Exploring Indoor and Outdoor Residential Factors of High-Density Communities for Promoting the Housing Development

Abstract

Effective residence planning is crucial to encourage sustainable housing development. Residents in densely populated cities inevitably have negative residential experiences caused by compact land use. Still, this situation is improvable through optimizing the physical environment or increasing service facilities that cater to dwellers’ residential preferences. Therefore, understanding the factors impacting residential satisfaction in high-population metropolitan areas is essential mainly. This study surveyed the citizens’ residential environment and satisfaction in dense urban residential areas. Results of this survey indicate that 13 environmental factors significantly impact residential evaluation. Among them, improving ventilation, privacy, and property maintenance can effectively address the adverse effects of densely populated communities. Additionally, neighborhoods or amenities could further impact younger respondents’ residential evaluation. Elderly citizens place high importance on the quality of their indoor living environment. Green space could promote the residential satisfaction of young and more senior citizens. Environmental factors can significantly affect the residential satisfaction of citizens across all age groups with their homes. As a result, real estate planners should provide a range of dwelling unit designs to support housing development. Real estate planners can better understand the needs of potential clients by considering the housing preferences of individuals across different age groups and the surrounding neighborhood. The indoor or outdoor environment might be adjusted to meet households’ demands, while non-essential factors could be omitted to cut expenses. This study might aid in the sound development of dwellings.

1. Introduction

As property sales have become slow-moving in the past few years, stimulating property consumption to improve living conditions has become a new approach to real estate development. Some inhabitants might become unsatisfied with their current accommodation, so they are inclined to buy another asset. They expect to seek to change their current residence for habitable, better-equipped, or more convenient dwellings [1]. However, this strategy does not observably enhance the gross sales of housing estates. A report from the National Bureau of Statistics shows that in 2018, the total sales growth rate was 14.7%, and in 2019, it was 10.3%. In 2020, the entire housing sales increased by 10.8% and by 5.3% in 2021. Three reasons may cause this situation: population sprawl and limited land use policy increased housing prices in megacities [2]. Significantly, the rise in housing prices was evident in densely populated cities [3]. The rapidly growing population promotes urban sprawl [4], especially in urban housing [5]. Young, unmarried, highly educated persons fiercely intend to migrate to large cities [6] due to plentiful employment opportunities and well-equipped infrastructures [7]. Because housing prices have increased rapidly in many metropolises [8], this phenomenon could impact the life of the original residents. Potential consumer groups needed help to afford a high-price dwelling. In addition, early-stage large-scale residential construction led to design neglect, resulting in a wait-and-see attitude among potential property buyers. Usually, the sentiment or confidence of target consumer groups is rooted in the housing market [9], housing quality, neighborhoods, and public amenities accessibility [10,11].

As a result, the environmental aspects of residences are a considerable way to develop dwellings in dense communities. The survey of the residential condition of large-population cities could adequately express the current developing status of residences. This study could be conducted through a survey of post-occupancy evaluation that includes indoor physical environmental factors, neighborhoods, and surrounding public amenities. Besides, an approved urban residential environment involves surrounding landscape conservation, traffic management, and economic livability [12]. The provision of social infrastructure is also linked to sustainable communities and urban sustainability [13]. According to disciplinary and sociological theory, the post-occupancy evaluation uses the concept of residential satisfaction. Residential satisfaction has been in use since the early 1960s as the basis for optimizing the housing design, where feedback was collected from residents of housing projects about residents’ views on the physical features of proposed housing developments and then feeding those views back into the design process [14]. Thus, the residential satisfaction survey could enhance residents’ quality of life and provides a dwelling construction basis for urban development. The degree to which individuals’ needs and aspirations are met by their housing conditions is worth knowing not only for researchers but also for housing developers and planners [15]. The residential satisfaction research will benefit the sustainable development of urban housing via a humanized design.

This study aims to measure which factors influenced dwellers’ residential satisfaction through a survey of 1060 residents living in high-density communities in three large population cities in China. The results of this study could help improve the residential conditions or community plans. It is generally believed that there are some very significant links between residential satisfaction, residents’ socio-demographics, housing features, and neighborhood characteristics [15,16,17,18,19]. In this study, the research variables involve three aspects factors listed above. For exploring detailed items, this study had two main steps. The first step explored the determinants of residential satisfaction based on indoor and outdoor residential environments. Further analysis was carried out according to age ranges because people of different ages have different living statuses. The significant factors affecting residential satisfaction were listed and compared for a detailed explanation.

This paper consists of five parts. The following section reviews the theoretical perspectives in research on residential evaluation. Section 3 introduces the survey area, data, and model. Section 4 presents the findings of the survey and discusses the possibility leading to these results. The end of this paper is the conclusion of this study.

