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Housing satisfaction and improvement demand considering housing lifestyles of young residents in public rental housing

Housing satisfaction and improvement demand considering housing lifestyles of young residents in... JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING https://doi.org/10.1080/13467581.2023.2205473 ARCHITECTURAL PLANNING AND DESIGN Housing satisfaction and improvement demand considering housing lifestyles of young residents in public rental housing a a a b Miseon Jang , Tae-Wan Kim , Ji-Yun Kim and Hua Zheng Department of Housing Environmental Design, Jeonbuk National University, Deokjin-gu, Jeonju-si, Jeollabuk-do, Republic of Korea; Department of Environmental Art Design, Shanghai Normal University, Shanghai, The People’s Republic of China ABSTRACT ARTICLE HISTORY Received 1 January 2023 The supply of public rental housing for young households has been on the rise in South Korea. Accepted 17 April 2023 Their size and composition vary depending on residents’ characteristics. However, even within similar groups, housing satisfaction may differ according to their lifestyle; hence, diversity may KEYWORDS exist in the demand for housing improvement. This study identified housing satisfaction and Housing improvement; improvement demands according to housing lifestyles of young residents of “Happy House”, housing satisfaction; housing a representative public rental housing for young households. The method used in this study lifestyle; public rental was an online survey targeting individuals younger than 39 years and living in Happy Houses. housing; young household A total of 536 responses were collected, and the respondents were divided into five housing lifestyle clusters despite being from similar groups. Depending on the lifestyle, differences existed in the satisfaction of space composition and size and basic options, such as facilities/ furniture/home appliances. In addition, there were also differences in the demand for housing improvements. The group actively using housing for leisure, cultural activities, and social exchanges showed high demands for improvement, such as space composition and basic options. This study can be used as a reference for establishing a housing improvement plan for customizable public rental housing, considering the lifestyles of young adults. 1. Introduction Statistics 2021a, 2021b), and the low birth rate problem is more serious than in any other world country. As the global economic downturn continues and labor Accordingly, the Korean government has strengthened market problems become more serious, the youth have policy support for young adults to overcome these become the most vulnerable group in the labor market problems. Among them, in the case of the housing (Tanveer, Marelli, and Signorelli 2012; Junankar 2015). sector, it has accelerated the expansion of housing sup- Young people with a weak economic foundation due to port through the supply of youth housing and loan unstable employment experience the complex problem support (Office for Government Policy Coordination, of high housing costs required to secure housing neces- 2020). A major example of housing policy support for sary for their independence (Berrington and Stone 2014; young adults is the provision of public rental housing. Milić and Zhou 2018). Unlike older generations, which The government expanded the supply of public rental are already securing self-home housing, young people housing with the “Happy House,” which is young adult- who need to secure homes are in a hierarchy that focused public rental housing. The house was first intro- increases the burden of housing costs due to the rise duced in 2015 and has been studied since its launch in in housing prices. These problems not only negatively 2017. These studies have solely focused on Happy affect their quality of life, but they also postpone their Houses in certain regions, identified their spatial char- independence and marriage, leading to lower fertility acteristics, or conducted post-occupancy evaluations, rates and other social issues (Presidential Committee on including housing satisfaction (Shin et al., 2020, Noh Ageing Society and Population Policy, 2020). In particu- and Jin, 2018, Song et al., 2018). Previous studies lar, the coronavirus (COVID-19) pandemic, which revealed that although Happy Houses are public rental occurred at the end of 2019 and created a global pan- homes tailored to young adults, residents’ overall satis- demic, has been recognized as another major cause of faction was slightly above average. Therefore, it is neces- delays in independence, marriage, and childbirth sary to consider young adults’ lifestyles and their among young people (Achdut and Refaeli 2020; Yukich preferences to improve space (Mo et al., 2013, Kwon et al. 2021). In South Korea (henceforth, Korea), the et al., 2016). However, when planning customized number of marriages and the total fertility rate have spaces for Happy Houses, it is essential to consider the been continuously decreasing since 2012 (Korea CONTACT Tae-Wan Kim pooh7669@naver.com Department of Housing Environmental Design, Jeonbuk National University, 567 Baekje-daero, Deokjin-gu, Jeonju-si, Jeollabuk-do 54896, Republic of Korea © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the Architectural Institute of Japan, Architectural Institute of Korea and Architectural Society of China. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. 2 M. JANG ET AL. characteristics, including the number of household respondents, activities in the dwelling, and changes members and types of households, such as university in living behavior due to COVID-19. Jang et al. (2022) students, those just starting their careers, and newly- identified the qualitative and quantitative levels of weds. Similarly, there may be various housing needs housing characteristics, including the physical state of within the same age group and family lifecycle stages, housing, its costs, and the physical housing environ- which must also be considered. Accordingly, studies ment and analyzed how these affect young adults’ have focused on the post-occupancy evaluation of quality of life by conducting a survey of 280 indepen- Happy House residents concerning their housing satis- dent young households. The results showed that over- faction based on sociodemographic characteristics or all satisfaction with the physical characteristics of the previous housing type (Shin et al., 2020, Noh and housing, physical characteristics of the residential Jin, 2018, Song et al., 2018). However, multiple studies environment, and burden of housing expenses had have expressed the need to consider residents’ lifestyles an effect on the quality of life of young households. to provide customized housing plans for young adults Among them, satisfaction with physical characteristics (Lee and Oh, 2019, Lim et al., 2019). As lifestyle greatly had the greatest influence, and this study shows that affects activities in homes, which will affect housing the consideration of physical characteristics is impor- satisfaction or the need for improvement, it is important tant for improving the quality of life of residents living to identify the improvement needs of houses consider- in young households. In addition, Noh and Jin (2018) ing lifestyle types. Limited studies exist against this conducted a housing satisfaction survey with about backdrop, focusing on housing preferences or satisfac- 1300 residents in public rental housing, including tion levels of young adult households based on lifestyle Happy Houses in Gwangju and the Jeollanam-do types. However, unlike previous studies, this study area, examining the satisfaction levels based on hous- focused on Happy Houses to identify housing satisfac- ing sizes and ownership types, rent and public facil- tion and the need for improvement according to the ities, and commute time. The study found that the lifestyles of young residents. The study participants were difference between the size of the desired house and residents of Happy Houses across Korea. This is unique that of the current house was larger than that of other in suggesting housing improvement measures based on types of rental housing, indicating that the size of the lifestyle types. The study results may be used as basic house was a problem. In addition, when the size of the data to devise spatial improvement measures for Happy house was larger than that of the existing house, hous- Houses as rental housing tailored to young adults, con- ing satisfaction was higher. Therefore, it can be con- sidering the lifestyle of young residents. firmed that the size of the house is an important variable in the satisfaction of residents with Happy Housing. Milić and Zhou (2018) surveyed 350 Serbian youth aged 20–35 years regarding housing satisfac- 2. Literature review tion. The authors found that households with higher 2.1. Trends in previous studies on housing for housing satisfaction had higher satisfaction with hous- young adults ing accessibility, preference for housing characteristics, and attachment to neighbors as well. In other words, The trend of previous studies related to housing housing satisfaction can be improved when housing demands for young adults can be divided into (1) that considers the preferences of young households is studies dealing with housing consciousness and beha- supplied, and this is a study that explains that in addi- vior, such as housing satisfaction, targeting general tion to the characteristics of the housing itself, loca- housing where young adults live; and (2) studies deal- tional characteristics and relationships with neighbors ing with spatial characteristics of youth housing or can affect housing satisfaction. spatial demands of young adults, which are summar- Second, similar to this study, some studies have ized as follows. focused on the spatial characteristics and needs of First, some studies have determined the housing young adult-targeted housing. Lee and Eom (2018) consciousness and other conditions of young adults, examined young adults living alone to identify the including housing satisfaction. Thus, Lee and Jee spatial demands of shared housing. These included (2021) classified the housing consciousness of young their preferences for basic housing installations, addi- households as greatly affected by the COVID-19 pan- tional installation spaces, and shared spaces and facil- demic due to poor housing conditions. They sug- ities. Lim et al. (2019) focused on the design gested changes in housing activities to develop preferences and needs of young adults who live young adult targeted housing programs after the pan- alone. As young adults living alone spend time in demic. To this end, the study conducted an online their bedrooms or living rooms, this must be consid- survey of 600 households, whose residents were 20– ered in housing designs. They also suggested expand- 39 years old. Consequently, the respondents were clas- ing the living room, where young adults participate in sified into four attentional clusters. Across the clusters, various activities, and adding walk-in closets to the there were differences in the characteristics of the JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 3 bedroom and other storage spaces. Shin et al. (2020) commonly used for analysis. AIO is effective identified the spatial characteristics of Happy Houses because it reflects various factors regarding hous- and the need for improvement among residents. ing, including consumption patterns, interests, and Improvements were required to meet the satisfaction values, concerning general aspects of life. levels of the location, surrounding environment, and Housing lifestyle studies have focused on the life- internal space of Happy Houses. The internal space was style of particular groups, including young adults, pre- focused on the area, noise, light, kitchenware, and old age, and those living in apartments (Kwon et al., bathroom facilities. The study suggested improvement 2016, Lee et al., 2007) or housing preferences based on measures based on these findings. Baek and Kim lifestyle. Regarding housing preferences, many studies (2022) surveyed a total of 595 young people have focused on housing type, location, or both as well aged<39 years living in shared housing and analyzed as lifestyle characteristics concerning housing plans. the factors affecting their housing satisfaction. It was Lee and Oh (2019) classified the lifestyles of young found that the physical, emotional, social, and benefi - adults and newlyweds in Korea and identified the cial characteristics of shared housing affected resi- housing sizes, types, and preferred plane structures. dents’ housing satisfaction. This result shows that They classified the housing lifestyles of young adults even in the case of a shared house, not a general into information oriented, uniqueness seeking, future independent house, it needs to be planned consider- oriented, self-development, and practicality oriented, ing its detailed properties. and analyzed housing preferences accordingly. They The literature revealed various types of housing revealed that people with all lifestyle types preferred ownership by young adults, from owning to renting to live in apartments, but the uniqueness-seeking a house, and various housing types, from general to types preferred “officetels” (buildings combining shared. Housing characteristics affect satisfaction offices and hotels). In contrast, the information- and quality of life. However, multifaceted research oriented type preferred detached housing. Future- on housing satisfaction has been affected by char- oriented types preferred large housing, whereas the acteristics such as gender, age, occupation, and life- uniqueness-seeking types did not have clear prefer- style. Several studies have examined housing ences for size. The future-and-practicality-oriented satisfaction among young adults. However, limited types preferred a plane structure with an expanded research has focused on the satisfaction levels and living room, while the information-oriented and needs for the improvement of young adults living in uniqueness-seeking types preferred a plane structure Happy Houses. While housing improvement needs with expanded bedrooms. Lee et al. (2014) classified in the past have been dealt with mainly based on the lifestyles of those in their 20s and 30s and living individual socio-demographic characteristics or eco- alone as students and workers. They studied the differ - nomic characteristics, in this study, even in the case ences in their preferences for shared housing. As the of groups with similar characteristics, there were students preferred a convenient diet, they enjoyed differences in lifestyle, and the corresponding instant food. Furthermore, they had a low demand improvement needs were identified. However, for their own houses and wanted a convenient urban there was a difference. housing environment close to public transportation, with a heavy focus on leisure activities. In contrast, workers spent more money on leisure activities than 2.2. Studies on housing lifestyle did students who were interested in their diet. For instance, they used pretty plates even when eating at Lazer introduced the concept of lifestyle to the home. Moreover, they have little desire to own a house American Marketing Association in 1963, which has and focus more on its internal structure and functional since been actively used. Lazer (1963) defined life- convenience than on its size. Yun (2019) analyzed the style as “a distinctive or characteristic mode of living relationship between lifestyle types and housing pre- in its aggregative and broadest sense, of a whole ferences of one-person households in Busan, Korea. society or segment thereof.” In the field of housing Although the study was conducted in one-person studies, the concept was incorporated from the households, 96% of the participants were in their 1960s to 1970s with studies on selecting housing twenties and thirties; thus, it can be said that this locations in the United States (Thorkild, 2006). study focuses on young adults living alone. The study Lifestyle has become an important factor that classified housing lifestyle types as follows: extroverted affects housing consciousness, including housing unique, passionate challenger, and success-focused preferences, satisfaction levels, and sociodemo- hardworking. Items of housing satisfaction included graphic characteristics (Kwon et al., 2016). There internal area, building facilities, external environment are many ways to analyze lifestyles. In housing stu- and factors, and installations. The findings revealed dies, Activity, Interest, and Opinion (AIO) is 4 M. JANG ET AL. distinctive preferences for all lifestyle types for bath- students. Furthermore, newlyweds were provided in room size and the direction of the windows. The pas- 36㎡ , 44㎡ , and 55㎡ houses, respectively. However, sionate challenger and success-focused hardworking if there are insufficient applicants, young adults living types showed high