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Article

Residential Satisfaction in Urban Regeneration Areas: A Multilevel Approach to Individual- and Neighborhood-Level Factors

by
Eun Jung Kim
* and
Hyemin Sim
Department of Urban Planning, Keimyung University, 1095 Dalgubeol-daero, Dalseo-gu, Daegu 42601, Republic of Korea
*
Author to whom correspondence should be addressed.
Buildings 2026, 16(1), 213; https://doi.org/10.3390/buildings16010213
Submission received: 26 November 2025 / Revised: 26 December 2025 / Accepted: 31 December 2025 / Published: 2 January 2026
(This article belongs to the Special Issue Urban Wellbeing: The Impact of Spatial Parameters—2nd Edition)
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Abstract

This study aims to identify how individual-level and neighborhood-level factors are associated with residential satisfaction in urban regeneration areas. We conducted a survey of 281 adult residents recruited on-site at six urban regeneration community facilities (URCFs) that had been in operation for at least one year in Daegu, South Korea, and constructed neighborhood-level built environment factors using GIS. Multilevel regression analysis was applied to simultaneously examine how individual-level (level 1) and neighborhood-level (level 2) factors are associated with residential satisfaction. The results indicated that residents who participated more actively in urban regeneration activities reported higher levels of residential satisfaction, and that age integration was also significantly associated with greater satisfaction. Among neighborhood-level built environment factors, a lower proportion of old housing and higher levels of normalized difference vegetation index (NDVI) and water area were related to higher residential satisfaction. These findings indicate that residential satisfaction in urban regeneration areas can be better understood when individual-level characteristics and neighborhood-level built environmental conditions are considered together, highlighting the importance of a multilevel approach that accounts for both levels simultaneously.

1. Introduction

Urban regeneration projects have been implemented as key policy instruments to improve the physical conditions of deteriorated urban areas and to enhance the quality of life in local communities k. In this context, residential satisfaction has been used as an important indicator to evaluate how regeneration initiatives affect actual living conditions and residential environments [1]. Residential satisfaction is a perception-based measure that reflects residents’ overall evaluations of housing quality, accessibility, and community relations [2,3], and it has been suggested as one of the useful criteria for discussing and assessing the outcomes of urban regeneration projects [4]. Therefore, to better understand the effectiveness of urban regeneration policies, it is crucial to identify the factors that shape residential satisfaction in such areas.
Residential satisfaction is influenced by residents’ individual characteristics and the conditions of the neighborhood environment [2,5]. Individual-level determinants include socio-demographic characteristics such as gender, age, education, income, and length of residence, as well as social factors such as participation in community activities [6,7]. Although these factors have a significant influence on residential satisfaction, it has been consistently noted that they are not sufficient to fully explain individuals’ perceived satisfaction with their place of residence [6,7]. This limitation highlights the need to consider neighborhood-level environmental attributes alongside individual characteristics when analyzing residential satisfaction.
Neighborhood environments also emerge as important determinants of residential satisfaction [5,8]. Physical characteristics such as housing age, housing type, and residential density influence how residents perceive both the safety and the amenity of the neighborhood [9,10], while green spaces and waterfront areas are closely associated with psychological stability and improved quality of life [11,12]. In addition, factors such as access to daily amenities, a walkable environment, and transportation infrastructure determine the convenience of residents’ mobility [9,13]. Taken together, these factors can be regarded as important neighborhood-level determinants of residents’ residential satisfaction.
Nevertheless, there have been relatively few studies that simultaneously consider both individual factors and neighborhood factors when analyzing their effects on residential satisfaction [3,6,7,14]. In particular, because only a limited number of studies have analyzed residential satisfaction in urban regeneration areas by linking individual characteristics with physical environmental features [1,8], there is a clear need for research that simultaneously examines factors at both levels. Therefore, this study aims to identify how individual-level factors and neighborhood-level built-environment factors are associated with residents’ perceived residential satisfaction in urban regeneration areas.

2. Literature Review

2.1. Individual-Level Factors and Residential Satisfaction

Socio-demographic factors such as gender, age, educational attainment, income, and length of residence have been found to have significant influences on residential satisfaction. Previous studies have reported that women and older residents tend to exhibit more stable and positive perceptions of their residential environments [15]. Higher levels of education are associated with greater emphasis on qualitative aspects of the neighborhood [16,17], and higher income is generally linked to greater residential satisfaction [18]. In addition, a longer duration of residence is associated with stronger attachment to, and higher satisfaction with, the neighborhood [19].
Residents’ community experiences also play a key role in explaining residential satisfaction. Participation in local activities, trust in the community, and the formation of social networks contribute to more positive perceptions of the neighborhood [20]. Involvement in community activities has been shown to strengthen residents’ sense of belonging and psychological well-being [21]. Social experiences such as intergenerational exchanges and community-based events enhance social ties and trust within the neighborhood, which in turn can increase residents’ satisfaction with their residential environment [20,21]. These effects tend to be particularly pronounced in urban regeneration areas. Residents’ experiences in urban regeneration activities may influence residential satisfaction through psychosocial mechanisms rather than through social interaction alone. Participation in such activities can strengthen place attachment and a psychological sense of community by enhancing residents’ sense of belonging and the meaning they attribute to their neighborhood. These shifts in attachment and perceived community can shape more favorable evaluations of local living conditions and, in turn, contribute to higher residential satisfaction [22,23]. Some studies have shown that residents’ level of social participation and the strength of their community networks are closely related to residential satisfaction [24,25,26,27], and that those who participate more actively in urban regeneration programs tend to have a better understanding of, and more positive attitudes toward, their neighborhood [26].
Age integration has been highlighted as an important social factor in the context of urban regeneration. Neighborhoods with active intergenerational interaction and a diverse age composition tend to show higher levels of community cohesion and psychological stability among residents [28,29]. Age integration goes beyond mere diversity in the age distribution; it refers to a social context in which residents of different generations are more likely to encounter one another and engage in routine, everyday interaction. Prior studies suggest that intergenerational contact can reduce social isolation and enhance emotional support and psychological stability. These social and psychological resources can foster more positive perceptions of neighborhood cohesion, trust, and safety, thereby contributing to higher residential satisfaction [30,31]. Studies focusing on urban regeneration areas have further found that age integration positively influences residents’ perceptions of the neighborhood and their experiences of living in the area, and thus plays an important role in explaining residential satisfaction [32]. In sum, residents’ experiences of engagement in regeneration activities and the degree of age integration function as key factors for understanding residential satisfaction and quality of life in urban regeneration areas [24,26,28,32].
Nevertheless, there are clear limits to explaining residents’ satisfaction with their neighborhood solely in terms of individual-level factors [11]. In practice, residential satisfaction is shaped not only by residents’ sociodemographic characteristics and level of social participation but also by features of the neighborhood built environment [33], which need to be taken into account.