2. Literature Review and Theoretical Framework

A dense community usually consists of mid- or high-rise apartment buildings arranged along the street or surrounded by an area and various amenities such as playgrounds, clubhouses, stores, and plants [20]. If the community is adjacent to a prosperous public place, including landscape, food services, public institutions, and public transportation, households are more willing to live in the area [21]. Nonetheless, which factors of the residential environment have a significant effect on residential satisfaction in large-population cities? Moreover, whether is different age groups with various living need all hold a favorable opinion of this type of community? After all, different age groups with multiple life statuses could have distinguished lifestyles and residential behaviors, which are the main factors to evoke residents’ various residential needs. A survey of these factors can play a crucial part in planning successful real estate developments through the feedback of residents’ experience. Thus, the research variables involve residential satisfaction, demographic characteristics, and indoor and outdoor environmental elements.

2.1. Residential Satisfaction

Residential satisfaction is conceptualized as an individual’s cognitive response to the residential environment [22]. Besides, housing satisfaction studies usually integrate objective and subjective attributes [23] based on the physical characteristics of housing and neighborhoods to assess residential experiences [24]. The physical characteristics of housing and the neighborhoods are critical factors in determining the level of residential satisfaction [14].

In some factual cases, provided services and public facilities surrounding the house have strongly influenced overall satisfaction [25]. Buys and Miller [26] believe that internal dwelling design, including facilities and size, is associated with residential satisfaction. David et al. highlighted that the interior dwelling environment, the exterior environment of the dwelling, and security concerns correlated with residential satisfaction [27]. Francescato [28] and Amole [29] explained that residential satisfaction is multi-dimensional. The various dimensions of residential satisfaction include a housing unit, neighborhood environment, estate management, and social services [30,31].

2.2. Demographic Characteristics

Empirical studies have identified essential demographic elements correlated with evaluating housing satisfaction [24]. Age is a crucial predicted factor in measuring residential satisfaction [3,5,17,32,33]. Usually, older people tend to be more satisfied with their dwellings than younger people [14]. Married or higher-income households tend to positively evaluate the residential environment [14,22,34,35]. Because higher economic status could support a suitable residential condition or choose new housing [36], income is a correlative variable of residential satisfaction [37]. Some scholars show the survey results that a couple with children is more satisfied with their housing [19,38]. Lu’s survey [15] indicated that married couples without children have higher neighborhood satisfaction than parents. Education and health also directly correlate with residential satisfaction [3,5,38,39]. Education level significantly impacts a person’s income [36]. Moreover, socio-demographic variables such as gender and family size [17,25,30,40] also affect residential evaluation.

2.3. Indoor Elements

The physical features of dwellings are a critical indoor element in enhancing residential satisfaction. In higher-density communities, inadequate size and uncontrolled noise could hurt residents’ life satisfaction [35]. Thus, the unit size is a primary determinant of the residential demand of households [41,42]. The size of the living room or dining room also directly affects residential comfort [3,24,42,43]. The condition (the number or size of space) of storage space, bathrooms, and bedrooms could influence residential satisfaction [14,18,43,44]. According to residential standards, a unit should provide separate bedrooms for children of different gender [44]. A separate kitchen could optimize the residential experience as a building feature [3,18]. The number of elevators is also associated with housing congestion [34,44,45]. The accessory space, such as parking and balconies, could promote the convenience and comfort of daily life [14,44].

Results of some studies reveal that housing services, including cleanliness, maintenance, security, noise control, and privacy, can impact residential satisfaction [41,43,46,47]. The building age and duration of residence are related to residential satisfaction [14,15,34]. Donggen and Fenglong [22] believe that residents engage in more daily activities and spend more time at home, which leads to more residential satisfaction. Therefore, it is reasonable to assume that the affective feelings or experiences generated from daily activities at home or in the neighborhoods may contribute to residential satisfaction.

The research on indoor air presents strong evidence that natural ventilation is more supportive of health than mechanical ventilation [48] and is beneficial to thermal emission reduction or improving climate [49]. Besides, ventilation is the process of exchanging indoor (polluted) air with outdoor (presumably fresh and clean) air and makes residents feel comfortable [50]. Thus, the condition of natural ventilation has also been an effective predictor of residential satisfaction.

Furthermore, there is evidence verified that the generation of falls and depression potentially originate from inadequate residential light, and natural light is more effective than artificial light in daily life [51]. Natural light significantly reduces energy use in buildings [52,53]; it is comfortable and healthy illumination in the control of the physiological and psychological senses of living beings [54,55,56]. Physical aspects of housing, such as ventilation, lighting, and orientation of windows, also contribute to overall housing satisfaction [14].

2.4. Outdoor Elements

Neighborhoods and amenities are outdoor elements that could universally impact residential comfort and convenience, which are listed as research variables to measure residential satisfaction [18,22,27]. Neighborhood characteristics include the physical environment, local facilities and services, and socioeconomic environment [17]. The physical environment includes open space, public facilities, traffic systems, and amenities [3,17]. The open space is a common area of urban communities helping residents’ social contacts [57], which might support dwellers’ informal meetings, social interaction, necessary activity, and outdoor play [25,35]. The local facilities or services could be measured through four items: health centers, entertainment, commercial institutions, and public transportation [31,42].