preferences for proximity to med- alone can also enroll in houses that are 36㎡ years old ium- or larger-sized hospitals, and the passionate chal- and larger. According to Ha and Kim (2020), the sizes of lenger type showed preferences for induction Happy Houses were 14㎡ , 26㎡ , 36㎡ , and 43㎡ for cooktops within the home. one-, two-, three-, and four-person households, respec- Although multiple studies exist on lifestyle and tively. However, the average house sizes were 31㎡ focusing on young adults, there are various ways to and 66.5㎡ for young adults living alone and newly- classify lifestyles depending on the purpose of the weds, respectively, which is 1.5 to 1.8 times larger than study. Furthermore, there are differences in housing the minimum level set by the government (Kim, 2019). preferences according to lifestyle types. Unlike pre- In terms of the actual composition of their sizes, the 16 vious studies, this study focused on the lifestyles of ㎡ houses are generally studio-type houses with sepa- young adults living in Happy Houses to emphasize the rate entrances, kitchens, dining and living rooms, bed- need to consider lifestyles when devising improve- rooms, bathrooms, and balconies. Some houses ment plans for Happy Houses. Furthermore, we com- provide a sliding door between the living room and prehensively investigated the relationship between kitchen to create a makeshift bedroom. Some 26㎡ lifestyle, need for improvement, and satisfaction levels houses are studio-type houses, such as 16㎡ houses, with current housing. and there are also one-bedroom houses that separate the bedroom from the living room. Of the 36㎡ houses, there was a bedroom, and they had larger kitchens or 2.3. Spatial characteristics of happy houses dining rooms than those of the 26㎡ houses. There were two bedrooms in 44㎡ houses with a living, din- Representative types of constructed-type public rental ing, and kitchen structure, with a separate living room housing supplied in Korea include permanent rental connected to the kitchen or dining room. Moreover, houses, national rental houses, and happy houses. the exact composition of houses may vary within the Permanent rental houses, which have the longest his- same size depending on the location. A study revealed tory, are mainly supplied to beneficiaries, can be lived that houses sized 36㎡ and larger might have up to six in for up to 50 years, and are supplied at a very low cost plane structures with different locations and room of 30% of the market price (Korea Land and Housing sizes, apart from the kitchen and bathroom (Ha and Corporation, 2022a). In contrast, the national rental Kim, 2021). houses are targeted to the second-level class, which There are also differences in the basic options pro- has more income than that, can be residents for up to vided, depending on the size of the house supplied. 30 years, and can be occupied at 60%–80%of the mar- Happy Houses have shoe storage, kitchenware, and ket price. The size of national rental houses is 60 m2, shower facilities at the entrance. However, furniture which is larger than that of permanent rental houses and appliances, including desks, bookshelves, and (40㎡ ). Unlike other rental types, Happy Houses show refrigerators, are only provided in small houses (less a difference in the increase in income standards and than 26㎡ ) for university students and young adults are mainly supplied for certain classes such as college living alone. However, some have gas cooktops in students, newlyweds, and young people. houses sized 36㎡ or larger; hence, the options pro- Consequently, happy houses are built and supplied vided may vary. near workplaces, schools, and public transportation. There are no distinct characteristics in the interior The criteria for net leasable area and rental costs are designs of Happy Houses. Generally, all houses use similar to those of the national rental houses, but the light brown vinyl linoleum for flooring and white silk actual housing size is smaller than the national rental wallpaper. houses. As of 2020, there are 89,000 Happy Houses in Korea and 9.1% of all long-term public rental housing. Furthermore, 31000 Happy Houses were provided, exceeding 61.6% of the year’s housing supply, con- 3. Materials and methods suming a large share of housing (Ministry of Land, 3.1. Developing the survey questionnaire Infrastructure, and Transport, 2020). The Happy Houses varied in size from 14㎡ to 55㎡ . This study categorized the housing lifestyle of The major types of sizes are 16㎡ , 26㎡ , 36㎡ , and 44 young adults and newlywed couples living in public ㎡ , which have been sustainably supplied on a similar rental housing and identified differences in housing scale since it is provided (Ha and Kim, 2020) (Figure 1). satisfaction and demands for improvement. First, The 16㎡ and 26㎡ houses are generally provided to a housing lifestyle research tool was developed young adults living alone, including those beginning using the “AIO Analysis” theory based on the hous- their careers, seeking employment, and university ing studied (Kwon et al., 2016, Lee et al., 2007, JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 5 Table 1. References for developing the housing lifestyle items. Lee Kwon Moon Kim and et al. et al. et al. Jang Classification Item (2007) (2016) (2019) (2021) Activity 1 I frequently study or work at home. ● ● ● ● 2 I frequently watch movies or listen to music at home. ● ● ● ● 3 I frequently enjoy leisure activities, including exercise or creative activities at home. ● ● ● ● 4 I frequently invite family members or guests home. ● ● 5 I generally cook my meals at home. ● ● ● 6 I generally have takeout or deliveries to eat at home. ● ● ● 7 I frequently take baths in the tub. ● ● 8 I generally shop online. ● ● Interest and 1 I want a house that is easy to keep clean. ● ● ● Opinion 2 I want a house where I can rest comfortably. ● 3 For me, a house is just a place to sleep. ● ● 4 I want to live in a beautiful house. ● ● ● 5 I want a house where I can spend time with my family and friends. ● ● ● 6 My opinion is the most important when making decisions related to the house. ● 7 I want a house where I can decorate and place furniture as I wish. ● ● ● ● 8 My house should have the latest technology. ● ● ● 9 I want a house where I will not be distracted by neighbors. ● ● 10 I consider long-term plans (marriage, childbirth, etc.) as well as the present ● ● ● conditions for my house. 11 I want a house with good security conditions where I can feel safe. ● ● ● 12 I want a house where it is easy to engage with neighbors. ● ● ● 13 I am interested in keeping the internal environment clean. ● ● ● 14 I want a house where I can live with an animal. ● ● 15 I want a house where I can grow plants. ● Moon and Lee, 2019). Another relevant study of Kim additional detailed items were developed. The and Jang (2021) was referred to reflect the charac- final version of the survey used the sociodemo- teristics of the housing lifestyle of young adults and graphic, economic, and physical characteristics of newlyweds. However, there were many items initi- the current house (Table 2). ally, which were later revised and omitted based on the study objectives. The developed survey items 3.2. Research participants and methods comprised 23 items, with eight items on daily life activities in the housing setting and 15 items on The survey participants comprised young adults and the level of interest and thoughts regarding the newlyweds residing in public rental housing called housing setting. Each item was measured using Happy Houses. Although older adults and general low- a five-point Likert scale, ranging from 1 (highly income households also reside in Happy Houses, the disagree) to 5 (highly agree) (Table 1). participants were limited to young adults aged 19–39 Also, some previous studies were reviewed to and newlyweds who have been married for no longer identify the differences in housing satisfaction and than 10 years. A pre-survey of 20 people from the demands for improvements. Based on the literature public with similar characteristics as the young adults (Lim et al., 2019, Lee and Oh, 2019), the actual and newlyweds living in Happy Houses and those composition of the house, its usable area, its basic majoring in housing was conducted. In the pre- options (appliances, furniture, equipment), and survey, participants had to fill out the house area interior design were selected to develop the survey exclusively in either pyeong (1 pyeong = 3.3 m ) items. The housing satisfaction level and demands or m . The results revealed that participants did not for improvement were used as survey items. Each answer using the unit or made mistakes by getting the item was based on a five-point Likert scale. unit confused with the area size unit. Therefore, to Furthermore, to identify the demands in detail, ensure consistent data collection on house size, the Table 2. Composition of the questionnaire. General Characteristics Sociodemographic Age of the Householder/Sex of the Householder/Occupation of the Householder/Number of People (6) Characteristics (5) in the Household/Household Type Economic Characteristics (1) Average monthly income Characteristics of the House (4) Region/Size/Number of Rooms/Number of Bathrooms/Length of Residence Housing Satisfaction * (5) Room Composition (Type and number)/Usable area per room/Basic options/Interior design/General satisfaction Demands for Improvements in Housing Room Composition (Type and number)/Usable area per room/Basic options/Interior design/General Environment * (5) demands/Detailed demands *Based on a 5-point Likert scale (1 (Highly disagree) − 5 (Highly agree)) 6 M. JANG ET AL. survey was edited so that the participants respond householders was from the general economic activ- in m . Also, the logical errors of optional items depend- ity sector, including office workers, entrepreneurs, ing on the characteristics of the participants and slight and self-employed, at 87.3%. There were 4.7% stu- changes to the wording were made to complete the dents and 8.0% unemployed participants. The aver- tool. Based on the developed tool and the research age number of people in the household was 1.45, plan, the survey was conducted after attaining as more than half (61.2%) were one-person house- approval from the research ethics committee of the holds. About 33.4% of the participants responded affiliated institution (anonymized for the review). that they were a two-people household, among An online survey was used for this study. With the which 77.1% were couples with no children, 11.2% cooperation of the supply organization of Happy were brothers and sisters, 9.5% were friends, and House, information on the questionnaire was attached 2.2% were others. Three-people households com- to the apartment complex. As there may be regional prised 4.9% of the participants and were generally differences in housing satisfaction and the demand for couples with children. The average monthly income improvement, the number of complexes asked to par- was considered to understand the participants’ eco- ticipate was selected by the number of households in nomic characteristics. The income was analyzed a complex. This ensured similar numbers of partici- using the income standards by the household pants from Greater Seoul and other regions. In addi- members based on the 100% level of the average tion, most of the chosen Happy House complexes were monthly income of urban households in 2021. On built after 2018, ensuring the deterioration of the average, the participants had a monthly income of houses was similar. After collecting a certain number KRW 3.1625 million. More than half (53.7%) of responses from the complexes to match the number responded that their monthly income was KRW of participants by region, more data were collected 2.99 million or under. Even though more than half from online communities of those living in Happy of the participants were one-person households, Houses and those who wish to live in Happy Houses. there were relatively more households with A total of 753 responses were collected, and 536 were a lower income than the average monthly income analyzed after eliminating invalid responses or those of one-person households. Participants had who did not fall under the inclusion criteria. Of the a monthly income of over KRW 2.99 million to valid responses, 92.6% were from the apartment com- KRW 4.56 million or less (27.4%), the standard for plexes, and the response rate of the distributed surveys two-people households. Considering two-people was approximately 4.4%. households took up 33.4% of the participants, this The collected data were analyzed using the SPSS shows that the participants generally had lower 22.0 statistics program. Descriptive statistics were used than average income. Lastly, 16.6% of the partici- to analyze the participants’ general characteristics and pants had a monthly income of more than KRW those of the current houses. Housing lifestyle types 4.56 million (Table 3). were analyzed using factor and cluster analyses. Lastly, the chi-square test and analysis of variance 4.2. Characteristics of the participants’ current were used to analyze differences in housing satisfac- houses tion and demands for improvement in housing envir- onments per the housing lifestyle types. The analysis of the characteristics of the Happy House, where the participants resided, revealed that 59.3% of the houses were in the Greater Seoul 4. Results region (Seoul, Gyeonggi-do, Incheon). The percen- The analysis results were organized according to the tages of responses from those living in metropolitan participants’ general characteristics, characteristics of cities, Sejong, and other regions were equal at the current houses, housing lifestyle types, housing 20.3%. The average house size was 33.02 m . The satisfaction, and demands for improvement by lifestyle house was divided into sections using the size stan- types. dard by the number of people per the minimum standards in housing to analyze the housing size. Hence, the most common size was houses that 4.1. Participants’ general characteristics were 36 m and over, suitable for households with The general characteristics of the participants were three or more people, with 59.7%, followed by analyzed for the householder. First, 57.8% of the houses that were 26 to under 36 m with 21.5%. householders were women, 15.6% higher than The average number of bedrooms was 1.94. The men. The average age of the householder was proportions of responses from those living in 30.19 years, and 51.3% of the householders were a studio-type apartment and a two-bedroom apart- 30 and older, which was more than those younger ment were similar at 35%, and 29.3% of participants than 30. The most common occupation among the lived in three-bedroom apartments. Most JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 7 Table 3. General characteristics of the participants. (N=536) Classification f(%)/M(SD) Sociodemographic Characteristics Householder Sex Male 226 (42.2) Female 310 (57.8) Age Younger than 30 261 (48.7) 30 or over 275 (51.3) Average (age) 30.19 (4.77) Education Level High school graduate 66 (12.3) 2-year or 4-year university graduate 411 (76.7) Master’s or Ph.D. 59 (11.0) Occupation Office worker/Entrepreneur/Self-employed 468 (87.3) Student 25 (4.7) Unemployed 43 (8.0) Number of people in the household 1 328 (61.2) 2 179 (33.4) 3 or more 29 (5.4) Average (people) 1.45 (0.61) Household Type 1-person household 328 (61.2) Couple with no children 138 (25.7) Couple with children 26 (4.9) Other 44 (8.2) a b Economic Characteristics Average Monthly Income − 299 (1-person household) 288 (53.7) (KRW 10,000) 299–456 (2-people household) 147 (27.4) 456- (3±people household) 89 (16.6) Average (KRW 10,000) 316.25(160.37) Only valid responses were analyzed. Classified according to the average monthly income levels of workers in the city in 2021 participants (98.5%) responded having one bath- the responses. Eight items on daily life activities room. Lastly, the participants had resided in their showed an average of a minimum of 1.50 to houses for an average of 11.74 months. More than a maximum of 4.28 out of five. The item with the half of the participants (58.5%) responded that they highest average among the eight items was “I had resided in the current house for less than a year, generally shop online” (4.28), followed by “I fre- and 35.9% were reportedly residing for more than quently watch movies or listen to music at home” a year but less than two years (Table 4). (4.12). Only these two factors had an average of over four. The responses to 14 items on interests and opinions generally had higher averages than 4.3. Housing lifestyle types of the participants the items related to daily life activities. The item and the characteristics of each type with the highest average was “I want a house where I can rest comfortably”(4.89), which was 4.3.1. Housing lifestyle factors of the participants close to five, and 11 items, including “I want There was an analysis on the results of the AIO a house where I will not be distracted by neigh- items on housing lifestyle. First, the averages and bors,” had an average of over four. Second, the bias were analyzed to verify the normality of Table 4. Characteristics of the current houses of the participants. (N=536) Classification f(%)/M(SD) Housing-related Characteristics Region Greater Seoul region 318 (59.3) Metropolitan cities/Sejong 109 (20.3) Other regions 109 (20.3) Size Smaller than 26 (1-person household) 92 (17.2) 2 a (m ) 26 – less than 36 (2-people household) 115 (21.5) 36 or larger (3±people household) 320 (59.7) Average 33.02 (9.48) Number of Rooms 1 (Studio-type) 188 (35.7) 2 184 (35.0) 3 154 (29.3) Average 1.94 (0.82) Number of Bathrooms 1 528 (98.5) 2 8 (1.5) Length of Residence 1 year or less 304 (58.5) More than 1 year, less than 2 years 190 (36.5) More than 2 years 26 (5.0) Average 11.74 (7.83) a Only valid responses were analyzed. 