2.2. Neighborhood Built Environment Factors and Residential Satisfaction

To understand residential satisfaction in urban regeneration areas, it is essential to consider the built environment [34]. The built environment includes various elements such as land use, the physical condition of housing, green and waterfront spaces, the density and quality of local amenities, and transportation accessibility, all of which interact to influence residents’ satisfaction with their neighborhood [35].
Diverse land uses affect the convenience and safety of daily life, and areas in which commercial and residential functions are appropriately mixed tend to show higher levels of residential satisfaction [14,18]. In addition, areas with lower slopes tend to have higher walkability, and such pedestrian-friendly environments can enhance residents’ satisfaction with their neighborhood [36,37].
The physical condition of housing is one of the key determinants of neighborhood residential satisfaction. In areas where old or deteriorated housing is concentrated, neighborhood residential satisfaction tends to be lower [38]. Housing type is also an important physical attribute affecting residential satisfaction; residents living in detached houses or multi-family housing report significantly lower satisfaction levels than apartment residents [17].
Natural environmental elements such as green spaces and waterfront areas also have positive effects on residents’ psychological stability and health, thereby contributing to stronger attachment to and higher satisfaction with their neighborhood. In areas with abundant greenery and high-quality natural environments, residents tend to experience less stress and report higher levels of comfort and amenity [35,39].
In addition, accessibility to amenities and transportation also plays an important role in neighborhood residential satisfaction. Neighborhoods that are well served by a diverse range of facilities, such as hospitals, pharmacies, and retail stores, tend to exhibit higher levels of residential satisfaction [16,40,41]. Furthermore, for older adults, accessibility to welfare facilities within the neighborhood has been identified as a key factor that enhances quality of life and strengthens attachment to the local area [42,43].
In terms of transportation accessibility, higher intersection density, a greater number of bus stops, and shorter distances to subway stations enhance neighborhood walkability, which in turn is associated with higher levels of neighborhood residential satisfaction [13,36,37,44].
In urban regeneration, improvements to the built environment are aimed not only at upgrading physical infrastructure, but also at enhancing the quality of residents’ everyday environments. These environmental improvements foster stronger place attachment and social cohesion among residents, thereby contributing to the long-term sustainability of neighborhood regeneration [35,45]. Accordingly, the enhancement of the neighborhood built environment can be considered a key determinant of residents’ quality of life.

2.3. The Conceptual Linkage Between Individual- and Neighborhood-Level Factors and Residential Satisfaction

Previous research indicates that residential satisfaction in urban regeneration areas is shaped by both individual-level characteristics and neighborhood-level built-environment conditions. Because these influences operate simultaneously, isolating their associations requires an approach that considers both levels together.
Despite extensive research on residential satisfaction, fewer studies empirically examine urban regeneration settings where subjective social experiences and objective built-environment conditions change concurrently. In addition, single-level designs make it difficult to separate individual influences from neighborhood influences. To address these limitations, this study integrates resident survey data with GIS-based built-environment indicators and applies multilevel regression to jointly estimate individual- and neighborhood-level associations with residential satisfaction in urban regeneration areas.

3. Materials and Methods

3.1. Research Design and Hypotheses

The multilevel research framework of this study is shown in Figure 1. Because residents’ residential satisfaction is determined by both individual characteristics and built environment conditions, an analytical approach that considers individual-level (level 1) and neighborhood-level (level 2) factors simultaneously is required.
Previous studies have relied on single-level analyses—focusing either on individuals or on neighborhoods—which limits their ability to capture the relationship between residents’ subjective perceptions and objective environmental conditions in a comprehensive way. In contrast, this study simultaneously incorporates residents’ individual characteristics and the built environment of urban regeneration areas, in order to empirically examine how factors at these two levels combine to shape residential satisfaction. In addition, this study uses both qualitative and quantitative data, including subjectively measured residents’ perceptions and objectively measured built environment characteristics, to identify in greater detail the factors that influence residential satisfaction.
Based on these considerations, this study proposes the following hypotheses regarding individual-level and neighborhood-level determinants of residential satisfaction.
H1. 
Residents with experience of participating in urban regeneration activities will report higher levels of residential satisfaction than those without such experience.
H2. 
Residents with higher perceived levels of age integration in their neighborhood will report higher levels of residential satisfaction than those with lower perceived levels.
H3. 
Residents living in neighborhoods with more pleasant and pedestrian-friendly built environments will report higher levels of residential satisfaction than those living in less pleasant and less pedestrian-friendly neighborhoods.

