-metropolitan area = 0), income bracket (upper = 0), housing type (other = 0), housing structure (not studio apartment = 0). * p < 0.05, ** p < 0.01, *** p < 0.001.

). The results of the Hosmer and Lemeshow test showed that the regression model was deemed appropriate (χ² = 9.919, p > 0.05), and the independent variables explained 16.8% of the variance in the utilization of financial support programs (Nagelkerke R² = 0.168).

The regression coefficient analysis revealed that the overall satisfaction with age, region, housing type, and housing had a significant impact on the use of financial support programs. Regarding age, young (18–34 years old) (OR = 8.191, p < 0.001), middle-aged (35–49 years old) (OR = 4.931, p < 0.001), elderly (50–64 years old) (OR = 2.814, p < 0.001), and early elderly (65–74 years old) (OR = 2.318, p < 0.001) people were more likely to use financial support programs compared with the late elderly (75 years or older). For region, those residing in metropolitan areas were approximately 1.685 times more likely to utilize financial support programs than those in rural areas (OR = 1.685, p < 0.001). For income bracket, the likelihood of utilizing financial support programs for the lower bracket was approximately 0.455 times lower than the upper bracket (p < 0.01).

Regarding housing type, detached houses were approximately 0.722 times less likely to utilize financial support programs than the “other” category (OR = 0.722, p < 0.05), while apartments were approximately 1.445 times more likely (OR = 1.445, p < 0.01). Additionally, studio-type housing was approximately 0.281 times less likely to utilize financial support programs compared with non-studio types (OR = 0.281, p < 0.001). Furthermore, with each one-step increase in overall satisfaction with housing, the likelihood of utilizing financial support programs increased by approximately 1.667 times (OR = 1.667, p < 0.001).

This study suggests that single-person households have a proportionately larger number of lower-income individuals, lower levels of educational attainment, and lower levels of housing satisfaction. The findings imply that support methods for lower-income households, rental households, and the elderly need to be re-evaluated.

4.3. Factors Influencing Satisfaction with Financial Support Programs for Single-Person Households

Multiple regression analysis was conducted to investigate the impact of demographic, socio-economic, and housing characteristics and housing perceptions on satisfaction with financial support programs for single-person households (

Table 8. Characteristics of single-person households influencing satisfaction with financial support programs.

Independent Variable		B	S.E	β	t	p	Tolerance	VIF
(constant)		2.256	0.154		14.662 ***	<0.001	-	-
Age	Youth (18–34 years old)	−0.022	0.054	−0.020	−0.409	0.682	0.604	1.656
	Middle-aged (35–49 years old)	−0.020	0.060	−0.017	−0.341	0.733	0.618	1.617
	Older middle-aged (50–64 years old)	−0.133	0.067	−0.092	−1.969 *	0.049	0.671	1.490
	Early elderly (65–74 years old)	0.128	0.091	0.058	1.409	0.159	0.851	1.176
Residential region	Metropolitan city	−0.025	0.048	−0.022	−0.525	.600	0.800	1.250
	Provincial area	−0.108	0.052	−0.089	−2.050 *	0.041	0.778	1.286
Housing type	Apartment	−0.127	0.053	−0.127	−2.411 *	0.016	0.524	1.907
	Etc.	−0.080	0.054	−0.074	−1.466	0.143	0.581	1.721
Housing situation	Residential type	0.135	0.050	0.135	2.715 **	0.007	0.594	1.683
Housing structure	A one-bedroom type	0.054	0.057	0.042	0.942	0.347	0.745	1.342
Intention to move into public rental housing	Yes	−0.006	0.044	−0.006	−0.129	0.897	0.742	1.347
Overall satisfaction with residential housing		0.087	0.041	0.094	2.094 *	0.037	0.726	1.377
Overall satisfaction with residential environment		0.190	0.044	0.191	4.322 ***	<0.001	0.745	1.342

F = 7.295 (p < 0.001), R² = 0.139, adjusted R² = 0.120, Durbin Watson = 2.030. Dummy variables: age group (youth, 18–34 years = 0), region classification (metropolitan area = 0), housing type (detached house = 0), tenure type (owner-occupied = 0), housing structure (not studio apartment = 0), intention to occupy public rental housing (no = 0). * p < 0.05, ** p < 0.01, *** p < 0.001.