The housing position with convenient public transportation could help reach destinations such as the town center, schools, markets, etc. [41]. High public transportation coverage is essential for achieving livable and more sustainable urban patterns [58]. In daily life, neighborhood activities include shopping, walking for leisure, outdoor physical activities, and social interactions with neighbors [22,59]. The neighborhoods of communities usually are composed of a series of elements—commercial services, recreation services, public institutions, green space, and common areas [17,22,31,35,41,57,60,61]. These profoundly improved urban function and changed urban formations [62].

In Chinese cities, children can enroll in a nearby public school based on their household registration and the housing property to receive nine years of compulsory education (from primary to junior school) [63]. Nevertheless, the local government can only financially support some public schools equally. As a result, excellent schools become scarce resources, and housing located in school zone become a popular concept in the real estate market. Thus, residential areas providing school opportunities can promote neighborhood satisfaction [3,24,31]. Moreover, people who live in a community with adequate parking spaces are more satisfied with their dwelling environment [3,30,42].

According to the contribution of the literature, the conceptual framework can be listed in Figure 1. Indoor and outdoor residential elements directly impact residential satisfaction and relate to personal residential demands.

2.5. The Existing Primary Studies in China

In recent years, studies on residential satisfaction have begun to be carried out in China [16]. Some current studies surveyed about residential satisfaction in specific living environments such as urban villages, redeveloped neighborhoods, and public rental housing [3,16,17,64,65] or surveyed residential satisfaction via used affective experience [22]. Other scholars investigated surrounding facilities that can positively affect residential satisfaction, for example, parks [66], green spaces [67], and premium schools [63]. The housing condition [68] and environmental satisfaction [69] also become clues to survey households’ residential evaluation. Moreover, several studies analyzed and researched residential satisfaction through observed specific population groups. The respondents have the same homogeneous socio-demographic characteristics, such as displaced residents [34], a group of migrants [30], and older persons [27].

However, few studies concentrated on the residents’ evaluation, especially, in largely populated cities in China. Furthermore, which factors could significantly impact the residential satisfaction of individuals in different age distributions are rarely analyzed.

3. Methodology

3.1. Study Area

Because of the research purpose and scope, this survey was conducted in three densely populated cities in China: Beijing, Shanghai, and Chongqing. These three cities are direct-controlled municipalities and the three largest cities in China by population. The total number of people is 21.88, 24.87, and 32.05 million, respectively [70]. These three cities have high populations. Therefore, congested living conditions are a universal phenomenon. Researchers randomly selected local inhabitants to participate in this study, and it was carried out in a densely populated area in three urban districts. Due to the high population density and varying construction eras of dwellings, many communities are blended together in one urban district. Our sampling work conducted focused on urban districts. For a diversified survey, the investigation team selected communities of different construction periods in sub-districts of three large cities (the details in Supplementary Materials).

The three cities experienced rapid population growth, which provided a large number of employment opportunities. Beijing is the cultural and political center of China, located in the eastern region. Shanghai is a Chinese economic trade center with the maximum population density. Chongqing is the largest population city located in the southwest region of China. To adapt to the rapid growth of residential demands, real estate developers must find a way to balance compact land use and residential comfort. The residents’ various demographic characteristics and living needs lead to different residential preferences. Thus, three cities are representative research cases (Figure 2).

3.2. Data Source

Through the summarized related literature, 32 items were listed in the questionnaire as independent variables to predict residential satisfaction, eight demographic characteristics, fifteen indoor environmental factors, and nine neighborhood factors (

Table 1. Definition of independent variables.

Variables	Definition
Demographic Characteristics
Age	1 = Below 30, 2 = 30–39, 3 = 40–49, 4 = 50–59, 5 = above 60
Gender	0 = male, 1 = female
Income	Monthly income of household (unit: Chinese yuan) 1 ≤ 5000, 2 = 5000–10,000, 3 = 10,000–20,000, 4 = 20,000–40,000, 5 ≥ 50,000
Education	1 = junior high school, 2 = high school, 3 = Bachelor, 4= Postgraduate
Marital status	1 = single, 2 = married, 3 = divorce
Child family members	There are children family members 0 = yes,1 = no.
Health	1 = very bad, 2 = bad, 3 = ordinary, 4 = good, 5 = very good
Family size	1 = one, 2 = two, 3 = three, 4 = four, 5 = more than 5 (unit: person)
Indoor Elements
Unit size	The indoor area of units (unit: square meter)
Living room	The size of the living room (unit: square meter)
Bedrooms	The number of bedrooms 1 = one, 2 = two, 3 = three, 4 = four, 5 ≥ five
Storage rooms	The number of storage rooms 1 = none, 2 = one, 3 = two, 4 = three, 5 = four
Kitchen	There is a unique kitchen 0 = no, 1 = yes.
Bathrooms	The number of bathrooms 1 = one, 2 = two, 3 = three, 4 = four, 5 = five
Balconies	The number of balconies
Ventilation	1 = mechanical ventilation is necessary, 2 = unsatisfactory natural ventilation, 3 = ordinary natural ventilation, 4 = well-ventilated, 5 = perfect natural ventilation
Lighting	1 = long-term artificial lighting, 2 = 4–5 h of natural lighting, 3 = 6 h of natural lighting, 4 = plentiful natural lighting, 5 = super good natural lighting
Orientation	The primary orientation of windows in the house 1 = south, 2 = north, 3 = west, 4 = east, 5 = more than two orientations
Elevators	The number of elevators
Building age	Duration of residence
Privacy	1 = very bad, 2 = bad, 3 = ordinary, 4 = good, 5 = very good
Property maintenance	1 = very bad, 2 = bad, 3 = ordinary, 4 = good, 5 = very good
Cleanliness	1 = very bad, 2 = bad, 3 = ordinary, 4 = good, 5 = very good
Outdoor Elements
Parking	1 = There is no parking, 2 = some parking space, 3 = suitable parking space, 4 = There are occasional vacant parking spots, 5 = plenty parking space
Public transportation	1 = only private car, 2 = few public vehicles, 3 = about 10 min walking from stations, 4 = subway and bus stations near the house, 5 = many convenient public transport
Green space	The greening rate of the house surrounding. 1 = almost no green space, 2 = about 10–15% greening rate, 3 = 16–25% greening rate, 4 = There is a park, 5 = waterfront landscape or natural landscape
Open space	0 = no common space, 1 = yes, have common space
Security	There are security arrangements. 0 = no, 1 = yes
School zone	Your house locates in a school district. 0 = no, 1 = yes
Public facilities	The number of public facilities such as hospitals, banks, libraries, cinemas, etc. 1 = Almost none, 2 = a few, 3 = meeting basic needs, 4 = meeting variety needs, 5 = sufficient
Commercial area	There are commercial areas or streets. 0 = no, 1 = yes
Noise control	1 = very dissatisfied, 2 = dissatisfied, 3 = ordinary, 4 = Satisfied, 5 = very Satisfied