3.2. Study Area and Data

This study examined Urban Regeneration Community Facilities (URCFs) in Daegu, South Korea. We employed a multi-stage purposive (criterion-based) sampling approach rather than simple random sampling. At the site-selection stage, eligible facilities were limited to those associated with completed urban regeneration projects and that had been in operation for at least one year after opening. From this eligible pool, six URCFs were selected to reflect geographic distribution across the city and diversity in project and facility/program characteristics; their locations are presented in Figure 2. City of Daegu, located in the southeastern region of South Korea, is the country’s fourth-largest city, with a population of 2,356,667 as of September 2025 [46]. The city has experienced challenges commonly targeted by urban regeneration initiatives, including declines in population and business activity associated with industrial restructuring, as well as an increasing stock of aging buildings. Since the enactment of the Special Act on the Promotion of and Support for Urban Regeneration in 2013, Daegu has continuously implemented urban regeneration projects aimed at improving living conditions and restoring local communities [47]. In this context, Daegu provides an appropriate setting for assessing residents’ satisfaction and neighborhood environment with a focus on URCFs.
URCFs are community spaces jointly used by local residents and are designed to enhance residents’ welfare, promote information exchange and communication, and revitalize the local community [47]. This study focuses on URCFs developed in areas where urban regeneration projects have been completed, and each facility was established to reflect distinct local conditions. The Dalseong URCF was developed in a residential neighborhood characterized by a high concentration of multi-family housing. It operates spaces that support everyday social interaction and leisure activities, with programs and spatial arrangements designed to accommodate local residents, including older adults. The Hyomok URCF is located in an area where a traditional market and residential blocks are adjacent. It serves as a local hub that encourages intergenerational exchange and resident participation, and it aims to facilitate meetings and communication through a range of community spaces. The Wongogae URCF was created by repurposing an existing building in a neighborhood with a dense stock of aging housing. It focuses on sharing the village’s history and everyday culture and on restoring a sense of community identity. The Indongchon URCF was established to improve living conditions in a residential area with a high proportion of older residents. Its operations primarily center on health management programs and the provision of welfare-oriented services. The Chimsan URCF supports resident-led activities and promotes self-sustaining operation. By combining community facilities with everyday living infrastructure, it aims to strengthen and revitalize the local community. The Cheukbaekhyang URCF is situated in a peri-urban area rich in natural and historical resources. It was developed to support resident activities that leverage local assets while also considering visitor inflows, and it is used to promote the area and host community activities simultaneously. Table 1 summarizes each selected URCF’s project timeline and facility characteristics, including the selection year, project period, opening date, and key-space inventory.
The data for this study were obtained from two main sources: a questionnaire survey and a geographic information system (GIS). First, the survey was conducted to examine the association of urban regeneration activity experience and age integration with neighborhood residential satisfaction among users of URFCs. The survey protocol was reviewed and approved by the Institutional Review Board (IRB) of the research institution. Respondents were recruited on-site among URCF users; the analytic sample was restricted to residents aged 18 years or older living in the corresponding regeneration area. Participant recruitment followed a non-probability, on-site approach rather than random sampling. Accordingly, the respondent sample reflects individuals who were accessible and willing to participate during the fieldwork period within each selected site. The survey was conducted over approximately five months, from 26 September 2024 to 28 February 2025. A total of 367 questionnaires were collected, and after excluding cases with missing values, 281 valid responses were retained for the final analysis. In addition, objective indicators for built environment factors were constructed using GIS. The detailed procedures for data construction and the sources of the GIS-based built environment measures are described in Section 3.3.

3.3. Measure

3.3.1. Residential Satisfaction

The dependent variable in this study is residential satisfaction among residents living in urban regeneration project areas, measured through the questionnaire survey (Table 2). To construct the measure of residential satisfaction, we first reviewed previous studies to identify key dimensions and items. Prieto-Flores et al. (2011) [45] analyzed the relationships among housing satisfaction, sense of belonging, and loneliness among older adults in Spain, and measured housing satisfaction based on evaluations of the dwelling and neighborhood environment. Zhang and Wei (2025) [48] examined residential satisfaction and sense of belonging in the context of a resettlement policy in Shanghai, China. It suggested that overall satisfaction, intention to stay, and sense of belonging are important components of neighborhood residential satisfaction. Mao et al. (2022) [49] validated a short-form index of perceived residential environment quality and neighborhood attachment in China. Neighborhood attachment, which consists of positive evaluation, an improvement attitude, and reluctance to leave, has been identified as a key construct explaining residents’ overall satisfaction and their intention to continue living in the area.
Building on these previous findings, this study conceptualized neighborhood residential satisfaction using four items: “Overall, I am satisfied with the area where I live”; “I would like to continue living in my current residential area”; “I feel a sense of belonging to the area where I live”; and “The area where I live is a place I would recommend others to move to.” All items were measured using a five-point Likert scale ranging from “strongly disagree” to “strongly agree.” In the analysis, we used the mean score of the four items as the indicator of neighborhood residential satisfaction.

3.3.2. Individual-Level Variables (Level 1)

The key individual-level (level 1) variables are respondents’ experience in urban regeneration activities and age integration, as shown in Table 2. Experience in urban regeneration activities was measured by asking respondents whether they had participated in any urban regeneration activities. Age integration is a multidimensional concept that goes beyond different generations merely sharing the same space, and includes levels of intergenerational interaction, social participation, trust building, and relational bonding [28,29]. Communities with a high level of age integration tend to reduce psychological and social distance between generations and to promote mutual trust and cooperation among residents, which provides an important foundation for the formation of residential satisfaction [29]. We adopted the age integration scale developed by Chung and Lim (2020) [50]. Age integration was measured using 13 items on a five-point Likert scale ranging from “strongly disagree” to “strongly agree,” and the mean score was used in the analysis. The specific survey items are presented in Table A1 in the Appendix A. In addition, gender, age, education level, income level, and period of residence were included as control variables.

3.3.3. Neighborhood-Level Built Environment Variables (Level 2)

The neighborhood-level (level 2) built environment variables capture the environmental conditions surrounding each URFC and were objectively measured using GIS. The spatial extent of the neighborhood environment was defined using a 400 m Euclidean buffer, which is commonly adopted in walkability-related research [51,52]. In particular, for pedestrian-oriented, small-scale neighborhoods such as urban regeneration areas, this range is deemed appropriate for capturing the environment that residents experience in daily life. Five domains of built environment attributes were considered: (1) urban form and land use, (2) housing characteristics, (3) open space, (4) neighborhood amenities, and (5) street network and transport infrastructure. We next provide brief descriptions of the variables in each domain.
The urban form and land use include two variables: slope and land use mix. Slope was measured as the average gradient within a 400 m airline buffer around each URFC, using data from the National Spatial Data. Land use mix was measured as the average land use mix within a 400 m airline buffer around each URFC, based on data from the Environmental Space Information Service.
The housing characteristics include two variables: the proportion of old housing and the proportion of multifamily housing. Old housing, in this analysis, refers to dwellings that were completed more than 20 years ago. Both proportions were calculated as the share of the corresponding housing units within a 400 m airline buffer around each URFC, using data from the National Spatial Data.
The open space includes two variables: normalized difference vegetation index (NDVI) and the proportion of water area. NDVI captures the level of vegetation within a 400 m airline buffer around each URFC and was derived from United States Geological Survey (USGS) data. The proportion of water area was calculated as the percentage of the area covered by rivers and streams within a 400 m airline buffer around each URFC, using Road Name Address data.
The neighborhood amenities include four variables: hospital density, pharmacy density, amenity density, and senior center density. Each variable represents the density of hospitals, pharmacies, amenities, and senior centers, respectively, within a 400 m airline buffer around each URFC, calculated by dividing the number of facilities by the area of the buffer.
The street network and transport infrastructure include three variables: intersection density, bus stop density, and distance to the nearest subway station entrance. Intersection density was measured as the density of intersections within a 400 m airline buffer around each URFC, using data from the National Spatial Data. Bus stop density was measured as the density of bus stops within a 400 m airline buffer around each URFC, and distance to the nearest subway station entrance was calculated as the distance from each URFC to the nearest subway station entrance. Both variables were derived from Road Name Address data.