8 M. JANG ET AL. Table 5. Analysis of housing lifestyle. (N=536) Classification Lifestyle Items Average* STD Activity 1 I frequently study or work at home. 2.87 1.34 2 I frequently watch movies or listen to music at home. 4.12 1.01 3 I frequently enjoy leisure activities, including exercise or creative activities at home. 2.80 1.32 4 I frequently invite family members or guests home. 2.68 1.28 5 I generally cook my meals at home. 3.50 1.18 6 I generally have takeout or deliveries to eat at home. 3.11 1.17 7 I frequently take baths in the tub. 1.50 1.08 8 I generally shop online. 4.28 0.94 Interest and Opinion 1 I want a house that is easy to keep clean. 4.81 0.47 2 I want a house where I can rest comfortably. 4.89 0.37 3 For me, a house is just a place to sleep. 4.00 1.10 4 I want to live in a beautiful house. 4.47 0.84 5 I want a house where I can spend time with my family and friends. 4.21 1.02 6 My opinion is the most important when making decisions related to the house. 4.30 0.98 7 I want a house where I can decorate and place furniture as I wish. 4.57 0.74 8 My house should have the latest technology. 3.96 1.11 9 I want a house where I will not be distracted by neighbors. 4.86 0.49 10 I consider long-term plans (marriage, childbirth, etc.) as well as the present conditions for my house. 4.30 1.08 11 I want a house with good security conditions where I can feel safe. 4.81 0.54 12 I want a house where it is easy to engage with neighbors. 2.64 1.20 13 I am interested in keeping the internal environment clean. 4.71 0.59 14 I want a house where I can live with an animal. 3.23 1.57 15 I want a house where I can grow plants. 3.78 1.30 ※ Shaded items are deleted items as a certain response had a concentration level that exceeds 70%. descriptive statistics was used to select only the sleeping. This factor’s reliability (Cronbach’s α) was items with a certain level of normality. Hence, five 0.665. Factor 2 comprised three items and had an items, including “I frequently take baths in the explanation power of 13.369% for all variables. Factor tub,” which had the lowest score among the daily 2 was named “Engagement Activities” as it included life activities items, “I want a house that is easy to engagement with neighbors and family members and keep clean,” and “I want a house where I can rest expanding the family in the long term (Cronbach’s α = comfortably” from the interest and opinion items 0.554). Factor 3 comprised three items. It was named were removed as the concentration level of “Home Styling” as it related to a lifestyle that prefers a certain response exceeded 70% (Table 5). aesthetic houses and wishes to decide the interior Third, there was a factor analysis using the 17 hous- design of the houses. Factor 3 had an explanation ing lifestyle items that passed the normality standard. power of 12.606% and a reliability of 0.588. Factor 4 Principal Components Analysis and Varimax were used comprised four items. It included a lifestyle that prior- for the analysis. After the analysis, four items, including itized watching movies, listening to music, exercising “I frequently study or work at home,” “I generally shop or participating in other leisure activities, and joining online,” and “My house should have the latest technol- parties. Accordingly, this factor was named “Leisure ogy,” were removed as the commonality for these here Activity,” and its explanation power was 10.952% items was less than 0.4. Another factor analysis was (Cronbach’s α = 0.463). Lastly, factor 5 comprised two conducted afterward with 14 items. Hence, housing items, with an explanation power of 10.087% lifestyle factors were classified into five factors. The (Cronbach’s α = 0.458). This factor included a lifestyle total cumulative variance of the factors was 60.726, that emphasized a life with animals or plants, and so resulting in an explanation power exceeding 60%. was named “Living with Companions” (Table 6). The KMO (Kaiser-Meyer-Olkin) value of the selected factor solution was 0.653, showing an appropriate 4.3.2. Housing lifestyle cluster of the participants sample fit. The significance level of the chi-square Based on the results of the factor analysis, there was test from Bartlett’s test of sphericity test was less than a cluster analysis using the standardized scores of each 0.001, verifying the statistical appropriateness. factor. After the hierarchical cluster analysis, three to Furthermore, as the commonality was at a minimum six cluster solutions were identified based on of 0.497 to a maximum of 0.741, the relative contribu- a dendrogram. Then, using K-means cluster analysis, tion level of individual factors was also high. the characteristics of each cluster solution were ana- Regarding the five factors, Factor 1 comprised three lyzed. The results revealed that five cluster solutions items. It had an explanation power of 13.712% for all would be most appropriate for this study’s purpose variables. Factor 1 was named “Basic Living” as it and have appropriately distributed housing lifestyle included basic lifestyle factors, including eating or factors in each cluster. Hence, these five clusters were JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 9 Table 6. Analysis of housing lifestyle factors. Factors Basic Engagement Home Leisure Living with Lifestyle Items Commonality Living Activities Styling Activity Companions I generally have takeout or deliveries to eat at home. 0.741 0.856 −0.011 −0.030 −0.060 0.059 I generally cook my meals at home. 0.711 0.796 0.089 −0.117 0.191 0.140 For me, a house is just a place to sleep. 0.516 0.591 0.018 0.334 0.116 −0.205 I want a house where I can spend time with my family and friends. 0.690 −0.002 0.762 0.261 0.200 −0.035 I consider long-term plans (marriage, childbirth, etc.) as well as the 0.497 0.098 0.683 0.097 −0.095 −0.058 present conditions for my house. I want a house where it is easy to engage with neighbors. 0.533 −0.068 0.599 −0.183 0.021 0.370 I want a house where I can decorate and place furniture as I wish. 0.670 0.060 0.215 0.775 −0.002 0.141 My opinion is the most important when making decisions related to 0.640 −0.116 −0.158 0.729 0.240 0.112 the house. I want to live in a beautiful house. 0.552 0.125 0.440 0.581 −0.017 −0.077 I frequently watch movies or listen to music at home. 0.529 0.096 −0.060 0.139 0.704 −0.029 I frequently invite family members or guests home. 0.643 −0.126 0.371 −0.084 0.693 −0.047 I frequently enjoy leisure activities, including exercise or creative 0.545 0.255 −0.106 0.126 0.622 0.257 activities at home. I want a house where I can live with an animal. 0.618 −0.116 −0.017 0.086 0.096 0.767 I want a house where I can grow plants. 0.615 0.232 0.202 0.093 −0.018 0.715 Eigen Value 1.920 1.872 1.765 1.533 1.412 Common Variance 13.712 13.369 12.606 10.952 10.087 Cumulative Variance 13.712 27.081 39.687 50.639 60.726 KMO=0.653/BARTLETT=1,257.916*** ***P<0.001. confirmed as the final clusters. Afterward, there was an households accepted the conditions of the house F test on the standardized scores of the factors of each that was handed over to them and engaged in mini- cluster. It revealed statistical significance among the mal housing activities. This cluster was named five clusters and the five factors (p < 0.001). “Minimally Using” (Table 7). The characteristics of the five clusters were as follows. Cluster 1 comprised the households that 4.4. Characteristics by housing lifestyle clusters actively used all parts of the house to participate in engagement and leisure activities, apart from the 4.4.1. General characteristics by housing lifestyle basic housing activities. This cluster was named clusters “Actively Using.” Cluster 2 had more interest in the The differences in general characteristics by housing house itself and decorated it by their tastes rather lifestyle clusters were analyzed. The results revealed than being interested in particular housing activities. that besides the ages and educational levels of the This cluster was named “Self-Expression.” Cluster 3 householders, all characteristics showed statistically was also interested in decorating their houses like significant differences by clusters. That is, there were Cluster 2 but was focused on basic housing activities, similar characteristics across all clusters, as many parti- such as eating and sleeping. They wished for a stable cipants were younger than 30 and had graduated from personal life by engaging with animals or plants. This two- or four-year universities. The differences in the cluster was named “Personal Activity.” Cluster 4’s life- major characteristics by cluster are as follows. style prioritized engagement with others, including First, many householders in the “Actively Using” friends or family, or plants or animals, over their lives. cluster participated in economic activities, and this This cluster was named “Engagement-Focused.” cluster had more households with two or more people Lastly, Cluster 5 had relatively less interest in all five or couples than other clusters. Many households in this factors, particularly decorating their houses. These cluster had relatively high monthly incomes that fell Table 7. Analysis of standardized scores of each factor by clusters. Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 (n=126) (n=106) (n=108) (n=109) (n=87) Actively Using Self-Expression Personal Activity Engagement-Focused Minimally Using Classification Cluster Cluster Cluster Cluster Cluster F Basic Living 0.49957 −0.73285 0.79460 −0.39782 −0.31860 68.813*** Engagement 0.72016 0.00928 −1.01366 0.61360 −0.56472 112.245*** Activities Home Styling 0.03258 0.52396 0.53817 0.20796 −1.61432 159.474*** Leisure Activity 0.74520 0.03406 −0.06533 −0.79292 −0.04623 46.720*** Living with 0.05975 −1.06921 0.76360 0.76360 −0.03617 73.964*** Companions ***p<0.001. 10 M. JANG ET AL. under the appropriate amount of household income households, who were not likely to participate in eco- with three or more people. That is, the households had nomic activities. They were relatively more economic- more than two people and high income. Hence, their ally vulnerable than other clusters. Therefore, their lifestyle focused on family and other leisure activities. lifestyle included basic activities, such as eating and The “Self-Expression” cluster had relatively more sleeping, which did not cost much, or living with ani- women student householders than other clusters and mals or plants. Households in the “Engagement- the highest proportion of one-person households. Focused” cluster had more householders where the Their incomes matched with one-person households. men participated in economic activities than other That is, as women living alone are the major type of clusters. These households comprised married couples household in this cluster, they focused on using the with two or more people in the household. There were house to self-express rather than for leisure activities or households that fell under the income bracket for two- engaging with others. The “Personal Activity” cluster people households, and relatively more households had the largest portion of women householders than fell under the three-people household income bracket. any other cluster and many unemployed house- That is, the households in this cluster had a certain holders. It had the second-most one-person house- income level and enjoyed married life. Although they holds, followed by the “Self-Expression” cluster, with prioritized family bonding time, they were relatively some two-people households. The income of this clus- less interested in leisure activities like the “Actively ter fell more in the one-person household category Using” cluster. Lastly, the “Minimally Using” cluster than the “Self-Expression” cluster and had relatively had the greatest number of households with a man few households with high income. That is, this cluster householder who participated in economic activities. mostly comprised women in one- or two-people This cluster mostly comprised one-person households Table 8. General characteristics by housing lifestyle cluster. Housing Lifestyle Cluster Engagement- Minimally Actively Using Self-Expression Personal Activity Focused Cluster Using Cluster Classification Cluster (126) Cluster (106) Cluster (108) (109) (87) χ Householder’s Sex Male 57 35 34 51 49 17.285** (45.2) (33.0) (31.5) (46.8) (56.3) Female 69 71 74 58 38 (54.8) (67.0) (68.5) (53.2) (43.7) n.s. Householder’s Age Younger than 30 66 50 51 52 42 0.926 (52.4) (47.2) (47.2) (47.7) (48.3) 30 or over 60 56 57 57 45 (47.6) (52.8) (52.8) (52.3) (51.7) n.s. Householder’s High school graduate 13 18 13 11 11 6.642 Education Level (10.3) (17.0) (12.0) (10.1) (12.6) 2-year or 4-year 98 76 80 86 71 university graduate (77.8) (71.7) (74.1) (78.9) (81.6) Master’s or Ph.D. 15 12 15 12 5 (11.9) (11.3) (13.9) (11.0) (5.7) Householder’s Office worker/ 109 91 87 99 82 16.905* Occupation Entrepreneur/Self- (86.5) (85.8) (80.6) (90.8) (94.3) employed Student 8 8 7 0 2 (6.3) (7.5) (6.5) (0.0) (2.3) Unemployed 9 7 14 10 3 (7.1) (6.6) (13.0) (9.2) (3.4) No. of Family 1 67 77 76 58 50 21.718* members (53.2) (72.6) (70.4) (53.2) (57.5) 2 47 26 31 43 32 (37.3) (24.5) (28.7) (39.4) (36.8) 3 or more 12 3 1 8 5 (9.5) (2.8) (0.9) (7.3) (5.7) Household Type 1-person household 67 77 76 58 50 30.900** (53.2) (72.6) (70.4) (53.2) (57.5) Couple with no children 38 19 19 34 28 (30.2) (17.9) (17.6) (31.2) (32.2) Couple with children 12 3 0 7 4 (9.5) (2.8) (0.0) (6.4) (4.6) Other 9 7 13 10 5 (7.1) (6.6) (12.0) (9.2) (5.7) Average Monthly − 299 (1-person 59 62 71 52 44 20.201* Income household) (48.4) (59.0) (68.9) (48.6) (50.6) (KRW 10,000) 299–456 (2-people 34 29 26 34 24 household) (27.9) (27.6) (25.2) (31.8) (27.6) 456- (3±people 29 14 6 21 19 household) (23.8) (13.3) (5.8) (19.6) (21.8) *p<0.05, **p<0.01, n.s. not significant. JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 11 or households with married couples without children. replied they lived in a three-bedroom house. Among Accordingly, many households in this cluster all clusters, this cluster had the smallest proportion of responded that their incomes fell under the one- households living in studio apartments. As seen from person to two-people household income brackets. the sociodemographic characteristics, many house- That is, this cluster can be defined as a one-person holds in the “Actively Using” cluster are married couples household engaged in economic activities or newly- with two or more people in the household. The most wed couples with relatively less interest in houses and common place of residence for the “Self-Expression” participation in minimal housing activities (Table 8). cluster was metropolitan cities and Sejong. They a Only valid responses were analyzed resided in houses with a size of less than 26 m . Therefore, the most common house type was a studio. This may be because there were relatively 4.4.2. Characteristics of the current houses by more students in the “Self-Expression” cluster than in housing lifestyle cluster other clusters with more one-person households. There was an analysis to identify the differences in the Among all clusters, the “Personal Activity” cluster had characteristics of the current houses by housing life- the highest proportion of households living in the style cluster. The results revealed that apart from the Greater Seoul region. Although many households number of bathrooms and the length of residence, all resided in houses that were 36 m or larger, compared characteristics showed statistically significant differ - with other clusters, there was a higher proportion of ences by lifestyle cluster. In all clusters, the most com- households living in houses that were 26 m or smaller. mon number of bathrooms was one, and the most This cluster also had many one-person households, common length of duration was 1 year or less. The with a high proportion of students or the unemployed, differences in the major characteristics by cluster are who did not engage in economic activities. This may as follows. have led to a greater proportion of households living in First, for the “Actively Using” cluster, there were the smallest houses than in other clusters. A large relatively more households in the Greater Seoul region, proportion of the“Engagement-Focused” cluster lived and the cluster had the least proportion of households in the Greater Seoul region. Although there were slight living in the province areas. The cluster had the most differences, the regional distribution of this cluster was proportion of houses that were 36㎡ or more and had like that of the “Actively Using” cluster. A large propor- the relatively less proportion of households living in tion of households in the “Engagement-Focused” clus- houses that were 26 m . As they lived in relatively ter lived in houses with a size of 36 m or more and two larger houses, the greatest number of households Table 9. Characteristics of the current houses by housing lifestyle cluster. Housing Lifestyle Cluster Minimally Actively Using Self-Expression Personal Activity Engagement-Focused Using Cluster Classification Cluster (126) Cluster (106) Cluster (108) Cluster (109) (87) χ Region Greater Seoul region 80 49 69 67 53 17.856* (63.5) (46.2) (63.9) (61.5) (60.9) Metropolitan cities/ 24 35 19 20 11 Sejong (19.0) (33.0) (17.6) (18.3) (12.6) Other regions 22 22 20 22 23 (17.5) (20.8) (18.5) (20.2) (26.4) Size Smaller than 26 12 24 28 17 11 19.010* 2 a (m ) (1-person household) (9.5) (24.0) (25.9) (15.9) (12.8) 26 – less than 36 28 26 23 20 18 (2-people household) (22.2) (26.0) (21.3) (18.7) (20.9) 36 or larger (3±people 86 50 57 70 57 household) (68.3) (50.0) (52.8) (65.4) (66.3) Number of 1 35 48 46 34 25 20.194* Rooms (Studio-type) (28.0) (45.3) (43.4) (33.0) (29.1) 2 41 36 28 43 36 (32.8) (34.0) (26.4) (41.7) (41.9) 3 49 22 32 26 25 (39.2) (20.8) (30.2) (25.2) (29.1) n. Number of 1 126 106 106 105 85 7.509 s. Bathrooms (100.0) (100.0) (98.1) (96.3) (97.7) 2 0 0 2 4 2 (0.0) (0.0) (1.9) (3.7) (2.3) n. Length of 1 year or less 66 61 70 59 48 6.107 a s. Residence (53.7) (59.8) (66.7) (55.7) (57.1) More than 1 year, less 51 37 31 39 32 than 2 years (41.5) (36.3) (29.5) (36.8) (38.1) More than 2 years 6 4 4 8 4 (4.9) (3.9) (3.8) (7.5) (4.8) *p<0.05, n.s. not significant. Only valid responses were analyzed. 