).

Moreover, the sampling process used the face-to-face interview to finish a standard questionnaire. Investigators can explain the items listed in the questionnaire to avoid unnecessary misunderstandings. The survey of three cities lasted 19 months (From October 2019 to May 2021). The survey in Shanghai started from October 2019 to April 2020, and the process in Beijing continued from January 2020 to June 2020. From January to May 2021, we finished the investigation of Chongqing. Our investigators distributed 1520 questionnaires to residents living in communities with facilities, amenities, and different construction periods. The investigation team collected 1060 effective questionnaires ultimately. The survey of Beijing contributed to 316 questionnaires. Besides, we gathered 445 and 299 questionnaires in Shanghai and Chongqing, respectively. All participants are adults in this survey. Participants were informed of the purpose of the study before they read the questionnaires.

3.3. Model

Because residential satisfaction is the ordinal level dependent variable, this study employs ordered logistic regression to measure what factors could affect it. Residential satisfaction is measured using a 5-point Likert scale (1 = very unsatisfactory; 2 = unsatisfactory; 3 = ordinary; 4 = satisfied; 5 = very satisfied). The ordered logistic regression model is presented as follows,

$$\frac{P\left(y\le j/x\right)}{P(y>j/x)}=\mathit{exp}\left({\alpha }_j-{\beta }^{T}x\right),\cdots j=1,\dots ,5$$

(1)

where $P\left(y\right)$ denotes the conditional probability of having at most $j$ level of residential satisfaction given a vector of covariate x; P(y > j/x) is the probability of being satisfied above the level j; β is a column vector of coefficients; and the unknown parameters α satisfy −∞ = α1 < α2 < α3 < α4 =+< α.

In the model, the regression coefficient β1 for the lth explanatory variable, Xl, is the log-odds ratio for the y by Xl association, else items being the same [71]. Logistic regression analysis in Stata 17 was used to calculate the significant independent variables affecting residential satisfaction.

4. Discussion and Result

4.1. Demographic Characteristics of Respondents

In this survey, 389 respondents aged between 30 to 39 years old accounted for 37.5 percent of the total number. The second largest group is 336 persons (31% of all respondents) whose age is more than 20 but lower than 29 years old. Most respondents’ household incomes do not exceed 40 thousand Chinese yuan. In this survey, 688 persons were awarded Bachelor’s degrees, and 206 respondents are graduate students. Up to 727 persons have marriage status, and 621 respondents have children. Three-person families account for 44.3 percent of all surveyed families (

Table 2. The socio-demographic characteristics of respondents.

Demographic Factors	Items	Number (%)
Age	Below 30,	336 (31)
	30–39,	398 (37.5)
	40–49,	165 (15.6)
	50–59,	103 (9.7)
	Above 60	58 (5.5)
Gender	male,	577 (54.4)
	female	483 (45.6)
Income (Unit: Chinese yuan)	≤5000,	131 (12.4)
	5000–10,000,	295 (27.8)
	10,000–20,000,	364 (34.3)
	20,000–40,000,	247 (23.3)
	≥50,000	23 (2.2)
Education	Junior high school,	49 (4.6)
	high school,	117 (11.0)
	Bachelor,	688 (64.9)
	Postgraduate	206 (19.4)
Marital status	Single,	287 (27.1)
	Married,	727 (68.6)
	Divorce	46 (4.3)
Child family members	Yes,	621 (58.6)
	No	439 (41.4)
Health	Very bad,	6 (0.6)
	Bad,	40 (3.8)
	Ordinary,	332 (31.2)
	Good,	461 (43.5)
	Very good	221 (20.8)
Family size (Unit: person)	One,	81 (7.6)
	Two,	151 (14.2)
	Three,	470 (44.3)
	Four,	199 (18.8)
	More than five	159 (15.0)
Total: 1060 respondents.