3.4. Analysis Method

Multilevel regression analysis was employed to examine the associations of individual-level and neighborhood-level variables with residential satisfaction. All statistical analyses were conducted using R version 4.4.2. Residential satisfaction and individual-level variables were obtained from the survey data, whereas neighborhood built environment variables were constructed using ArcGIS version 10.5(Esri, Redlands, CA, USA).

4. Results

4.1. Descriptive Statistics of Variables

The descriptive statistics for the variables used in this study are shown in Table 3. As the dependent variable, residential satisfaction was calculated as the mean score of four items (Cronbach’s α = 0.873). Across all URCFs, the mean residential satisfaction score was 3.49 on a 5-point scale (3 = neutral), with URCF-level means ranging from 3.31 to 3.77.
The descriptive statistics for the individual-level variables (level 1) are as follows. Overall, 30.6% of respondents reported having experience with urban regeneration activities. Age integration was measured using the mean score of 13 items (Cronbach’s α = 0.917), with an average score of 2.90. With regard to gender, 64.8% of all respondents were female. Age was distributed across age groups, with 25.3% of respondents aged 18–39 years, 29.9% in their 40s–50s, and 44.8% aged 60 years or older. Regarding educational attainment, 48.0% of respondents had a high school education or less, whereas 42.0% had a university degree or higher. As for income, 33.8% of respondents reported a monthly income of less than 1 million KRW, 52.7% reported an income between 1 and 4 million KRW, and 13.5% reported an income of 4 million KRW or more. In terms of length of residence, 24.9% of respondents had lived in their current neighborhood for less than 10 years, whereas 75.1% had lived there for 10 years or more.
For the neighborhood-level built environment variables (level 2), descriptive statistics are presented below. Among the urban form and land use domain, the mean slope across all URCFs was 1.9°. Cheukbaekhyang URCF had the steepest terrain, with an average slope of 3.9°, whereas Indongchon URCF had the gentlest slope at 0.9°. Regarding land use mix, Hyomok URCF showed the highest value (0.822), while Wongogae URCF (0.442) and Cheukbaekhyang URCF (0.417) exhibited relatively low levels of land use mix.
For housing characteristics, the proportion of old housing was highest in Wongogae URCF (98.2%) and Hyomok URCF (96.0%). In contrast, Dalseong URCF (75.9%) and Cheukbaekhyang URCF (81.9%) showed lower proportions of old housing than the overall mean of 89.9%. The proportion of multi-family housing was generally low across all URCFs, with an overall mean of 7.8%. Hyomok URCF (6.5%) and Cheukbaekhyang URCF (0.0%) had lower proportions of multi-family housing than the mean.
Regarding open space, the mean NDVI across all URCFs was 0.172, with Cheukbaekhyang URCF showing the highest value (0.331). The proportion of water areas was also highest in Cheukbaekhyang URCF (6.75%), whereas Wongogae URCF, Indongchon URCF, and Chimsan URCF all had 0.0%.
As for neighborhood amenities, hospital density was highest around Hyomok URCF (70 counts/km2), whereas no hospitals were located near Cheukbaekhyang URCF. Pharmacy density was also highest around Hyomok URCF (28 counts/km2), while no pharmacies were present in the vicinity of Cheukbaekhyang URCF. Retail shop density was highest around Indongchon URCF (90 counts/km2) and lowest around Cheukbaekhyang URCF (4 counts/km2). Although there was relatively little variation in senior center density across facilities, Dalseong URCF showed the highest density (14 counts/km2).
In terms of street network and transport infrastructure, the mean intersection density across all URCFs was 1058 counts/km2, and Dalseong, Chimsan, and Cheukbaekhyang URCFs fell below this average. Bus stop density varied substantially across URCFs, with Chimsan URCF showing the highest density (737 counts/km2) and Cheukbaekhyang URCF the lowest (8 counts/km2). The distance to the nearest subway station was longest for Cheukbaekhyang URCF (4590.4 m), whereas Dalseong URCF had the shortest distance (360.9 m), indicating the best subway accessibility.

4.2. Multilevel Associations of Individual- and Neighborhood-Level Factors with Residential Satisfaction

We estimated multilevel regression models to examine the associations of individual- and neighborhood-level factors with residential satisfaction (Table 4). To address multicollinearity among the neighborhood-level variables, only 4 of the 13 variables were retained in the final model. The R2 of the model was 0.43. The intraclass correlation coefficient (ICC) was 0.121, which indicates that approximately 12.1% of the total variance was attributable to between-level-2 (cluster) differences. The ICC (0.121) from the unconditional model indicates between-neighborhood differences; therefore, applying a multilevel model is appropriate to reflect the hierarchical data structure and to avoid underestimation of standard errors [53,54,55,56]. We also examined variance inflation factors (VIFs) for the variables included in the analysis. All VIF values were below 10, indicating no serious multicollinearity concerns.
Among the individual-level variables, experience with urban regeneration activities, age integration, and age were positively associated with neighborhood satisfaction. Residents with experience in urban regeneration activities reported higher neighborhood satisfaction than those without such experience (β = 0.06, p = 0.08). Higher age integration was also associated with higher neighborhood satisfaction (β = 0.25, p < 0.001). In addition, older respondents reported higher neighborhood satisfaction (β = 0.63, p < 0.001). By contrast, gender, educational level, income level, and length of residence were not statistically significant.
Among the neighborhood-level variables, a higher proportion of old housing was associated with lower neighborhood satisfaction (β = −0.38, p = 0.06). In contrast, both NDVI and the proportion of water area showed positive associations with neighborhood satisfaction (NDVI: β = 0.26, p = 0.07; proportion of water area: β = 0.20, p = 0.03). By contrast, bus stop density did not have a statistically significant association with neighborhood satisfaction.