12 M. JANG ET AL. rooms. As there were many households with two or Using” clusters. After analyzing the satisfaction levels more people like the “Actively Using” cluster, many in the sizes in detail, 40% or more of the two clusters of households lived in larger houses. Lastly, although “Self-Expression” and “Engagement-Focused” clusters a large proportion of households in the “Minimally with relatively lower satisfaction levels responded Using” cluster lived in the Greater Seoul area, there that they were not satisfied with the sizes of the was also a large proportion of those living in the houses. There are relatively more households in the province area than in other clusters. Many households “Self-Expression” cluster living in the provinces. Even in this cluster lived in houses sized 36 m or more. This though many households in this cluster were one- cluster had the highest proportion of houses with two person households living in a house of 36㎡ or larger, or more rooms (Table 9). due to the differences in the subjective housing norms in the area in size, they might find their houses small. As the “Engagement-Focused” cluster had more people 4.4.3. Housing satisfaction by housing lifestyle in the households than the “Self-Expression” cluster and cluster more married households, they showed relatively There was an F test to identify the differences in the greater dissatisfaction regarding housing sizes. satisfaction levels in the current houses by housing Regarding the differences in the satisfaction levels in lifestyle clusters. The results revealed statistically sig- the basic provided equipment, appliances, and furni- nificant differences in satisfaction with the space com- ture, there were differences between the “Minimally position of the house, house size, and basic provided Using” cluster and the other three clusters. The satisfac- equipment, furniture, and appliances by cluster. That tion level of the “Minimally Using” cluster was 3.09, is, no difference existed in the overall satisfaction and relatively higher than other clusters. Approximately the interior design by cluster. To analyze the differ - 80% of householders in this cluster responded that ences in the clusters with differences in the satisfaction they felt neutral, satisfied, or greatly satisfied with the level, there was a Duncan post hoc test. “Personal equipment, furniture, or appliances. As the “Minimally Activity” and “Engagement-Focused” clusters showed Using” cluster participated in minimal housing activ- differences in the satisfaction levels in the space com- ities within the house, they were relatively more satis- position. The “Personal Activity” cluster showed an fied with the equipment, furniture, or appliances for average satisfaction level of 3.61 for the space compo- the housing activities. However, their highest satisfac- sition, higher than the “Engagement-Focused” cluster. tion level was just above three, a near neutral, which This may be because the “Personal Activity” cluster had meant that the other clusters were dissatisfied regard- a high proportion of one-person households, but many ing the equipment, appliances, and furniture houses were 36㎡ or more in size with three rooms. (Table 10). Approximately half of this cluster lived in such two- bedroom houses, leading to high satisfaction levels with relatively more space. Although there were 4.4.4. Demands for improvement in housing many one-person households in the “Engagement- environments by housing lifestyle cluster Focused” cluster, there were relatively more house- There was an analysis on the demands for improve- holds with married couples. This may have led to low ment in housing environments by housing lifestyle satisfaction levels in the space composition. The satis- cluster. The results revealed significant differences by faction levels in the housing sizes differed between the cluster. First, statistically significant differences existed “Self-Expression” and “Engagement-Focused” clusters, in the general demands for improvement from the together as a group, and the “Personal Activity” and “Minimally Using” and “Actively Using” clusters as “Minimally Using” clusters, put together as a group. a group, compared with the “Self-Expression” and That is, the “Self-Expression” and “Engagement-Focused “Engagement-Focused” clusters as a group. The ” clusters had an average satisfaction level of 2.81, “Minimally Using” cluster had an average demand lower than the “Personal Activity” and “Minimally level of 3.13 for all types of improvements, relatively Table 10. Differences in satisfaction in the current houses by housing lifestyle. Housing Lifestyle Cluster Engagement- Minimally Actively Using Self-Expression Personal Activity Focused Cluster Using Cluster Classification Cluster (126) Cluster (106) Cluster (108) (109) (87) F n.s. Overall Satisfaction with Housing 3.54b 3.43ab 3.62b 3.27a 3.52ab 2.291 Satisfaction with Housing Composition (no. of 3.39bc 3.15ab 3.61c 3.02a 3.37bc 5.616*** rooms, layout, etc.) Satisfaction with Housing Size 2.99ab 2.81a 3.26b 2.81a 3.24b 3.557** Satisfaction on Housing Basic built-in 2.62a 2.63a 2.94ab 2.70a 3.09b 3.573** equipment, furniture, and home appliances n.s. Satisfaction with Housing Interior Design 3.17a 3.39a 3.43a 3.14a 3.31a 1.733 **p<0.01, ***p<0.001, n.s. not significant. JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 13 lower than other clusters. The satisfaction levels of the machines. In the bedroom, the two groups did not “Minimally Using” cluster in the equipment, appliances, differ in their demands for wardrobes and desks. and furniture were relatively higher than those of the However, in the bathroom, the “Actively Using” cluster other clusters, as the cluster did not use the house as had a very high demand for bathtubs, whereas the much as the other clusters. Hence, the cluster had “Personal Activity” cluster responded with no additional relatively fewer demands for the improvement of the needs. Lastly, a significant difference existed in the housing environment than other clusters. “Actively demand levels of interior design between the “Self- Using” and “Engagement-Focused” clusters had greater Expression” and “Minimally Using” clusters as a group demands for improvement in the space composition of and the “Actively Using” and “Personal Activity” clusters the houses than the “Self-Expression” and “Minimally as a group. The Self-Expression” and “Minimally Using” Using” clusters. The “Personal Activity” and clusters had relatively lower demand for improve- “Engagement-Focused” clusters showed differences in ments in interior design than other clusters. For the housing satisfaction levels, as the “Engagement- two clusters with high demands for improvements in Focused” cluster had lower satisfaction levels. The clus- interior design, the highest demand came from ter with lower satisfaction levels had greater demands improvements in soundproof levels and finishing for improvements in the space composition. The great- materials (Table 11). est demand for improvement for the “Actively Using” and “Engagement-Focused” clusters was having more 5. Discussion rooms, followed by having two bathrooms. The “Actively Using” and “Engagement-Focused” clusters This identified the housing improvement measures by had greater demands for a larger house than the lifestyle types of young adults living in Happy Houses. “Minimally Using” cluster. A large proportion of these The results are as follows. clusters demanded a large kitchen, dining room, and First, although all young adults living in Happy living room, and more than half demanded larger bed- Houses were in their twenties and thirties, we could rooms than the present ones. Many households in this classify them into five lifestyle types depending on cluster also demanded large bathrooms. These clusters how they used their homes. The first was the “Actively participated in various housing activities in the house Using” cluster, utilizing the house for leisure, forming or had a big affection on their house, which may lead relationships with various groups, and basic living pur- to increased demands for a big house. The “Personal poses. Another cluster was the “Minimally Using” clus- Activity” and “Engagement-Focused” clusters had differ - ter which barely used their houses, and the “Personal ent levels of demand for improving basic equipment, Activity” cluster, which focused on using the house for furniture, and appliances. Like the demand for a bigger basic living purposes and engaging with their compa- house, the “Actively Using” cluster demanded improved nion animals or pets. The “Engagement-focused” cluster equipment, furniture, and appliances. For detailed used the houses to engage with others and participate demands for improvement, the “Actively Using” cluster in personal activities, and the “Self-expression” cluster submitted more demands than the “Personal Activity” used houses to express themselves. Many young cluster. The former submitted 892 detailed demands, adults in their twenties and thirties lived in Happy while the latter submitted 511. Regarding the Houses, including university students, those beginning demands for basic options of the house, the “Actively their careers, newlyweds, and couples with toddlers. Using” cluster had high demands for an improved air Hence, the young adults in Happy Houses had varying conditioner in the living room and induction cooktops lifestyles. Currently, Happy House considers the num- and dishwashers in the kitchen. Contrarily, the ber of household members depending on the mini- “Personal Activity” cluster had high demands for induc- mum housing standard provided by the government tion cooktops in the kitchen but relatively higher and the age and sex of children as a standard to apply demands for refrigerators in the kitchen and washing to each housing size. However, there are various ways Table 11. Differences in the demands for improvements in the housing environment by housing lifestyle cluster. Housing Lifestyle Cluster Engagement- Actively Using Self-Expression Personal Activity Focused Cluster Minimally Using Classification Cluster (126) Cluster (106) Cluster (108) (109) Cluster (87) F Overall Demand for Housing 3.56b 3.40b 3.33ab 3.38b 3.13a 3.746** Demand on Housing Composition (no. of 3.52b 3.32ab 3.13a 3.57b 3.00a 4.142** rooms, layout, etc.) Demand for Housing Size 3.75b 3.79b 3.62ab 3.54ab 3.33a 2.635* Demand for Housing Basic built-in equipment, 3.69c 3.65bc 3.24a 3.35ab 3.33ab 3.680** furniture, and home appliances Demand for Housing Interior Design 3.27b 2.85a 3.31b 3.07ab 2.85a 3.207* *p<0.05, **p<0.01. 14 M. JANG ET AL. Figure 1. Examples of Happy Houses. *Source: Happy House pamphlet of Paju Unjeong District Sannae Village (Land and Corporation 2022b) that the residents use the house for varied lifestyles. living in other types of public rental housing, it is Lifestyles should be considered when planning the necessary to increase the area per house and improve composition of Happy Houses. the spatial composition standards. There should be Second, regardless of lifestyle clusters, residents of more housing models as compared with the present Happy Houses generally showed higher-than-average scenario. satisfaction levels. However, there were differences in Third, there were differences in clusters in their satisfaction levels by lifestyle clusters for the spatial demands for housing improvement of Happy Houses composition, size, equipment/furniture/appliances, for overall and detailed improvements. All clusters and other basic installments. The “Engagement- showed higher-than-average demands for housing focused” cluster had lower satisfaction levels than improvements. The “Minimally Using” cluster, which other clusters regarding the spatial composition, size, used homes for some purposes, showed relatively and basic installation options. It comprised married low demands for general and detailed improvements. couples with relatively high incomes living in two- The “Actively Using” cluster, which used the homes the bedroom houses in the Seoul area. They had the low- most, had the highest demands for general and est satisfaction levels in all areas. “Actively Using” clus- detailed improvements. It is necessary for Happy ter had similar demographic characteristics and used Houses to be diverse in spatial composition, area, and the house for various activities, lived in generally large interior design while considering the residents’ use of homes with three bedrooms, or the Seoul area. Those housing. Although there is a demand for large houses living in the Seoul area were less likely to be satisfied with varied room compositions and basic options that with smaller houses than those living in areas outside consider interior design, it may be a viable option to Seoul, hence the differences in satisfaction levels. provide the current Happy Houses with various Although the participants lived in houses larger than options for interior design, leading to low cost. In the the minimum standards provided by the government, “Self-expression” cluster, those who vested in their married couples with high-income levels were not houses showed low demands for improvement. satisfied with small houses with two bedrooms. In Hence, it may be viable to provide various options to rural areas, due to location or housing sizes, Happy the young adults to customize their houses depending Houses are frequently left vacant for a long time. The on their tastes. The regulations of rental housing must difference in demand for space between urban and be reviewed, and changes made to the house in the rural areas is a topic that has been discussed exten- interior design must be changed when returning the sively. As the differences between urban and rural house. areas are considered for the sizes of general housing, the regional differences for Happy Houses must also be 6. Conclusion considered. Moreover, as the residents are more likely to take part in more activities in the house in areas with This study verified that there are differences in poor living infrastructure, and those living in Happy demands for housing improvements depending on Houses have a relatively higher income than those lifestyle clusters among young adults living in public JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 15 rental housing. It also showed that there are demands Ethics approval statement for housing improvements in the Happy Houses which This work was approved by the Research Ethics Committee of are representative public rental housing the young Jeonbuk National University (IRB File No. : JBNU 2022-01-013- households. To resolve the housing issues of young 003). adults, the Korean government has expanded policy support in the policy area. As Happy House is used as a major policy support program to resolve the housing References issues of the young adults, this study is significant in Achdut, N., and T. Refaeli. 2020. “Unemployment and presenting a post-occupancy evaluation happening six Psychological Distress Among Young People During the years after the first residents of Happy Houses moved COVID-19 Pandemic: Psychological Resources and Risk in. 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A study on the lifestyle and preference of 715–730. doi:10.1007/s10901-017-9579-9. single-person households. Master’s thesis, Dong-eui Ministry of Land, Infrastructure, and Transport. 2020. Housing University, Busan. welfare roadmap. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Asian Architecture and Building Engineering Taylor & Francis