Note: The percentage is reserved in one decimal place.

).

4.2. Residential Satisfaction

This survey evaluates interior and external residential environments in the questionnaire on a 1–5 Likert scale. Despite being from different age groups, as shown in Figure 3, most respondents were satisfied with their residential environment. People aged 30–49 have more robust satisfaction evaluations than other groups.

A similar situation occurs in assessing the residential neighborhoods and internal environmental factors (Figure 4 and Figure 5). Fifty-two percent of the total respondents were satisfied with their indoor residential environment. Moreover, 552 interviewees affirmed that surrounding facilities could support convenience and livability in daily life. However, comparing the total evaluation of the interior and outside environments, the ratio of each item showed a small gap. The data present that indoor and outdoor elements relate to residential satisfaction.

4.3. The Main Factors Affecting Residential Satisfaction in Densely Residential Areas

Table 3. Overall ordered logistic regression of factors affecting residential satisfaction.

Variables	Coefficient	z	Odds Ratio
Demographic Characteristics
Age	0.167 **	2.79	1.182
Gender	0.204 *	1.78	1.226
Income	0.406 ***	6.48	1.50
Education	−0.200 *	−2.15	0.818
Marital status	0.091	0.63	1.0955
Child family members	0.031	0.21	1.032
Health	0.507 ***	6.92	1.661
Family size	0.304 ***	5.38	1.356
N = 1060	Pseudo R2 = 0.0522
Indoor elements
Unit size	0.016 **	2.72	1.016
Living room	−0.007	−0.61	0.993
Bedrooms	−0.137	−1.04	0.872
Storage rooms	0.130	1.21	1.138
Kitchen	0.320	1.30	1.376
Bathrooms	−0.034	−0.25	0.967
Balconies	0.184 *	1.82	1.2022
Ventilation	0.372 ***	4.56	1.450
Lighting	0.071	1.15	1.073
Orientation	−0.027	−0.48	0.974
Elevators	−0.133 *	−2.18	0.875
Building age	0.065	1.08	1.067
Privacy	0.740 ***	9.35	2.097
Property maintenance	0.684 ***	7.96	1.982
Cleanliness	0.430 ***	5.18	1.538
N = 1060	Pseudo R2 = 0.2487
Outdoor elements
Parking	0.268 ***	3.99	1.307
Public transportation	0.170 **	2.66	1.185
Green space	0.426 ***	6.21	1.532
Open space	−0.118	−0.75	0.889
Security	0.325 *	1.78	1.384
School zone	0.227 *	1.77	1.255
Public facilities	0.236 **	3.22	1.266
Commercial area	0.099	0.68	1.104
Noise control	0.889 ***	13.68	2.434
N = 1060	Pseudo R2 = 0.1545

* p < 0.1 ** p < 0.01 *** p < 0.001.

reports the results of ordered logistic regression with research variables and residential satisfaction. Six socio-demographic features of age, gender, monthly income, education level, health, and family size significantly impact residential satisfaction. The significant level of three items (monthly income, health, and family size) arrives at p < 0.000. In the case of Donggen and Fenglong [22], income and education level are curial factors in obtaining better residential conditions. However, in this survey, education level is negatively related to residential evaluation. This result might arise from the pressure of life in large cities or crowded living environments. People with higher education levels might feel that a crowded residential environment has less chance of bringing them well-being. Worse health could lead to an unsatisfied life evaluation and diminish residential satisfaction directly [35] and vice versa. Usually, family size could hurt households’ residential experiences due to crowded living environments [47]. However, added family members did not negatively impact residential satisfaction in this study. The possible reason is that the long-term family planning policy (The Chinese Family Planning Policy was enacted over 40 years. The policy aims to control rapid population growth and reduce congenital disabilities. Couples were encouraged to raise one child.) promotes the normalization of small-scale families. This situation leads to limited development of family size in cities of China. In addition, the intimate relationship between family members is in line with the traditional cultural concept of China, which could enhance residents’ life satisfaction. Age significantly affects residential satisfaction, and its p-value is less than 0.01. Therefore, we inferred that different age groups have diverse residential demands and evaluations.

The coefficients given in Table 3 displayed seven indoor residential environment items that significantly impact residential satisfaction. Generally, larger-sized housing units could provide better residential experiences [72], but the housing size usually corresponds to family size [3]. Balconies are a space connecting indoors and outdoors, which could expand the interior activity area. Thus, the additional balconies could bring a better experience for residents. The desired natural ventilation could help circulate cold and fresh air to support health [73], and it can consistently lower room temperature and relative humidity [49]. Privacy is a crucial factor associated with social densities, especially in a highly densely populated area. Thus, privacy is worthy of concern for residents living in intensive communities. Property maintenance and cleanliness belong to housing or community services. Residents should pay the fee for these services monthly. The quality of service determines the living experience and affects residential satisfaction [45]. Typically, the number of elevators will be determined according to the total number of units in a building. Elevators also mean that plenty of households must share common facilities. This situation could generate a negative influence.