5. Discussion

This study confirmed that both individual-level and neighborhood-level factors jointly shape neighborhood satisfaction in urban regeneration areas. In particular, not only individual factors such as experience with urban regeneration activities, age integration, and age, but also neighborhood environmental factors such as the proportion of old housing, NDVI, and the proportion of water area were significantly associated with neighborhood satisfaction. These findings suggest the need to consider both residents’ characteristics and the built environment when analyzing neighborhood satisfaction in the context of urban regeneration. The results of testing the hypotheses proposed in this study are as follows.
First, residents with experience of participating in urban regeneration activities reported higher levels of residential satisfaction than those without such experience, which is consistent with Hypothesis 1 (H1). Active resident participation is understood to enhance trust in public policies and strengthen a sense of community belonging, while also deepening residents’ understanding of, and positive orientation toward, processes of neighborhood change. This is consistent with previous research, which has reported that neighborhoods with higher levels of resident participation tend to exhibit greater satisfaction with regeneration projects and stronger community cohesion [22,24,26]. Importantly, similar participation–satisfaction linkages have also been documented in urban renewal/regeneration contexts outside South Korea, suggesting that the underlying pathways (e.g., social capital) may generalize across different institutional contexts [22]. In particular, participation in regeneration activities can improve residents’ comprehension of the neighborhood transformation process and strengthen place attachment, both of which are likely to contribute to higher residential satisfaction [23]. Moreover, participation experience may encourage residents to interpret changes and emerging local issues more proactively and to cope with disruptions associated with regeneration, thereby helping to sustain residential satisfaction during periods of transition [33]. Taken together, these findings suggest that resident participation operates as a key social mechanism for enhancing residential satisfaction by fostering trust and relational ties within the community.
Second, higher levels of age integration were associated with higher levels of residential satisfaction, which is consistent with Hypothesis 2 (H2). Neighborhoods where different age groups interact actively tend to offer stronger emotional support and social networks. As a result, residents are more likely to perceive their living environment as safe and stable. This pattern is consistent with prior international evidence reporting a positive association between age integration (or age-diverse neighborhood settings) and residents’ neighborhood-related evaluations, including residential satisfaction [28,30,31]. Previous research has also shown that intergenerational programs and activities enhance the emotional stability and well-being of older adults [31], which supports this finding. More broadly, age-diverse neighborhood contexts can strengthen social ties through intergenerational exchange, and such ties may function as an important condition for residents’ psychological stability and residential satisfaction [28]. In addition, intergenerational interaction can facilitate residents’ adaptation to physical and social changes in the neighborhood, which may further contribute to higher residential satisfaction amid regeneration-driven transitions [30].
Third, higher levels of pleasantness and walkability in the built environment were associated with higher levels of residential satisfaction, which is consistent with Hypothesis 3 (H3). Among the 13 neighborhood environmental variables, three were found to be particularly important and statistically significant: the proportion of old housing, NDVI, and the proportion of water area. This finding is also consistent with prior international evidence from urban regeneration contexts suggesting that neighborhood environmental characteristics—such as housing age/condition, green environments, and blue (water) spaces—are positively associated with residential satisfaction [10,14,35,38,57,58,59,60].
In particular, neighborhoods with higher proportions of old housing showed lower levels of residential satisfaction. Areas with a high concentration of deteriorated dwellings tend to have a run-down appearance and reduced pedestrian amenity, which can easily lead to lower overall satisfaction with the residential environment. This finding is consistent with previous studies suggesting that the physical condition of housing is a key determinant of residential satisfaction [10,38]. As shown in Table 5, low levels of residential satisfaction were observed in Wongogae URCF (3.31), Hyomok URCF (3.45), Indongchon URCF (3.39), and Chimsan URCF (3.44), all of which had high proportions of old housing (98.2%, 96.3%, 93.5%, and 93.8%, respectively). By contrast, the areas around the Cheokbaekhyang URCF (3.61) and the Dalseong URCF (3.77), which recorded higher satisfaction levels, had comparatively lower proportions of old housing (43.5% and 75.9%, respectively).
A second important variable was green space. The results showed that areas with higher NDVI values tended to have higher levels of residential satisfaction. As shown in Table 5, the Cheokbaekhyang URCF, which recorded the second highest level of residential satisfaction (3.61), had the highest NDVI value (0.331) among the study sites. The Dalseong URCF likewise exhibited a relatively high NDVI value (0.182) and the highest level of residential satisfaction (3.77). In contrast, Hyomok URCF (0.133), Wongogae URCF (0.106), and Indongchon URCF (0.104) had lower NDVI values, indicating a relative lack of green space, and also showed lower levels of residential satisfaction (3.45, 3.31, 3.39, respectively). These findings support previous research suggesting that green spaces contribute to stress reduction, emotional stability, and everyday recovery [58,59], and indicate that the quality of the natural environment can play an important role in shaping residential satisfaction.
Another significant variable was water area. Water areas were also positively associated with residential satisfaction. Areas with a higher proportion of water tend to have higher landscape quality and greater visual openness, which can provide a sense of psychological stability [57,60]. As shown in Table 5, the Cheokbaekhyang URCF, which recorded a relatively high level of residential satisfaction (3.61), is adjacent to Bullo Stream, which flows from the southwest to the northeast, and consequently has a water area ratio of 6.75%. Similarly, the Dalseong URCF (residential satisfaction: 3.77) is located near Cheonnae Stream, which flows from the northwest to the southeast, and has a water area ratio of 2.6%. In both areas, the streams that traverse the local landscape provide good accessibility to waterfront spaces, which may have contributed positively to higher levels of residential satisfaction. In contrast, Wongogae URCF, Hyomok URCF, Indongchon URCF, and Chimsan URCF had virtually no waterfront spaces, with their water area ratios being close to 0%.
Taken together, the overall findings indicate that the built environment plays a crucial role in enhancing residential satisfaction. Even relatively small improvements—such as the refurbishment of old housing, the expansion of green spaces, streetscape greening, and the creation of waterfront promenades—can substantially increase residents’ perceived satisfaction [57,59]. In addition, when age-integrated programs and community activities are strengthened in parallel, improved social relationships can further amplify the benefits of built environmental improvements [31]. Resident participation also emerged as an important factor; the more residents are involved in decision-making processes, the higher their levels of trust in those policies tend to be [22,26]. Therefore, it is necessary to establish a governance system that enables the participation of diverse groups in local policy decision-making, particularly ensuring that older adults and other vulnerable populations can also be involved. Overall, enhancing local residents’ satisfaction with their neighborhoods requires both strong social cohesion—fostered through community participation and intergenerational integration—and a pleasant neighborhood built environment.
This study makes three contributions. First, it contributes methodologically by developing and applying a multilevel empirical framework that links resident-level responses to neighborhood-level conditions in urban regeneration areas. We operationalize this linkage by estimating multilevel regression models that include individual-level factors (Level 1) alongside neighborhood-level built-environment factors (Level 2). Importantly, the framework integrates survey-based measures capturing residents’ perceptions and experiences (subjective indicators) with GIS-based measures describing spatial and physical contexts (objective indicators), enabling a coordinated examination of social and physical dimensions within a single analytical design. Second, it contributes academically by advancing the Korean urban regeneration literature beyond approaches that treat evaluation domains in isolation. Whereas prior studies have frequently focused on either the physical environment (e.g., facilities, streetscape, land use) or residents’ social experiences (e.g., participation, perceived community change), this study explicitly examines concurrent social-experience change and physical-environment change and their associations with residential satisfaction. By foregrounding this simultaneity, the study clarifies why residential satisfaction is difficult to explain through a single-domain or single-level lens and offers empirical evidence that supports a more integrative interpretation of regeneration outcomes. Third, it contributes to policy and practice by providing resident-centered, neighborhood-specific evidence that can complement national or city-level assessments that rely largely on macro indicators and may not fully capture lived experiences in particular places [61]. Given that Korea’s urban regeneration policy has been institutionalized for only about a decade [47], robust post-implementation evidence remains limited—especially for projects with sufficient time elapsed to assess operational effects. To address this gap, we focus on URCFs with at least one year of operation, thereby producing practical implications for evaluation criteria, program design, and ongoing management that are grounded in both perceived (survey) and observed (GIS) neighborhood conditions.
This study has several limitations and directions for future research. First, because we focus on urban regeneration project areas in Daegu, caution is required when generalizing the findings to other settings with different demographic, spatial, and policy contexts. City of Daegu was considered an appropriate case for exploring the characteristics of Korea’s urban regeneration initiatives because it combines metropolitan features with a mixed urban–rural spatial structure, allowing observation of diverse urban environments within a single metropolitan city. Nevertheless, the findings should not be overextended to all cities with different population structures or policy environments. Future research should therefore conduct cross-city comparative analyses to more systematically assess the generalizability of these results. Second, the survey sample is relatively small, which limits the extent to which the findings can be generalized to a wider range of cities and urban regeneration project areas. Future studies should expand both the study areas and sample size to test and validate the findings more robustly. Third, the study relies on cross-sectional data, which constrains our ability to identify causal relationships and to capture medium- to long-term or dynamic temporal changes in residents’ satisfaction. Future research should therefore conduct comparative analyses across different types of cities and regeneration models, and employ longitudinal designs that track pre- and post-project changes. Such studies would allow for a more rigorous assessment of the spatiotemporal effects of urban regeneration and the pathways through which built environment improvements and community-based interventions influence residential satisfaction over time. Fourth, because the present analysis is conducted primarily at the neighborhood level, it does not directly evaluate building- or facility-level design measures. Future research could adopt a multi-scale framework that connects neighborhood-level analyses with building- or facility-level design interventions, which were beyond the scope of the present study.