Housing satisfaction and improvement demand considering housing lifestyles of young residents in public rental housing

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JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING https://doi.org/10.1080/13467581.2023.2205473 ARCHITECTURAL PLANNING AND DESIGN Housing satisfaction and improvement demand considering housing lifestyles of young residents in public rental housing a a a b Miseon Jang , Tae-Wan Kim , Ji-Yun Kim and Hua Zheng Department of Housing Environmental Design, Jeonbuk National University, Deokjin-gu, Jeonju-si, Jeollabuk-do, Republic of Korea; Department of Environmental Art Design, Shanghai Normal University, Shanghai, The People’s Republic of China ABSTRACT ARTICLE HISTORY Received 1 January 2023 The supply of public rental housing for young households has been on the rise in South Korea. Accepted 17 April 2023 Their size and composition vary depending on residents’ characteristics. However, even within similar groups, housing satisfaction may differ according to their lifestyle; hence, diversity may KEYWORDS exist in the demand for housing improvement. This study identified housing satisfaction and Housing improvement; improvement demands according to housing lifestyles of young residents of “Happy House”, housing satisfaction; housing a representative public rental housing for young households. The method used in this study lifestyle; public rental was an online survey targeting individuals younger than 39 years and living in Happy Houses. housing; young household A total of 536 responses were collected, and the respondents were divided into five housing lifestyle clusters despite being from similar groups. Depending on the lifestyle, differences existed in the satisfaction of space composition and size and basic options, such as facilities/ furniture/home appliances. In addition, there were also differences in the demand for housing improvements. The group actively using housing for leisure, cultural activities, and social exchanges showed high demands for improvement, such as space composition and basic options. This study can be used as a reference for establishing a housing improvement plan for customizable public rental housing, considering the lifestyles of young adults. 1. Introduction Statistics 2021a, 2021b), and the low birth rate problem is more serious than in any other world country. As the global economic downturn continues and labor Accordingly, the Korean government has strengthened market problems become more serious, the youth have policy support for young adults to overcome these become the most vulnerable group in the labor market problems. Among them, in the case of the housing (Tanveer, Marelli, and Signorelli 2012; Junankar 2015). sector, it has accelerated the expansion of housing sup- Young people with a weak economic foundation due to port through the supply of youth housing and loan unstable employment experience the complex problem support (Office for Government Policy Coordination, of high housing costs required to secure housing neces- 2020). A major example of housing policy support for sary for their independence (Berrington and Stone 2014; young adults is the provision of public rental housing. Milić and Zhou 2018). Unlike older generations, which The government expanded the supply of public rental are already securing self-home housing, young people housing with the “Happy House,” which is young adult- who need to secure homes are in a hierarchy that focused public rental housing. The house was first intro- increases the burden of housing costs due to the rise duced in 2015 and has been studied since its launch in in housing prices. These problems not only negatively 2017. These studies have solely focused on Happy affect their quality of life, but they also postpone their Houses in certain regions, identified their spatial char- independence and marriage, leading to lower fertility acteristics, or conducted post-occupancy evaluations, rates and other social issues (Presidential Committee on including housing satisfaction (Shin et al., 2020, Noh Ageing Society and Population Policy, 2020). In particu- and Jin, 2018, Song et al., 2018). Previous studies lar, the coronavirus (COVID-19) pandemic, which revealed that although Happy Houses are public rental occurred at the end of 2019 and created a global pan- homes tailored to young adults, residents’ overall satis- demic, has been recognized as another major cause of faction was slightly above average. Therefore, it is neces- delays in independence, marriage, and childbirth sary to consider young adults’ lifestyles and their among young people (Achdut and Refaeli 2020; Yukich preferences to improve space (Mo et al., 2013, Kwon et al. 2021). In South Korea (henceforth, Korea), the et al., 2016). However, when planning customized number of marriages and the total fertility rate have spaces for Happy Houses, it is essential to consider the been continuously decreasing since 2012 (Korea CONTACT Tae-Wan Kim pooh7669@naver.com Department of Housing Environmental Design, Jeonbuk National University, 567 Baekje-daero, Deokjin-gu, Jeonju-si, Jeollabuk-do 54896, Republic of Korea © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group on behalf of the Architectural Institute of Japan, Architectural Institute of Korea and Architectural Society of China. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent. 2 M. JANG ET AL. characteristics, including the number of household respondents, activities in the dwelling, and changes members and types of households, such as university in living behavior due to COVID-19. Jang et al. (2022) students, those just starting their careers, and newly- identified the qualitative and quantitative levels of weds. Similarly, there may be various housing needs housing characteristics, including the physical state of within the same age group and family lifecycle stages, housing, its costs, and the physical housing environ- which must also be considered. Accordingly, studies ment and analyzed how these affect young adults’ have focused on the post-occupancy evaluation of quality of life by conducting a survey of 280 indepen- Happy House residents concerning their housing satis- dent young households. The results showed that over- faction based on sociodemographic characteristics or all satisfaction with the physical characteristics of the previous housing type (Shin et al., 2020, Noh and housing, physical characteristics of the residential Jin, 2018, Song et al., 2018). However, multiple studies environment, and burden of housing expenses had have expressed the need to consider residents’ lifestyles an effect on the quality of life of young households. to provide customized housing plans for young adults Among them, satisfaction with physical characteristics (Lee and Oh, 2019, Lim et al., 2019). As lifestyle greatly had the greatest influence, and this study shows that affects activities in homes, which will affect housing the consideration of physical characteristics is impor- satisfaction or the need for improvement, it is important tant for improving the quality of life of residents living to identify the improvement needs of houses consider- in young households. In addition, Noh and Jin (2018) ing lifestyle types. Limited studies exist against this conducted a housing satisfaction survey with about backdrop, focusing on housing preferences or satisfac- 1300 residents in public rental housing, including tion levels of young adult households based on lifestyle Happy Houses in Gwangju and the Jeollanam-do types. However, unlike previous studies, this study area, examining the satisfaction levels based on hous- focused on Happy Houses to identify housing satisfac- ing sizes and ownership types, rent and public facil- tion and the need for improvement according to the ities, and commute time. The study found that the lifestyles of young residents. The study participants were difference between the size of the desired house and residents of Happy Houses across Korea. This is unique that of the current house was larger than that of other in suggesting housing improvement measures based on types of rental housing, indicating that the size of the lifestyle types. The study results may be used as basic house was a problem. In addition, when the size of the data to devise spatial improvement measures for Happy house was larger than that of the existing house, hous- Houses as rental housing tailored to young adults, con- ing satisfaction was higher. Therefore, it can be con- sidering the lifestyle of young residents. firmed that the size of the house is an important variable in the satisfaction of residents with Happy Housing. Milić and Zhou (2018) surveyed 350 Serbian youth aged 20–35 years regarding housing satisfac- 2. Literature review tion. The authors found that households with higher 2.1. Trends in previous studies on housing for housing satisfaction had higher satisfaction with hous- young adults ing accessibility, preference for housing characteristics, and attachment to neighbors as well. In other words, The trend of previous studies related to housing housing satisfaction can be improved when housing demands for young adults can be divided into (1) that considers the preferences of young households is studies dealing with housing consciousness and beha- supplied, and this is a study that explains that in addi- vior, such as housing satisfaction, targeting general tion to the characteristics of the housing itself, loca- housing where young adults live; and (2) studies deal- tional characteristics and relationships with neighbors ing with spatial characteristics of youth housing or can affect housing satisfaction. spatial demands of young adults, which are summar- Second, similar to this study, some studies have ized as follows. focused on the spatial characteristics and needs of First, some studies have determined the housing young adult-targeted housing. Lee and Eom (2018) consciousness and other conditions of young adults, examined young adults living alone to identify the including housing satisfaction. Thus, Lee and Jee spatial demands of shared housing. These included (2021) classified the housing consciousness of young their preferences for basic housing installations, addi- households as greatly affected by the COVID-19 pan- tional installation spaces, and shared spaces and facil- demic due to poor housing conditions. They sug- ities. Lim et al. (2019) focused on the design gested changes in housing activities to develop preferences and needs of young adults who live young adult targeted housing programs after the pan- alone. As young adults living alone spend time in demic. To this end, the study conducted an online their bedrooms or living rooms, this must be consid- survey of 600 households, whose residents were 20– ered in housing designs. They also suggested expand- 39 years old. Consequently, the respondents were clas- ing the living room, where young adults participate in sified into four attentional clusters. Across the clusters, various activities, and adding walk-in closets to the there were differences in the characteristics of the JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 3 bedroom and other storage spaces. Shin et al. (2020) commonly used for analysis. AIO is effective identified the spatial characteristics of Happy Houses because it reflects various factors regarding hous- and the need for improvement among residents. ing, including consumption patterns, interests, and Improvements were required to meet the satisfaction values, concerning general aspects of life. levels of the location, surrounding environment, and Housing lifestyle studies have focused on the life- internal space of Happy Houses. The internal space was style of particular groups, including young adults, pre- focused on the area, noise, light, kitchenware, and old age, and those living in apartments (Kwon et al., bathroom facilities. The study suggested improvement 2016, Lee et al., 2007) or housing preferences based on measures based on these findings. Baek and Kim lifestyle. Regarding housing preferences, many studies (2022) surveyed a total of 595 young people have focused on housing type, location, or both as well aged<39 years living in shared housing and analyzed as lifestyle characteristics concerning housing plans. the factors affecting their housing satisfaction. It was Lee and Oh (2019) classified the lifestyles of young found that the physical, emotional, social, and benefi - adults and newlyweds in Korea and identified the cial characteristics of shared housing affected resi- housing sizes, types, and preferred plane structures. dents’ housing satisfaction. This result shows that They classified the housing lifestyles of young adults even in the case of a shared house, not a general into information oriented, uniqueness seeking, future independent house, it needs to be planned consider- oriented, self-development, and practicality oriented, ing its detailed properties. and analyzed housing preferences accordingly. They The literature revealed various types of housing revealed that people with all lifestyle types preferred ownership by young adults, from owning to renting to live in apartments, but the uniqueness-seeking a house, and various housing types, from general to types preferred “officetels” (buildings combining shared. Housing characteristics affect satisfaction offices and hotels). In contrast, the information- and quality of life. However, multifaceted research oriented type preferred detached housing. Future- on housing satisfaction has been affected by char- oriented types preferred large housing, whereas the acteristics such as gender, age, occupation, and life- uniqueness-seeking types did not have clear prefer- style. Several studies have examined housing ences for size. The future-and-practicality-oriented satisfaction among young adults. However, limited types preferred a plane structure with an expanded research has focused on the satisfaction levels and living room, while the information-oriented and needs for the improvement of young adults living in uniqueness-seeking types preferred a plane structure Happy Houses. While housing improvement needs with expanded bedrooms. Lee et al. (2014) classified in the past have been dealt with mainly based on the lifestyles of those in their 20s and 30s and living individual socio-demographic characteristics or eco- alone as students and workers. They studied the differ - nomic characteristics, in this study, even in the case ences in their preferences for shared housing. As the of groups with similar characteristics, there were students preferred a convenient diet, they enjoyed differences in lifestyle, and the corresponding instant food. Furthermore, they had a low demand improvement needs were identified. However, for their own houses and wanted a convenient urban there was a difference. housing environment close to public transportation, with a heavy focus on leisure activities. In contrast, workers spent more money on leisure activities than 2.2. Studies on housing lifestyle did students who were interested in their diet. For instance, they used pretty plates even when eating at Lazer introduced the concept of lifestyle to the home. Moreover, they have little desire to own a house American Marketing Association in 1963, which has and focus more on its internal structure and functional since been actively used. Lazer (1963) defined life- convenience than on its size. Yun (2019) analyzed the style as “a distinctive or characteristic mode of living relationship between lifestyle types and housing pre- in its aggregative and broadest sense, of a whole ferences of one-person households in Busan, Korea. society or segment thereof.” In the field of housing Although the study was conducted in one-person studies, the concept was incorporated from the households, 96% of the participants were in their 1960s to 1970s with studies on selecting housing twenties and thirties; thus, it can be said that this locations in the United States (Thorkild, 2006). study focuses on young adults living alone. The study Lifestyle has become an important factor that classified housing lifestyle types as follows: extroverted affects housing consciousness, including housing unique, passionate challenger, and success-focused preferences, satisfaction levels, and sociodemo- hardworking. Items of housing satisfaction included graphic characteristics (Kwon et al., 2016). There internal area, building facilities, external environment are many ways to analyze lifestyles. In housing stu- and factors, and installations. The