Additionally, seven neighborhood factors significantly correlate with residential satisfaction (Table 3). The parking capacity and public transportation could promote convenient daily traveling, which is crucial for meeting the rapid pace of life in bustling cities. The usability of the surrounding green area supplies relaxation or outdoor activity space [31,74]. In large population cities, the density of residential areas could compel citizens to prefer a peaceful landscape. Moreover, a quiet environment could ensure comfortable sleep that benefits to residents’ health [73]. Thus, the significant coefficients of green space and noise control on residential satisfaction are set at p < 0.001. Salleh believes that neighborhood security is essential to assessing residential satisfaction [18]. Because public facilities positively heighten the convenience of daily life, it is also a significant determinant of residential satisfaction [17]. A community with an admission quota of excellent schools could greatly arouse parental preference [75]. It is a positive factor in residential satisfaction that good educational resources are easy to reach [31].

4.4. The Factors Affecting Residential Satisfaction in Different Age Groups

The comparison between different generations and residential satisfaction is significant (p = 0.049) in light of ANOVA detection. We separated all respondents into five groups based on age to further properly investigate the effects of the variables. The ages of the residents in the first group (N = 336) range from 23 to 29. The second group has 398 persons aged from 30 to 39. There are 165 respondents aged between 40 and 49 in the third group. The fourth group includes interviewees over 50 years old but under 59. Because older people are unwilling to live in a compact metropolitan area associated with a rapid life pace, in this survey, 58 respondents aged more than 60 finished the questionnaire.

Residents’ differing lifestyles and behaviors influence how they assess the residential environment. Demographic factors might be control variables for in-depth research. Therefore, the test planned two models for every age group. Take Group 1 as an example, which includes Model 1 and Model 2; Model 1 consists of sociodemographic features and indoor residential environment items. The sociodemographic characteristics were not observed in the test of Model 2.

Table 4. The ordered logistic regression of different age groups in indoor elements.

Variables	Group 1		Group 2		Group 3		Group 4		Group 5
	Model 1	Model 2	Model 3	Model 4	Model 5	Model 6	Model 7	Model 8	Model 9	Model 10
Demographic Characteristics
Gender	0.540 *		−0.149		0.457		−0.470		−2.057 *
Income	0.567 ***		0.206		0.094		−0.240		−0.605
Education	−0.462 *		−0.555		0.522		0.199		−1.065
Marital status	0.669 **		−0.509 *		0.109		−1.059		4.177 *
Child family members	0.987 *		−0.070		−0.330		−0.667		−2.861 *
Health	0.350 *		0.300 *		0.214		0.365		0.750
Family size	0.043		0.281 *		0.131		−0.110		−0.509
Indoorelements
Unit size	0.020	0.029 *	0.016	0.014	−0.030	−0.021	0.059 *	0.038 *	0.050	0.059
Living room	−0.027	−0.031	−0.020	−0.012	0.057	0.046	0.014	0.017	0.051	0.004
Bedrooms	−0.048	−0.312	−0.143	0.022	0.491	0.335	−1.493 **	−1.081 *	0.014	−0.320
Storage rooms	0.125	0.120	0.453 *	0.347 *	0.008	−0.037	−0.519	−0.208	−0.998	−0.189
Kitchen	0.719 *	1.038 **	−0.462	−0.560	−0.876	−1.312	−1.871	−1.678	−11.84 *	−6.541 *
Bathrooms	−0.004	0.037	−0.645 *	−0.634 *	0.647 *	0.664 *	−1.791 *	−1.514 *	−0.010	−0.164
Balconies	−0.241	−0.176	0.816 ***	0.849 ***	0.043	0.099	−0.082	−0.112	1.231	0.805
Ventilation	0.326 *	0.337 *	0.472 **	0.492 **	0.632 **	0.616 **	0.229	0.295	2.106 **	1.243 *
Lighting	0.092	0.134	−0.029	0.015	−0.197	−0.195	0.616 *	0.524 *	−0.011	−0.469
Orientation	0.288 **	0.262 **	−0.085	−0.089	−0.328 *	−0.336 *	−0.687 *	−0.608 *	−0.483	−0.336
Elevators	−0.042	−0.007	0.018	0.039	−0.028	−0.040	−0.496 *	−0.487 *	−1.441 *	−0.711 *
Building age	−0.054	0.026	0.028	0.050	0.443 *	0.398 *	0.132	0.079	1.096 *	0.740 *
Privacy	0.418 **	0.490 **	0.752 ***	0.740 ***	1.179 ***	1.179 ***	1.713 ***	1.713 ***	0.616	0.375
Property maintenance	0.696 ***	0.617 ***	0.587 ***	0.643 ***	1.141 ***	1.105 ***	1.163 **	1.163 **	2.698 **	2.084 **
Cleanliness	0.412 **	0.345 *	0.601 ***	0.557 ***	−0.335	−0.197	0.762 *	0.762 *	0.701	0.369
Pseudo R2	0.2781	0.2286	0.2838	0.2687	0.3297	0.3181	0.4819	0.4610	0.6131	0.5252
N	336		398		165		103		58