6. Conclusions

This study examined the associations between neighborhood residential satisfaction and both individual-level and neighborhood-level environmental characteristics in urban regeneration project areas. A multilevel modeling approach was employed to assess how individual characteristics and neighborhood built-environment attributes are, respectively, associated with residential satisfaction. The analysis showed that neighborhood residential satisfaction was higher among residents who had participated in urban regeneration activities and in neighborhoods with a higher level of age integration. Among built environmental factors, residential satisfaction increased as the proportion of old housing decreased and as both the NDVI and the proportion of water area increased. These findings indicate that the residential environment of a neighborhood plays a critical role in shaping residents’ perceptions of and satisfaction with their local area. Overall, both individual-level and neighborhood-level factors were found to significantly influence residential satisfaction. This study is meaningful in that it conducts a multidimensional analysis of residential environments in urban regeneration project areas by integrating survey-based individual data with GIS-based environmental data. Furthermore, the analytical approach proposed in this study provides an empirical basis that can be utilized to understand and assess neighborhood residential satisfaction in diverse urban contexts. In addition, by empirically examining the effects of individual and neighborhood factors in Korea—where urban regeneration has been institutionalized relatively recently—this study can complement conventional approaches to evaluating urban regeneration policies and provide evidence to inform future policy directions.

Author Contributions

Conceptualization, E.J.K.; methodology, E.J.K. and H.S.; software, E.J.K. and H.S.; validation, E.J.K.; formal analysis, E.J.K. and H.S.; investigation, E.J.K.; resources, E.J.K. and H.S.; data curation, E.J.K. and H.S.; writing—original draft preparation, E.J.K. and H.S.; writing—review and editing, E.J.K. and H.S.; visualization, E.J.K. and H.S.; supervision, E.J.K.; project administration, E.J.K.; funding acquisition, E.J.K. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2025S1A5A2A01006049).

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Institutional Review Board of Keimyung University (IRB No. 40525-202407-HR-030-02, 26 September 2024).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

The questionnaire used in this study was designed to assess residents’ satisfaction with living in urban regeneration project areas and their individual characteristics. The survey items were developed based on measurement scales validated in previous studies.
Table A1. Survey Questionnaire Items.
Table A1. Survey Questionnaire Items.
VariableQuestionnaire Items
Residential
Satisfaction		I am overall satisfied with the area where I live.
I want to continue living in my current residential area.
I feel a sense of belonging to the area where I live.
I would recommend my residential area to others.
Age
Integration		There are leisure activity programs that allow different generations to enjoy time together.
There are cultural contents that can be enjoyed jointly by people of different generations.
Mass media offer programs featuring older adults as main characters or primary audiences.
Clubs or social groups include members of diverse age groups, from young children to older adults.
Universities provide various learning opportunities and courses for middle-aged and older adults.
Older adults and younger people understand each other and socialize together.
People of different ages study together in the same classroom.
Older and younger generations make efforts to understand each other’s values.
Promotion opportunities are offered based on individual ability rather than age.
Individuals can enter the labor market at any time if they wish, regardless of age.
Employers make hiring decisions based on applicants’ competence or experience, not their age.
Knowledge, skills, and experience are shared between younger and older workers in the workplace.
Both younger and older adults receive income security from the state on an equal basis.