findings revealed dies, Activity, Interest, and Opinion (AIO) is 4 M. JANG ET AL. distinctive preferences for all lifestyle types for bath- students. Furthermore, newlyweds were provided in room size and the direction of the windows. The pas- 36㎡ , 44㎡ , and 55㎡ houses, respectively. However, sionate challenger and success-focused hardworking if there are insufficient applicants, young adults living types showed high preferences for proximity to med- alone can also enroll in houses that are 36㎡ years old ium- or larger-sized hospitals, and the passionate chal- and larger. According to Ha and Kim (2020), the sizes of lenger type showed preferences for induction Happy Houses were 14㎡ , 26㎡ , 36㎡ , and 43㎡ for cooktops within the home. one-, two-, three-, and four-person households, respec- Although multiple studies exist on lifestyle and tively. However, the average house sizes were 31㎡ focusing on young adults, there are various ways to and 66.5㎡ for young adults living alone and newly- classify lifestyles depending on the purpose of the weds, respectively, which is 1.5 to 1.8 times larger than study. Furthermore, there are differences in housing the minimum level set by the government (Kim, 2019). preferences according to lifestyle types. Unlike pre- In terms of the actual composition of their sizes, the 16 vious studies, this study focused on the lifestyles of ㎡ houses are generally studio-type houses with sepa- young adults living in Happy Houses to emphasize the rate entrances, kitchens, dining and living rooms, bed- need to consider lifestyles when devising improve- rooms, bathrooms, and balconies. Some houses ment plans for Happy Houses. Furthermore, we com- provide a sliding door between the living room and prehensively investigated the relationship between kitchen to create a makeshift bedroom. Some 26㎡ lifestyle, need for improvement, and satisfaction levels houses are studio-type houses, such as 16㎡ houses, with current housing. and there are also one-bedroom houses that separate the bedroom from the living room. Of the 36㎡ houses, there was a bedroom, and they had larger kitchens or 2.3. Spatial characteristics of happy houses dining rooms than those of the 26㎡ houses. There were two bedrooms in 44㎡ houses with a living, din- Representative types of constructed-type public rental ing, and kitchen structure, with a separate living room housing supplied in Korea include permanent rental connected to the kitchen or dining room. Moreover, houses, national rental houses, and happy houses. the exact composition of houses may vary within the Permanent rental houses, which have the longest his- same size depending on the location. A study revealed tory, are mainly supplied to beneficiaries, can be lived that houses sized 36㎡ and larger might have up to six in for up to 50 years, and are supplied at a very low cost plane structures with different locations and room of 30% of the market price (Korea Land and Housing sizes, apart from the kitchen and bathroom (Ha and Corporation, 2022a). In contrast, the national rental Kim, 2021). houses are targeted to the second-level class, which There are also differences in the basic options pro- has more income than that, can be residents for up to vided, depending on the size of the house supplied. 30 years, and can be occupied at 60%–80%of the mar- Happy Houses have shoe storage, kitchenware, and ket price. The size of national rental houses is 60 m2, shower facilities at the entrance. However, furniture which is larger than that of permanent rental houses and appliances, including desks, bookshelves, and (40㎡ ). Unlike other rental types, Happy Houses show refrigerators, are only provided in small houses (less a difference in the increase in income standards and than 26㎡ ) for university students and young adults are mainly supplied for certain classes such as college living alone. However, some have gas cooktops in students, newlyweds, and young people. houses sized 36㎡ or larger; hence, the options pro- Consequently, happy houses are built and supplied vided may vary. near workplaces, schools, and public transportation. There are no distinct characteristics in the interior The criteria for net leasable area and rental costs are designs of Happy Houses. Generally, all houses use similar to those of the national rental houses, but the light brown vinyl linoleum for flooring and white silk actual housing size is smaller than the national rental wallpaper. houses. As of 2020, there are 89,000 Happy Houses in Korea and 9.1% of all long-term public rental housing. Furthermore, 31000 Happy Houses were provided, exceeding 61.6% of the year’s housing supply, con- 3. Materials and methods suming a large share of housing (Ministry of Land, 3.1. Developing the survey questionnaire Infrastructure, and Transport, 2020). The Happy Houses varied in size from 14㎡ to 55㎡ . This study categorized the housing lifestyle of The major types of sizes are 16㎡ , 26㎡ , 36㎡ , and 44 young adults and newlywed couples living in public ㎡ , which have been sustainably supplied on a similar rental housing and identified differences in housing scale since it is provided (Ha and Kim, 2020) (Figure 1). satisfaction and demands for improvement. First, The 16㎡ and 26㎡ houses are generally provided to a housing lifestyle research tool was developed young adults living alone, including those beginning using the “AIO Analysis” theory based on the hous- their careers, seeking employment, and university ing studied (Kwon et al., 2016, Lee et al., 2007, JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 5 Table 1. References for developing the housing lifestyle items. Lee Kwon Moon Kim and et al. et al. et al. Jang Classification Item (2007) (2016) (2019) (2021) Activity 1 I frequently study or work at home. ● ● ● ● 2 I frequently watch movies or listen to music at home. ● ● ● ● 3 I frequently enjoy leisure activities, including exercise or creative activities at home. ● ● ● ● 4 I frequently invite family members or guests home. ● ● 5 I generally cook my meals at home. ● ● ● 6 I generally have takeout or deliveries to eat at home. ● ● ● 7 I frequently take baths in the tub. ● ● 8 I generally shop online. ● ● Interest and 1 I want a house that is easy to keep clean. ● ● ● Opinion 2 I want a house where I can rest comfortably. ● 3 For me, a house is just a place to sleep. ● ● 4 I want to live in a beautiful house. ● ● ● 5 I want a house where I can spend time with my family and friends. ● ● ● 6 My opinion is the most important when making decisions related to the house. ● 7 I want a house where I can decorate and place furniture as I wish. ● ● ● ● 8 My house should have the latest technology. ● ● ● 9 I want a house where I will not be distracted by neighbors. ● ● 10 I consider long-term plans (marriage, childbirth, etc.) as well as the present ● ● ● conditions for my house. 11 I want a house with good security conditions where I can feel safe. ● ● ● 12 I want a house where it is easy to engage with neighbors. ● ● ● 13 I am interested in keeping the internal environment clean. ● ● ● 14 I want a house where I can live with an animal. ● ● 15 I want a house where I can grow plants. ● Moon and Lee, 2019). Another relevant study of Kim additional detailed items were developed. The and Jang (2021) was referred to reflect the charac- final version of the survey used the sociodemo- teristics of the housing lifestyle of young adults and graphic, economic, and physical characteristics of newlyweds. However, there were many items initi- the current house (Table 2). ally, which were later revised and omitted based on the study objectives. The developed survey items 3.2. Research participants and methods comprised 23 items, with eight items on daily life activities in the housing setting and 15 items on The survey participants comprised young adults and the level of interest and thoughts regarding the newlyweds residing in public rental housing called housing setting. Each item was measured using Happy Houses. Although older adults and general low- a five-point Likert scale, ranging from 1 (highly income households also reside in Happy Houses, the disagree) to 5 (highly agree) (Table 1). participants were limited to young adults aged 19–39 Also, some previous studies were reviewed to and newlyweds who have been married for no longer identify the differences in housing satisfaction and than 10 years. A pre-survey of 20 people from the demands for improvements. Based on the literature public with similar characteristics as the young adults (Lim et al., 2019, Lee and Oh, 2019), the actual and newlyweds living in Happy Houses and those composition of the house, its usable area, its basic majoring in housing was conducted. In the pre- options (appliances, furniture, equipment), and survey, participants had to fill out the house area interior design were selected to develop the survey exclusively in either pyeong (1 pyeong = 3.3 m ) items. The housing satisfaction level and demands or m . The results revealed that participants did not for improvement were used as survey items. Each answer using the unit or made mistakes by getting the item was based on a five-point Likert scale. unit confused with the area size unit. Therefore, to Furthermore, to identify the demands in detail, ensure consistent data collection on house size, the Table 2. Composition of the questionnaire. General Characteristics Sociodemographic Age of the Householder/Sex of the Householder/Occupation of the Householder/Number of People (6) Characteristics (5) in the Household/Household Type Economic Characteristics (1) Average monthly income Characteristics of the House (4) Region/Size/Number of Rooms/Number of Bathrooms/Length of Residence Housing Satisfaction * (5) Room Composition (Type and number)/Usable area per room/Basic options/Interior design/General satisfaction Demands for Improvements in Housing Room Composition (Type and number)/Usable area per room/Basic options/Interior design/General Environment * (5) demands/Detailed demands *Based on a 5-point Likert scale (1 (Highly disagree) − 5 (Highly agree)) 6 M. JANG ET AL. survey was edited so that the participants respond householders was from the general economic activ- in m . Also, the logical errors of optional items depend- ity sector, including office workers, entrepreneurs, ing on the characteristics of the participants and slight and self-employed, at 87.3%. There were 4.7% stu- changes to the wording were made to complete the dents and 8.0% unemployed participants. The aver- tool. Based on the developed tool and the research age number of people in the household was 1.45, plan, the survey was conducted after attaining as more than half (61.2%) were one-person house- approval from the research ethics committee of the holds. About 33.4% of the participants responded affiliated institution (anonymized for the review). that they were a two-people household, among An online survey was used for this study. With the which 77.1% were couples with no children, 11.2% cooperation of the supply organization of Happy were brothers and sisters, 9.5% were friends, and House, information on the questionnaire was attached 2.2% were others. Three-people households com- to the apartment complex. As there may be regional prised 4.9% of the participants and were generally differences in housing satisfaction and the demand for couples with children. The average monthly income improvement, the number of complexes asked to par- was considered to understand the participants’ eco- ticipate was selected by the number of households in nomic characteristics. The income was analyzed a complex. This ensured similar numbers of partici- using the income standards by the household pants from Greater Seoul and other regions. In addi- members based on the 100% level of the average tion, most of the chosen Happy House complexes were monthly income of urban households in 2021. On built after 2018, ensuring the deterioration of the average, the participants had a monthly income of houses was similar. After collecting a certain number KRW 3.1625 million. More than half (53.7%) of responses from the complexes to match the number responded that their monthly income was KRW of participants by region, more data were collected 2.99 million or under. Even though more than half from online communities of those living in Happy of the participants were one-person households, Houses and those who wish to live in Happy Houses. there were relatively more households with A total of 753 responses were collected, and 536 were a lower income than the average monthly income analyzed after eliminating invalid responses or those of one-person households. Participants had who did not fall under the inclusion criteria. Of the a monthly income of over KRW 2.99 million to valid responses, 92.6% were from the apartment com- KRW 4.56 million or less (27.4%), the standard for plexes, and the response rate of the distributed surveys two-people households. Considering two-people was approximately 4.4%. households took up 33.4% of the participants, this The collected data were analyzed using the SPSS shows that the participants generally had lower 22.0 statistics program. Descriptive statistics were used than average income. Lastly, 16.6% of the partici- to analyze the participants’ general characteristics and pants had a monthly income of more than KRW those of the current houses. Housing lifestyle types 4.56 million (Table 3). were analyzed using factor and cluster analyses. Lastly, the chi-square test and analysis of variance 4.2. Characteristics of the participants’ current were used to analyze differences in housing satisfac- houses tion and demands for improvement in housing envir- onments per the housing lifestyle types. The analysis of the characteristics of the Happy House, where the participants resided, revealed that 59.3% of the houses were in the Greater Seoul 4. Results region (Seoul, Gyeonggi-do, Incheon). The percen- The analysis results were organized according to the tages of responses from those living in metropolitan participants’ general characteristics, characteristics of cities, Sejong, and other regions were equal at the current houses, housing lifestyle types, housing 20.3%. The average house size was 33.02 m . The satisfaction, and demands for improvement by lifestyle house was divided into sections using the size stan- types. dard by the number of people per the minimum standards in housing to analyze the housing size. Hence, the most common size was houses that 4.1. Participants’ general characteristics were 36 m and over, suitable for households with The general characteristics of the participants were three or more people, with 59.7%, followed by analyzed for the householder. First, 57.8% of the houses that were 26 to under 36 m with 21.5%. householders were women, 15.6% higher than The average number of bedrooms was 1.94. The men. The average age of the householder was proportions of responses from those living in 30.19 years, and 51.3% of the householders were a studio-type apartment and a two-bedroom apart- 30 and older, which was more than those younger ment were similar at 35%, and 29.3% of participants than 30. The most common occupation among the lived in three-bedroom apartments. Most JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 7 Table 3. General characteristics of the participants. (N=536) Classification f(%)/M(SD) Sociodemographic Characteristics Householder Sex Male 226 (42.2) Female 310 (57.8) Age Younger than 30 261 (48.7) 30 or over 275 (51.3) Average (age) 30.19 (4.77) Education Level High school graduate 66 (12.3) 2-year or 4-year university graduate 411 (76.7) Master’s or Ph.D. 59 (11.0) Occupation Office worker/Entrepreneur/Self-employed 468 (87.3) Student 25 (4.7) Unemployed 43 (8.0) Number of people in the household 1 328 (61.2) 2 179 (33.4) 3 or more 29 (5.4) Average (people) 1.45 (0.61) Household Type 1-person household 328 (61.2) Couple with no children 138 (25.7) Couple with children 26 (4.9) Other 44 (8.2) a b Economic Characteristics Average Monthly Income − 299 (1-person household) 288 (53.7) (KRW 10,000) 299–456 (2-people household) 147 (27.4) 456- (3±people household) 89 (16.6) Average (KRW 10,000) 316.25(160.37) Only valid responses were analyzed. Classified according to the average monthly income levels of workers in the city in 2021 participants (98.5%) responded having one bath- the responses. Eight items on daily life activities room. Lastly, the participants had resided in their showed an average of a minimum of 1.50 to houses for an average of 11.74 months. More than a maximum of 4.28 out of five. The item with the half of the participants (58.5%) responded that they highest average among the eight items was “I had resided in the current house for less than a year, generally shop online” (4.28), followed by “I fre- and 35.9% were reportedly residing for more than quently watch movies or listen to music at home” a year but less than two years (Table 4). (4.12). Only these two factors had an average of over four. The responses to 14 items on interests and opinions generally had higher averages than 4.3. Housing lifestyle types of the participants the items related to daily life activities. The item and the characteristics of each type with the highest average was “I want a house where I can rest comfortably”(4.89), which was 4.3.1. Housing lifestyle factors of the participants close to five, and 11 items, including “I want There was an analysis on the results of the AIO a house where I will not be distracted by neigh- items on housing lifestyle. First, the averages and bors,” had an average of over four. Second, the bias were analyzed to verify the normality of Table 4. Characteristics of the current houses of the participants. (N=536) Classification f(%)/M(SD) Housing-related Characteristics Region Greater Seoul region 318 (59.3) Metropolitan cities/Sejong 109 (20.3) Other regions 109 (20.3) Size Smaller than 26 (1-person household) 92 (17.2) 2 a (m ) 26 – less than 36 (2-people household) 115 (21.5) 36 or larger (3±people household) 320 (59.7) Average 33.02 (9.48) Number of Rooms 1 (Studio-type) 188 (35.7) 2 184 (35.0) 3 154 (29.3) Average 1.94 (0.82) Number of Bathrooms 1 528 (98.5) 2 8 (1.5) Length of Residence 1 year or less 304 (58.5) More than 1 year, less than 2 years 190 (36.5) More than 2 years 26 (5.0) Average 11.74 (7.83) a Only valid responses were analyzed. 