* p < 0.1 ** p < 0.01 *** p < 0.001.

shows the logistic regression result of what indoor residential environment factors affect residence satisfaction. Except for unit size, six items listed in Models 1 and 2 significantly relate to residential satisfaction. Separate kitchens, natural ventilation, and window orientation are crucial determinants of the indoor physical environment. Privacy, property maintenance, and cleanliness could strongly impact residential comfort. Respondents under thirty might believe that inadequate indoor size could affect their privacy and become crowded due to raised children. In the other four groups, the regression results show that the same items significantly affected residential satisfaction regardless of whether there were added sociodemographic factors. The residents in their thirties could hold higher residential evaluations caused by the space of storerooms and balconies. However, the number of bathrooms negatively impacts residential satisfaction. Sometimes added bathrooms have no positive effect on residential satisfaction.

Models 5–6 in Group 3 present that building age is a factor related to residential satisfaction, and the same significance level was found in the test of Group 5. The duration of residence positively affects residential satisfaction, where people might feel satisfied with their living environment [14], which generates familiarity via frequent daily activity. Moreover, window orientation negatively impacts residential satisfaction (Models 5–10). The variables of window orientation are listed based on four directions; therefore, residents of Group 3 also care about the effect of window orientation on the indoor physical environment. Furthermore, the number of bedrooms and elevators hurts residential experiences, but natural lighting promotes it (Group 4 of Table 4). The residents aged 50 to 59 have less chance of living with their children, and several bedrooms are unnecessary. Poor lighting could undermine vision and mental health [50], especially for older people. The analysis of Group 5 presents five significant factors that affect residential satisfaction, including separate kitchens, natural ventilation, elevators, building age, and property maintenance.

Table 5. The ordered logistic regression of different age groups in neighborhoods.

Variables	Group 1		Group 2		Group 3		Group 4		Group 5
	Model 11	Mode 12	Model 13	Model 14	Model 15	Model 16	Model 17	Model 18	Model 19	Model 20
Demographic Characteristics
Gender	0.507 *		0.160		0.212		−0.175		−0.167
Income	0.510 ***		0.048		0.162		−0.431		0.637
Education	−0.798 ***		−0.101		−0.030		0.053		−1.103 *
Marital status	0.529 *		−0.449		0.536		−0.086		2.173 *
Child family members	0.497 *		−0.168		−0.809 *		−0.676		−1.300
Health	0.350 *		0.242 *		0.225		0.486 *		−0.142
Family size	0.223 *		0.320 **		0.034		0.004		−0.706 *
Outdoor elements
Parking	0.251 *	0.348 **	0.258 *	0.270 *	0.136	0.165	0.401 *	0.309	0.442	0.427
Public transportation	0.395 **	0.462 ***	0.014	0.019	−0.080	−0.007	0.456 *	0.164	0.136	0.490
Green space	0.461 ***	0.466 ***	0.548 ***	0.594 ***	0.168	0.223	0.217	0.193	1.420 **	1.076 **
Open space	−0.390	−0.353	−0.028	0.084	−0.312	−0.231	0.181	0.200	−1.889 *	−1.247 *
Security	0.397	0.228	0.710 *	0.732 *	0.224	0.207	0.323	0.136	−2.749 *	−3.082 **
School zone	0.367	0.397 *	0.203	0.097	−0.100	−0.092	0.927 *	0.679	−0.646	−0.274
Public facilities	0.006	−0.159	0.434 **	0.434 **	0.440 *	0.424 *	0.322	0.340	0.589	0.458
Commercial area	−0.272	−0.290	0.471 *	0.504 *	0.020	−0.044	0.278	0.007	0.057	0.534
Noise control	0.763 ***	0.824 ***	0.744 ***	0.751 ***	1.178 ***	1.220 ***	1.016 ***	1.061 ***	1.753 ***	1.218 ***
Pseudo R2	0.2173	0.1643	0.1977	0.1827	0.2151	0.1944	0.1913	0.1588	0.3261	0.2463
N	336		398		165		103		58

* p < 0.1 ** p < 0.01 *** p < 0.001.

consists of five groups and ten models (Models 11–20) that present the statistical coefficient of neighborhoods. The odd number models include variables of neighborhoods and sociodemographic characteristics. The even number models are the analysis results of neighborhoods in different age groups.

The Model 11 column contains four environmental elements: parking capacity, public transportation, green space, and noise control. A favorable community should have good availability of parking spaces [42]. Public transportation positively affects comfortable urban life and is a crucial factor in residents’ daily life [76]. Green spaces, such as gardens and landscapes, can provide a space supporting outdoor activities and mental relaxation to citizens in their twenties. In the Model 12 column, the school zone becomes a significant positive factor in residential satisfaction. Because people in their twenties might raise children, a superior elementary school will be considered a necessary facility. Model 13 and Model 14 have six of the same significant factors in Group 2. Public facilities and commercial areas could provide some institutions served for daily affairs. Mid-aged people have active consumer intention, financial management practices, and a solid economic base. Public facilities (banks, hospitals, libraries, museums, etc.) also are valuable factors for residents in their thirties.