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Buildings 16 00213 g001
Figure 1. Multilevel research framework for analyzing residential satisfaction. (The grey shading and arrows represent the associations among individual-level (Level 1) factors, neighborhood-level (Level 2) factors, and residential satisfaction within the multilevel analytical framework.)
Figure 1. Multilevel research framework for analyzing residential satisfaction. (The grey shading and arrows represent the associations among individual-level (Level 1) factors, neighborhood-level (Level 2) factors, and residential satisfaction within the multilevel analytical framework.)
Buildings 16 00213 g001
Buildings 16 00213 g002
Figure 2. Study Area. (The red box highlights the area in which the selected URCFs are concentrated, and the red dots represent the six URCFs included in the analysis.)
Figure 2. Study Area. (The red box highlights the area in which the selected URCFs are concentrated, and the red dots represent the six URCFs included in the analysis.)
Buildings 16 00213 g002
Table 1. Urban regeneration project timeline and facility characteristics of the selected URCFs.
Table 1. Urban regeneration project timeline and facility characteristics of the selected URCFs.
URCFSelection YearProject PeriodOpening DateMajor Facilities (Key Spaces; Inventory)
Dalseong2019Jan. 2019–Dec. 2024Jun. 2024Café; learning room; shared community room; fitness/training room; club/activity room
Hyomok2017Aug. 2018–Dec. 2022Dec. 2023Youth center; daycare room; multipurpose meeting room; café/community lounge
Wongogae2015Jan. 2016–Dec. 2021Apr. 2021Multipurpose rooms; laundry facility; shared kitchen; youth space
Indongchon2018Jan. 2019–Dec. 2024Mar. 2023Senior center; shared kitchen; lecture/class rooms; computer room; calligraphy room; fitness/training room; auditorium; meeting rooms
Chimsan2017Aug. 2018–Dec. 2022Oct. 2023Café; senior center; mental-health welfare center; cooperative office; workshop/maker space; community gym
Cheukbaekhyang2015Jan. 2016–Jun. 2021Apr. 2021Local-food store; convenience store; café
Note: URCF = Urban Regeneration Community Facility.
Table 2. Measurement and data source of the variables.
Table 2. Measurement and data source of the variables.
VariableMeasurementData Source
Residential Satisfaction5-point scaleSurvey
Individual-level variables (Level 1)
Experience in Urban Regeneration Activities1 = Yes, 0 = NoSurvey
Age Integration
Gender		5-point scale
1 = Female, 0 = Male
Age1 = 18–29, 2 = 30–39, 3 = 40–49, 4 = 50–59, 5 = 60–69, 6 = 70 or older
Education1 = Elementary school or lower, 2 = Middle school graduate,
3 = High school graduate, 4 = College graduate or higher
Income1 = Less than 1 million KRW, 2 = 1–2 million KRW, 3 = 2–3 million KRW, 4 = 3–4 million KRW, 5 = 4–5 million KRW,
6 = More than 5 million KRW
Length of Residence1 = Less than 1 year, 2 = 1–3, 3 = 3–5, 4 = 5–10, 5 = More than 10 years
Neighborhood-level Built Environment variables (Level 2)
Urban Form and
Land Use		Mean SlopeMean slope (°)National Spatial Data
Land Use Mix (LUM)Land Use Mix Index (0–1)Environmental Space Information Service
Housing
Characteristics		Proportion of Old HousingPercentage of Old Housing (%)National Spatial Data
Proportion of Multi-Family HousingPercentage of Multi-Family Housing (%)
Open SpaceNormalized Difference
Vegetation Index (NDVI)		Mean NDVI (−1–1)United States Geological
Survey (USGS)
Proportion of Water AreaPercentage of Water Area (%)Road Name Address
Neighborhood
Amenities		Hospital density Number of Hospitals (count/km2)Local Data
Pharmacy density Number of Pharmacies (count/km2)
Retail Shop density Number of Retail Shops (count/km2)
Senior Center density Number of Senior Centers (count/km2)
Street network and Transport
Infrastructure		Intersection densityNumber of Intersections (count/km2)Road Name Address
Bus Stop density Number of Bus Stops (count/km2)National Spatial Data
Distance to Subway StationDistance to the Nearest Subway Station Entrance (m)
All spatial variables were calculated within a 400 m Euclidean buffer, except for the distance to the nearest subway entrance, which was measured as network distance in meters.
Table 3. Descriptive statistics of variables.
Table 3. Descriptive statistics of variables.
VariableMeasurementDalseong URCFHyomok URCFWongogae URCFIndongchon URCFChimsan
URCF		Cheukbaek
Hyang URCF		URCF Mean (All Sites)
N592848666119281
Mean (SD)
Residential Satisfaction5-point scale3.77 (0.68)3.45 (0.77)3.31 (0.82)3.39 (0.98)3.44 (0.78)3.61 (1.01)3.49 (0.85)
Individual-level variables (Level 1)
Age Integration5-point scale2.85 (0.57)2.76 (0.57)3.03 (0.58)3.20 (0.75)2.76 (0.54)2.32 (0.66)2.90 (0.66)
Count (%)
Experience in Urban
Regeneration Activities		Yes24 (40.7)9 (32.1)21 (43.8)9 (13.6)20 (32.8)3 (15.8)86 (30.6)
No35 (59.3)19 (67.9)27 (56.3)57 (86.4)41 (67.2)16 (84.2)195 (69.4)
GenderMale21 (35.6)11 (39.3)11 (22.9)24 (36.4)24 (39.3)8 (42.1)99 (35.2)
Female38 (64.4)17 (60.7)37 (77.1)42 (63.6)37 (60.7)11 (57.9)182 (64.8)