8 M. JANG ET AL. Table 5. Analysis of housing lifestyle. (N=536) Classification Lifestyle Items Average* STD Activity 1 I frequently study or work at home. 2.87 1.34 2 I frequently watch movies or listen to music at home. 4.12 1.01 3 I frequently enjoy leisure activities, including exercise or creative activities at home. 2.80 1.32 4 I frequently invite family members or guests home. 2.68 1.28 5 I generally cook my meals at home. 3.50 1.18 6 I generally have takeout or deliveries to eat at home. 3.11 1.17 7 I frequently take baths in the tub. 1.50 1.08 8 I generally shop online. 4.28 0.94 Interest and Opinion 1 I want a house that is easy to keep clean. 4.81 0.47 2 I want a house where I can rest comfortably. 4.89 0.37 3 For me, a house is just a place to sleep. 4.00 1.10 4 I want to live in a beautiful house. 4.47 0.84 5 I want a house where I can spend time with my family and friends. 4.21 1.02 6 My opinion is the most important when making decisions related to the house. 4.30 0.98 7 I want a house where I can decorate and place furniture as I wish. 4.57 0.74 8 My house should have the latest technology. 3.96 1.11 9 I want a house where I will not be distracted by neighbors. 4.86 0.49 10 I consider long-term plans (marriage, childbirth, etc.) as well as the present conditions for my house. 4.30 1.08 11 I want a house with good security conditions where I can feel safe. 4.81 0.54 12 I want a house where it is easy to engage with neighbors. 2.64 1.20 13 I am interested in keeping the internal environment clean. 4.71 0.59 14 I want a house where I can live with an animal. 3.23 1.57 15 I want a house where I can grow plants. 3.78 1.30 ※ Shaded items are deleted items as a certain response had a concentration level that exceeds 70%. descriptive statistics was used to select only the sleeping. This factor’s reliability (Cronbach’s α) was items with a certain level of normality. Hence, five 0.665. Factor 2 comprised three items and had an items, including “I frequently take baths in the explanation power of 13.369% for all variables. Factor tub,” which had the lowest score among the daily 2 was named “Engagement Activities” as it included life activities items, “I want a house that is easy to engagement with neighbors and family members and keep clean,” and “I want a house where I can rest expanding the family in the long term (Cronbach’s α = comfortably” from the interest and opinion items 0.554). Factor 3 comprised three items. It was named were removed as the concentration level of “Home Styling” as it related to a lifestyle that prefers a certain response exceeded 70% (Table 5). aesthetic houses and wishes to decide the interior Third, there was a factor analysis using the 17 hous- design of the houses. Factor 3 had an explanation ing lifestyle items that passed the normality standard. power of 12.606% and a reliability of 0.588. Factor 4 Principal Components Analysis and Varimax were used comprised four items. It included a lifestyle that prior- for the analysis. After the analysis, four items, including itized watching movies, listening to music, exercising “I frequently study or work at home,” “I generally shop or participating in other leisure activities, and joining online,” and “My house should have the latest technol- parties. Accordingly, this factor was named “Leisure ogy,” were removed as the commonality for these here Activity,” and its explanation power was 10.952% items was less than 0.4. Another factor analysis was (Cronbach’s α = 0.463). Lastly, factor 5 comprised two conducted afterward with 14 items. Hence, housing items, with an explanation power of 10.087% lifestyle factors were classified into five factors. The (Cronbach’s α = 0.458). This factor included a lifestyle total cumulative variance of the factors was 60.726, that emphasized a life with animals or plants, and so resulting in an explanation power exceeding 60%. was named “Living with Companions” (Table 6). The KMO (Kaiser-Meyer-Olkin) value of the selected factor solution was 0.653, showing an appropriate 4.3.2. Housing lifestyle cluster of the participants sample fit. The significance level of the chi-square Based on the results of the factor analysis, there was test from Bartlett’s test of sphericity test was less than a cluster analysis using the standardized scores of each 0.001, verifying the statistical appropriateness. factor. After the hierarchical cluster analysis, three to Furthermore, as the commonality was at a minimum six cluster solutions were identified based on of 0.497 to a maximum of 0.741, the relative contribu- a dendrogram. Then, using K-means cluster analysis, tion level of individual factors was also high. the characteristics of each cluster solution were ana- Regarding the five factors, Factor 1 comprised three lyzed. The results revealed that five cluster solutions items. It had an explanation power of 13.712% for all would be most appropriate for this study’s purpose variables. Factor 1 was named “Basic Living” as it and have appropriately distributed housing lifestyle included basic lifestyle factors, including eating or factors in each cluster. Hence, these five clusters were JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 9 Table 6. Analysis of housing lifestyle factors. Factors Basic Engagement Home Leisure Living with Lifestyle Items Commonality Living Activities Styling Activity Companions I generally have takeout or deliveries to eat at home. 0.741 0.856 −0.011 −0.030 −0.060 0.059 I generally cook my meals at home. 0.711 0.796 0.089 −0.117 0.191 0.140 For me, a house is just a place to sleep. 0.516 0.591 0.018 0.334 0.116 −0.205 I want a house where I can spend time with my family and friends. 0.690 −0.002 0.762 0.261 0.200 −0.035 I consider long-term plans (marriage, childbirth, etc.) as well as the 0.497 0.098 0.683 0.097 −0.095 −0.058 present conditions for my house. I want a house where it is easy to engage with neighbors. 0.533 −0.068 0.599 −0.183 0.021 0.370 I want a house where I can decorate and place furniture as I wish. 0.670 0.060 0.215 0.775 −0.002 0.141 My opinion is the most important when making decisions related to 0.640 −0.116 −0.158 0.729 0.240 0.112 the house. I want to live in a beautiful house. 0.552 0.125 0.440 0.581 −0.017 −0.077 I frequently watch movies or listen to music at home. 0.529 0.096 −0.060 0.139 0.704 −0.029 I frequently invite family members or guests home. 0.643 −0.126 0.371 −0.084 0.693 −0.047 I frequently enjoy leisure activities, including exercise or creative 0.545 0.255 −0.106 0.126 0.622 0.257 activities at home. I want a house where I can live with an animal. 0.618 −0.116 −0.017 0.086 0.096 0.767 I want a house where I can grow plants. 0.615 0.232 0.202 0.093 −0.018 0.715 Eigen Value 1.920 1.872 1.765 1.533 1.412 Common Variance 13.712 13.369 12.606 10.952 10.087 Cumulative Variance 13.712 27.081 39.687 50.639 60.726 KMO=0.653/BARTLETT=1,257.916*** ***P<0.001. confirmed as the final clusters. Afterward, there was an households accepted the conditions of the house F test on the standardized scores of the factors of each that was handed over to them and engaged in mini- cluster. It revealed statistical significance among the mal housing activities. This cluster was named five clusters and the five factors (p < 0.001). “Minimally Using” (Table 7). The characteristics of the five clusters were as follows. Cluster 1 comprised the households that 4.4. Characteristics by housing lifestyle clusters actively used all parts of the house to participate in engagement and leisure activities, apart from the 4.4.1. General characteristics by housing lifestyle basic housing activities. This cluster was named clusters “Actively Using.” Cluster 2 had more interest in the The differences in general characteristics by housing house itself and decorated it by their tastes rather lifestyle clusters were analyzed. The results revealed than being interested in particular housing activities. that besides the ages and educational levels of the This cluster was named “Self-Expression.” Cluster 3 householders, all characteristics showed statistically was also interested in decorating their houses like significant differences by clusters. That is, there were Cluster 2 but was focused on basic housing activities, similar characteristics across all clusters, as many parti- such as eating and sleeping. They wished for a stable cipants were younger than 30 and had graduated from personal life by engaging with animals or plants. This two- or four-year universities. The differences in the cluster was named “Personal Activity.” Cluster 4’s life- major characteristics by cluster are as follows. style prioritized engagement with others, including First, many householders in the “Actively Using” friends or family, or plants or animals, over their lives. cluster participated in economic activities, and this This cluster was named “Engagement-Focused.” cluster had more households with two or more people Lastly, Cluster 5 had relatively less interest in all five or couples than other clusters. Many households in this factors, particularly decorating their houses. These cluster had relatively high monthly incomes that fell Table 7. Analysis of standardized scores of each factor by clusters. Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 (n=126) (n=106) (n=108) (n=109) (n=87) Actively Using Self-Expression Personal Activity Engagement-Focused Minimally Using Classification Cluster Cluster Cluster Cluster Cluster F Basic Living 0.49957 −0.73285 0.79460 −0.39782 −0.31860 68.813*** Engagement 0.72016 0.00928 −1.01366 0.61360 −0.56472 112.245*** Activities Home Styling 0.03258 0.52396 0.53817 0.20796 −1.61432 159.474*** Leisure Activity 0.74520 0.03406 −0.06533 −0.79292 −0.04623 46.720*** Living with 0.05975 −1.06921 0.76360 0.76360 −0.03617 73.964*** Companions ***p<0.001. 10 M. JANG ET AL. under the appropriate amount of household income households, who were not likely to participate in eco- with three or more people. That is, the households had nomic activities. They were relatively more economic- more than two people and high income. Hence, their ally vulnerable than other clusters. Therefore, their lifestyle focused on family and other leisure activities. lifestyle included basic activities, such as eating and The “Self-Expression” cluster had relatively more sleeping, which did not cost much, or living with ani- women student householders than other clusters and mals or plants. Households in the “Engagement- the highest proportion of one-person households. Focused” cluster had more householders where the Their incomes matched with one-person households. men participated in economic activities than other That is, as women living alone are the major type of clusters. These households comprised married couples household in this cluster, they focused on using the with two or more people in the household. There were house to self-express rather than for leisure activities or households that fell under the income bracket for two- engaging with others. The “Personal Activity” cluster people households, and relatively more households had the largest portion of women householders than fell under the three-people household income bracket. any other cluster and many unemployed house- That is, the households in this cluster had a certain holders. It had the second-most one-person house- income level and enjoyed married life. Although they holds, followed by the “Self-Expression” cluster, with prioritized family bonding time, they were relatively some two-people households. The income of this clus- less interested in leisure activities like the “Actively ter fell more in the one-person household category Using” cluster. Lastly, the “Minimally Using” cluster than the “Self-Expression” cluster and had relatively had the greatest number of households with a man few households with high income. That is, this cluster householder who participated in economic activities. mostly comprised women in one- or two-people This cluster mostly comprised one-person households Table 8. General characteristics by housing lifestyle cluster. Housing Lifestyle Cluster Engagement- Minimally Actively Using Self-Expression Personal Activity Focused Cluster Using Cluster Classification Cluster (126) Cluster (106) Cluster (108) (109) (87) χ Householder’s Sex Male 57 35 34 51 49 17.285** (45.2) (33.0) (31.5) (46.8) (56.3) Female 69 71 74 58 38 (54.8) (67.0) (68.5) (53.2) (43.7) n.s. Householder’s Age Younger than 30 66 50 51 52 42 0.926 (52.4) (47.2) (47.2) (47.7) (48.3) 30 or over 60 56 57 57 45 (47.6) (52.8) (52.8) (52.3) (51.7) n.s. Householder’s High school graduate 13 18 13 11 11 6.642 Education Level (10.3) (17.0) (12.0) (10.1) (12.6) 2-year or 4-year 98 76 80 86 71 university graduate (77.8) (71.7) (74.1) (78.9) (81.6) Master’s or Ph.D. 15 12 15 12 5 (11.9) (11.3) (13.9) (11.0) (5.7) Householder’s Office worker/ 109 91 87 99 82 16.905* Occupation Entrepreneur/Self- (86.5) (85.8) (80.6) (90.8) (94.3) employed Student 8 8 7 0 2 (6.3) (7.5) (6.5) (0.0) (2.3) Unemployed 9 7 14 10 3 (7.1) (6.6) (13.0) (9.2) (3.4) No. of Family 1 67 77 76 58 50 21.718* members (53.2) (72.6) (70.4) (53.2) (57.5) 2 47 26 31 43 32 (37.3) (24.5) (28.7) (39.4) (36.8) 3 or more 12 3 1 8 5 (9.5) (2.8) (0.9) (7.3) (5.7) Household Type 1-person household 67 77 76 58 50 30.900** (53.2) (72.6) (70.4) (53.2) (57.5) Couple with no children 38 19 19 34 28 (30.2) (17.9) (17.6) (31.2) (32.2) Couple with children 12 3 0 7 4 (9.5) (2.8) (0.0) (6.4) (4.6) Other 9 7 13 10 5 (7.1) (6.6) (12.0) (9.2) (5.7) Average Monthly − 299 (1-person 59 62 71 52 44 20.201* Income household) (48.4) (59.0) (68.9) (48.6) (50.6) (KRW 10,000) 299–456 (2-people 34 29 26 34 24 household) (27.9) (27.6) (25.2) (31.8) (27.6) 456- (3±people 29 14 6 21 19 household) (23.8) (13.3) (5.8) (19.6) (21.8) *p<0.05, **p<0.01, n.s. not significant. JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 11 or households with married couples without children. replied they lived in a three-bedroom house. Among Accordingly, many households in this cluster all clusters, this cluster had the smallest proportion of responded that their incomes fell under the one- households living in studio apartments. As seen from person to two-people household income brackets. the sociodemographic characteristics, many house- That is, this cluster can be defined as a one-person holds in the “Actively Using” cluster are married couples household engaged in economic activities or newly- with two or more people in the household. The most wed couples with relatively less interest in houses and common place of residence for the “Self-Expression” participation in minimal housing activities (Table 8). cluster was metropolitan cities and Sejong. They a Only valid responses were analyzed resided in houses with a size of less than 26 m . Therefore, the most common house type was a studio. This may be because there were relatively 4.4.2. Characteristics of the current houses by more students in the “Self-Expression” cluster than in housing lifestyle cluster other clusters with more one-person households. There was an analysis to identify the differences in the Among all clusters, the “Personal Activity” cluster had characteristics of the current houses by housing life- the highest proportion of households living in the style cluster. The results revealed that apart from the Greater Seoul region. Although many households number of bathrooms and the length of residence, all resided in houses that were 36 m or larger, compared characteristics showed statistically significant differ - with other clusters, there was a higher proportion of ences by lifestyle cluster. In all clusters, the most com- households living in houses that were 26 m or smaller. mon number of bathrooms was one, and the most This cluster also had many one-person households, common length of duration was 1 year or less. The with a high proportion of students or the unemployed, differences in the major characteristics by cluster are who did not engage in economic activities. This may as follows. have led to a greater proportion of households living in First, for the “Actively Using” cluster, there were the smallest houses than in other clusters. A large relatively more households in the Greater Seoul region, proportion of the“Engagement-Focused” cluster lived and the cluster had the least proportion of households in the Greater Seoul region. Although there were slight living in the province areas. The cluster had the most differences, the regional distribution of this cluster was proportion of houses that were 36㎡ or more and had like that of the “Actively Using” cluster. A large propor- the relatively less proportion of households living in tion of households in the “Engagement-Focused” clus- houses that were 26 m . As they lived in relatively ter lived in houses with a size of 36 m or more and two larger houses, the greatest number of households Table 9. Characteristics of the current houses by housing lifestyle cluster. Housing Lifestyle Cluster Minimally Actively Using Self-Expression Personal Activity Engagement-Focused Using Cluster Classification Cluster (126) Cluster (106) Cluster (108) Cluster (109) (87) χ Region Greater Seoul region 80 49 69 67 53 17.856* (63.5) (46.2) (63.9) (61.5) (60.9) Metropolitan cities/ 24 35 19 20 11 Sejong (19.0) (33.0) (17.6) (18.3) (12.6) Other regions 22 22 20 22 23 (17.5) (20.8) (18.5) (20.2) (26.4) Size Smaller than 26 12 24 28 17 11 19.010* 2 a (m ) (1-person household) (9.5) (24.0) (25.9) (15.9) (12.8) 26 – less than 36 28 26 23 20 18 (2-people household) (22.2) (26.0) (21.3) (18.7) (20.9) 36 or larger (3±people 86 50 57 70 57 household) (68.3) (50.0) (52.8) (65.4) (66.3) Number of 1 35 48 46 34 25 20.194* Rooms (Studio-type) (28.0) (45.3) (43.4) (33.0) (29.1) 2 41 36 28 43 36 (32.8) (34.0) (26.4) (41.7) (41.9) 3 49 22 32 26 25 (39.2) (20.8) (30.2) (25.2) (29.1) n. Number of 1 126 106 106 105 85 7.509 s. Bathrooms (100.0) (100.0) (98.1) (96.3) (97.7) 2 0 0 2 4 2 (0.0) (0.0) (1.9) (3.7) (2.3) n. Length of 1 year or less 66 61 70 59 48 6.107 a s. Residence (53.7) (59.8) (66.7) (55.7) (57.1) More than 1 year, less 51 37 31 39 32 than 2 years (41.5) (36.3) (29.5) (36.8) (38.1) More than 2 years 6 4 4 8 4 (4.9) (3.9) (3.8) (7.5) (4.8) *p<0.05, n.s. not significant. Only valid responses were analyzed. 