). The results showed that the model was appropriate, with F = 7.295 (p < 0.001), and had an explanatory power of approximately 13.9%. Additionally, the Durbin–Watson statistic yielded a value of 2.030, indicating that there were no issues with the independence assumption of the residuals.

The regression coefficients were tested for significance, and it was found that occupancy type (rental) (β = 0.135, p < 0.01), overall satisfaction with the house (β = 0.094, p < 0.05), and overall satisfaction with the residential environment (β = 0.191, p < 0.001) had statistically significant positive effects on satisfaction with financial support programs. Conversely, age group (elderly individuals aged 65–74) (β = −0.092, p < 0.05), regional classification (rural areas) (β = −0.089, p < 0.05), and housing type (apartment) (β = −0.127, p < 0.05) had statistically significant negative effects on satisfaction with financial support programs.

It was found that being a tenant and having higher overall satisfaction with the house and residential environment were associated with higher satisfaction with financial support programs. On the other hand, being in the elderly age group (65–74 years), residing in rural areas, and living in an apartment were associated with lower satisfaction with financial support programs.

5. Discussion

This study analyzed the factors that influenced awareness, utilization, and satisfaction with financial support programs for single-person households, considering demographic, socio-economic characteristics, housing environment, and perceptions.

First, this study found that awareness of financial support programs for single-person households tended to decrease with age, and females were less aware of these programs than males. Those living in rural areas, high-income groups, and rental households were also less aware of these programs than those living in metropolitan regions and owner-occupied households. Despite rental and elderly single-person households having a higher housing cost burden and greater concerns related to assets and retirement planning, their awareness of financial support programs was lower. Compared with previous studies, our findings corroborated similar trends observed in prior research. For instance, our results aligned with the findings of previous studies [4,11], demonstrating that the awareness of financial support programs decreased with age and was lower among females. Therefore, there is a need to improve eligibility criteria awareness and promote easier access.

Second, this study found that relatively low utilization rates were observed among the elderly, lower-income households, rental households, and one-room dwelling households. Similarly, our findings are consistent with prior research [14,16], indicating lower awareness among rural residents and higher-income groups. Likewise, the relatively low utilization rates among the elderly, low-income households, and rental households observed in our study correspond to the findings of previous studies [4,21]. This suggests the need to reassess existing support mechanisms and expand housing support to low-income, non-homeowning elderly households. Additionally, policies for single-person households should be diversified to better serve their unique characteristics.

Third, this study found that owner-occupied, elderly, rural, and apartment-dwelling households had relatively low satisfaction with financial support program utilization. The suggestion for a comprehensive support system tailored to the diverse needs of single-person households aligns with proposals from prior research [7,11,14,17], while the emphasis on the necessity for collaboration between central and local governments in our study echoes recommendations from previous studies [10,21,28]. This indicates the need to expand housing support to low-income, non-homeowning elderly households and improve repayment burdens and easier access to financial support information.

Fourth, to alleviate housing cost burdens for single-person households, various developments in lease deposit loan products, adjustments to income deductions for principal and interest repayments, preferential interest rates, and changes in financial support are necessary. This study found that lease deposit loans were in highest demand among single-person households (44.6%), followed by rental assistance (30.4%) and housing purchase loans (24.9%). Therefore, there is a need for budget allocations toward housing finance reform to meet the high demand for lease deposit loans.

Lastly, single-person households require a comprehensive support system that integrates housing and services, with age-specific responses. Differentiated approaches based on age can be effective, such as housing searches and rental education for younger individuals, financial education for middle-aged individuals, and housing renovation support and retirement financial planning education for elderly individuals. Inclusive policies are essential for improving housing conditions and satisfaction for single-person households, considering regional variations in their housing demands. Collaborative efforts between central and local governments are necessary to formulate appropriate housing policies.

6. Conclusions

We have presented the fundamental direction and response strategies for financial support for single-person household housing based on factors that influenced awareness, utilization, and satisfaction with financial support programs. The key findings are summarized as follows:

First, awareness of financial support programs tended to decrease with age and was lower among females, rural residents, high-income groups, and rental households. Second, relatively low utilization rates were observed among the elderly, lower-income households, and rental households. Third, owner-occupied, elderly, rural, and apartment-dwelling households exhibited relatively low satisfaction with financial support program utilization. These findings aligned with previous research, indicating the need for improved awareness, utilization, and satisfaction with financial support programs for single-person households. Collaboration between central and local governments is crucial for formulating appropriate housing policies to address the diverse needs of single-person households.