The survey of group 4 shows different results in Model 17 and Model 18. In the Model 17 column, four neighborhood items correlate with residential satisfaction. Only one factor (noise control) could impact residential satisfaction in the Model 18 column. The results show that residential satisfaction could be enhanced from parking capacity, transportation, and school zone under demographic factors. Four factors significantly correlate with residential satisfaction in the survey of Group 5. However, open space and security are presented with negative coefficients. Open space might produce more people flow and noise, which is an unpleasant situation for older persons. Moreover, the results of all models show that noise control positively affects residential satisfaction (p < 0.001). We could deduce that noise is an issue in high-density communities with compact land use. Controlling noise could effectively improve residential experiences in density communities.

Besides, six factors (bedroom number, store rooms, separate kitchen, natural light, orientation, and building age) in Table 4, but not in Table 3, effectively affect residential satisfaction. Moreover, the open space (in Table 5) is also not listed in Table 3. We could deduce that the practical elements impacting residential evaluation are not identical in every age group.

Figure 6 presents the influence of indoor and outdoor factors on different age respondents. Respondents in Groups 1–4 also care about the privacy of life. Furthermore, most people believe room ventilation and property maintenance are important factors in a praiseful residential experience. The size and quantity of balconies might improve dwellers’ contentment with their homes in their 30 s. Parking capacities and public transportation had no significant effects on the residential needs of individuals aged 60 or older. The residential preference of senior citizens is associated with building age and green space.

Because dense communities also regard population per spatial unit and buildings in terms of floor space and plot coverage, increasing population density might lead to negative evaluation when the anticipated residential environment differs from the realistic residential density [58]. The improvements in ventilation, privacy, and property maintenance could effectively adjust the negative factors of dense communities. Green space could promote the residential satisfaction of young and older citizens. Mid-aged people more prefer to live in communities surrounding multiple public facilities. Public transportation systems are essential for achieving livable and sustainable urban patterns, especially for young people. Adding bathrooms and bedrooms might negatively impact people who do not need them. For sustainable development of dwellings, planners should provide more alternative dwelling-unit designs. Beyond this, the real estate planner could presuppose the potential customers via the preferences of people of different ages and the surrounding environment. They could adjust indoor or outdoor environmental elements to meet residents’ needs and discard unapparent factors to avoid unnecessary expenditure. This study might aid in the sound development of dwellings.

5. Conclusions

Several different factors may cause unsalable reasons for housing properties, but finding the problem of a housing plan is a crucial way to promote the propitious development of residences. This study reveals the main factors affecting residential satisfaction in large-population cities in China. Urban development has accelerated over the past century, and more than 50% of the global population now lives in urban areas [61]. Because of the compact land use approach, people who live in crowded communities are possibly dissatisfied with their residential quarters. However, an effective way of enhancing residential evaluation in intensive communities is by providing desirable service facilities which could serve mass residents. Furthermore, the results of residential evaluations might have discrepancies due to the age of citizens. Understanding these focuses could provide appropriate service facilities and improve unfavorable factors of residential environments effectively.

According to the study, the age difference is a significant factor in deciding residential evaluation, even though these people live in similar urban environments. Moreover, income, health status, and family size also have a powerful influence on residential evaluation. Besides, sociodemographic aspects could prompt residents of different ages to have various residential preferences. In group test results, several research variables practically impact residential evaluation. Although these elements were not listed as evident influencing factors in the overall test, they still have importance to an age group of respondents.

The survey results describe that most residents could adapt to the residential environment of dense residential areas. More younger people hold higher satisfaction with existing communities. Even in different age groups, some factors affecting residential satisfaction are the same, such as property maintenance, privacy, ventilation, and noise control. These elements are essential in large cities to decide on residential comfort and promote satisfaction. In addition, some environmental factors become crucial elements affecting the evaluation of communities in the test of different age groups. For instance, people in their twenties and fifties might have child family members waiting for enrollment in primary school. Therefore, they will consider school district houses of a favorable condition. The parking capacity and green space significantly affect residential satisfaction to relatively youthful residents. The middle-aged crowd could enhance their satisfaction via better public facilities.

One limitation of this survey is that certain personal factors may influence how residents evaluate their living situation. Different cities have their living standards, which can impact how residents assess their residential environment. Additionally, residents’ housing experiences can influence their current evaluations. To address these potential issues, further research should account for these factors and analyze a range of environmental elements to provide a more in-depth study.

From the survey results, variables with significant levels are dispersed in different age groups (Table 4 and Table 5). This result suggests that a factor affecting residential evaluation has a possibility of both prominent and unapparent based on the age difference of residents. Thus, the design of the residential environment and the plan of neighborhoods could refer to the dominant factors directed at the needs of different age groups. These factors could help to construct a targeted comfort community, because the livability environment is an important aspect of sustainable urban development [38]. This study presents practical information for building intensive communities and is a valuable reference for planning a livable residential environment in large cities.