12 M. JANG ET AL. rooms. As there were many households with two or Using” clusters. After analyzing the satisfaction levels more people like the “Actively Using” cluster, many in the sizes in detail, 40% or more of the two clusters of households lived in larger houses. Lastly, although “Self-Expression” and “Engagement-Focused” clusters a large proportion of households in the “Minimally with relatively lower satisfaction levels responded Using” cluster lived in the Greater Seoul area, there that they were not satisfied with the sizes of the was also a large proportion of those living in the houses. There are relatively more households in the province area than in other clusters. Many households “Self-Expression” cluster living in the provinces. Even in this cluster lived in houses sized 36 m or more. This though many households in this cluster were one- cluster had the highest proportion of houses with two person households living in a house of 36㎡ or larger, or more rooms (Table 9). due to the differences in the subjective housing norms in the area in size, they might find their houses small. As the “Engagement-Focused” cluster had more people 4.4.3. Housing satisfaction by housing lifestyle in the households than the “Self-Expression” cluster and cluster more married households, they showed relatively There was an F test to identify the differences in the greater dissatisfaction regarding housing sizes. satisfaction levels in the current houses by housing Regarding the differences in the satisfaction levels in lifestyle clusters. The results revealed statistically sig- the basic provided equipment, appliances, and furni- nificant differences in satisfaction with the space com- ture, there were differences between the “Minimally position of the house, house size, and basic provided Using” cluster and the other three clusters. The satisfac- equipment, furniture, and appliances by cluster. That tion level of the “Minimally Using” cluster was 3.09, is, no difference existed in the overall satisfaction and relatively higher than other clusters. Approximately the interior design by cluster. To analyze the differ - 80% of householders in this cluster responded that ences in the clusters with differences in the satisfaction they felt neutral, satisfied, or greatly satisfied with the level, there was a Duncan post hoc test. “Personal equipment, furniture, or appliances. As the “Minimally Activity” and “Engagement-Focused” clusters showed Using” cluster participated in minimal housing activ- differences in the satisfaction levels in the space com- ities within the house, they were relatively more satis- position. The “Personal Activity” cluster showed an fied with the equipment, furniture, or appliances for average satisfaction level of 3.61 for the space compo- the housing activities. However, their highest satisfac- sition, higher than the “Engagement-Focused” cluster. tion level was just above three, a near neutral, which This may be because the “Personal Activity” cluster had meant that the other clusters were dissatisfied regard- a high proportion of one-person households, but many ing the equipment, appliances, and furniture houses were 36㎡ or more in size with three rooms. (Table 10). Approximately half of this cluster lived in such two- bedroom houses, leading to high satisfaction levels with relatively more space. Although there were 4.4.4. Demands for improvement in housing many one-person households in the “Engagement- environments by housing lifestyle cluster Focused” cluster, there were relatively more house- There was an analysis on the demands for improve- holds with married couples. This may have led to low ment in housing environments by housing lifestyle satisfaction levels in the space composition. The satis- cluster. The results revealed significant differences by faction levels in the housing sizes differed between the cluster. First, statistically significant differences existed “Self-Expression” and “Engagement-Focused” clusters, in the general demands for improvement from the together as a group, and the “Personal Activity” and “Minimally Using” and “Actively Using” clusters as “Minimally Using” clusters, put together as a group. a group, compared with the “Self-Expression” and That is, the “Self-Expression” and “Engagement-Focused “Engagement-Focused” clusters as a group. The ” clusters had an average satisfaction level of 2.81, “Minimally Using” cluster had an average demand lower than the “Personal Activity” and “Minimally level of 3.13 for all types of improvements, relatively Table 10. Differences in satisfaction in the current houses by housing lifestyle. Housing Lifestyle Cluster Engagement- Minimally Actively Using Self-Expression Personal Activity Focused Cluster Using Cluster Classification Cluster (126) Cluster (106) Cluster (108) (109) (87) F n.s. Overall Satisfaction with Housing 3.54b 3.43ab 3.62b 3.27a 3.52ab 2.291 Satisfaction with Housing Composition (no. of 3.39bc 3.15ab 3.61c 3.02a 3.37bc 5.616*** rooms, layout, etc.) Satisfaction with Housing Size 2.99ab 2.81a 3.26b 2.81a 3.24b 3.557** Satisfaction on Housing Basic built-in 2.62a 2.63a 2.94ab 2.70a 3.09b 3.573** equipment, furniture, and home appliances n.s. Satisfaction with Housing Interior Design 3.17a 3.39a 3.43a 3.14a 3.31a 1.733 **p<0.01, ***p<0.001, n.s. not significant. JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 13 lower than other clusters. The satisfaction levels of the machines. In the bedroom, the two groups did not “Minimally Using” cluster in the equipment, appliances, differ in their demands for wardrobes and desks. and furniture were relatively higher than those of the However, in the bathroom, the “Actively Using” cluster other clusters, as the cluster did not use the house as had a very high demand for bathtubs, whereas the much as the other clusters. Hence, the cluster had “Personal Activity” cluster responded with no additional relatively fewer demands for the improvement of the needs. Lastly, a significant difference existed in the housing environment than other clusters. “Actively demand levels of interior design between the “Self- Using” and “Engagement-Focused” clusters had greater Expression” and “Minimally Using” clusters as a group demands for improvement in the space composition of and the “Actively Using” and “Personal Activity” clusters the houses than the “Self-Expression” and “Minimally as a group. The Self-Expression” and “Minimally Using” Using” clusters. The “Personal Activity” and clusters had relatively lower demand for improve- “Engagement-Focused” clusters showed differences in ments in interior design than other clusters. For the housing satisfaction levels, as the “Engagement- two clusters with high demands for improvements in Focused” cluster had lower satisfaction levels. The clus- interior design, the highest demand came from ter with lower satisfaction levels had greater demands improvements in soundproof levels and finishing for improvements in the space composition. The great- materials (Table 11). est demand for improvement for the “Actively Using” and “Engagement-Focused” clusters was having more 5. Discussion rooms, followed by having two bathrooms. The “Actively Using” and “Engagement-Focused” clusters This identified the housing improvement measures by had greater demands for a larger house than the lifestyle types of young adults living in Happy Houses. “Minimally Using” cluster. A large proportion of these The results are as follows. clusters demanded a large kitchen, dining room, and First, although all young adults living in Happy living room, and more than half demanded larger bed- Houses were in their twenties and thirties, we could rooms than the present ones. Many households in this classify them into five lifestyle types depending on cluster also demanded large bathrooms. These clusters how they used their homes. The first was the “Actively participated in various housing activities in the house Using” cluster, utilizing the house for leisure, forming or had a big affection on their house, which may lead relationships with various groups, and basic living pur- to increased demands for a big house. The “Personal poses. Another cluster was the “Minimally Using” clus- Activity” and “Engagement-Focused” clusters had differ - ter which barely used their houses, and the “Personal ent levels of demand for improving basic equipment, Activity” cluster, which focused on using the house for furniture, and appliances. Like the demand for a bigger basic living purposes and engaging with their compa- house, the “Actively Using” cluster demanded improved nion animals or pets. The “Engagement-focused” cluster equipment, furniture, and appliances. For detailed used the houses to engage with others and participate demands for improvement, the “Actively Using” cluster in personal activities, and the “Self-expression” cluster submitted more demands than the “Personal Activity” used houses to express themselves. Many young cluster. The former submitted 892 detailed demands, adults in their twenties and thirties lived in Happy while the latter submitted 511. Regarding the Houses, including university students, those beginning demands for basic options of the house, the “Actively their careers, newlyweds, and couples with toddlers. Using” cluster had high demands for an improved air Hence, the young adults in Happy Houses had varying conditioner in the living room and induction cooktops lifestyles. Currently, Happy House considers the num- and dishwashers in the kitchen. Contrarily, the ber of household members depending on the mini- “Personal Activity” cluster had high demands for induc- mum housing standard provided by the government tion cooktops in the kitchen but relatively higher and the age and sex of children as a standard to apply demands for refrigerators in the kitchen and washing to each housing size. However, there are various ways Table 11. Differences in the demands for improvements in the housing environment by housing lifestyle cluster. Housing Lifestyle Cluster Engagement- Actively Using Self-Expression Personal Activity Focused Cluster Minimally Using Classification Cluster (126) Cluster (106) Cluster (108) (109) Cluster (87) F Overall Demand for Housing 3.56b 3.40b 3.33ab 3.38b 3.13a 3.746** Demand on Housing Composition (no. of 3.52b 3.32ab 3.13a 3.57b 3.00a 4.142** rooms, layout, etc.) Demand for Housing Size 3.75b 3.79b 3.62ab 3.54ab 3.33a 2.635* Demand for Housing Basic built-in equipment, 3.69c 3.65bc 3.24a 3.35ab 3.33ab 3.680** furniture, and home appliances Demand for Housing Interior Design 3.27b 2.85a 3.31b 3.07ab 2.85a 3.207* *p<0.05, **p<0.01. 14 M. JANG ET AL. Figure 1. Examples of Happy Houses. *Source: Happy House pamphlet of Paju Unjeong District Sannae Village (Land and Corporation 2022b) that the residents use the house for varied lifestyles. living in other types of public rental housing, it is Lifestyles should be considered when planning the necessary to increase the area per house and improve composition of Happy Houses. the spatial composition standards. There should be Second, regardless of lifestyle clusters, residents of more housing models as compared with the present Happy Houses generally showed higher-than-average scenario. satisfaction levels. However, there were differences in Third, there were differences in clusters in their satisfaction levels by lifestyle clusters for the spatial demands for housing improvement of Happy Houses composition, size, equipment/furniture/appliances, for overall and detailed improvements. All clusters and other basic installments. The “Engagement- showed higher-than-average demands for housing focused” cluster had lower satisfaction levels than improvements. The “Minimally Using” cluster, which other clusters regarding the spatial composition, size, used homes for some purposes, showed relatively and basic installation options. It comprised married low demands for general and detailed improvements. couples with relatively high incomes living in two- The “Actively Using” cluster, which used the homes the bedroom houses in the Seoul area. They had the low- most, had the highest demands for general and est satisfaction levels in all areas. “Actively Using” clus- detailed improvements. It is necessary for Happy ter had similar demographic characteristics and used Houses to be diverse in spatial composition, area, and the house for various activities, lived in generally large interior design while considering the residents’ use of homes with three bedrooms, or the Seoul area. Those housing. Although there is a demand for large houses living in the Seoul area were less likely to be satisfied with varied room compositions and basic options that with smaller houses than those living in areas outside consider interior design, it may be a viable option to Seoul, hence the differences in satisfaction levels. provide the current Happy Houses with various Although the participants lived in houses larger than options for interior design, leading to low cost. In the the minimum standards provided by the government, “Self-expression” cluster, those who vested in their married couples with high-income levels were not houses showed low demands for improvement. satisfied with small houses with two bedrooms. In Hence, it may be viable to provide various options to rural areas, due to location or housing sizes, Happy the young adults to customize their houses depending Houses are frequently left vacant for a long time. The on their tastes. The regulations of rental housing must difference in demand for space between urban and be reviewed, and changes made to the house in the rural areas is a topic that has been discussed exten- interior design must be changed when returning the sively. As the differences between urban and rural house. areas are considered for the sizes of general housing, the regional differences for Happy Houses must also be 6. Conclusion considered. Moreover, as the residents are more likely to take part in more activities in the house in areas with This study verified that there are differences in poor living infrastructure, and those living in Happy demands for housing improvements depending on Houses have a relatively higher income than those lifestyle clusters among young adults living in public JOURNAL OF ASIAN ARCHITECTURE AND BUILDING ENGINEERING 15 rental housing. 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Journal

Journal of Asian Architecture and Building Engineering – Taylor & Francis

Published: Nov 2, 2023

Keywords: Housing improvement; housing satisfaction; housing lifestyle; public rental housing; young household

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