Age18–291 (1.7)6 (21.4)16 (33.3)1 (1.5)7 (11.5)3 (15.8)34 (12.1)
30–391 (1.7)7 (25.0)2 (4.2)3 (4.5)17 (27.9)7 (36.8)37 (13.2)
40–496 (10.2)3 (10.7)5 (10.4)4 (6.1)10 (16.4)0 (0.0)28 (10.0)
50–5913 (22)4 (14.3)18 (37.5)8 (12.1)7 (11.5)6 (31.6)56 (19.9)
60–6929 (49.2)7 (25)4 (8.3)15 (22.7)13 (21.3)2 (10.5)70 (24.9)
70 or older9 (15.3)1 (3.6)3 (6.3)35 (53.0)7 (11.5)1 (5.3)56 (19.9)
EducationElementary school or lower3 (5.1)0 (0.0)1 (2.1)22 (33.3)2 (3.3)1 (5.3)29 (10.3)
Middle school graduate7 (11.9)1 (3.6)3 (6.3)12 (18.2)8 (13.1)0 (0.0)31 (11.0)
High school graduate21 (35.6)6 (21.4)27 (56.3)20 (30.3)25 (41.0)4 (21.1)103 (36.7)
College graduate or higher28 (47.5)21 (75.0)17 (35.4)12 (18.2)26 (42.6)14 (73.7)118 (42.0)
IncomeLess than 1 million KRW14 (23.7)6 (21.4)18 (37.5)43 (65.2)13 (21.3)1 (5.3)95 (33.8)
1–2 million KRW8 (13.6)4 (14.3)18 (37.5)12 (18.2)10 (16.4)2 (10.5)54 (19.2)
2–3 million KRW13 (22.0)9 (32.1)6 (12.5)5 (7.6)12 (19.7)9 (47.4)54 (19.2)
3–4 million KRW8 (13.6)5 (17.9)6 (12.5)4 (6.1)13 (21.3)4 (21.1)40 (14.2)
4–5 million KRW12 (20.3)2 (7.1)0 (0.0)2 (3)5 (8.2)0 (0.0)21 (7.5)
More than 5 million KRW4 (6.8)2 (7.1)0 (0.0)0 (0)8 (13.1)3 (15.8)17 (6.0)
Length of ResidenceLess than 1 year0 (0)1 (3.6)0 (0)0 (0)5 (8.2)0 (0)6 (2.1)
1–34 (6.8)1 (3.6)1 (2.1)3 (4.5)6 (9.8)1 (5.3)16 (5.7)
3–55 (8.5)3 (10.7)1 (2.1)2 (3.0)5 (8.2)4 (21.1)20 (7.1)
5–105 (8.5)6 (21.4)4 (8.3)7 (10.6)5 (8.2)1 (5.3)28 (10.0)
More than 10 years45 (76.3)17 (60.7)42 (87.5)54 (81.8)40 (65.6)13 (68.4)211 (75.1)
Neighborhood-level
Built Environment variables (Level 2)		Unit
Urban Form and
Land Use		Mean Slope°1.21.41.20.92.53.91.9
LUM-0.7710.8220.4420.5570.8090.4170.636
Housing CharacteristicsProportion of Old Housing%75.996.398.293.593.881.989.9
Proportion of Multi-Family Housing10.26.59.08.912.10.07.8
Open SpaceNDVI-0.1820.1330.1060.1040.1740.3310.172
Proportion of Water Area%2.630.010006.751.57
Neighborhood
Amenities		Hospital density count/km2547011446031
Pharmacy density 18286206013
Retail Shop density 2654849040450
Senior Center density 14412121229
Street network and Transport
Infrastructure		Intersection density9161185180513587593271058
Bus Stop density 145753941687378255
Distance to Subway Stationm360.91378.81456.4930.4865.44590.41597.1
Table 4. Multilevel model results for residential satisfaction.
Table 4. Multilevel model results for residential satisfaction.
VariableβSEtp
Individual-level variables (Level 1)(Intercept)3.570.0752.180.02
Experience in Urban
Regeneration Activities (Yes = 1)		0.06 *0.041.730.08
Age Integration0.25 ***0.046.83<0.001
Gender
(Female = 1)		−0.020.04−0.490.63
Age0.63 ***0.0512.60<0.001
Education−0.050.04−1.200.23
Income0.040.040.930.35
Length of Residence0.030.040.850.40
Neighborhood-level Built Environment variables (Level 2)Proportion of Old Housing−0.38 *0.32−1.180.06
NDVI0.26 *0.261.010.07
Proportion of Water Area0.20 **0.151.300.03
Bus Stop Density−0.090.11−0.840.14
N281
ICC0.121
R20.433
Adjusted R20.501
* p < 0.10, ** p < 0.05, *** p < 0.01.
Table 5. Built environment characteristics and residential satisfaction by study area.
Table 5. Built environment characteristics and residential satisfaction by study area.
(1) Dalseong URCF(2) Hyomok URCF(3) Wongogae URCF(4) Indongchon URCF(5) Chimsan URCF(6) Cheukbaekhyang URCFBar Chart
Proportion of Old Housing
Buildings 16 00213 i001Buildings 16 00213 i002Buildings 16 00213 i003Buildings 16 00213 i004Buildings 16 00213 i005Buildings 16 00213 i006Buildings 16 00213 i007
75.9%96.3%98.2%93.5%93.8%81.9%
NDVI
Buildings 16 00213 i008Buildings 16 00213 i009Buildings 16 00213 i010Buildings 16 00213 i011Buildings 16 00213 i012Buildings 16 00213 i013Buildings 16 00213 i014
0.1820.1330.1060.1040.1740.331
Proportion of Water Area
Buildings 16 00213 i015Buildings 16 00213 i016Buildings 16 00213 i017Buildings 16 00213 i018Buildings 16 00213 i019Buildings 16 00213 i020Buildings 16 00213 i021
2.6%0.01%0.0%0.0%0.0%6.75%
Residential Satisfaction
3.773.453.313.393.443.61
Buildings 16 00213 i022
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Kim, E.J.; Sim, H. Residential Satisfaction in Urban Regeneration Areas: A Multilevel Approach to Individual- and Neighborhood-Level Factors. Buildings 2026, 16, 213. https://doi.org/10.3390/buildings16010213

AMA Style

Kim EJ, Sim H. Residential Satisfaction in Urban Regeneration Areas: A Multilevel Approach to Individual- and Neighborhood-Level Factors. Buildings. 2026; 16(1):213. https://doi.org/10.3390/buildings16010213

Chicago/Turabian Style

Kim, Eun Jung, and Hyemin Sim. 2026. "Residential Satisfaction in Urban Regeneration Areas: A Multilevel Approach to Individual- and Neighborhood-Level Factors" Buildings 16, no. 1: 213. https://doi.org/10.3390/buildings16010213

APA Style

Kim, E. J., & Sim, H. (2026). Residential Satisfaction in Urban Regeneration Areas: A Multilevel Approach to Individual- and Neighborhood-Level Factors. Buildings, 16(1), 213. https://doi.org/10.3390/buildings16010213

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