After conducting a comprehensive analysis, the following suggestions are proposed to improve the living conditions of single-person households:

First, addressing information disparities Establish age-specific support and financial policies for middle-aged and elderly single-person households facing housing blind spots. Provide information and education related to housing contracts for young single-person households. Support housing stability through asset accumulation and homeownership education for middle-aged individuals. Explore options like housing pensions to alleviate economic uncertainties for elderly single-person households.

Second, comprehensive support system and financial system diversification: Develop a comprehensive platform and manuals for local government utilization to promptly respond to and support the diverse needs of single-person households. Ensure nationwide information sharing, promotion, and operation without the burden of developing separate platforms for each region.

Third, enhancing policy support effects: Conduct a comprehensive panel survey on the overall situation of single-person households. Establish a private professional institution responsible for operating an integrated single-person household platform to unify policies and projects related to single-person households from various departments.

Fourth, alleviating housing cost burdens: Develop lease deposit loan products, adjust income deductions for principal and interest repayments, offer preferential interest rates, and implement changes in financial support to alleviate housing cost burdens for single-person households.

Fifth, tailored support system: Provide age-specific responses, such as housing searches and rental education for younger individuals, financial education for middle-aged individuals, and housing renovation support and retirement financial planning education for elderly individuals.

These findings align with previous research, indicating the need for improved awareness, utilization, and satisfaction with financial support programs for single-person households. Collaboration between central and local governments is crucial for formulating appropriate housing policies to address the diverse needs of single-person households.

The increasing number and changing composition of single-person households underscore the growing importance of tailored policies to meet diverse housing demands at the regional level. To achieve this, collaboration between central and local governments is essential. This study is expected to contribute to future improvement measures for enhancing the effectiveness of financial support programs for single-person households, alongside existing policies.

Single-person households exhibit varied characteristics, posing a challenge to meet all their needs through a singular policy. This study addressed these challenges through a literature review and an in-depth analysis of single-person household characteristics. By comprehensively analyzing the usage patterns and influencing factors of financial support programs for single-person households, this study provides policy recommendations. As tailored policies for securing housing stability for single-person households gain increasing emphasis, this research holds significant importance in enhancing policy effectiveness.

To understand the usage environment and improvement requirements of financial support programs for single-person households, this study employed statistical analysis. However, this study focused on programs analyzed with current data, excluding newly established support systems for single-person households. Therefore, ongoing research efforts are necessary to continuously enhance the effectiveness of support programs and develop performance indicators for new systems.

Based on these research findings, the following recommendations are proposed for policymakers and practitioners:

First, develop region-specific housing support policies tailored to the unique needs of single-person households, considering demographic, socio-economic, and housing environment factors.

Second, enhance collaboration between central and local governments to ensure effective implementation and monitoring of housing support programs for single-person households across different regions.

Third, conduct regular evaluations and assessments of existing financial support programs for single-person households to identify areas for improvement and adjustment.

Fourth, invest in research and data collection efforts to better understand the evolving needs and challenges faced by single-person households, facilitating evidence-based policymaking.

Fifth, establish mechanisms for information sharing and knowledge exchange between stakeholders involved in housing support programs for single-person households to foster innovation and best practices.

By implementing these recommendations, policymakers and practitioners can develop responsive and effective policies to support the housing needs of single-person households, ultimately enhancing housing conditions and satisfaction.

Development of tailored housing support policies for single-person households considering unique housing demands in each region. Enhanced collaboration between central and local governments for effective implementation and monitoring of housing support programs for single-person households across different regions. Regular evaluation of existing financial support programs for single-person households to enable improvements and adjustments. Investment in research and data collection efforts to better understand the evolving needs and challenges of single-person households. Establishment of mechanisms for information sharing and knowledge exchange among stakeholders involved in housing support programs for single-person households. By implementing these recommendations, policymakers and practitioners can develop responsive and effective policies to support the housing needs of single-person households, ultimately enhancing housing conditions and satisfaction.